Basic Strategies Forex Strategies & Systems Revealed
Forex Strategies FXProSystems - Free trading systems and ...
Free Forex Trading Strategies And Systems That Work
The Best Forex Trading Strategies That Work In 2020
A place for redditors to discuss quantitative trading, statistical methods, econometrics, programming, implementation, automated strategies, and bounce ideas off each other for constructive criticism. Feel free to submit papers/links of things you find interesting.
Forex Trading System X – EMA, MACD MFT, BBands and RSI Based Forex Strategy
Forex Trading System X – EMA, MACD MFT, BBands and RSI based Forex Strategy First, you will copy all needed files of Forex Trading System X and then run MT4. Next, you will open any major pair that you wish to trade like GBP/USD or EUUSD and so on. Then, you will have to set time frame of chart to 30 minutes. Now, you will apply the given template. As you will do this, you will find a chart such as this: Forex Trading System X – EMA, MACD MFT, BBands and RSI based Forex Strategy This trading looks little baffling when you find so many indicators on trading chart. However, the fun part is, this strategy is actually very simple. A trader can go for 25 pips S/L as well as 25 pips T/P orders here. If you find yourself in a good profitable trading position, opt for partial closing & let the remaining part run with 15 pip stop. Rules of Forex Trading System X: Buy only if every indicator turns blue while price candle takes green color Sell only if every indicator turns red while price candle takes purple color This chart here will enable you to get a fair understanding of the entire process. As I mentioned previously, this strategy is just a breeze. There’re many other vital stuff on charts. You must use them diligently. A trader here can even set his/her S/L and T/P targets as per resistance and support levels. Just check out beforehand market hours. It’s a handy template. Forex Trading Strategy
This may appear to be a noob question, but read on carefully and please try and understand the point I'm trying to make! I'm hoping your answers might be helpful to people both learning Forex and looking to get into it, so please don't hate on me for this post. I am relatively new to FX and have learned about break and retest strategies, MACD crossovers and stop losses below structure and risk to reward ratios (usually going for 1:1 or 2/3:1) and so on. I say this only so you know I've a general (very basic) understanding of charts, price action etc. I definitely do NOT expect to step into the markets and instantly win a majority of my trades, however, to illustrate my thoughts please note the example below. If I am winning 2% on a winning trade and losing 1% on a losing trade (2:1 reward risk per trade), a strategy that wins just 50% of the time trading once per trading day would be +10% each month. (10 days of -1%, 10 days of +2%). +10% is a HUGE increase in accounts and if a $1000 account was +10% per month for 12 months the end of year balance would be over $3138.43 or a 213.84% return! This leads me to a theory that almost NO system can be returning 50% on a 2:1 reward risk, even with careful trade selection (let's say I monitor the 7 major pairs, gold and GBP/JPY as I do and pick one entry a day) Am I wrong? I appreciate it is a hypothetical example designed to make a point, but my thoughts are if you monitored lots of pairs and took only ONE entry a day, we might expect to win 50% of the time. Let's expand this further. I have seen numerous algos (can't name them but looking like they win at LEAST 50% of the time) which tempt me because they appear to indicate moves I could jump on and where I could pull a bunch of pips out of the market. However, there surely cannot be a holy grail or are people making this type of insane return? It cannot be as easy as buying an algo, signing up to $300,000 worth of FTMO funding and earning 10% per month for an easy $21,000 per month income with profit share. Or maybe it is and I'm just cynical?! I end up getting tempted by courses etc. in the hope that if I spent £400 on a good course it would open the door to what I need to do, but I'm nervous this is just another huge mistake. I genuinely would love to trade Forex for a living. Really I would. I hope it's possible and I hope to learn a strategy I can wash, rinse and repeat. I love watching videos and live streamers who seem to have a great understanding of what's going on but I wonder if it's really possible. It seems a million miles away but I'm determined to keep learning and trading. Reading your considered thoughts to this post would be helpful for me and I'm sure others and thank you for reading it.
Former investment bank FX trader: Risk management part II
Firstly, thanks for the overwhelming comments and feedback. Genuinely really appreciated. I am pleased 500+ of you find it useful. If you didn't read the first post you can do so here: risk management part I. You'll need to do so in order to make sense of the topic. As ever please comment/reply below with questions or feedback and I'll do my best to get back to you. Part II
Letting stops breathe
When to change a stop
Entering and exiting winning positions
Letting stops breathe
We talked earlier about giving a position enough room to breathe so it is not stopped out in day-to-day noise. Let’s consider the chart below and imagine you had a trailing stop. It would be super painful to miss out on the wider move just because you left a stop that was too tight. Imagine being long and stopped out on a meaningless retracement ... ouch! One simple technique is simply to look at your chosen chart - let’s say daily bars. And then look at previous trends and use the measuring tool. Those generally look something like this and then you just click and drag to measure. For example if we wanted to bet on a downtrend on the chart above we might look at the biggest retracement on the previous uptrend. That max drawdown was about 100 pips or just under 1%. So you’d want your stop to be able to withstand at least that. If market conditions have changed - for example if CVIX has risen - and daily ranges are now higher you should incorporate that. If you know a big event is coming up you might think about that, too. The human brain is a remarkable tool and the power of the eye-ball method is not to be dismissed. This is how most discretionary traders do it. There are also more analytical approaches. Some look at the Average True Range (ATR). This attempts to capture the volatility of a pair, typically averaged over a number of sessions. It looks at three separate measures and takes the largest reading. Think of this as a moving average of how much a pair moves. For example, below shows the daily move in EURUSD was around 60 pips before spiking to 140 pips in March. Conditions were clearly far more volatile in March. Accordingly, you would need to leave your stop further away in March and take a correspondingly smaller position size. ATR is available on pretty much all charting systems Professional traders tend to use standard deviation as a measure of volatility instead of ATR. There are advantages and disadvantages to both. Averages are useful but can be misleading when regimes switch (see above chart). Once you have chosen a measure of volatility, stop distance can then be back-tested and optimised. For example does 2x ATR work best or 5x ATR for a given style and time horizon? Discretionary traders may still eye-ball the ATR or standard deviation to get a feeling for how it has changed over time and what ‘normal’ feels like for a chosen study period - daily, weekly, monthly etc.
Reasons to change a stop
As a general rule you should be disciplined and not change your stops. Remember - losers average losers. This is really hard at first and we’re going to look at that in more detail later. There are some good reasons to modify stops but they are rare. One reason is if another risk management process demands you stop trading and close positions. We’ll look at this later. In that case just close out your positions at market and take the loss/gains as they are. Another is event risk. If you have some big upcoming data like Non Farm Payrolls that you know can move the market +/- 150 pips and you have no edge going into the release then many traders will take off or scale down their positions. They’ll go back into the positions when the data is out and the market has quietened down after fifteen minutes or so. This is a matter of some debate - many traders consider it a coin toss and argue you win some and lose some and it all averages out. Trailing stops can also be used to ‘lock in’ profits. We looked at those before. As the trade moves in your favour (say up if you are long) the stop loss ratchets with it. This means you may well end up ‘stopping out’ at a profit - as per the below example. The mighty trailing stop loss order It is perfectly reasonable to have your stop loss move in the direction of PNL. This is not exposing you to more risk than you originally were comfortable with. It is taking less and less risk as the trade moves in your favour. Trend-followers in particular love trailing stops. One final question traders ask is what they should do if they get stopped out but still like the trade. Should they try the same trade again a day later for the same reasons? Nope. Look for a different trade rather than getting emotionally wed to the original idea. Let’s say a particular stock looked cheap based on valuation metrics yesterday, you bought, it went down and you got stopped out. Well, it is going to look even better on those same metrics today. Maybe the market just doesn’t respect value at the moment and is driven by momentum. Wait it out. Otherwise, why even have a stop in the first place?
Entering and exiting winning positions
Take profits are the opposite of stop losses. They are also resting orders, left with the broker, to automatically close your position if it reaches a certain price. Imagine I’m long EURUSD at 1.1250. If it hits a previous high of 1.1400 (150 pips higher) I will leave a sell order to take profit and close the position. The rookie mistake on take profits is to take profit too early. One should start from the assumption that you will win on no more than half of your trades. Therefore you will need to ensure that you win more on the ones that work than you lose on those that don’t. Sad to say but incredibly common: retail traders often take profits way too early This is going to be the exact opposite of what your emotions want you to do. We are going to look at that in the Psychology of Trading chapter. Remember: let winners run. Just like stops you need to know in advance the level where you will close out at a profit. Then let the trade happen. Don’t override yourself and let emotions force you to take a small profit. A classic mistake to avoid. The trader puts on a trade and it almost stops out before rebounding. As soon as it is slightly in the money they spook and cut out, instead of letting it run to their original take profit. Do not do this.
Entering positions with limit orders
That covers exiting a position but how about getting into one? Take profits can also be left speculatively to enter a position. Sometimes referred to as “bids” (buy orders) or “offers” (sell orders). Imagine the price is 1.1250 and the recent low is 1.1205. You might wish to leave a bid around 1.2010 to enter a long position, if the market reaches that price. This way you don’t need to sit at the computer and wait. Again, typically traders will use tech analysis to identify attractive levels. Again - other traders will cluster with your orders. Just like the stop loss we need to bake that in. So this time if we know everyone is going to buy around the recent low of 1.1205 we might leave the take profit bit a little bit above there at 1.1210 to ensure it gets done. Sure it costs 5 more pips but how mad would you be if the low was 1.1207 and then it rallied a hundred points and you didn’t have the trade on?! There are two more methods that traders often use for entering a position. Scaling in is one such technique. Let’s imagine that you think we are in a long-term bulltrend for AUDUSD but experiencing a brief retracement. You want to take a total position of 500,000 AUD and don’t have a strong view on the current price action. You might therefore leave a series of five bids of 100,000. As the price moves lower each one gets hit. The nice thing about scaling in is it reduces pressure on you to pick the perfect level. Of course the risk is that not all your orders get hit before the price moves higher and you have to trade at-market. Pyramiding is the second technique. Pyramiding is for take profits what a trailing stop loss is to regular stops. It is especially common for momentum traders. Pyramiding into a position means buying more as it goes in your favour Again let’s imagine we’re bullish AUDUSD and want to take a position of 500,000 AUD. Here we add 100,000 when our first signal is reached. Then we add subsequent clips of 100,000 when the trade moves in our favour. We are waiting for confirmation that the move is correct. Obviously this is quite nice as we humans love trading when it goes in our direction. However, the drawback is obvious: we haven’t had the full amount of risk on from the start of the trend. You can see the attractions and drawbacks of both approaches. It is best to experiment and choose techniques that work for your own personal psychology as these will be the easiest for you to stick with and build a disciplined process around.
Risk:reward and win ratios
Be extremely skeptical of people who claim to win on 80% of trades. Most traders will win on roughly 50% of trades and lose on 50% of trades. This is why risk management is so important! Once you start keeping a trading journal you’ll be able to see how the win/loss ratio looks for you. Until then, assume you’re typical and that every other trade will lose money. If that is the case then you need to be sure you make more on the wins than you lose on the losses. You can see the effect of this below. A combination of win % and risk:reward ratio determine if you are profitable A typical rule of thumb is that a ratio of 1:3 works well for most traders. That is, if you are prepared to risk 100 pips on your stop you should be setting a take profit at a level that would return you 300 pips. One needn’t be religious about these numbers - 11 pips and 28 pips would be perfectly fine - but they are a guideline. Again - you should still use technical analysis to find meaningful chart levels for both the stop and take profit. Don’t just blindly take your stop distance and do 3x the pips on the other side as your take profit. Use the ratio to set approximate targets and then look for a relevant resistance or support level in that kind of region.
Not all returns are equal. Suppose you are examining the track record of two traders. Now, both have produced a return of 14% over the year. Not bad! The first trader, however, made hundreds of small bets throughout the year and his cumulative PNL looked like the left image below. The second trader made just one bet — he sold CADJPY at the start of the year — and his PNL looked like the right image below with lots of large drawdowns and volatility. Would you rather have the first trading record or the second? If you were investing money and betting on who would do well next year which would you choose? Of course all sensible people would choose the first trader. Yet if you look only at returns one cannot distinguish between the two. Both are up 14% at that point in time. This is where the Sharpe ratio helps . A high Sharpe ratio indicates that a portfolio has better risk-adjusted performance. One cannot sensibly compare returns without considering the risk taken to earn that return. If I can earn 80% of the return of another investor at only 50% of the risk then a rational investor should simply leverage me at 2x and enjoy 160% of the return at the same level of risk. This is very important in the context of Execution Advisor algorithms (EAs) that are popular in the retail community. You must evaluate historic performance by its risk-adjusted return — not just the nominal return. Incidentally look at the Sharpe ratio of ones that have been live for a year or more ... Otherwise an EA developer could produce two EAs: the first simply buys at 1000:1 leverage on January 1st ; and the second sells in the same manner. At the end of the year, one of them will be discarded and the other will look incredible. Its risk-adjusted return, however, would be abysmal and the odds of repeated success are similarly poor.
The Sharpe ratio works like this:
It takes the average returns of your strategy;
It deducts from these the risk-free rate of return i.e. the rate anyone could have got by investing in US government bonds with very little risk;
It then divides this total return by its own volatility - the more smooth the return the higher and better the Sharpe, the more volatile the lower and worse the Sharpe.
For example, say the return last year was 15% with a volatility of 10% and US bonds are trading at 2%. That gives (15-2)/10 or a Sharpe ratio of 1.3. As a rule of thumb a Sharpe ratio of above 0.5 would be considered decent for a discretionary retail trader. Above 1 is excellent. You don’t really need to know how to calculate Sharpe ratios. Good trading software will do this for you. It will either be available in the system by default or you can add a plug-in.
VAR is another useful measure to help with drawdowns. It stands for Value at Risk. Normally people will use 99% VAR (conservative) or 95% VAR (aggressive). Let’s say you’re long EURUSD and using 95% VAR. The system will look at the historic movement of EURUSD. It might spit out a number of -1.2%. A 5% VAR of -1.2% tells you you should expect to lose 1.2% on 5% of days, whilst 95% of days should be better than that This means it is expected that on 5 days out of 100 (hence the 95%) the portfolio will lose 1.2% or more. This can help you manage your capital by taking appropriately sized positions. Typically you would look at VAR across your portfolio of trades rather than trade by trade. Sharpe ratios and VAR don’t give you the whole picture, though. Legendary fund manager, Howard Marks of Oaktree, notes that, while tools like VAR and Sharpe ratios are helpful and absolutely necessary, the best investors will also overlay their own judgment. Investors can calculate risk metrics like VaR and Sharpe ratios (we use them at Oaktree; they’re the best tools we have), but they shouldn’t put too much faith in them. The bottom line for me is that risk management should be the responsibility of every participant in the investment process, applying experience, judgment and knowledge of the underlying investments.Howard Marks of Oaktree Capital What he’s saying is don’t misplace your common sense. Do use these tools as they are helpful. However, you cannot fully rely on them. Both assume a normal distribution of returns. Whereas in real life you get “black swans” - events that should supposedly happen only once every thousand years but which actually seem to happen fairly often. These outlier events are often referred to as “tail risk”. Don’t make the mistake of saying “well, the model said…” - overlay what the model is telling you with your own common sense and good judgment.
Coming up in part III
Available here Squeezes and other risks Market positioning Bet correlation Crap trades, timeouts and monthly limits *** Disclaimer:This content is not investment advice and you should not place any reliance on it. The views expressed are the author's own and should not be attributed to any other person, including their employer.
I am a Software Engineer / Data Scientist and I decided to give a go at automating a strategy based on the ParallaxFX strategy floating around and backtests the results, also due to some inspiration by Vanguer
I backtested on the majors 4H timeframe between January 2015 to January 2020.
I am only considering trades from the top and bottom bands for now.
Hello to whoever sees this I would like some advice. I am a 19 year old that started trading forex about a year and a half ago and I’ve learned a lot in that period of time. Ive took some extensive breaks in between this time period as well. I’ve tried trading pure price action, mechanical systems, zone to zone, different indicators and I just can’t seem to figure out what is the best style of trading for me. I feel like I’ve mastered risk management but I just can’t find a strategy that I can be consistent with. I need to get over the hump of becoming a consistently profitable trader. Could anyone provide some advice to help me get to that point? Any help is greatly appreciated.
When I first started trading, I used to add all indicators on my chart. MACD, RSI, super trend, ATR, ichimoku cloud, Bollinger Bands, everything! My chart was pretty messy. I understood nothing and my analysis was pretty much just a gamble. Nothing worked. DISCLOSURE- I've written this article on another sub reddit, if you've already read it, you make skip this one and come back tomorrow. Then I learned price action trading. And things started to change. It seemed difficult and unreliable at first. There's a saying in my country. "Bhav Bhagwan Che" it means "Price Is GOD". That holds true in the market. Amos Every indicator you see is based on price. RSI uses open/close price and so does moving average. MACD uses price. Price is what matters the most. Everything depends on the price, and then the indicators send a signal. Price Action trading is trading based on Candlestick patterns and support and resistance. You don't use any indicators (SMA sometimes), use plot trend lines and support and resistance zones, maybe Fibs or Pivot points. It is not 100% successful, but the win rate is quite high if you know how to analyse it correctly. How To Learn Price Action Trading? YouTube channels- 1. Trading with Rayner Teo. 2. Adam Khoo. 3. The Chart Guys. 4. The Trading Channel (and some other channels including regional ones). Books- 1. Technical Analysis Explained. 2. The trader's book of volume. 3. Trading price action trends. 4. Trading price action reversals. 5. Trading price actions ranges. 6. Naked forex. 7. Technical analysis of the financial markets. I think this is enough information to help you get started. Price Action trading includes a few parts.
Candlestick patterns You'll have to be able to spot a bullish engulfing or a bearish engulfing pattern. Or a doji or a morning star.
Chart Patterns. The flag, wedge, channels or triangles. These are often quite helpful in chart analysis without using indicators.
Support or Resistance. I've seen people draw 15 lines of support and resistance, this just makes your chart messy and you don't know where the price will take a support.
You can also you the demand and supply zone concept if you're more comfortable with that.
Volume. There's a quote "Boule precedes price". Volume analysis is a bit hard, but it's totally worth learning. Divergence is also a great concept.
Multiple time frames. To confirm a trend or find the long term support or resistance, you can use a higher time frame. Plus, it is more reliable and divergence is way stronger on it.
You can conclude everything to make a powerful system. Like if there's a divergence (price up volume down) and there's a major resistance on some upper level and a double top is formed, That's a very reliable strategy to go short. Combinations of various systems work very good imo. Does this mean that indicators are useless? No, I use moving averages and RSI quite frequently. Using price action and confirming it through indicators gives me a higher win rate. "Bhav Bhagwan Che". -Vikrant C.
Factset: How You can Invest in Hedge Funds’ Biggest Investment Tl;dr FactSet is the most undervalued widespread SaaS/IT solution stock that exists If any of you have relevant experience or are friends with people in Investment Banking/other high finance, you know that Factset is the lifeblood of their financial analysis toolkit if and when it’s not Bloomberg, which isn’t even publicly traded. Factset has been around since 1978 and it’s considered a staple like Bloomberg in many wealth management firms, and it offers some of the easiest to access and understandable financial data so many newer firms focused less on trading are switching to Factset because it has a lot of the same data Bloomberg offers for half the cost. When it comes to modern financial data, Factset outcompetes Reuters and arguably Bloomberg as well due to their API services which makes Factset much more preferable for quantitative divisions of banks/hedge funds as API integration with Python/R is the most important factor for vast data lakes of financial data, this suggests Factset will be much more prepared for programming making its way into traditional finance fields. According to Factset, their mission for data delivery is to: “Integrate the data you need with your applications, web portals, and statistical packages. Whether you need market, company, or alternative data, FactSet flexible data delivery services give you normalized data through APIs and a direct delivery of local copies of standard data feeds. Our unique symbology links and aggregates a variety of content sources to ensure consistency, transparency, and data integrity across your business. Build financial models and power customized applications with FactSet APIs in our developer portal”. Their technical focus for their data delivery system alone should make it stand out compared to Bloomberg, whose UI is far more outdated and complex on top of not being as technically developed as Factset’s. Factset is the key provider of buy-side portfolio analysis for IBs, Hedge funds, and Private Equity firms, and it’s making its way into non-quantitative hedge funds as well because quantitative portfolio management makes automation of risk management and the application of portfolio theory so much easier, and to top it off, Factset’s scenario analysis and simulation is unique in its class. Factset also is able to automate trades based on individual manager risk tolerance and ML optimization for Forex trading as well. Not only does Factset provide solutions for financial companies, they are branching out to all corporations now and providing quantitative analytics for them in the areas of “corporate development, M&A, strategy, treasury, financial planning and analysis, and investor relations workflows”. Factset will eventually in my opinion reach out to Insurance Risk Management a lot more in the future as that’s a huge industry which has yet to see much automation of risk management yet, and with the field wide open, Factset will be the first to take advantage without a shadow of a doubt. So let’s dig into the company’s financials now: Their latest 8k filing reported the following: Revenue increased 2.6%, or $9.6 million, to $374.1 million compared with $364.5 million for the same period in fiscal 2019. The increase is primarily due to higher sales of analytics, content and technology solutions (CTS) and wealth management solutions. Annual Subscription Value (ASV) plus professional services was $1.52 billion at May 31, 2020, compared with $1.45 billion at May 31, 2019. The organic growth rate, which excludes the effects of acquisitions, dispositions, and foreign currency movements, was 5.0%. The primary contributors to this growth rate were higher sales in FactSet's wealth and research workflow solutions and a price increase in the Company's international region Adjusted operating margin improved to 35.5% compared with 34.0% in the prior year period primarily as a result of reduced employee-related operating expenses due to the coronavirus pandemic. Diluted earnings per share (EPS) increased 11.0% to $2.63 compared with $2.37 for the same period in fiscal 2019. Adjusted diluted EPS rose 9.2% to $2.86 compared with $2.62 in the prior year period primarily driven by an improvement in operating results. The Company’s effective tax rate for the third quarter decreased to 15.0% compared with 18.6% a year ago, primarily due to an income tax expense in the prior year related to finalizing the Company's tax returns with no similar event for the three months ended May 31, 2020. FactSet increased its quarterly dividend by $0.05 per share or 7% to $0.77 marking the fifteenth consecutive year the Company has increased dividends, highlighting its continued commitment to returning value to shareholders. As you can see, there’s not much of a negative sign in sight here. It makes sense considering how FactSet’s FCF has never slowed down: https://preview.redd.it/frmtdk8e9hk51.png?width=276&format=png&auto=webp&s=1c0ff12539e0b2f9dbfda13d0565c5ce2b6f8f1a https://preview.redd.it/6axdb6lh9hk51.png?width=593&format=png&auto=webp&s=9af1673272a5a2d8df28f60f4707e948a00e5ff1 FactSet’s annual subscriptions and professional services have made its way to foreign and developing markets, and many of them are opting for FactSet’s cheaper services to reduce costs and still get copious amounts of data and models to work with. Here’s what FactSet had to say regarding its competitive position within the market of providing financial data in its last 10k: “Despite competing products and services, we enjoy high barriers to entry and believe it would be difficult for another vendor to quickly replicate the extensive databases we currently offer. Through our in-depth analytics and client service, we believe we can offer clients a more comprehensive solution with one of the broadest sets of functionalities, through a desktop or mobile user interface or through a standardized or bespoke data feed.” And FactSet is confident that their ML services cannot be replaced by anybody else in the industry either: “In addition, our applications, including our client support and service offerings, are entrenched in the workflow of many financial professionals given the downloading functions and portfolio analysis/screening capabilities offered. We are entrusted with significant amounts of our clients' own proprietary data, including portfolio holdings. As a result, our products have become central to our clients’ investment analysis and decision-making.” (https://last10k.com/sec-filings/fds#link_fullReport), if you read the full report and compare it to the most recent 8K, you’ll find that the real expenses this quarter were far lower than expected by the last 10k as there was a lower than expected tax rate and a 3% increase in expected operating margin from the expected figure as well. The company also reports a 90% customer retention rate over 15 years, so you know that they’re not lying when they say the clients need them for all sorts of financial data whether it’s for M&A or wealth management and Equity analysis: https://www.investopedia.com/terms/f/factset.asp https://preview.redd.it/yo71y6qj9hk51.png?width=355&format=png&auto=webp&s=a9414bdaa03c06114ca052304a26fae2773c3e45 FactSet also has remarkably good cash conversion considering it’s a subscription based company, a company structure which usually takes on too much leverage. Speaking of leverage, FDS had taken on a lot of leverage in 2015: https://preview.redd.it/oxaa1wel9hk51.png?width=443&format=png&auto=webp&s=13d60d2518980360c403364f7150392ab83d07d7 So what’s that about? Why were FactSet’s long term debts at 0 and all of a sudden why’d the spike up? Well usually for a company that’s non-cyclical and has a well-established product (like FactSet) leverage can actually be good at amplifying returns, so FDS used this to their advantage and this was able to help the share’s price during 2015. Also, as you can see debt/ebitda is beginning a rapid decline anyway. This only adds to my theory that FactSet is trying to expand into new playing fields. FactSet obviously didn’t need the leverage to cover their normal costs, because they have always had consistently growing margins and revenue so the debt financing was only for the sake of financing growth. And this debt can be considered covered and paid off, considering the net income growth of 32% between 2018 and 2019 alone and the EPS growth of 33% https://preview.redd.it/e4trju3p9hk51.png?width=387&format=png&auto=webp&s=6f6bee15f836c47e73121054ec60459f147d353e EBITDA has virtually been exponential for FactSet for a while because of the bang-for-buck for their well-known product, but now as FactSet ventures into algorithmic trading and corporate development the scope for growth is broadly expanded. https://preview.redd.it/yl7f58tr9hk51.png?width=489&format=png&auto=webp&s=68906b9ecbcf6d886393c4ff40f81bdecab9e9fd P/E has declined in the past 2 years, making it a great time to buy. https://preview.redd.it/4mqw3t4t9hk51.png?width=445&format=png&auto=webp&s=e8d719f4913883b044c4150f11b8732e14797b6d Increasing ROE despite lowering of leverage post 2016 https://preview.redd.it/lt34avzu9hk51.png?width=441&format=png&auto=webp&s=f3742ed87cd1c2ccb7a3d3ee71ae8c7007313b2b Mountains of cash have been piling up in the coffers increasing chances of increased dividends for shareholders (imo dividend is too low right now, but increasing it will tempt more investors into it), and on top of that in the last 10k a large buyback expansion program was implemented for $210m worth of shares, which shows how confident they are in the company itself. https://preview.redd.it/fliirmpx9hk51.png?width=370&format=png&auto=webp&s=1216eddeadb4f84c8f4f48692a2f962ba2f1e848 SGA expense/Gross profit has been declining despite expansion of offices I’m a bit concerned about the skin in the game leadership has in this company, since very few executives/board members have significant holdings in the company, but the CEO himself is a FactSet veteran, and knows his way around the company. On top of that, Bloomberg remains king for trading and the fixed income security market, and Reuters beats out FactSet here as well. If FactSet really wants to increase cash flow sources, the expansion into insurance and corp dev has to be successful. Summary: FactSet has a lot of growth still left in its industry which is already fast-growing in and of itself, and it only has more potential at its current valuation. Earnings September 24th should be a massive beat due to investment banking demand and growth plus Hedge fund requirements for data and portfolio management hasn’t gone anywhere and has likely increased due to more market opportunities to buy-in. Calls have shitty greeks, but if you're ballsy October 450s LOL, I'm holding shares I’d say it’s a great long term investment, and it should at least be on your watchlist.
ARE YOU INTERESTED IN EARNING A CONSISTENT INCOME BY TRADING ONLINE. Then trading Option/Forex is for you !!! I can help teach/trade and manage your account with my best strategy on FOREX/OPTIONS TRADING !!! With my good trading strategy Its possible for you to earn up to $15,000 or more than in 1 week(7 trading days).Register with our trading company today for free and stand a chance to be taught/traded for by a professional trader that will manage your account with the profitable system that is 100% accurate, transparent and helps you win always. Am only telling you this because of the fact that there are simple and legitimate ways of making money online as people usually get bored of the 9-5 jobs DM ME NOW... ASK ME HOW !!!
My trading is getting easier, and I'm getting worried.
I have some years studying trading and forex. Some years ago traded a succesful strategy in the 4H timeframe. It went good, it made 6 positive months, just one almost breakeven. But at some point the system edge was lost and started to get breakeven only. Then I understand that markets change and a system lose its edge with time. Then I started a new research for a system for day trading, that is robust, and it is a high probability system. In this way I can trade with a bigger lot, and if it starts failing, then stop. Now I've been trading a new system in the past 2 weeks. It is day trading with technical analysis. I think I found that system. My first week was a 10% return. My second week has been 7% return. I am the first to know that I could be pure luck. But I am feeling it very consistent and easy. I feel my trading very natural now. But at the same time I'm afraid that I am just deluded.
How much money would it cost to setup high-frequency trading?
I worked with many HFT startups and I have a pretty good idea of the initial costs that such trading shops have. Data: High-frequency strategies are data-intensive, so you need to get the best data providers at the tick level (level 3). That’s expensive. Depending on the market you are in (forex, futures, bonds, etc) the cost could vary. FX is even more complex, because of its highly fragmented nature, so they will need to have a broad view of all of them. Each provider cost could start from $5k per month each, up to $50k per month Servers: You will need power. A decent server (please don’t use the cloud), could cost you 20k at least. It needs to have 32-cores at least. You can rent a dedicated server, and its cost could start from $2k per month Collocation: That powerful server must be placed inside a collocated environment. The idea is to reduce the latency as much as you can, so being close to the exchanges/venues is the best choice. These data centers will charge you for your server space and for the connectivity you use (cross-connection). This varies considerably depending on the markets you are in. Software: this would be the most expensive piece of your setup. Remember, that the software is the brain of your operation. Not only needs to get ALL the data from the exchanges/venues but normalize it, store it, manipulate it, and prepare it to be consumed by your strategies(s) that will be doing tons of different calculations based on the data they receive. And all that must be done in a fraction of milliseconds (hopefully within 10–50 microseconds) On top of that, you must be sure, that you will have all the different modules in place: price aggregators, order management systems (OMS), execution management systems (EMS), smart order routing (SOR), liquidity manager (LM), risk management systems (RMS). and any interface you may need (to databases, storage, monitoring systems, reporting, etc) Cost-wise, all of this will depends on what you choose. If you go with an off-the-shelf solution (not recommended, cheaper, you don’t own anything, slow), or you start your own development (time to market +1 year, very costly). The cost could vary between $300K to $1M People: you will need human resources. This is not a one-guy operation. You will need to have software engineers, quantitative analysts, and researchers. Think about 150k /year at the low end. Brokers/Prime Brokers: you will need to open up a brokerage account to have access to the trading venues. They will require you to have a minimum capital to trade (besides the commissions/fees they may charge). So, that adds up to your initial setup cost. Conclusions It’s a very lucrative business but is hard to get started. Usually, startups try to start small and grow as they see profits, but that always falls into failure. If you do that, you will fail to have all the above points I’ve listed. Your initial investment is high, and keeping in mind that after having all these startup costs, all your infrastructure in place, and the software ready to run, your first profitable trades could start to come in after 6 to 12 months of operations. I hope my question is not as vague as the others… Please, let me know if I was missing something else, so we can add it to this list 😎 Ariel Silahian http://www.sisSoftwareFactory.com/blog
Disclaimer: None of this is financial advice. I have no idea what I'm doing. Please do your own research or you will certainly lose money. I'm not a statistician, data scientist, well-seasoned trader, or anything else that would qualify me to make statements such as the below with any weight behind them. Take them for the incoherent ramblings that they are. TL;DR at the bottom for those not interested in the details. This is a bit of a novel, sorry about that. It was mostly for getting my own thoughts organized, but if even one person reads the whole thing I will feel incredibly accomplished.
For those of you not familiar, please see the various threads on this trading system here. I can't take credit for this system, all glory goes to ParallaxFX! I wanted to see how effective this system was at H1 for a couple of reasons: 1) My current broker is TD Ameritrade - their Forex minimum is a mini lot, and I don't feel comfortable enough yet with the risk to trade mini lots on the higher timeframes(i.e. wider pip swings) that ParallaxFX's system uses, so I wanted to see if I could scale it down. 2) I'm fairly impatient, so I don't like to wait days and days with my capital tied up just to see if a trade is going to win or lose. This does mean it requires more active attention since you are checking for setups once an hour instead of once a day or every 4-6 hours, but the upside is that you trade more often this way so you end up winning or losing faster and moving onto the next trade. Spread does eat more of the trade this way, but I'll cover this in my data below - it ends up not being a problem. I looked at data from 6/11 to 7/3 on all pairs with a reasonable spread(pairs listed at bottom above the TL;DR). So this represents about 3-4 weeks' worth of trading. I used mark(mid) price charts. Spreadsheet link is below for anyone that's interested.
I'm pretty much using ParallaxFX's system textbook, but since there are a few options in his writeups, I'll include all the discretionary points here:
I'm using the stop entry version - so I wait for the price to trade beyond the confirmation candle(in the direction of my trade) before entering. I don't have any data to support this decision, but I've always preferred this method over retracement-limit entries. Maybe I just like the feeling of a higher winrate even though there can be greater R:R using a limit entry. Variety is the spice of life.
I put my stop loss right at the opposite edge of the confirmation candle. NOT at the edge of the 2-candle pattern that makes up the system. I'll get into this more below - not enough trades are saved to justify the wider stops. (Wider stop means less $ per pip won, assuming you still only risk 1%).
All my profit/loss statistics are based on a 1% risk per trade. Because 1 is real easy to multiply.
There are definitely some questionable trades in here, but I tried to make it as mechanical as possible for evaluation purposes. They do fit the definitions of the system, which is why I included them. You could probably improve the winrate by being more discretionary about your trades by looking at support/resistance or other techniques.
I didn't use MBB much for either entering trades, or as support/resistance indicators. Again, trying to be pretty mechanical here just for data collection purposes. Plus, we all make bad trading decisions now and then, so let's call it even.
As stated in the title, this is for H1 only. These results may very well not play out for other time frames - who knows, it may not even work on H1 starting this Monday. Forex is an unpredictable place.
I collected data to show efficacy of taking profit at three different levels: -61.8%, -100% and -161.8% fib levels described in the system using the passive trade management method(set it and forget it). I'll have more below about moving up stops and taking off portions of a position.
And now for the fun. Results!
Total Trades: 241
TP at -61.8%: 177 out of 241: 73.44%
TP at -100%: 156 out of 241: 64.73%
TP at -161.8%: 121 out of 241: 50.20%
Adjusted Proft % (takes spread into account):
TP at -61.8%: 5.22%
TP at -100%: 23.55%
TP at -161.8%: 29.14%
As you can see, a higher target ended up with higher profit despite a much lower winrate. This is partially just how things work out with profit targets in general, but there's an additional point to consider in our case: the spread. Since we are trading on a lower timeframe, there is less overall price movement and thus the spread takes up a much larger percentage of the trade than it would if you were trading H4, Daily or Weekly charts. You can see exactly how much it accounts for each trade in my spreadsheet if you're interested. TDA does not have the best spreads, so you could probably improve these results with another broker. EDIT: I grabbed typical spreads from other brokers, and turns out while TDA is pretty competitive on majors, their minors/crosses are awful! IG beats them by 20-40% and Oanda beats them 30-60%! Using IG spreads for calculations increased profits considerably (another 5% on top) and Oanda spreads increased profits massively (another 15%!). Definitely going to be considering another broker than TDA for this strategy. Plus that'll allow me to trade micro-lots, so I can be more granular(and thus accurate) with my position sizing and compounding.
A Note on Spread
As you can see in the data, there were scenarios where the spread was 80% of the overall size of the trade(the size of the confirmation candle that you draw your fibonacci retracements over), which would obviously cut heavily into your profits. Removing any trades where the spread is more than 50% of the trade width improved profits slightly without removing many trades, but this is almost certainly just coincidence on a small sample size. Going below 40% and even down to 30% starts to cut out a lot of trades for the less-common pairs, but doesn't actually change overall profits at all(~1% either way). However, digging all the way down to 25% starts to really make some movement. Profit at the -161.8% TP level jumps up to 37.94% if you filter out anything with a spread that is more than 25% of the trade width! And this even keeps the sample size fairly large at 187 total trades. You can get your profits all the way up to 48.43% at the -161.8% TP level if you filter all the way down to only trades where spread is less than 15% of the trade width, however your sample size gets much smaller at that point(108 trades) so I'm not sure I would trust that as being accurate in the long term. Overall based on this data, I'm going to only take trades where the spread is less than 25% of the trade width. This may bias my trades more towards the majors, which would mean a lot more correlated trades as well(more on correlation below), but I think it is a reasonable precaution regardless.
Time of Day
Time of day had an interesting effect on trades. In a totally predictable fashion, a vast majority of setups occurred during the London and New York sessions: 5am-12pm Eastern. However, there was one outlier where there were many setups on the 11PM bar - and the winrate was about the same as the big hours in the London session. No idea why this hour in particular - anyone have any insight? That's smack in the middle of the Tokyo/Sydney overlap, not at the open or close of either. On many of the hour slices I have a feeling I'm just dealing with small number statistics here since I didn't have a lot of data when breaking it down by individual hours. But here it is anyway - for all TP levels, these three things showed up(all in Eastern time):
7pm-4am: Fewer setups, but winrate high.
5am-6am: Lots of setups, but but winrate low.
12pm-3pm Medium number of setups, but winrate low.
I don't have any reason to think these timeframes would maintain this behavior over the long term. They're almost certainly meaningless. EDIT: When you de-dup highly correlated trades, the number of trades in these timeframes really drops, so from this data there is no reason to think these timeframes would be any different than any others in terms of winrate. That being said, these time frames work out for me pretty well because I typically sleep 12am-7am Eastern time. So I automatically avoid the 5am-6am timeframe, and I'm awake for the majority of this system's setups.
Moving stops up to breakeven
This section goes against everything I know and have ever heard about trade management. Please someone find something wrong with my data. I'd love for someone to check my formulas, but I realize that's a pretty insane time commitment to ask of a bunch of strangers. Anyways. What I found was that for these trades moving stops up...basically at all...actually reduced the overall profitability. One of the data points I collected while charting was where the price retraced back to after hitting a certain milestone. i.e. once the price hit the -61.8% profit level, how far back did it retrace before hitting the -100% profit level(if at all)? And same goes for the -100% profit level - how far back did it retrace before hitting the -161.8% profit level(if at all)? Well, some complex excel formulas later and here's what the results appear to be. Emphasis on appears because I honestly don't believe it. I must have done something wrong here, but I've gone over it a hundred times and I can't find anything out of place.
Moving SL up to 0% when the price hits -61.8%, TP at -100%
Adjusted Proft % (takes spread into account): 5.36%
Taking half position off at -61.8%, moving SL up to 0%, TP remaining half at -100%
Adjusted Proft % (takes spread into account): -1.01% (yes, a net loss)
Now, you might think exactly what I did when looking at these numbers: oof, the spread killed us there right? Because even when you move your SL to 0%, you still end up paying the spread, so it's not truly "breakeven". And because we are trading on a lower timeframe, the spread can be pretty hefty right? Well even when I manually modified the data so that the spread wasn't subtracted(i.e. "Breakeven" was truly +/- 0), things don't look a whole lot better, and still way worse than the passive trade management method of leaving your stops in place and letting it run. And that isn't even a realistic scenario because to adjust out the spread you'd have to move your stoploss inside the candle edge by at least the spread amount, meaning it would almost certainly be triggered more often than in the data I collected(which was purely based on the fib levels and mark price). Regardless, here are the numbers for that scenario:
Moving SL up to 0% when the price hits -61.8%, TP at -100%
Winrate(breakeven doesn't count as a win): 46.4%
Adjusted Proft % (takes spread into account): 17.97%
Taking half position off at -61.8%, moving SL up to 0%, TP remaining half at -100%
Winrate(breakeven doesn't count as a win): 65.97%
Adjusted Proft % (takes spread into account): 11.60%
From a literal standpoint, what I see behind this behavior is that 44 of the 69 breakeven trades(65%!) ended up being profitable to -100% after retracing deeply(but not to the original SL level), which greatly helped offset the purely losing trades better than the partial profit taken at -61.8%. And 36 went all the way back to -161.8% after a deep retracement without hitting the original SL. Anyone have any insight into this? Is this a problem with just not enough data? It seems like enough trades that a pattern should emerge, but again I'm no expert. I also briefly looked at moving stops to other lower levels (78.6%, 61.8%, 50%, 38.2%, 23.6%), but that didn't improve things any. No hard data to share as I only took a quick look - and I still might have done something wrong overall. The data is there to infer other strategies if anyone would like to dig in deep(more explanation on the spreadsheet below). I didn't do other combinations because the formulas got pretty complicated and I had already answered all the questions I was looking to answer.
2-Candle vs Confirmation Candle Stops
Another interesting point is that the original system has the SL level(for stop entries) just at the outer edge of the 2-candle pattern that makes up the system. Out of pure laziness, I set up my stops just based on the confirmation candle. And as it turns out, that is much a much better way to go about it. Of the 60 purely losing trades, only 9 of them(15%) would go on to be winners with stops on the 2-candle formation. Certainly not enough to justify the extra loss and/or reduced profits you are exposing yourself to in every single other trade by setting a wider SL. Oddly, in every single scenario where the wider stop did save the trade, it ended up going all the way to the -161.8% profit level. Still, not nearly worth it.
As I've said many times now, I'm really not qualified to be doing an analysis like this. This section in particular. Looking at shared currency among the pairs traded, 74 of the trades are correlated. Quite a large group, but it makes sense considering the sort of moves we're looking for with this system. This means you are opening yourself up to more risk if you were to trade on every signal since you are technically trading with the same underlying sentiment on each different pair. For example, GBP/USD and AUD/USD moving together almost certainly means it's due to USD moving both pairs, rather than GBP and AUD both moving the same size and direction coincidentally at the same time. So if you were to trade both signals, you would very likely win or lose both trades - meaning you are actually risking double what you'd normally risk(unless you halve both positions which can be a good option, and is discussed in ParallaxFX's posts and in various other places that go over pair correlation. I won't go into detail about those strategies here). Interestingly though, 17 of those apparently correlated trades ended up with different wins/losses. Also, looking only at trades that were correlated, winrate is 83%/70%/55% (for the three TP levels). Does this give some indication that the same signal on multiple pairs means the signal is stronger? That there's some strong underlying sentiment driving it? Or is it just a matter of too small a sample size? The winrate isn't really much higher than the overall winrates, so that makes me doubt it is statistically significant. One more funny tidbit: EUCAD netted the lowest overall winrate: 30% to even the -61.8% TP level on 10 trades. Seems like that is just a coincidence and not enough data, but dang that's a sucky losing streak. EDIT: WOW I spent some time removing correlated trades manually and it changed the results quite a bit. Some thoughts on this below the results. These numbers also include the other "What I will trade" filters. I added a new worksheet to my data to show what I ended up picking.
Total Trades: 75
TP at -61.8%: 84.00%
TP at -100%: 73.33%
TP at -161.8%: 60.00%
Moving SL up to 0% when the price hits -61.8%, TP at -100%: 53.33%
Taking half position off at -61.8%, moving SL up to 0%, TP remaining half at -100%: 53.33% (yes, oddly the exact same winrate. but different trades/profits)
Adjusted Proft % (takes spread into account):
TP at -61.8%: 18.13%
TP at -100%: 26.20%
TP at -161.8%: 34.01%
Moving SL up to 0% when the price hits -61.8%, TP at -100%: 19.20%
Taking half position off at -61.8%, moving SL up to 0%, TP remaining half at -100%: 17.29%
To do this, I removed correlated trades - typically by choosing those whose spread had a lower % of the trade width since that's objective and something I can see ahead of time. Obviously I'd like to only keep the winning trades, but I won't know that during the trade. This did reduce the overall sample size down to a level that I wouldn't otherwise consider to be big enough, but since the results are generally consistent with the overall dataset, I'm not going to worry about it too much. I may also use more discretionary methods(support/resistance, quality of indecision/confirmation candles, news/sentiment for the pairs involved, etc) to filter out correlated trades in the future. But as I've said before I'm going for a pretty mechanical system. This brought the 3 TP levels and even the breakeven strategies much closer together in overall profit. It muted the profit from the high R:R strategies and boosted the profit from the low R:R strategies. This tells me pair correlation was skewing my data quite a bit, so I'm glad I dug in a little deeper. Fortunately my original conclusion to use the -161.8 TP level with static stops is still the winner by a good bit, so it doesn't end up changing my actions. There were a few times where MANY (6-8) correlated pairs all came up at the same time, so it'd be a crapshoot to an extent. And the data showed this - often then won/lost together, but sometimes they did not. As an arbitrary rule, the more correlations, the more trades I did end up taking(and thus risking). For example if there were 3-5 correlations, I might take the 2 "best" trades given my criteria above. 5+ setups and I might take the best 3 trades, even if the pairs are somewhat correlated. I have no true data to back this up, but to illustrate using one example: if AUD/JPY, AUD/USD, CAD/JPY, USD/CAD all set up at the same time (as they did, along with a few other pairs on 6/19/20 9:00 AM), can you really say that those are all the same underlying movement? There are correlations between the different correlations, and trying to filter for that seems rough. Although maybe this is a known thing, I'm still pretty green to Forex - someone please enlighten me if so! I might have to look into this more statistically, but it would be pretty complex to analyze quantitatively, so for now I'm going with my gut and just taking a few of the "best" trades out of the handful. Overall, I'm really glad I went further on this. The boosting of the B/E strategies makes me trust my calculations on those more since they aren't so far from the passive management like they were with the raw data, and that really had me wondering what I did wrong.
What I will trade
Putting all this together, I am going to attempt to trade the following(demo for a bit to make sure I have the hang of it, then for keeps):
"System Details" I described above.
TP at -161.8%
Static SL at opposite side of confirmation candle - I won't move stops up to breakeven.
Trade only 7am-11am and 4pm-11pm signals.
Nothing where spread is more than 25% of trade width.
Looking at the data for these rules, test results are:
Adjusted Proft % (takes spread into account): 47.43%
I'll be sure to let everyone know how it goes!
Other Technical Details
ATR is only slightly elevated in this date range from historical levels, so this should fairly closely represent reality even after the COVID volatility leaves the scalpers sad and alone.
The sample size is much too small for anything really meaningful when you slice by hour or pair. I wasn't particularly looking to test a specific pair here - just the system overall as if you were going to trade it on all pairs with a reasonable spread.
Here's the spreadsheet for anyone that'd like it. (EDIT: Updated some of the setups from the last few days that have fully played out now. I also noticed a few typos, but nothing major that would change the overall outcomes. Regardless, I am currently reviewing every trade to ensure they are accurate.UPDATE: Finally all done. Very few corrections, no change to results.) I have some explanatory notes below to help everyone else understand the spiraled labyrinth of a mind that put the spreadsheet together.
I'm on the East Coast in the US, so the timestamps are Eastern time.
Time stamp is from the confirmation candle, not the indecision candle. So 7am would mean the indecision candle was 6:00-6:59 and the confirmation candle is 7:00-7:59 and you'd put in your order at 8:00.
I found a couple AM/PM typos as I was reviewing the data, so let me know if a trade doesn't make sense and I'll correct it.
Insanely detailed spreadsheet notes
For you real nerds out there. Here's an explanation of what each column means:
Pair - duh
Date/Time - Eastern time, confirmation candle as stated above
Win to -61.8%? - whether the trade made it to the -61.8% TP level before it hit the original SL.
Win to -100%? - whether the trade made it to the -100% TP level before it hit the original SL.
Win to -161.8%? - whether the trade made it to the -161.8% TP level before it hit the original SL.
Retracement level between -61.8% and -100% - how deep the price retraced after hitting -61.8%, but before hitting -100%. Be careful to look for the negative signs, it's easy to mix them up. Using the fib% levels defined in ParallaxFX's original thread. A plain hyphen "-" means it did not retrace, but rather went straight through -61.8% to -100%. Positive 100 means it hit the original SL.
Retracement level between -100% and -161.8% - how deep the price retraced after hitting -100%, but before hitting -161.8%. Be careful to look for the negative signs, it's easy to mix them up. Using the fib% levels defined in ParallaxFX's original thread. A plain hyphen "-" means it did not retrace, but rather went straight through -100% to -161.8%. Positive 100 means it hit the original SL.
Trade Width(Pips) - the size of the confirmation candle, and thus the "width" of your trade on which to determine position size, draw fib levels, etc.
Loser saved by 2 candle stop? - for all losing trades, whether or not the 2-candle stop loss would have saved the trade and how far it ended up getting if so. "No" means it didn't save it, N/A means it wasn't a losing trade so it's not relevant.
Spread(ThinkorSwim) - these are typical spreads for these pairs on ToS.
Spread % of Width - How big is the spread compared to the trade width? Not used in any calculations, but interesting nonetheless.
True Risk(Trade Width + Spread) - I set my SL at the opposite side of the confirmation candle knowing that I'm actually exposing myself to slightly more risk because of the spread(stop order = market order when submitted, so you pay the spread). So this tells you how many pips you are actually risking despite the Trade Width. I prefer this over setting the stop inside from the edge of the candle because some pairs have a wide spread that would mess with the system overall. But also many, many of these trades retraced very nearly to the edge of the confirmation candle, before ending up nicely profitable. If you keep your risk per trade at 1%, you're talking a true risk of, at most, 1.25% (in worst-case scenarios with the spread being 25% of the trade width as I am going with above).
Win or Loss in %(1% risk) including spread TP -61.8% - not going to go into huge detail, see the spreadsheet for calculations if you want. But, in a nutshell, if the trade was a win to 61.8%, it returns a positive # based on 61.8% of the trade width, minus the spread. Otherwise, it returns the True Risk as a negative. Both normalized to the 1% risk you started with.
Win or Loss in %(1% risk) including spread TP -100% - same as the last, but 100% of Trade Width.
Win or Loss in %(1% risk) including spread TP -161.8% - same as the last, but 161.8% of Trade Width.
Win or Loss in %(1% risk) including spread TP -100%, and move SL to breakeven at 61.8% - uses the retracement level columns to calculate profit/loss the same as the last few columns, but assuming you moved SL to 0% fib level after price hit -61.8%. Then full TP at 100%.
Win or Loss in %(1% risk) including spread take off half of position at -61.8%, move SL to breakeven, TP 100% - uses the retracement level columns to calculate profit/loss the same as the last few columns, but assuming you took of half the position and moved SL to 0% fib level after price hit -61.8%. Then TP the remaining half at 100%.
Overall Growth(-161.8% TP, 1% Risk) - pretty straightforward. Assuming you risked 1% on each trade, what the overall growth level would be chronologically(spreadsheet is sorted by date).
Based on the reasonable rules I discovered in this backtest:
Date range: 6/11-7/3
Adjusted Proft % (takes spread into account): 47.43%
Demo Trading Results
Since this post, I started demo trading this system assuming a 5k capital base and risking ~1% per trade. I've added the details to my spreadsheet for anyone interested. The results are pretty similar to the backtest when you consider real-life conditions/timing are a bit different. I missed some trades due to life(work, out of the house, etc), so that brought my total # of trades and thus overall profit down, but the winrate is nearly identical. I also closed a few trades early due to various reasons(not liking the price action, seeing support/resistance emerge, etc). A quick note is that TD's paper trade system fills at the mid price for both stop and limit orders, so I had to subtract the spread from the raw trade values to get the true profit/loss amount for each trade. I'm heading out of town next week, then after that it'll be time to take this sucker live!
Date range: 7/9-7/30
Adjusted Proft % (takes spread into account): 20.73%
Starting Balance: $5,000
Ending Balance: $6,036.51
Live Trading Results
I started live-trading this system on 8/10, and almost immediately had a string of losses much longer than either my backtest or demo period. Murphy's law huh? Anyways, that has me spooked so I'm doing a longer backtest before I start risking more real money. It's going to take me a little while due to the volume of trades, but I'll likely make a new post once I feel comfortable with that and start live trading again.
eToro: impressions, doubts and (ignored) lessons from copy trading
(no promotional content, no affiliate links) Hi, exactly four years ago, I started copying eToro investors / traders that I selected using the broker's built-in search engine (profitable in last two years, already being copied by others), followed by manual filtering, to take into account fluctuations in yearly returns, composition of their portfolios etc. With that, I got a list of 10 people whom I started to copy on a demo account: https://drive.google.com/file/d/1u52f0XHfr-LauIscKcFDYF0yGTTUr6VY/view?usp=sharing In the screenshot you can see that in case of the first two of them the amount invested was $10,000, while for the rest it was just $100. This is because I started copying the first two a couple of weeks earlier; eventually I changed this into $100 the same day I made the screenshot and this is when my calculations start - so this thing is irrelevant, I just cannot travel in time to make another screenshot. What I did after that? Well, within the next six weeks my profits oscillated between -$11 and +$9.50 (the biggest profit was on Nov 9, a day after US presidential elections). I found this "boring" and discontinued experimenting with copy trading. Today I looked back at those ten traders. Here is what I found. Firstly, seven of them are not with eToro anymore; investorNo1, Simple-Stock-Mkt, tradingrelax, 4exPirate, primit, Gallojack, xjurokx. The other three traders are:
toppertrader: not being copied by anyone and for a good reason: his loss this year alone is 61.16%!
Jean-marcLenfant: copied by only 67 people; his loss this year is -1.09% but in general he is quite successful, with yearly profits ranging from 3.57% to 7.32%.
Girem2: he has no copiers, his profit this year is 41.45% but in 2018 he experienced a loss of 83.15%!
My observations and thoughts are as follows:
Seven out of ten traders are not with eToro anymore, which makes me wonder why. I have no proof but my guess is they simply performed poorly, lost their copiers and closed their accounts. This is already alarming but what if they opened another account? Or, even worse, multiple accounts? They could be investing small money and try different risky approaches, hoping that at least one account will turn out profitable in the long turn, attracting potential copiers. (I'm not claiming that those 7 particular traders did this, it's just my general suspicion regarding some of eToro traders)
I'm unable to calculate what would be my profit if I never stopped copying them, because I cannot check at what day and with what profit those seven traders left eToro. I'm guessing this would be an immense loss. On the other hand, considering the three traders who are still with eToro, I would lose more than a quarter of my assets!
What now? I must be a quite adventurous person or at least an incorrigible optimist, because a month ago (exactly on Aug 26th) I started copying three traders with real money. Here is who they are. rubymza (Heloise Greeff)
invests in stocks, with GOOG, INTC, BLDP, MA, MSFT, AMZN, V, MU, IBM and NXPI making up 50.3% of her portfolio (allocation of each of them is in between 3.02% and 6.85%)
active since 2016 (only the year 2016 ended with a loss)
has 3044 copiers and $2M-$5M of copy assets under management
strategy (her own words): "My investing strategy focusses mostly on US indices, tech and pharma, promising future (5-10years) growth. My trades are based on technical analysis using machine learning to understand patterns and trends in the markets. I prefer to keep a diverse portfolio to spread risk while achieving great returns."
he is a Forex trader, making typically 21 trades per week; his favorite currency pairs are EURCHF (12% of trades), CADCHF and GBPUSD; the trades, however, typically make up below 5% of his portfolio (at least whenever I'm checking it), making most of my funds unused
active since January 2017: surprisingly enough, he has every single month profitable, though monthly profits are in the range of 0.03% to 3.34% only
has 8977 copiers and more than $5M of copy assets under management
strategy (his own words): "I monitor currency pairs all day to find the best entry. There is some management/scaling position for perfect entry. The risk control is a big part of my strategy," (quite vague, to be honest)
commodities compose 76% of his portfolio and his favorite assets are Gold and Oil (at the moment, Gold makes up half of invested amount)
active since July 2016, with the following yearly profits, starting from 2016: 6.56%, 10.05%, 13.09%, 32.26% and -2.03% (the current year)
has 1493 copiers and $1M-$2M of copy assets under management
strategy (his own words): "My system is based on patterns, and a variety of technical analysis tools and some fundamental analysis. I primarily trade in commodities. " (quite vague as well)
own experience: my profit with rayvahey is 2.56%
What was my strategy to hand-pick these particular traders? First I did some basic scanning using eToro's built-in search engine. The most important filter was that the trader was profitable within the last two years: unfortunately, eToro does not allow to reach details of earlier performance automatically. To know how the trader performed before 2019, I had to look at stats in the profile of each of them. I was also taking into account how often they trade (to avoid those who do only a couple of trades yearly), whether they were trading recently and whether they write posts regularly in their feed. With this, I got a list of fifteen candidates to copy:
As you already know, I finally chose three of them. Rubymza seemed to be the most trustworthy stock trader, based on profits, posts feed and regular trading, among other things. Regarding OlivierDanvel, his uniqueness is the ability to record continuous profits with the Forex market. Finally, with rayvahey I wanted to increase my exposure to the commodities market. Wish me good luck! Michael P.S. You might find those copy-trading related readings interesting:
This thread is the direct continuation of my previous entry, which you can find here. I have the feeling my rambles may be long, so I'm not going to repeat anything I already said in my previous post for the sake of keeping this brief. What is this? I am backtesting the strategy shared by ParallaxFx. I have just completed my second run of testing, and I am here to share my results with those who are interested. If you want to read more about the strategy, go to my previous thread where I linked it. What changed? Instead of using a fixed target of the -100.0 Fibonacci extension, I tracked both the -61.8 and the -100.0 targets. ParallaxFx used the -61.8 as a target, but never tried the second one, so I wanted to compare the two and see what happens. Where can I see your backtested result? I am going to do something I hope I won't regret and share the link to my spreadsheet. Hopefully I won't be doxxed, but I think I should be fine. You can find my spreadsheet at this link. There are a lot of entries, so it may take a while for them to load. In the "Trades" tab, you will find every trade I backtested with an attached screenshot and the results it would have had with the extended and the unextended target. You can see the UNCOMPOUNDED equity curve in the Summary tab, together with the overall statistics for the system. What was the sample size? I backtested on the Daily chart, from January 2017 to December 2019, over 28 currency pairs. I took a total of 310 trades - although keep in mind that every position is most often composed by two entries, meaning that you can roughly halve this number. What is the bottom line? If you're not interested in the details, here are the stats of the strategy based on how I traded it.
Extended: 223.46 R of return, 2.34 of profit factor, 0.72 R of expected value, 46.13% winrate. The average win is 2.72 R while the average loss is -1.00 R.
Unextended: 172.20 R of return, 2.19 of profit factor, 0.56 R of expected value, 53.23% winrate. The average win is 1.92 R while the average loss is -1.00 R.
The highest drawdown for both systems was 18 R. This seems like a lot, but remember you're splitting risk in half.
Here you can see the two uncompounded equity curves side by side: red is unextended and blue is extended. Who wins? The test suggests the strategy to be more profitable with the extended target. In addition, most of the trades that reached the unextended target but reversed before reaching the extended, were trades that I would have most likely not have taken with the extented target. This is because there was a resistance/support area in the way of the -100.0 extension level, but there was enough room for price to reach the -61.8 level. I will probably trade this strategy using the -100.0 level as target, unless there is an area in the way. In that case I will go for the unextended target. Drawdown management The expected losing streak for this system, using the extended target, is 7 trades in a row in a sample size of 100 trades. My goal is to have a drawdown cap of 4%, so my risk per trade will be 0.54%. If I ever find myself in a losing streak of more than 8 trades, I will reduce my risk per trade further. What's next? I'll be taking this strategy live. The wisest move would be to repeat the same testing over lower timeframes to verify the edge plays out there as well, but I would not be able to trust my results because I would have vague memories of where price went because of the testing I just did. I also believe markets are fractals, so I see no reason why this wouldn't work on lower timeframes. Before going live, I will expand this spreadsheet to include more specific analysis and I will continue backtesting at a slower pace. The goal is to reach 20 years of backtesting over these 28 pairs and put everything into this spreadsheet. It's not something I will do overnight, but I'll probably do one year every odd day, and maybe a couple more during the weekend. I think I don't have much else to add. I like the strategy. Feel free to ask questions.
Creating a blog couldn’t be easier and yet more complicated in 2020. There are so many different things to think about, and yet so many different platforms you can use to streamline the process. Understandably you’ll already have an idea of what you want to write about, I, unfortunately, can’t help you with that, but what I can do is show you how you can set up a killer blog that will drive readers to your website. We’ll take you through what you’ll need to get started, our five steps to setting your blog up, the best blogging platforms to use, how to get your blog discovered, and the do’s and don’ts of blogging. But first, we need to establish what type of blog you want to set up.
What type of blog?
Firstly you’ll want to have a goal in mind. What are you aiming to achieve through your blog? Do you want to pull in more users to your sales pages by writing about your brand, to increase its publicity? Do you want to build a blog that promotes brands and products from other companies? Or do you just want to set up a blog documenting your travels around the world? In order to pick the right software for you, you’ll want to have a grasp before you start of how big this blog is going to be, whether you’re going to monetize it, and what type of blog it’s going to become. For example, if you’re planning on building an affiliate blogging programme, where you promote other brand’s products and call readers to action to but the products, you’ll be writing a lot of content and will benefit from having a more comprehensive blogging system with lots of plugins to promote sales. But if you’re looking to just set up a personal, or a personal brand blog talking about yourself and your brand, you may not perhaps need as many comprehensive features as you would if you were building an affiliate blog. You may also want to build an online portfolio of your work, which could require an entirely different piece of blogging kit, as opposed to the traditional blog that hosts articles and journals.
What you’ll need to get started.
There are 3 key things you’ll need to get up and running.
A blogging platform.
After you’ve identified the type of blog you want to set up, plus whether you’re going to make money from it, you’ll then need to pick a blogging platform tailored to your needs. Many people chose to operate on WordPress as it is one of the most comprehensive blogging systems going, but they forget platforms like Wix and Squarespace that are great for both helping you save and make money and are great options for those who are less tech-savvy and are new to the blogging game. Plus if you’re blogging for business, you might want to think about using LinkedIn for your business blog. We’ll go into more detail on what blogging platforms are best for your needs shortly, but make sure to keep in mind your objectives and technical experience when choosing the right platform for you.
A hosting platform.
Every website needs a web host to store their website’s information on the internet. A web host is an online service provider that will store your website’s information on one of its online servers. This will put your blog out there to the world. The best web hosts will perform a variety of functions for you, for example, Wix is an all-in-one package that will host your website for you, allow you to register a domain name, and has easy to use website design tools to help you start your blog. Web hosting can be expensive though so make sure you pick the best value for money host that can cater to the amount of traffic you have running through your website. Check out our post on the 11 best hosting providers. [Insert blog link here]
A domain name.
I’m sure by now you already know what sort of blog you want to set up, whether that’s a travel, blog, a blog accompanying your online store, or perhaps an affiliate marketing product review blog. You’ll have a niche and an idea and now all you need is a name. Every website online has what’s called a domain name. It’s included in the website address at the top of your search bar, for example, our domain name is www.digitalsupermarket.com. You’ll need to register a domain name after you purchase a hosting plan, to enable customers to find your site quickly and easily. One good tip is to find a hosting platform like Bluehost or GoDaddy that will provide you with a free domain name when you register for one of their web hosting plans as domain registration can be fairly pricey. Pick a great domain name that is easy for customers to read and type into Google so they can find it easier online. TOP TIP: To increase your blog’s search engine ranking, and to help more people find you on Google, try to pick a domain name that has either a .com or .co.uk ending. These domains often rank a lot higher in Google searches than .org’s, .net’s, and .info’s, and for that reason can be slightly more expensive, yet can help boost your site’s reach and credibility.
The Best Blogging Platforms For You.
There are a wealth of platforms out there catering to all your blogging or online portfolio needs. We have listed some of the main ones below shedding some light on what needs they service and why they might be a great option for you.
WordPress - The best software to give you full customisation.
WordPress is perhaps one of the most renowned blogging platforms in the world, running approximately 35% of the internet. It’s favoured highly by professional bloggers because it gives you total freedom to do whatever you want with your blog. WordPress can help you build your blog using one if its search engine optimised themes, you can customise using its drag and drop website builder tool to create a stunning blog. What’s more, is you’ll be able to use its professional blogging service to post your content online and take advantage of the hundreds of third party app plugins, you can integrate into your blog, to improve automation, add new features, and drive traffic to your site. The only downside of WordPress is that it can be quite technical and can take some time getting used to, but once you’ve got the hang of things, you’ll have great control over everything on your webpage. Pros: Cons:
Domain name registration
Tons of third-party plugins and apps
Technical and can take some getting used to
Not the best if you’re not tech-savvy or are just starting out.
Wix - Best for monetizing your site.
Wix is probably the most streamlined and easiest blog providers. It’s so simple and easy to use, it’s therefore great for anyone just starting out in the blogging world. You can customise one of its stunning templates with Wix’s drag and drop editor, and then upload blog posts to your site by slotting in pictures, gifs, social media buttons, sidebars, and other widgets that will help your blog stand out. One of the coolest features about Wix is its marketplace integration, where you can install a whole variety of third-party applications to your blog to provide your users with greater features and usability. Wix is the perfect all-in-one blogging solution to help you easily build a platform to amplify your business to the world, helping you to make more money, but it can also save you a lot of money as it’s cost-efficient plans roll up, web hosting, blog posting, and domain registration all into one product! Check out our Wix review and our comparison of Wix and Squarespace for a deep dive into Wix’s main blogging features. [Insert link here] Pros: Cons:
Streamlined and easy to use blogging software
Includes as a package, web building tools, domain registration, and web hosting
Tons of third-party plugins and apps on the Wix marketplace
Great platform to help make money and save money on its reasonably priced subscription plans
Don’t get the same full control as you see with WordPress
Locked into using Wix’s templates.
Squarespace - Best for creating visually stunning blogs.
Squarespace is very similar to Wix, in that it is an all-in-one web building and blogging platform that can help you build a blog you can monetize efficiently. It sets itself aside though through its better design and customisation features, making it one of the best platforms on the marketing if you’re looking to design a visually aesthetic blog. I’d recommend using this platform if you are a business operating in some sort of design, arts, or culinary industry. Although it offers minimal template options, Squarespace’s templates are works of art and offer you great customization when building your blog. Plus Squarespace offers a great blogging tool that lets you schedule posts and customize your blog to suit more mobile audiences. Pros: Cons:
Streamlined and easy to use blogging software
Can build a visually stunning blog on Squarespace with its streamlined tools
Excellent blogging features
All-in-one web host, domain registrar, and web builder
Can’t add third-party applications on Squarespace
LinkedIn - Best for blogging businesses.
Aside from setting up a blog on your own site, corporate entities can use LinkedIn to enhance and amplify their presence online. LinkedIn has more than 575 million users, most of whom are professionals and members of corporate conglomerates, and you can use this social platform to target some of the most influential people in the world. If you’re blogging about business this is the perfect platform to use a pre-existing community of people to enhance your social standing. You’ll then be able to build connections and followers on your profile who can easily share your blog on their platform through a couple of simple clicks. Pros: Cons:
Utilise LinkedIn’s pre-existing community of business people to amplify your brand
Target corporate directors and influential people directly through LinkedIn
Check out what people are looking at on LinkedIn and tailor your content to that market
Again you are confined within what LinkedIn’s platform will let you do, it’s not your site and you don’t have full customisation
Instagram - Best for the Artists.
Instagram is one of the biggest blogging sites in the world and without realising it, we are all technically bloggers in some way with our Instagram accounts, right? Ultimately for professional use, it is great for building a portfolio that has some form of visual or graphic eye-catching media around it. Instagram lets you post videos, photos, boomerangs, even write a blog in the photo’s caption if you wanted to! Best of all, Instagram is free, and you can use its business software to link up your online store, to drag users away from your profile, using its product tagging features, and land them in your online checkouts. Our top tip for using Instagram is to post regularly and keep on the theme of your blog. Don’t go off-piste as you’re followers will catch on quickly and unfollow you. And with 1 billion people using the platform each day, it is a great way to gain people’s attention and build your brand’s presence online. Pros: Cons:
Best for the creatives.
Totally free and easy to use interface.
Access to a pre-existing community of people.
Online selling capabilities.
Again you are confined within what Instagram’s platform will let you do, it’s not your site and you don’t have full customisation
The Do’s And Don’ts Of Blogging
Here are a couple of top tips to bear in mind when building your blog to help you create an awesome, lead driven platform.
Don’t use complicated language too soon.
With that in mind, do include language that your target audience will understand. But remember they are still here to learn, so don’t drop people in at the deep end right away by using complex jargon off the bat. Define terms and spell it out in layman’s terms for people at the outset, and as the post goes on, then introduce more complex writing. Introducing technical jargon at the start of your posts is an instant turn off for most readers.
Don’t waffle - Keep it succinct.
People want to get to the punchline now. 43% of people admit to skimming through blogs to get to the information they need, meaning to get your blogging site converting leads, you need to engage the reader early on and offer information succinctly throughout your post. Plus don’t make your blog too long. Depending on what you’re writing, a lot of people will see large volumes of text and will switch off immediately. There is no set limit for what a good and bad amount of text is, that’s something you’ll have to figure out per your industry, but from my experience, the shorter, the better.
Don’t make headlines too long.
Also ensure that your headline is not more than 60 characters long. If it gets too long it won’t rank well in search engines and people just won’t want to read it. Check out this headline analysis tool which will analyse the effectiveness of your proposed headlines.
Don’t plagiarise or use credited images.
Copying other people’s work is lazy and can land you in a lot of hot water in extreme cases if you breach a copyright regulation. But it’s also just unfair on the person who has worked hard or been creative to write that work. The same goes for images, people need to make a living from the content and photos they’re taking so don’t steal that off them.
Do write killer headlines.
People are like goldfish. You only have about 3 seconds to get their attention. That’s why it is important to write catchy, funny, and enticing headlines to draw your reader in. One good way to do it is to use the “How To” and “10 Best” strategies. These sorts of titles telling people ‘How to set up a blog’ or ‘the ten best web hosting platforms’ are search engine optimised, lead winning titles that rank highly in Google searches. Try them out and see!
Do post regularly.
The key to creating a great blog that builds leads is posting regularly. Although it is not the best idea to post regularly. Ideally, you want to post 3-4 times a week to get the best influx of traffic to your site. You’ll also want to check out when’s best to post for your target audience, for example, if you’re in the FOREX market, you’ll want to post your blogs perhaps at 8 AM, before the markets open when city workers are on their staring at their phones on their morning commuter trains to the city.
Do share on social media.
Share your content far and wide on your social platforms. Everyone is on social media these days and its outreach is simply phenomenal. That’s why you should always share your posts to your social channels to get greater traffic on your website, and include share buttons all-around your blog to invite your readers to share your articles too!
Do use SEO keywords to drive more traffic.
In a nutshell, SEO keywords are the phrases people put into search engines when they are looking for information on a certain subject. They are how you get found on your website. Depending on what you are writing about, there is always a set of keywords relating to that topic that you can implement, to help you show up higher in people’s google searches. For example, people might regularly search in google, ‘what is the best compost for growing sunflowers?’ When you come to writing about growing sunflowers in your blog, you might want to use these words or incorporate this question into your blog somewhere, to help you rank higher on Google.
Do use call’s to action to take your readers to the next step.
If you don’t challenge your reader at the end of your blog to follow you on Instagram, or check out your sales pages, you’ll never get the leads or sales you are looking for. With that in mind, build compelling calls to action at the end of each of your posts, to pull readers into taking the next step. Check out our post on landing pages to see a couple of cool ways on how to implement calls to action on your site [insert link here].
Do identify a target audience.
People will often tell you to write as though you were in the shoes of the person you’re looking to bring to your website, but it’s true! Identify what type of people you’re writing to, for instance, if you’re writing a business blog about FOREX trading, you’ll write with potential traders in mind who have one eye on the stock market and the other on your blog. Or if you’re a wedding florist, you’ll set your portfolio up to target those people looking to get married in the next year.
Leads, Sales, Results.
Blogging is one of the most influential marketing strategies in the world and the best bloggers can reap some awesome rewards for producing some truly awesome content. It is fairly straightforward to get started and we advise if you’re a small business, or someone with minimal blogging experience, to try out Wix or Squarespace first before you jump into using more technical platforms like WordPress. Once you’re up and running remember our top tips on what to do and what to avoid when writing your blog. Plus don’t forget to think about optimising and adding useful applications to your site to help you build and grow your content. Check out these 39 awesome blogging tools you can use to drive greater traffic to your site! Found this article useful? Make sure you share it with your friends on Facebook and Twitter and let us know in the comments if you have any other useful blogging tips.
Bitcoin Broker Understand the Benefits of CryptoCurrency Trading
Bitcoin is a cryptocurrency, which can be spent, saved, or invested, and it can be stolen too. Trading with Bitcoins was considered to be risky, but the current trends show that it has become a big hit the binary options sector. This decentralized currency is not regulated by any Government, or by any central authority. What determines the price of Bitcoins? Bitcoin's price is determined according to the supply and demand ratio. Price increases when the demand increases, the rates plummet downwards when the demand falls. Bitcoins in circulation are limited, and new ones are created at a very slow rate. Since it does not have enough cash reserve to move the market price, its price can be extremely volatile. Bitcoin trading is popular because of -
Low inflation risk - Inflation is the biggest issue for traders, because all the currencies lose some of their purchasing power when the reserve banks keep printing more currency. With Bitcoin minting system being limited to just 21 million Bitcoins, it hardly gets impacted with inflation.
Low collapse risk - Currencies fluctuations depend on government trade policies, which at times cause hyperinflation, and even lead to the collapse of currency. Bitcoin is a virtual universal currency, which is not regulated by any government.
Simple, safe and cheap - The Bitcoin payments take place between peer-to-peer without any intermediary, which is why it is simple and cheap.
Easy to carry - Bitcoins worth million dollars can be carried in your pocket, in a memory stick. This cannot be done with gold or cash.
Untraceable - Issuance of Bitcoin is not regulated by any government, so the risk of seizure is nil.
Binary options Bitcoin trading platform bitcoin binary options are getting familiar with popularity of these Bitcoins, and its constant fluctuating values. Therefore they are using this opportunity to offer traders with the latest volatile crypto-currency as an additional payment method. Bitcoin brokers providing crypto-currency as trading option include -
One touch option - Bitcoin trading can be done with AnyOption or one-touch option. For example the current popular currency pair is BTC/USD.
SetOption - The latest option available for asset trading is BITCOIN/USD.
Bitcoin brokers provide a simple trading online platform. All you have to do is visit their website, enter your details, and create an account. You can start with demo account to understand the market action. The trading screen is simple.
Pick the price direction (UP/DOWN)
Select the timeframe
Is Bitcoin trading secure? Bitcoin network is possibly the world's vast spread computing project. The most common weakness here is the user errors. Bitcoin wallet files can get lost, stolen, or deleted accidentally just like any other files in the digital form. However, users can use sound security strategies to protect their cash. Alternatively, you could choose the service providers who offer high-level security, as well as insurance against loss or theft. We provide latest information on Bitcoin brokers and online trading platforms on our website. Please visit our website to check out the broker reviews in order to make the right choices.
vfxAlert it's a tool for a binary options traders which they will use in their own trading strategies. Using vfxAlert assumes that the users are conversant in the essential principles of the forex market. and that they understand the principles of technical analysis and statistical methods. There are two main ways the way to use vfxAlert: Create a trading strategy supported signals of vfxAlert. Using adaptive algorithm for confirmation signals of existing trading strategy. Especially For Beginners Most of you think that binary options it's easy, that's absolutely wrong. Please feel the difference between easy to trade and simply earn money. Binary options are easy to trade - that's true... But successful trading requires discipline and strict compliance with the principles of the trading strategy. It's are going to be very difficult to know what exactly vfxAlert propose and the way to use of these statistical data. Our recommendation is to use free signals within the free version and learn technical analysis and statistical principles. Trade 2 hours per day less . Trade at an equivalent time a day . Trade long-term signals. (Min. 5 min expiration time) Learn about assets what you getting to trade. How price moves in several trading sessions. See how trend influence on signals profitable. See how heatmaps&power influence on signals profitable. Analyse your trading statistics. Trade on demo-account. After one month you'll feel the market and possible you'll be ready to create your first trading strategy. Signals for binary options, Best binary options signals, Free Binary Options Signals, Binary Options Signals, binary signals, binary options signals software !Important: Signals aren't a recommendation for action. Signals are the results of marketing research on a specific algorithm, a trader has got to understand how signals are formed, and what's current market tendencies to form the proper decision. Signals for binary options !Important: vfxAlert don't offer trading strategies. vfxAlert offer signals and real-time statistics counting on current indicators values. See below: The trading strategy may be a system of rules, on the idea of which the trader makes his own decisions. Such a system is made only on the idea of individual trading experience, gleaned knowledge and purchased skills. The strategy allows a deep understanding of the structure of the market and therefore the mechanisms of its operation, therefore, the exchange player makes decisions supported the present situation. On the idea of a private strategy, a trader can develop several trading systems and use them counting on market conditions. The strategy always takes under consideration fundamental factors, statistical data, also because the basic postulates of risk and money management.
Factset: How You can Invest in Hedge Funds’ Biggest Investment Tl;dr FactSet is the most undervalued widespread SaaS/IT solution stock that exists If any of you have relevant experience or are friends with people in Investment Banking/other high finance, you know that Factset is the lifeblood of their financial analysis toolkit if and when it’s not Bloomberg, which isn’t even publicly traded. Factset has been around since 1978 and it’s considered a staple like Bloomberg in many wealth management firms, and it offers some of the easiest to access and understandable financial data so many newer firms focused less on trading are switching to Factset because it has a lot of the same data Bloomberg offers for half the cost. When it comes to modern financial data, Factset outcompetes Reuters and arguably Bloomberg as well due to their API services which makes Factset much more preferable for quantitative divisions of banks/hedge funds as API integration with Python/R is the most important factor for vast data lakes of financial data, this suggests Factset will be much more prepared for programming making its way into traditional finance fields. According to Factset, their mission for data delivery is to: “Integrate the data you need with your applications, web portals, and statistical packages. Whether you need market, company, or alternative data, FactSet flexible data delivery services give you normalized data through APIs and a direct delivery of local copies of standard data feeds. Our unique symbology links and aggregates a variety of content sources to ensure consistency, transparency, and data integrity across your business. Build financial models and power customized applications with FactSet APIs in our developer portal”. Their technical focus for their data delivery system alone should make it stand out compared to Bloomberg, whose UI is far more outdated and complex on top of not being as technically developed as Factset’s. Factset is the key provider of buy-side portfolio analysis for IBs, Hedge funds, and Private Equity firms, and it’s making its way into non-quantitative hedge funds as well because quantitative portfolio management makes automation of risk management and the application of portfolio theory so much easier, and to top it off, Factset’s scenario analysis and simulation is unique in its class. Factset also is able to automate trades based on individual manager risk tolerance and ML optimization for Forex trading as well. Not only does Factset provide solutions for financial companies, they are branching out to all corporations now and providing quantitative analytics for them in the areas of “corporate development, M&A, strategy, treasury, financial planning and analysis, and investor relations workflows”. Factset will eventually in my opinion reach out to Insurance Risk Management a lot more in the future as that’s a huge industry which has yet to see much automation of risk management yet, and with the field wide open, Factset will be the first to take advantage without a shadow of a doubt. So let’s dig into the company’s financials now: Their latest 8k filing reported the following: Revenue increased 2.6%, or $9.6 million, to $374.1 million compared with $364.5 million for the same period in fiscal 2019. The increase is primarily due to higher sales of analytics, content and technology solutions (CTS) and wealth management solutions. Annual Subscription Value (ASV) plus professional services was $1.52 billion at May 31, 2020, compared with $1.45 billion at May 31, 2019. The organic growth rate, which excludes the effects of acquisitions, dispositions, and foreign currency movements, was 5.0%. The primary contributors to this growth rate were higher sales in FactSet's wealth and research workflow solutions and a price increase in the Company's international region Adjusted operating margin improved to 35.5% compared with 34.0% in the prior year period primarily as a result of reduced employee-related operating expenses due to the coronavirus pandemic. Diluted earnings per share (EPS) increased 11.0% to $2.63 compared with $2.37 for the same period in fiscal 2019. Adjusted diluted EPS rose 9.2% to $2.86 compared with $2.62 in the prior year period primarily driven by an improvement in operating results. The Company’s effective tax rate for the third quarter decreased to 15.0% compared with 18.6% a year ago, primarily due to an income tax expense in the prior year related to finalizing the Company's tax returns with no similar event for the three months ended May 31, 2020. FactSet increased its quarterly dividend by $0.05 per share or 7% to $0.77 marking the fifteenth consecutive year the Company has increased dividends, highlighting its continued commitment to returning value to shareholders. As you can see, there’s not much of a negative sign in sight here. It makes sense considering how FactSet’s FCF has never slowed down FactSet’s annual subscriptions and professional services have made its way to foreign and developing markets, and many of them are opting for FactSet’s cheaper services to reduce costs and still get copious amounts of data and models to work with. Here’s what FactSet had to say regarding its competitive position within the market of providing financial data in its last 10k: “Despite competing products and services, we enjoy high barriers to entry and believe it would be difficult for another vendor to quickly replicate the extensive databases we currently offer. Through our in-depth analytics and client service, we believe we can offer clients a more comprehensive solution with one of the broadest sets of functionalities, through a desktop or mobile user interface or through a standardized or bespoke data feed.” And FactSet is confident that their ML services cannot be replaced by anybody else in the industry either: “In addition, our applications, including our client support and service offerings, are entrenched in the workflow of many financial professionals given the downloading functions and portfolio analysis/screening capabilities offered. We are entrusted with significant amounts of our clients' own proprietary data, including portfolio holdings. As a result, our products have become central to our clients’ investment analysis and decision-making.” (https://last10k.com/sec-filings/fds#link_fullReport), if you read the full report and compare it to the most recent 8K, you’ll find that the real expenses this quarter were far lower than expected by the last 10k as there was a lower than expected tax rate and a 3% increase in expected operating margin from the expected figure as well. The company also reports a 90% customer retention rate over 15 years, so you know that they’re not lying when they say the clients need them for all sorts of financial data whether it’s for M&A or wealth management and Equity analysis: https://www.investopedia.com/terms/f/factset.asp FactSet also has remarkably good cash conversion considering it’s a subscription based company, a company structure which usually takes on too much leverage. Speaking of leverage, FDS had taken on a lot of leverage in 2015: So what’s that about? Why were FactSet’s long term debts at 0 and all of a sudden why’d the spike up? Well usually for a company that’s non-cyclical and has a well-established product (like FactSet) leverage can actually be good at amplifying returns, so FDS used this to their advantage and this was able to help the share’s price during 2015. Also, as you can see debt/ebitda is beginning a rapid decline anyway. This only adds to my theory that FactSet is trying to expand into new playing fields. FactSet obviously didn’t need the leverage to cover their normal costs, because they have always had consistently growing margins and revenue so the debt financing was only for the sake of financing growth. And this debt can be considered covered and paid off, considering the net income growth of 32% between 2018 and 2019 alone and the EPS growth of 33% EBITDA has virtually been exponential for FactSet for a while because of the bang-for-buck for their well-known product, but now as FactSet ventures into algorithmic trading and corporate development the scope for growth is broadly expanded. P/E has declined in the past 2 years, making it a great time to buy. Increasing ROE despite lowering of leverage post 2016 Mountains of cash have been piling up in the coffers increasing chances of increased dividends for shareholders (imo dividend is too low right now, but increasing it will tempt more investors into it), and on top of that in the last 10k a large buyback expansion program was implemented for $210m worth of shares, which shows how confident they are in the company itself. SGA expense/Gross profit has been declining despite expansion of offices I’m a bit concerned about the skin in the game leadership has in this company, since very few executives/board members have significant holdings in the company, but the CEO himself is a FactSet veteran, and knows his way around the company. On top of that, Bloomberg remains king for trading and the fixed income security market, and Reuters beats out FactSet here as well. If FactSet really wants to increase cash flow sources, the expansion into insurance and corp dev has to be successful. Summary: FactSet has a lot of growth still left in its industry which is already fast-growing in and of itself, and it only has more potential at its current valuation. Earnings September 24th should be a massive beat due to investment banking demand and growth plus Hedge fund requirements for data and portfolio management hasn’t gone anywhere and has likely increased due to more market opportunities to buy-in.
Next steps after finishing Trading and Machine Learning specialization
Hello everyone, I just finished a specialization entailing using google AI platform and Big Query ML to develop trading strategies as well as RL agents, yet I’ve only been able to do this on historical data, I was hoping someone who’s already been through all this could advise me on the next steps. I’m looking to now go ahead and create automated trading systems based on the models and Reinforcement learning agents I have learned to develop. The books and courses I have taken have lead me up to what seems to be everything other than actually connecting to a live demo account to go ahead and create an automated system to now play out the models and such. I’ve been using Quandl and Open AI gym, not sure how I transition my agent from a Gym environment to live trading on a demo account because all the books and courses I have taken seem to purposely avoid this step. I’m really looking to use RL for forex trading but I don’t know how I would connect systems to a MT4 GUI, so I was just hoping someone might be able to point me in the right direction about how I should go about connecting an API to my AI platform notebooks to test my models live. Any direction would be greatly appreciated thanks everyone, I’m really looking forward to getting started in the industry; if I can figure this last thing out I don’t think it will be a problem haha, but stuck till then!
The Next Crypto Wave: The Rise of Stablecoins and its Entry to the U.S. Dollar Market
Author: Christian Hsieh, CEO of Tokenomy This paper examines some explanations for the continual global market demand for the U.S. dollar, the rise of stablecoins, and the utility and opportunities that crypto dollars can offer to both the cryptocurrency and traditional markets. The U.S. dollar, dominant in world trade since the establishment of the 1944 Bretton Woods System, is unequivocally the world’s most demanded reserve currency. Today, more than 61% of foreign bank reserves and nearly 40% of the entire world’s debt is denominated in U.S. dollars1. However, there is a massive supply and demand imbalance in the U.S. dollar market. On the supply side, central banks throughout the world have implemented more than a decade-long accommodative monetary policy since the 2008 global financial crisis. The COVID-19 pandemic further exacerbated the need for central banks to provide necessary liquidity and keep staggering economies moving. While the Federal Reserve leads the effort of “money printing” and stimulus programs, the current money supply still cannot meet the constant high demand for the U.S. dollar2. Let us review some of the reasons for this constant dollar demand from a few economic fundamentals.
Demand for U.S. Dollars
Firstly, most of the world’s trade is denominated in U.S. dollars. Chief Economist of the IMF, Gita Gopinath, has compiled data reflecting that the U.S. dollar’s share of invoicing was 4.7 times larger than America’s share of the value of imports, and 3.1 times its share of world exports3. The U.S. dollar is the dominant “invoicing currency” in most developing countries4. https://preview.redd.it/d4xalwdyz8p51.png?width=535&format=png&auto=webp&s=9f0556c6aa6b29016c9b135f3279e8337dfee2a6 https://preview.redd.it/wucg40kzz8p51.png?width=653&format=png&auto=webp&s=71257fec29b43e0fc0df1bf04363717e3b52478f This U.S. dollar preference also directly impacts the world’s debt. According to the Bank of International Settlements, there is over $67 trillion in U.S. dollar denominated debt globally, and borrowing outside of the U.S. accounted for $12.5 trillion in Q1 20205. There is an immense demand for U.S. dollars every year just to service these dollar debts. The annual U.S. dollar buying demand is easily over $1 trillion assuming the borrowing cost is at 1.5% (1 year LIBOR + 1%) per year, a conservative estimate. https://preview.redd.it/6956j6f109p51.png?width=487&format=png&auto=webp&s=ccea257a4e9524c11df25737cac961308b542b69 Secondly, since the U.S. has a much stronger economy compared to its global peers, a higher return on investments draws U.S. dollar demand from everywhere in the world, to invest in companies both in the public and private markets. The U.S. hosts the largest stock markets in the world with more than $33 trillion in public market capitalization (combined both NYSE and NASDAQ)6. For the private market, North America’s total share is well over 60% of the $6.5 trillion global assets under management across private equity, real assets, and private debt investments7. The demand for higher quality investments extends to the fixed income market as well. As countries like Japan and Switzerland currently have negative-yielding interest rates8, fixed income investors’ quest for yield in the developed economies leads them back to the U.S. debt market. As of July 2020, there are $15 trillion worth of negative-yielding debt securities globally (see chart). In comparison, the positive, low-yielding U.S. debt remains a sound fixed income strategy for conservative investors in uncertain market conditions. Source: Bloomberg Last, but not least, there are many developing economies experiencing failing monetary policies, where hyperinflation has become a real national disaster. A classic example is Venezuela, where the currency Bolivar became practically worthless as the inflation rate skyrocketed to 10,000,000% in 20199. The recent Beirut port explosion in Lebanon caused a sudden economic meltdown and compounded its already troubled financial market, where inflation has soared to over 112% year on year10. For citizens living in unstable regions such as these, the only reliable store of value is the U.S. dollar. According to the Chainalysis 2020 Geography of Cryptocurrency Report, Venezuela has become one of the most active cryptocurrency trading countries11. The demand for cryptocurrency surges as a flight to safety mentality drives Venezuelans to acquire U.S. dollars to preserve savings that they might otherwise lose. The growth for cryptocurrency activities in those regions is fueled by these desperate citizens using cryptocurrencies as rails to access the U.S. dollar, on top of acquiring actual Bitcoin or other underlying crypto assets.
The Rise of Crypto Dollars
Due to the highly volatile nature of cryptocurrencies, USD stablecoin, a crypto-powered blockchain token that pegs its value to the U.S. dollar, was introduced to provide stable dollar exposure in the crypto trading sphere. Tether is the first of its kind. Issued in 2014 on the bitcoin blockchain (Omni layer protocol), under the token symbol USDT, it attempts to provide crypto traders with a stable settlement currency while they trade in and out of various crypto assets. The reason behind the stablecoin creation was to address the inefficient and burdensome aspects of having to move fiat U.S. dollars between the legacy banking system and crypto exchanges. Because one USDT is theoretically backed by one U.S. dollar, traders can use USDT to trade and settle to fiat dollars. It was not until 2017 that the majority of traders seemed to realize Tether’s intended utility and started using it widely. As of April 2019, USDT trading volume started exceeding the trading volume of bitcoina12, and it now dominates the crypto trading sphere with over $50 billion average daily trading volume13. https://preview.redd.it/3vq7v1jg09p51.png?width=700&format=png&auto=webp&s=46f11b5f5245a8c335ccc60432873e9bad2eb1e1 An interesting aspect of USDT is that although the claimed 1:1 backing with U.S. dollar collateral is in question, and the Tether company is in reality running fractional reserves through a loose offshore corporate structure, Tether’s trading volume and adoption continues to grow rapidly14. Perhaps in comparison to fiat U.S. dollars, which is not really backed by anything, Tether still has cash equivalents in reserves and crypto traders favor its liquidity and convenience over its lack of legitimacy. For those who are concerned about Tether’s solvency, they can now purchase credit default swaps for downside protection15. On the other hand, USDC, the more compliant contender, takes a distant second spot with total coin circulation of $1.8 billion, versus USDT at $14.5 billion (at the time of publication). It is still too early to tell who is the ultimate leader in the stablecoin arena, as more and more stablecoins are launching to offer various functions and supporting mechanisms. There are three main categories of stablecoin: fiat-backed, crypto-collateralized, and non-collateralized algorithm based stablecoins. Most of these are still at an experimental phase, and readers can learn more about them here. With the continuous innovation of stablecoin development, the utility stablecoins provide in the overall crypto market will become more apparent.
In addition to trade settlement, stablecoins can be applied in many other areas. Cross-border payments and remittances is an inefficient market that desperately needs innovation. In 2020, the average cost of sending money across the world is around 7%16, and it takes days to settle. The World Bank aims to reduce remittance fees to 3% by 2030. With the implementation of blockchain technology, this cost could be further reduced close to zero. J.P. Morgan, the largest bank in the U.S., has created an Interbank Information Network (IIN) with 416 global Institutions to transform the speed of payment flows through its own JPM Coin, another type of crypto dollar17. Although people argue that JPM Coin is not considered a cryptocurrency as it cannot trade openly on a public blockchain, it is by far the largest scale experiment with all the institutional participants trading within the “permissioned” blockchain. It might be more accurate to refer to it as the use of distributed ledger technology (DLT) instead of “blockchain” in this context. Nevertheless, we should keep in mind that as J.P. Morgan currently moves $6 trillion U.S. dollars per day18, the scale of this experiment would create a considerable impact in the international payment and remittance market if it were successful. Potentially the day will come when regulated crypto exchanges become participants of IIN, and the link between public and private crypto assets can be instantly connected, unlocking greater possibilities in blockchain applications. Many central banks are also in talks about developing their own central bank digital currency (CBDC). Although this idea was not new, the discussion was brought to the forefront due to Facebook’s aggressive Libra project announcement in June 2019 and the public attention that followed. As of July 2020, at least 36 central banks have published some sort of CBDC framework. While each nation has a slightly different motivation behind its currency digitization initiative, ranging from payment safety, transaction efficiency, easy monetary implementation, or financial inclusion, these central banks are committed to deploying a new digital payment infrastructure. When it comes to the technical architectures, research from BIS indicates that most of the current proofs-of-concept tend to be based upon distributed ledger technology (permissioned blockchain)19. https://preview.redd.it/lgb1f2rw19p51.png?width=700&format=png&auto=webp&s=040bb0deed0499df6bf08a072fd7c4a442a826a0 These institutional experiments are laying an essential foundation for an improved global payment infrastructure, where instant and frictionless cross-border settlements can take place with minimal costs. Of course, the interoperability of private DLT tokens and public blockchain stablecoins has yet to be explored, but the innovation with both public and private blockchain efforts could eventually merge. This was highlighted recently by the Governor of the Bank of England who stated that “stablecoins and CBDC could sit alongside each other20”. One thing for certain is that crypto dollars (or other fiat-linked digital currencies) are going to play a significant role in our future economy.
There is never a dull moment in the crypto sector. The industry narratives constantly shift as innovation continues to evolve. Twelve years since its inception, Bitcoin has evolved from an abstract subject to a familiar concept. Its role as a secured, scarce, decentralized digital store of value has continued to gain acceptance, and it is well on its way to becoming an investable asset class as a portfolio hedge against asset price inflation and fiat currency depreciation.Stablecoins have proven to be useful as proxy dollars in the crypto world, similar to how dollars are essential in the traditional world. It is only a matter of time before stablecoins or private digital tokens dominate the cross-border payments and global remittances industry. There are no shortages of hypes and experiments that draw new participants into the crypto space, such as smart contracts, new blockchains, ICOs, tokenization of things, or the most recent trends on DeFi tokens. These projects highlight the possibilities for a much more robust digital future, but the market also needs time to test and adopt. A reliable digital payment infrastructure must be built first in order to allow these experiments to flourish. In this paper we examined the historical background and economic reasons for the U.S. dollar’s dominance in the world, and the probable conclusion is that the demand for U.S. dollars will likely continue, especially in the middle of a global pandemic, accompanied by a worldwide economic slowdown. The current monetary system is far from perfect, but there are no better alternatives for replacement at least in the near term. Incremental improvements are being made in both the public and private sectors, and stablecoins have a definite role to play in both the traditional and the new crypto world. Thank you. Reference:  How the US dollar became the world’s reserve currency, Investopedia  The dollar is in high demand, prone to dangerous appreciation, The Economist  Dollar dominance in trade and finance, Gita Gopinath  Global trades dependence on dollars, The Economist & IMF working papers  Total credit to non-bank borrowers by currency of denomination, BIS  Biggest stock exchanges in the world, Business Insider  McKinsey Global Private Market Review 2020, McKinsey & Company  Central banks current interest rates, Global Rates  Venezuela hyperinflation hits 10 million percent, CNBC  Lebanon inflation crisis, Reuters  Venezuela cryptocurrency market, Chainalysis  The most used cryptocurrency isn’t Bitcoin, Bloomberg  Trading volume of all crypto assets, coinmarketcap.com  Tether US dollar peg is no longer credible, Forbes  New crypto derivatives let you bet on (or against) Tether’s solvency, Coindesk  Remittance Price Worldwide, The World Bank  Interbank Information Network, J.P. Morgan  Jamie Dimon interview, CBS News  Rise of the central bank digital currency, BIS  Speech by Andrew Bailey, 3 September 2020, Bank of England
Below is a list of some of the top Forex trading strategies revealed and discussed so you can try and find the right one for you. 50-Pips a Day Forex Strategy. One of the latest Forex trading strategies to be used is the 50-pips a day Forex strategy which leverages the early market move of certain highly liquid currency pairs. The GBPUSD and ... Basic strategies - where the education for all beginner traders starts.. Basic strategies use simple chart pattern recognition rules and one or two basic indicators. By learning to recognize and trade simple patterns, novice Forex traders will be able to make a much smoother transition to more advanced trading systems and methods. Forex Strategies. In this category are collected only the best trading systems and strategies for forex trading, which really deserve attention. Here are published trading systems of various types, such as for scalping, day trading, etc. As always, all trading strategies are freely available, which means that you can download them absolutely free. These Forex trading systems range from simple Forex trading strategies to complex Forex trading systems, from Forex trading strategies for beginners to advanced traders and including Forex price action trading strategies. Here are the 6 different types of Forex trading strategies and systems on this site: [toc] 1. Forex Day Trading Strategies Day trading strategy represents the act of buying and selling a security within the same day, which means that a day trader cannot hold a trading position overnight.Day trading strategies include: Scalping; Fading; Daily pivots; Momentum trading; In case of performing day trading, traders can carry out numerous trades within a day but should liquidate all the ...
If you learn this one Forex pattern, you will be better off than 90% of all other traders your competing against. This simple strategy is the difference betw... My forex trading strategies on GBPUSD! ***FREE DEMO Click below - Want to learn simple forex trading strategies and nail EXACT highs and lows? Capture huge p... Learn how to trade forex like a pro.... Understand how the market structure works! Learn how to use trading tools like indicators, robots and other trading s... The 4 forex strategies that every trader should know ! 🚨🚨Trading Performance 🚨🚨 Improve Your Trading Performance at our Fundamental Trading Academy https://w... Learn our Other Scalping Strategy: https://bit.ly/2xol8aS In this video, I will walk you through a simple forex scalping strategy I've been using successfull...