Options Trading Strategies For Enhanced Profits In Texas Forex – The foreign exchange (forex) market is the most liquid market in the world. In this trading tutorial, learn from the first-hand experience of a software developer on creating forex algorithmic trading strategies and more.
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Rogelio is a versatile and motivated full-stack engineer with over 13 years of experience working across multiple languages, frameworks and platforms.
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Editor’s note. Our editorial team updated this article on July 21, 2022. It has been changed to include the latest sources and to meet our current editorial standards.
As you may know, the foreign exchange (forex or FX) market is used to trade between currency pairs. But you might not know that it is the most liquid market in the world. (Yes, even compared to cryptocurrency, forex is generally considered safer and more profitable.)
A few years ago, driven by curiosity, I took my first steps into the world of algorithmic forex trading by creating a demo account and playing simulations (with fake money) on the Meta Trader 4 trading platform.
After a week of “trading” I almost doubled my money. Encouraged by my successful algorithmic trading, I dug deeper and ended up signing up for several FX forums. Soon I was spending hours reading about forex algorithmic trading systems (rule sets that determine whether you should buy or sell), custom indicators, market sentiment, and more.
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Around this time I happened to hear that someone was trying to find a software developer to build a simple, automated forex trading system. This was back in college when I was learning about concurrent programming in Java (threads, semaphores and more). I thought this forex automated trading system couldn’t be much more complicated than my advanced data science coursework, so I inquired about the job and applied.
The client wanted algorithmic trading software built with MQL4, a functional programming language used by the Meta Trader 4 platform to perform stock operations.
Since then, MQL5 has been released. As you might expect, it solves some of the problems of MQL4 and comes with more built-in features that make life easier.
The job of the trading platform (in this case Meta Trader 4) is to provide the connection to the forex broker. The broker then provides the platform with real-time market information and executes buy/sell orders. For readers who are not familiar with forex algorithmic trading, here is the information provided by the data feed:
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With Meta Trader 4, you can access all of these data with built-in functions available in different timeframes: M1 (every minute), M5 (every five minutes), M15, M30, H1 (hourly), H4, D1 (every day). ), W1 (weekly) and MN (monthly).
The movement of the current price is called a tick. A mark is a change in the bid or ask price of a currency pair. During active markets there can be many ticks per second. During slow trading, minutes may pass without a tick. A tick is the heartbeat of a forex robot.
When you place an order through such a platform, you buy or sell a certain amount of a certain currency. You also set stop-loss and take-profit limits. The stop-loss limit is the maximum number of points (price variations) you can afford to lose before abandoning the trade. The profit limit is the number of points you will accumulate to your credit before withdrawing money.
If you want to learn more about the basics of trading (eg pips, order types, spread, slippage, market orders and more), BabyPips is a great resource.
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The client’s algorithmic trading specifications were simple: a forex robot based on two indicators. For basic information, indicators are very useful when trying to define market conditions and make trading decisions because they are based on past data (such as the highest price value in recent
Days). Many are built into Meta Trader 4. However, the indicators of interest to my client came from a custom forex trading system.
The client wanted to trade every time two of these custom indicators crossed, and only at a certain angle.
The start function is the heart of every MQL4 program. It is executed every time the market moves (so this function is executed once per tick). This happens regardless of the time period. For example, you could run on an H1 (one hour) time frame, but the start function would be executed many thousands of times per hour.
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When I created my algorithmic trading system, I wanted to know if it works properly and if the forex trading strategy it uses is good.
Backtesting is the process of testing a certain system (automated or not) against past events. In other words, you test your system using the past as a proxy for the present.
MT4 comes with an affordable tool for backtesting your forex trading strategy (nowadays there are more professional tools that offer more functionality). To get started, set your timelines and run the program during the simulation; the tool will simulate each mark, knowing that for each unit it should open at a certain price, close at a certain price, and reach certain highs and lows.
By comparing the performance of the program with historical prices, you will have a good idea of whether it is working correctly.
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Using backtesting, I checked the FX bot’s return ratio for some random time intervals; I knew that my client was not going to get rich with the trading strategy I was using – the indicators chosen together with the logic behind the decisions were not profitable. Below are the results of running the program in the M15 window for 164 operations:
One caveat: Saying that a system is “profitable” or “unprofitable” is not necessarily accurate. Often, systems are (un)profitable for a period of time based on market ‘sentiment’, which can follow several chart patterns:
Although the backtest made me concerned about the usefulness of this FX bot, I was intrigued when I started playing around with its external parameters and noticed a big difference in the overall return ratio. It is known as
I did a rough check to try to deduce the importance of external parameters on the rate of return and came up with this:
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You may think like me that you should use parameter A. But the decision is not as simple as it seems. Note in particular the unpredictability of the A parameter: its return changes dramatically for small error values. In other words, parameter A is very likely to over-predict future results because any uncertainty—any change at all—will degrade performance.
But truly, the future is uncertain! Therefore, the return of parameter A is also unclear. The best choice is actually to rely on unpredictability. Often, a parameter with a lower maximum return but better predictability (less volatility) will be preferred over a parameter with a high return but poor predictability.
The only thing you can know for sure is that you don’t know the future of the market, and it’s a mistake to assume you know how the market will perform based on past data. Thus, you need to recognize this unpredictability in your forex predictions.
It is a mistake to think that you know how the market will do based on past data.
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This does not necessarily mean that we should use parameter B, because even the lowest return of parameter A performs better than the return of parameter B; parameter optimization can lead to tests that exaggerate possible future results, and such thinking is not obvious.
Since my first experience with forex algorithmic trading, I have built several automated trading systems for clients and I can tell you that there is always room to explore and do further forex analysis. For example, I recently built a system based on finding the so-called “big fish” moves: huge variations of the dice in very small units of time. This is a topic that fascinates me.
Building your own FX simulation system is a great way to learn more about trading the forex market, and the possibilities are endless. For example, you can try to decipher the probability distribution of price changes as a function of volatility in a single market (e.g. EUR/USD) or create a Monte Carlo simulation model using the distribution over the volatility state using any degree of accuracy. you prefer I’ll leave that as an exercise
The forex world can be overwhelming at times, but I encourage you to explore your algorithmic trading strategy forex.
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Today, there is a wide range of tools available to build, test and improve the automation of forex trading systems: Trading Blox for testing, NinjaTrader for trading and OCaml programming to name a few.
I have read a lot about the mysterious world that is the currency market. Here are some resources for programmers and avid readers: A bull spread is an options trading strategy designed to capitalize on limited price gains in stocks. The strategy uses two call options to create a range consisting of a lower strike price and an upper bid price. the price. Appeal
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