Hey everyone,
This is an update on the continued development of my FX market AI algorithm. I’ve been a forex trader for about two years, and one thing I’ve always struggled with is finding the time to analyze the graphs (technical) and keep up with the news (fundamental). Trust me, there’s a lot of noise out there. Trading is an emotional rollercoaster, and I’ve enjoyed being in the front seat through the highs and lows. So, a year ago, I began researching a new style of trading: AI, or algorithms. The experiences I gained drew me into optimizing a fairly convoluted trading strategy into AI algorithms that are fully automatic (literally rinsing, washing, and repeating the market). I predict that in a few years, most of the global markets will be controlled by computers anyway, so why not get ahead of the game?
My preferred currency pair is the Euro/Australian dollar. It’s one that I feel I understand well, and because the trading hours of the two continents’ economies only overlap narrowly, there isn’t any extensive one-directional movement. Hence, it tends to range between point A and B (see graph below). Any sudden movement that could be caused by news simultaneously weakens one currency and strengthens the other, which evens out the impact.
Now that “The Covid Spike,” as seen in the image below, has subsided and the markets have settled back between points A and B since May 2019, with a range of 600 pips, we can confirm that the spike was not a long-term change in trend. In June 2020, the graph retraced back to the “sweet zone.” With multiple confirmations of resistance at 1.66512, I have started trading again within the forex market using my algorithms.
Following my first post, I haven’t addressed what is unique about my algorithm. Before I even begin, I would like everyone reading this to understand that trading with algorithms is completely different from conventional manual trading.
Here are some of the differences:
1. The algorithm works in all market trends!
Most traders are looking for trending markets with clear upwards or downwards trends. It is difficult to find good entry points or look for long term investments in ranging markets, such as EURAUD. My algorithms work best in these ranging markets because it makes risk management simpler. Trending markets can make more money, but it requires more micromanaging on my part, this means I can choose the days when I want to be more actively involved compared to days of just passive income.
2. Different risk management
When using AI trading, the risk is chosen in the settings (hedging/martingale strategy). This is not a trading method if you are adamant about not utilising more than 1% of your account per trade. You need to look at the bigger picture (explained later).
3. The Hedging/Martingale strategy
This strategy is highly debatable for most traders because of the limitless potential if you had indefinite capital. However, with markets such as EURAUD, which are ranging comfortably between 600 pips, you can safely quantify risk management within this range. Such that we can assume the market will unlikely leave this bracket without a good reason or a gradual trend change, which anyone can identify
4. Stop loss option
There is no option to use a stop loss on individual trades. The only capital preservation options are to force close all open trades that you are not happy with, or execute force close in all trades once your account reaches a certain balance (what I have set up!). Of course, this is the standard martingale problem. You reap both high rewards and high risks. Remember that normally a person would be executing these trades as their full-time job, but my AI algorithm provides me with profit as a passive income.
Limitations on Reaching the Limitless Potential
I have had clients that have been brave to use my algorithm, and profits were shown, although from past experience some losses have occurred because of insufficient balance. This is why I believe and recommend an initial capital of £1000+. Anything lower would work too, but the profit will exponentially decrease in proportion.
With one of the lowest settings I have developed for EURAUD, I have calculated that £1000 can withstand a 600 pips movement. In addition, there are measures I take once a certain threshold is reached. Utilising this, I see an average of £65–80 of monthly return, which is a good ROI (annually predicted £840). This is better than any high street interest rate or savings account.
The only way I would need to force close trades is if there was a sharp movement of 800+ pips without any market pullback. Normally, a one-third retracement from the peak would be required to close the trades in profit. Typically, I could expect an average of 1–3 critical spikes in a year, such as the covid spike.
EURAUD — Annual occurrence rate of a spike
I am currently developing a way to identify and test my algorithms in the optimum range. I will update you when I have the figures (the best guess is around 600–800 pips). So in theory: anyone who has a large enough capital and is willing to take a defined and quantified higher risk ratio can never lose with the hedging/martingale strategy unless the market does something that it has never done historically (e.g. Covid, 2008 recession).
Jon Doy“Only those who will risk going too far can possibly find out how far one can go.” — T.S Eliot
Why I believe in the Trading algorithm?
A good trader is constantly using the previous price to make their trades more biased in their favour. I can prove using back-testing that the algorithm can successfully run from 2014 to pre-covid 2020 markets, making a 15% return of investment (ROI) per month. In my opinion, this is sufficient, given that no further unforeseen sudden spikes occur. Covid was an obvious time to stop trading.
Customisations to my attitude to risk
I can set the parameters in such a way that as long as the market does not have a 1000 pip spike (like covid) you can never lose your money. However, this means the amount you would make is proportionate to that risk (basically next to zero profit — maybe just about breaking even with running costs).
Some of my results so far:
Calm Markets
This is a sample of a low activity week at one of the lowest rates (the safest range). As you can see, there was a relatively low drawdown on the account, the risk management chosen by the client will decide how much their maximal drawdown of unrealised profit or loss (P/L) will be.
Volatile Markets
This week, there was a lot of (Brexit) news (18 October- 22 October), hence the EUR increased by over 330 pips, this meant my account when to around £-370 in unrealised P/L, but then according to my assumption, the market retraced by one-third and all positions were closed in profit. One of my risk strategies was applied when over 200 pips of the movement had occurred. This is a precautionary measure I like to do (330 pips is a medium movement — this movement occurs 10–12 times annually).
Conclusion
Thank you for reading this far, this is my personal project. I haven’t seen a lot of people use algorithms with this strategy, and I have tremendously enjoyed analysing and correcting the parameters based on data produced. This is a way I can express my excitement for passive income (anything from housing, royalties, stocks, interest, or bonds).
I hope I have inspired you to understand that passive income can be used by anyone. I’m a university student, and spending just a little time each day has brought me this far.
