As promised, here’s the next part of my series on algorithmic forex trading systems. Make sure you check out the first part on What You Need to Know about Algo FX Trading before reading on!
This trading approach usually appeals to those who are looking to eliminate or reduce human emotional interference in making trade decisions. After all, buy or sell signals can be generated using a programmed set of instructions and can be executed right on your trading platform.
“Amazeballs! Here’s my money! Where do I sign?”
Hold your horses, young padawan! Put your hard-earned cash back in your wallet and spend a little more time understanding algorithmic trading first. To start off, let’s take a look at the different classifications of this trading approach.
Algorithmic Trading Strategies
There are eight main kinds of algo trading based on the strategies used. Pretty overwhelming, huh? Of course you can mix and match these strategies too, which yields so many possible combinations.
One of the simplest strategies is simply to follow market trends, with buy or sell orders generated based on a set of conditions fulfilled by technical indicators. This strategy can also compare historical and current data in predicting whether trends are likely to continue or reverse.
2. Mean reversion
Another basic kind of algo trading strategy is the mean reversion system, which operates under the assumption that markets are ranging 80% of the time. Black boxes that employ this strategy typically calculate an average asset price using historical data and takes trades in anticipation of the current price returning to the average price.
Ever try trading the news? Well, this strategy can do it for you! A news-based algorithmic trading system is usually hooked to news wires, automatically generating trade signals depending on how actual data turns out in comparison to the market consensus or the previous data.
4. Market sentiment
As you’ve learned in our School lesson on market sentiment, commercial and non-commercial positioning can also be used to pinpoint market tops and bottoms. Forex algo strategies based on market sentiment can involve using the COT report or a system that detects extreme net short or long positions. More modern approaches are also capable of scanning social media networks to gauge currency biases.
Now here’s where it gets a little more complicated than usual. Making use of arbitrage in algorithmic trading means that the system hunts for price imbalances across different markets and makes profits off those. Since the forex price differences are in usually micropips though, you’d need to trade really large positions to make considerable profits. Triangular arbitrage, which involves two currency pairs and a currency cross between the two, is also a popular strategy under this classification.
6. High-frequency trading
As the name suggests, this kind of trading system operates at lightning-fast speeds, executing buy or sell signals and closing trades in a matter of milliseconds. These typically use arbitrage or scalping strategies based on quick price fluctuations and involves high trading volumes.
This is a strategy employed by large financial institutions who are very secretive about their forex positions. Instead of placing one huge long or short position with just one broker, they break up their trade into smaller positions and execute these under different brokers. Their algorithm can even enable these smaller trade orders to be placed at different times to keep other market participants from finding out! This way, financial institutions are able to execute trades under normal market conditions without sudden price fluctuations. Retail traders who keep track of trading volumes are able to see only the “tip of the iceberg” when it comes to these large trades.
If you think iceberging is sneaky, then the stealth strategy is even sneakier! Iceberging has been such a common practice in the past few years that hardcore market watchers were able to hack into this idea and come up with an algorithm to piece together these smaller orders and figure out if a large market player is behind all of it.
As you’ve probably guessed, it takes a solid background in financial market analysis and computer programming to be able to design such sophisticated trading algorithms. Quantitative analysts or quants are typically trained in C++, C#, or Java programming before they are able to come up with algorithmic trading systems.
Don’t let that discourage you though! The first three or four kinds of algorithmic trading strategies should already be very familiar to you if you’ve been trading for quite some time or if you were a diligent student in our School of Pipsology.
Do stay tuned for the next part of this series, as I plan to let you in on the latest developments and the future of algorithmic FX trading. ‘Til next week!