“It’s not the strongest of the species that survives, nor the most intelligent, but the one most responsive to change.” – Charles Darwin (1809)
All of a sudden, financial markets today are all about algos and routers. Machine learning has an increasingly important role in the calibration of trading decisions in real-time. Most hedge funds and financial institutions are using algos.
But wait a minute – what is algorithmic trading or simply put algo trading?
Algo trading is an automated trading system that involves the use of automated, programmed trading instructions to make extremely fast, objective trading decisions. Algos are the ‘infinity stones’ that can incredibly enhance speed and accuracy in trading. We are talking about a speed that can be measured in fractions of a second, faster than humans can perceive. It opens the doors to better prices as trades can be analyzed and executed more quickly. Moreover, a computer algorithm double-checks to ensure that the correct order is entered. Gone are the days of accidentally putting in the wrong trade, the wrong currency pair, the wrong amount, and all those wrongs associated with manual entries.
Algo trading is that one giant step towards the utopia of a perfectly rational market without human sentiments. Algos are not susceptible to fear and greed – two of the multitude of human emotions that lead to irrational decisions. In addition, algo traders don’t have to spend as much time monitoring the markets as non-algo traders because their trades can be executed without continuous supervision. This reduction in time for trading lowers transaction costs due to the saved opportunity cost of continuous supervision.
Perhaps, the most significant advantage of algo trading is that its rules can be backtested to analyze its effectiveness, thereby making it easier for an algo trader to be patient and disciplined – arguably the two most essential traits for a trader.
Algo trading makes the trader a beast of a multitasker. Algos can be used simultaneously on multiple asset classes like stocks, futures, options, commodities, currencies, and cryptocurrencies.
However, the cognitive power of a human still hasn’t been replaced by machines. Just as humans cannot beat machines in execution, machines cannot beat humans in creation. We equip the human with the machine and not the machine with the human. Trades are executed in algo trading based on certain pre-programmed instructions of the trader referred to as algo trading strategies.
Let’s give you a walkthrough of ten algo trading strategies to improve your earnings:
- Mean Reversion:
This common usage of algos calculates the standard deviation of the stock’s recent prices as a buy or sell indicator. A stock becomes attractive when the current market price lags behind the average price owing to the hope that the price will increase towards the average price and vice-versa.
Let’s face it, price differentials don’t appear often, and when they appear, it’s for a short time window. You can create an algorithm that will monitor the market to capitalize on the price differentials for generating risk-free profit. For example, a differential can appear between the spot price and an F&O price for a currency pair.
This strategy can be used to monitor the market for executing trades that utilize technical analysis (chart patterns and indicators) to make decisions. It is relatively easy to deploy as its algos are comparatively easier to design and use. The trend-following strategy can use anything from oscillators to indicators and from moving averages to mean reversion.
- Execution Based Strategies:
The bread and butter of institutional investors, it’s the perfect type of strategy for executing large quantity orders by breaking up the purchase in terms of volume or time, thereby ensuring maximum stability.
- Delta Neutral Strategies:
With the continuous movement of an asset, it is manually impossible to neutralize deltas by utilizing multiple positions for balancing positive and negative deltas in the case of derivatives. You can create a delta-neutral portfolio that is immune to market movements with the help of algorithms that even out the response to market movements for a specific range to bring the net change of the position to zero. These algorithms automatically calculate the deltas of your position and keep you updated every second about your current portfolio or position.
- Position Sizing:
Algorithms facilitate position sizing based on commands predefined in the system. For example, irrespective of the stock price, you can prefix that the value of each trade will not be more than Rs. X on any share. This encourages investing in each stock of the same value independent of favouritism in any stock.
- Stop Loss Modification:
There are algo trading strategies that change stop losses based on market movements (from prices to technical indicators) of the stocks in the portfolio.
Whether you buy when the market advances (forward scalping) or when the market declines (reverse scalping), you can create scalping models to buy and sell a particular share or commodity at a fixed interval.
- Index Fund Rebalancing:
Want to capitalize on the expected trades depending on the number of stocks in the index fund based on best prices, low costs, and timely results? Use algorithmic trading for creating opportunities through index fund rebalancing.
- Market Timing Strategies:
Designed to generate alpha, they use a method that includes live testing, backtesting, and forward testing.
It’s getting complex, isn’t it? Well, practising is the key to embracing this change. Algo trading is here to stay.
Disclaimer – The article is only for educational purposes and all the information given in the articles is available in the public domain.