
Algorithmic trading is slowly becoming the natural order of the capital markets. According to a circular found on the NSE website, about 60-70% of the total trading volume comes from algorithms or computers. First, let us understand the difference between Algorithmic and Quantitative Trading and later see how they differ from discretionary trading(manual trading).
Algorithmic trading means you have written/defined rules in any computer language & let the program trade automatically for you. It could be as simple as - buy after the open and sell - before the close. This is an albeit very simple algorithm but an algorithm nonetheless. The word Quantitative analysis is more to do with the testing process of your trading rule. For example - You have a trading strategy and you want to know the robustness or the credibility of that strategy, you can quantify the strategy by testing it out and coming up with exponential instances or with n-number of trades. Using these statistics you can quantify/validate the strategy.
Why algorithmic or systematic trading? How are they better than discretionary trading?
Let assume you are a very skilled trader, how many screens can you monitor simultaneously? At max half a dozen, but a machine doesn’t have such a problem. It can track 1000+ securities simultaneously, moreover with no fatigue. Also, the machine doesn’t need bathroom breaks and is at its peak performance all the time. Can we say the same for a human? Also whenever a human trades, the weakest part of the system is generally the human himself, because of his/her emotions. Let’s say you are up 2% in a trade? What are you likely to do? Book profits and exit. And what are you likely to do when down 2%? ‘Hold or wait’ is the word that springs to your mind. This is the exact opposite of what you should be doing if you want to make money. Also, we are not very good at regulating our emotions, more often than not, we exit too soon or too late. Like Mr. Laurent Bernaut says – “We are just monkeys wearing sneakers. We are emotional creatures who overestimate our faculties of logic and critical thinking”, a major flaw when the goal is ruthlessly efficient trading.
Also, the biggest challenge when trading discretionarily is Time. Most people don’t have the luxury to be at screens all the time. So if we could quantify our statistical edge and get the computer to trade it, wouldn’t it be much better? Also, even the fastest and most nimble of traders take at least 0.5 seconds to place an order, a computer can place 1000+ at the same time. Also, it can modify existing orders at an even better speed. Next comes scalability - may it be one thousand or one crore, doesn’t make any difference to a computer. But for humans it makes a lot of difference, not realizing that the return on capital in percentage terms is important, not the absolute amount made or lost. In terms of sheer computational power, the algorithm and the hardware supporting it, are capable of looking at exceedingly complex rules & conditions, that too at blazing speeds.
Also, most arbitrage opportunities are fleeting and don’t last for more than a few minutes at max, so you need a computer to identify them because humans are too slow to process such information. Next, with the help of NLP-Natural Language processing, we can now see the public sentiment behind securities and use it in analysis to trade those securities and make money with a high probability. Since the main driver behind the markets is public sentiment, such analysis gives a big edge on knowing the current market scenario. With the help of Machine Learning, we can optimize and enhance strategies such that they have higher odds in our favor, with better risk management.
But also realize that Algorithmic trading is not a silver bullet, you will not suddenly start minting money if you move to algorithms from manual trading. It comes with its learning curve, its own set of knowledge and work that needs to be put into it, and it just offers different pros & cons than the manual style.
Given all this information, at the very least, it is safe to say that the combination of man and machine, in this industry, is a very strong and fruitful one and those who work upon bringing them together, will be rewarded by the markets.