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Human Emotions and How Systematic Investing Can Mitigate the Impact on Your Portfolio?

The last week, the week of October 7th, displayed a good example to our investment team about the virtue of systematic decision making in investing. Often it is difficult to control emotions in markets and the times when extraordinary events occur become even more testing. September 20th saw the largest single day jump in BSE Sensex and NIFTY 50 (the two most popular stock market indices in India) in recent times. The market then gradually inched downwards. It seemed like the fire power of the corporate tax cuts had run its course and there was nothing else for the market to do but steadily limp lower.

Our systematic model, which uses a quant and sentiment (NLP) driven logic, was long the market. It typically goes long a number of stocks in Nifty 50, and expresses any market bearish views via a short Nifty futures contract. However, around this time, it did not express any bearish views. There was no Nifty short in the model. On Monday, October 7th, we saw the Sensex fall. Our emotional thought process wondered why our model did not express any market short. Was there any obvious weakness in the model? Did it need any tweaking?
There is a parameter in our model that controls the onset of the market short. Based on our research, it is at a moderate value that shorts the market relatively sparingly. Setting this same parameter to a more aggressive value would short the market more often. There is nothing wrong with this, just as there is nothing wrong with a long-short strategy. Setting this parameter to a mild value tilts the model towards a long only model, and setting it to a more aggressive value gives the model a long-short character. A-priori, one must make the decision of what one’s requirement is – is it total return, or is it Sharpe – and stick to the decision.

Since we are not using much leverage in the model, it focuses on total return. A fully long-short strategy – which would short Nifty futures more often – will have a better Sharpe but lower returns – something better exploited using leverage. In any case, when we looked at the model after the volatile movements over the last few months, we decided to go with the model parameter that puts on Nifty only infrequently. But on Monday, October 7th, we saw the Sensex fall, and wondered whether the model was on the correct course of action. Having the short Nifty position on would have been great as the market gradually struggled lower. The model would have made money on this lower market move.

But this reversed on Wednesday, October 9th. As the market opened after the October 8th holiday, the Sensex and Nifty soared. If we had followed our emotions, and shorted Nifty futures, we would have lost significantly. Our decision has been to be steady in our course and avoid any emotional decisions. The market movement was mixed on Thursday and Friday. Overall, the market movement on Wednesday was the most dominant and deciding for the week.

The lesson is two-fold. It takes great discipline to not follow emotions in investment. And, even if one has a quantitative, machine learning based model, it is easy to yield to emotions and start tweaking with the model parameters. A number of quant managers yield to this temptation and tweak the parameters at the worst possible moment. Emotional decision making is not just an affliction of the discretionary trader, quant traders are just as wont to giving in to emotions. Discipline does not come easy. It takes experience and practice.

Research Team
EM Alpha LLC

For more EMAlphainsights on Emerging Markets, please visit https://emalpha.com/insights/. To know how you can use EMAlpha’s unstructured data on Emerging Markets for better investment decisions, please send us an email at research@emalpha.com.

About EMAlpha:

EMAlpha, a data analytics and investment management firm focused on making Emerging Markets (EMs) accessible to global investors and unlocking EM investing using machines. EMAlpha’s focus is on Unstructured Data as the EMs are particularly susceptible to swings in news flow driven investor sentiment. We use thoroughly researched machine learning tools to track evolving sentiment specifically towards EMs and EMAlpha pays special attention to the timely measurement of news sentiment for investors as these markets can be finicky and sentiment can be capricious.Our team members have deep expertise in research and trading in multiple Emerging Markets and EMAlpha’s collaborative approach to combining machine learning tools with a fundamental approach help us understand these markets better.

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