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.
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 [email protected].
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.
This insight article is provided for informational purposes only. The information included in this article should not be used as the sole basis for making a decision as to whether or not to invest in any particular security. In making an investment decision, you must rely on your own examination of the securities and the terms of the offering. You should not construe the contents of these materials as legal, tax, investment or other advice, or a recommendation to purchase or sell any particular security. The information included in this article is based upon information reasonably available to EMAlpha as of the date noted herein. Furthermore, the information included in this site has been obtained from sources that EMAlpha believes to be reliable; however, these sources cannot be guaranteed as to their accuracy or completeness. Information contained in this insight article does not purport to be complete, nor does EMAlpha undertake any duty to update the information set forth herein. No representation, warranty or undertaking, express or implied, is given as to the accuracy or completeness of the information contained herein, by EMAlpha, its members, partners or employees, and no liability is accepted by such persons for the accuracy or completeness of any such information. This article contains certain “forward-looking statements,” which may be identified by the use of such words as “believe,” “expect,” “anticipate,” “should,” “planned,” “estimated,” “potential,” “outlook,” “forecast,” “plan” and other similar terms. Examples of forward-looking statements include, but are not limited to, estimates with respect to financial condition, results of operations, and success or lack of success of certain investment strategy. All are subject to various factors, including, but not limited to, general and local economic conditions, changing levels of competition within certain industries and markets, changes in interest rates, changes in legislation or regulation, and other economic, competitive, governmental, regulatory and technological factors affecting the operations of the companies identified herein, any or all of which could cause actual results to differ materially from projected results.