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Do Stocks Have a “Memory”? Evidence from the Indian Stock Market


Affiliations
1 MBA (Tech.) Student, NMIMS University, Vile Parle (West), Mumbai - 400 056, India
2 Assistant Professor, Department of Data Science, NMIMS University, Vile Parle (West), Mumbai - 400 056, India

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This paper predicted the price movement of Nifty 50 stocks on the Indian stock market using probability theory. It answered the question, what is the probability of a consecutive up day for a stock after a previous up day, where an up day refers to a trading day on which the closing price of a stock was greater than its previous day's closing price. It further found out the probability of a consecutive up day for a stock after two, three, four, and five previous up days, respectively. We used Bayes' theorem to calculate this. The period of study was from May 17, 2018 to August 10, 2018. The results showed that for some stocks, the probability of a consecutive up day after previous up days was not the same as having a “normal” up day (an up day not conditioned on any previous event whatsoever). This meant that some stocks had a “memory” and their previous up days could be used to predict their future up/down days. The findings of this paper would help both retail and institutional investors make better trading decisions.

Keywords

Bayes' theorem, conditional probability, Indian stock market, Nifty 50, Up day

C02, C11, C12

Paper Submission Date: August 20, 2018 ; Paper sent back for Revision : December 20, 2018 ; Paper Acceptance Date : December 26, 2018

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  • Do Stocks Have a “Memory”? Evidence from the Indian Stock Market

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Authors

Archit Gupta
MBA (Tech.) Student, NMIMS University, Vile Parle (West), Mumbai - 400 056, India
Siba Panda
Assistant Professor, Department of Data Science, NMIMS University, Vile Parle (West), Mumbai - 400 056, India

Abstract


This paper predicted the price movement of Nifty 50 stocks on the Indian stock market using probability theory. It answered the question, what is the probability of a consecutive up day for a stock after a previous up day, where an up day refers to a trading day on which the closing price of a stock was greater than its previous day's closing price. It further found out the probability of a consecutive up day for a stock after two, three, four, and five previous up days, respectively. We used Bayes' theorem to calculate this. The period of study was from May 17, 2018 to August 10, 2018. The results showed that for some stocks, the probability of a consecutive up day after previous up days was not the same as having a “normal” up day (an up day not conditioned on any previous event whatsoever). This meant that some stocks had a “memory” and their previous up days could be used to predict their future up/down days. The findings of this paper would help both retail and institutional investors make better trading decisions.

Keywords


Bayes' theorem, conditional probability, Indian stock market, Nifty 50, Up day

C02, C11, C12

Paper Submission Date: August 20, 2018 ; Paper sent back for Revision : December 20, 2018 ; Paper Acceptance Date : December 26, 2018




DOI: https://doi.org/10.17010/ijrcm%2F2018%2Fv5%2Fi4%2F141544