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Profits Are in the Eyes of the Beholder: Entropy-Based Volatility Indicators and Portfolio Rotation Strategies

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Computational Management

Part of the book series: Modeling and Optimization in Science and Technologies ((MOST,volume 18))

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Abstract

Literature suggests that traders and investors in financial markets perceive changes in expected market volatility represented by the implied volatility index such as the VIX for timing their strategies of portfolio rotation. Researchers have successfully employed the entropy-based measures to study financial time-series to address the issue of nonlinearity and the restrictions associated with theoretical probability distributions. In this study, we implement the approximate entropy (ApEn) and the sample entropy (SaEn) indicators—computed from the India Volatility Index (India VIX)—to study the feasibility of portfolio rotation strategies based on style, size and time horizons. We compute the approximate and the sample entropies, and the India VIX. We find that ApEn and SaEn capture the higher order movements better than the change in India VIX, implying a better indicator of volatile market. Between ApEn and SaEn, the later reflects the fluctuations better. Our findings provide computationally supportive arguments in favour of a potentially beneficial alternative for portfolio managers. Practitioners can use this approach to enhance portfolio returns and to mitigate risk in the context on Indian market.

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Notes

  1. 1.

    The thresholds used for signalling using the India VIX change are: -30, -20, -10, 10, 20, 30, 40, 50, 60, 70, 80 and 90 percentages. Also, multiples of SD in the ApEn and the SpEn considered are -1.75, -1.5, -1.25, -1, -0.75, -0.5, -0.25, 0.25, 0.5, 0.75, 1, 1.25, 1.5.

  2. 2.

    Holding periods of 2, 5, 10, 20, 30, 40, 50, 60 and 90 days are taken for the analyses.

  3. 3.

    For the purpose of computing the Sharpe ratio, we use the risk-free rate (Rf) = 2% for benchmarking or buy-and-hold strategies, and Rf = 0% for zero investment strategies.

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Author information

Authors and Affiliations

  1. Vinod Gupta School of Management, Indian Institute of Technology Kharagpur, Kharagpur, 721302, West Bengal, India

    Abhijeet Chandra

  2. Financial Engineering, Indian Institute of Technology Kharagpur, Kharagpur, 721302, India

    Gaurav Jadhao

  3. BlackRock, Inc., Mumbai, 400063, India

    Gaurav Jadhao

Authors
  1. Abhijeet Chandra
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  2. Gaurav Jadhao
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Corresponding author

Correspondence to Abhijeet Chandra .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Faculty of Engineering, SOA University, Bhubaneswar, Odisha, India

    Srikanta Patnaik

  2. Strategic Management and International Business, Tokyo Institute of Technology, Tokyo, Japan

    Kayhan Tajeddini

  3. School of Management, Victoria University of Wellington, Wellington, New Zealand

    Vipul Jain

Appendix 1: Trading Strategies Using India VIX Change and the Entropies (Both Approximate and Sample Entropies) Tested Through Simulations

Appendix 1: Trading Strategies Using India VIX Change and the Entropies (Both Approximate and Sample Entropies) Tested Through Simulations

See Tables 4.11 and 4.12.

Table 4.11 Trading strategies based on sample entropy and approximate entropy
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Table 4.12 Trading strategies based on India VIX changes
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Chandra, A., Jadhao, G. (2021). Profits Are in the Eyes of the Beholder: Entropy-Based Volatility Indicators and Portfolio Rotation Strategies. In: Patnaik, S., Tajeddini, K., Jain, V. (eds) Computational Management. Modeling and Optimization in Science and Technologies, vol 18. Springer, Cham. https://doi.org/10.1007/978-3-030-72929-5_4

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