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The perception of time, risk and return during periods of speculation

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  • Emanuel Derman

Abstract

What return should you expect when you take on a given amount of risk? How should that return depend upon other people's behaviour? What principles can you use to answer these questions? In this paper, I approach these topics by exploring the consequences of two simple hypotheses about risk. The first is a common-sense invariance principle: assets with the same perceived risk must have the same expected return. It leads directly to the well known Sharpe ratio and the classic risk-return relationships of arbitrage pricing theory and the capital asset pricing model. The second hypothesis concerns the perception of time. I conjecture that in times of speculative excitement, short-term investors may instinctively imagine stock prices to be evolving in a time measure different from that of calendar time. They may perceive and experience the risk and return of a stock in intrinsic time, a dimensionless time scale that counts the number of trading opportunities that occur, but pays no attention to the calendar time that passes between them. Applying the first hypothesis in the intrinsic time measure suggested by the second, I derive an alternative set of relationships between risk and return. Its most noteworthy feature is that, in the short-term, a stock's trading frequency affects its expected return. I show that short-term stock speculators will expect returns proportional to the temperature of a stock, where temperature is defined as the product of the stock's traditional volatility and the square root of its trading frequency. Furthermore, I derive a modified version of the capital asset pricing model in which a stock's excess return relative to the market is proportional to its traditional beta multiplied by the square root of its trading frequency. I also present a model for the joint interaction of long-term calendar-time investors and short-term intrinsic-time speculators that leads to market bubbles characterized by stock prices that grow super-exponentially with time. Finally, I show that the same short-term approach to options speculation can lead to an implied volatility skew. I hope that this model will have some relevance to the behaviour of investors expecting inordinate returns in highly speculative markets.

Suggested Citation

  • Emanuel Derman, 2002. "The perception of time, risk and return during periods of speculation," Quantitative Finance, Taylor & Francis Journals, vol. 2(4), pages 282-296.
  • Handle: RePEc:taf:quantf:v:2:y:2002:i:4:p:282-296
    DOI: 10.1088/1469-7688/2/4/304
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    References listed on IDEAS

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    Cited by:

    1. Siddiqi, Hammad, 2014. "Analogy Making and the Structure of Implied Volatility Skew," MPRA Paper 60921, University Library of Munich, Germany.
    2. Zapart, Christopher A., 2009. "On entropy, financial markets and minority games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(7), pages 1157-1172.
    3. Siddiqi, Hammad, 2013. "Mental Accounting: A Closed-Form Alternative to the Black Scholes Model," MPRA Paper 50759, University Library of Munich, Germany.
    4. Stephen Matteo Miller, 2015. "Leverage effect breakdowns and flight from risky assets," Quantitative Finance, Taylor & Francis Journals, vol. 15(5), pages 865-871, May.
    5. Julia M. Puaschunder, 2020. "Social Volatility and Temporal Foci as Accelerators of Economic Trends," Proceedings of the 20th International RAIS Conference, December 6-7, 2020 016jpm, Research Association for Interdisciplinary Studies.
    6. Patrick Chang & Etienne Pienaar & Tim Gebbie, 2020. "The Epps effect under alternative sampling schemes," Papers 2011.11281, arXiv.org, revised Aug 2021.
    7. Patrick Schotanus, 2022. "Cognitive economics and the Market Mind Hypothesis: Exploring the final frontier of economics," Economic Affairs, Wiley Blackwell, vol. 42(1), pages 87-114, February.
    8. Siddiqi, Hammad, 2015. "Anchoring Heuristic in Option Pricing," MPRA Paper 63218, University Library of Munich, Germany.
    9. Dieter Hendricks & Tim Gebbie & Diane Wilcox, 2015. "Detecting intraday financial market states using temporal clustering," Papers 1508.04900, arXiv.org, revised Feb 2017.
    10. Patrick Chang & Roger Bukuru & Tim Gebbie, 2019. "Revisiting the Epps effect using volume time averaging: An exercise in R," Papers 1912.02416, arXiv.org, revised Feb 2020.
    11. Chang, Patrick & Pienaar, Etienne & Gebbie, Tim, 2021. "The Epps effect under alternative sampling schemes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    12. Iacopo Giampaoli & Wing Lon Ng & Nick Constantinou, 2013. "Periodicities Of Foreign Exchange Markets And The Directional Change Power Law," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 20(3), pages 189-206, July.
    13. Han, Ruokang & Takahashi, Taiki, 2012. "Psychophysics of time perception and valuation in temporal discounting of gain and loss," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(24), pages 6568-6576.
    14. Hervé OTT, 2012. "Fertilizer markets and its interplay with commodity and food prices," JRC Research Reports JRC73043, Joint Research Centre.
    15. Albert S. Kyle & Anna A. Obizhaeva, 2016. "Market Microstructure Invariance: Empirical Hypotheses," Econometrica, Econometric Society, vol. 84(4), pages 1345-1404, July.

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