Test of Persistence in Indian Stock Market: A Rescaled Range Analysis

While most traditional science deals with supposedly predictable phenomena like gravity, electricity, or chemical reactions, Chaos Theory deals with nonlinear things that are effectively impossible to predict or control, like turbulence, weather, the stock market, our brain states, and so on. Hence,...

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Bibliographic Details
Published in:The ICFAI journal of applied finance 2015-10, Vol.21 (4), p.5
Main Authors: Mishra, Sibanjan, Mishra, Bimal Chandra
Format: Article
Language:English
Subjects:
Chaos theory
Dow Jones averages
Efficient markets
Emerging markets
Equity
Financial analysis
Fractals
Hypotheses
Prices
Rates of return
Securities markets
Stock exchanges
Studies
Time series
Volatility
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Summary:While most traditional science deals with supposedly predictable phenomena like gravity, electricity, or chemical reactions, Chaos Theory deals with nonlinear things that are effectively impossible to predict or control, like turbulence, weather, the stock market, our brain states, and so on. Hence, such processes focus on non-randomness, nonlinearity and chaotic characteristics. In recent times, such nonlinear dynamics and chaotic dynamics have augmented in the field of financial analysis. This paper studies the extent to which the daily return data from the Indian Stock Exchange indices (Nifty and Sensex) exhibit these nonlinear, non-random characteristics. The Hurst exponent in rescaled range analysis rejects the hypothesis that the index return series are random, independent and identically distributed. The BDS test provides evidence for nonlinearity. The results confirm the existence of fractal structure (i.e., self-similarity across different scales) in Nifty and Sensex. Basing on these results, technical analysis theory, i.e., Elliot Wave Theory, can also be justifiable.
ISSN:0972-5105