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Fractal Dimensional Analysis in Financial Time Series


Affiliations
1 Center for Interdisciplinary Studies in Science and Technology (CISST), Sardar Patel University, Vallabh Vidyanagar, Gujarat, India
2 Department of Mathematics, Sardar Patel University, Vallabh Vidyanagar, Gujarat, India
3 Department of Mathematics, G. H. Patel College of Engineering & Technology, Vallabh Vidyanagar, Gujarat, India
     

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A predictability index for time series of a financial market vector consisting of chosen market parameters is suggested providing a measure of long range predictability of the market. It is based on fractional Brownian motion that includes Brownian motion as a particular case followed by the time series of financial market parameters. By analysing respective time series, these indices are computed for parameters like volatility, FII investments in the local market, IIP numbers, CPI numbers, Dow Jones Index, different stock market indices, currency rates, and gold prices.

Keywords

Fractional Brownian Motion, Hurst Exponent, Fractal Dimension, Predictability Index.
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  • Bhatt, S. J., Dedania, H. V., & Shah, V. R. (2013). Fractional brownian motion and predictability index in financial market. Global Journal of Mathematical Sciences: Theory and Practical, 5(3), 197-203.
  • Black, F., & Scholes, M. (1973). The pricing of options and corporate liabilities. Journal of Political Economy, 81(3), 637-654.
  • Falconer, K. (2003). Fractal geometry: Mathematical foundations and applications. John Wiley & Sons Ltd, England.
  • Lo, A. W., & MacKinlay, A. C. (1988). Stock market prices do not follow random walks: Evidence from a simple specification test. The Review of Financial Studies, 1(1), 41-66.
  • Mandelbrot, B. B., & Van Ness, J. W. (1968). Fractional Brownian motions, fractional noises and applications. SIAM Review, 10(4), 422-437.
  • Mandelbrot, B. B. (1977). The fractal geometry of nature, W. H. Freeman and Co., New York.
  • Merton, R. C. (1973). Theory of rational option pricing. The Bell Journal of Economics and Management Science, 4(1), 141-183.
  • Mulligen, R. F. (2004). Fractal analysis of highly volatile markets: An application to technology equities. The Quarterly Review of Economics and Finance, 44(1), 155-179.
  • Petukhov, K. (2009). Rescaled Range Analysis. Retrieved from www.mathworks.in/matlabcentral/ fileexchange/25414-rescaled-range-analysis
  • Qian, B., & Rasheed, K. (2004). Hurst exponent and financial market predictability, Proc. of 2nd IASTED Intern. Conference on Financial Engineering and Applications, 203-209.
  • Rangarajan, G., & Sant, D. A. (1997). A climate predictability index and its applications. Geophysical Research Letters, 24(10), 1239-1242.
  • Rangarajan, G., & Sant, D. A. (2004). Fractal dimensional analysis of Indian climatic dynamics. Chaos, Solitons and Fractals, 19, 285-291.
  • Rostek, S. (2009). Optional pricing in fractional Brownian markets. 622 Lecture Notes in Economics & Mathematical Systems, Springer-Verlag, New York.
  • Sagan, H. (1994). Space-Filling Curves, Springer-Verlag, Berlin.
  • Suppannavar, S. (2008). Indian Securities Market Review, NSE, XI.
  • www.bloomberg.com
  • www.globalfinancialdata.com
  • www.gold.org
  • www.mospi.nic.in
  • www.nseindia.com
  • www.sebi.gov.in

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  • Fractal Dimensional Analysis in Financial Time Series

Abstract Views: 350  |  PDF Views: 0

Authors

S. J. Bhatt
Center for Interdisciplinary Studies in Science and Technology (CISST), Sardar Patel University, Vallabh Vidyanagar, Gujarat, India
H. V. Dedania
Department of Mathematics, Sardar Patel University, Vallabh Vidyanagar, Gujarat, India
Vipul R. Shah
Department of Mathematics, G. H. Patel College of Engineering & Technology, Vallabh Vidyanagar, Gujarat, India

Abstract


A predictability index for time series of a financial market vector consisting of chosen market parameters is suggested providing a measure of long range predictability of the market. It is based on fractional Brownian motion that includes Brownian motion as a particular case followed by the time series of financial market parameters. By analysing respective time series, these indices are computed for parameters like volatility, FII investments in the local market, IIP numbers, CPI numbers, Dow Jones Index, different stock market indices, currency rates, and gold prices.

Keywords


Fractional Brownian Motion, Hurst Exponent, Fractal Dimension, Predictability Index.

References