Abstract

Inverse cubic law has been an established Econophysics law. However, it has been only carried out on the distribution tails of the log returns of different asset classes (stocks, commodities, etc.). Financial Reynolds number, an Econophysics proxy for bourse volatility has been tested here with Hill estimator to find similar outcome. The Tail exponent or α ≈ 3, is found to be well outside the Levy regime (0 < α < 2). This confirms that asymptotic decay pattern for the cumulative distribution in fat tails following inverse cubic law. Hence, volatility like stock returns also follow inverse cubic law, thus stay way outside the Levy regime. This piece of work finds the volatility proxy (econophysical) to be following asymptotic decay with tail exponent or α ≈ 3, or, in simple terms, ‘inverse cubic law’. Risk (volatility proxy) and return (log returns) being two inseparable components of quantitative finance have been found to follow the similar law as well. Hence, inverse cubic law truly becomes universal in quantitative finance.

Highlights

  • Bachelier’s trailblazing random walk model had an assumption such as the price changes emerge out as a result of many independent and external shocks

  • It has been found that the tails in case of return distribution for any index interestingly found to follow the power law

  • The observation points were substantially lower for regular Reynolds number (Re) in comparison to ReHFT

Read more

Summary

INTRODUCTION

Bachelier’s trailblazing random walk model (inspired from Brownian motion of particles) had an assumption such as the price changes emerge out as a result of many independent and external shocks. He predicted the resulting distribution of returns to be Gaussian (Bachelier, 1900). The study found similar tail index for ‘Risk’ (represented by volatility) that of ‘Return’. This in turn completes the ‘Risk-Return’ characteristics comparison. Both ‘Risk’ and ‘Return’ ware found to experience the same decay coefficient in its tails

LITERATURE REVIEW
Economics of superstars
METHODOLOGY
CONCLUSION
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call