Stylized Facts in Internal Rates of Return on Stock Index and its Derivative Transactions

TL;DR

This paper investigates universal statistical features of internal rates of return in stock and derivative markets, revealing differences based on trading duration and potential for causality analysis and strategy inference.

Contribution

It introduces the analysis of probability distributions of internal rates of return in stock and derivative transactions, highlighting their potential for understanding market dynamics and investor strategies.

Findings

Distributions differ between stock indices and derivatives when a duration threshold is applied.

Discrete spectra from noise trader strategies contrast with smooth distributions from fundamentalist strategies.

Internal rate of return distributions can help infer causality and investment strategies.

Abstract

Universal features in stock markets and their derivative markets are studied by means of probability distributions in internal rates of return on buy and sell transaction pairs. Unlike the stylized facts in log normalized returns, the probability distributions for such single asset encounters encorporate the time factor by means of the internal rate of return defined as the continuous compound interest. Resulting stylized facts are shown in the probability distributions derived from the daily series of TOPIX, S & P 500 and FTSE 100 index close values. The application of the above analysis to minute-tick data of NIKKEI 225 and its futures market, respectively, reveals an interesting diffference in the behavior of the two probability distributions, in case a threshold on the minimal duration of the long position is imposed. It is therefore suggested that the probability distributions of the internal rates of return could be used for causality mining between the underlying and derivative stock markets. The highly specific discrete spectrum, which results from noise trader strategies as opposed to the smooth distributions observed for fundamentalist strategies in single encounter transactions may be also useful in deducing the type of investment strategy from trading revenues of small portfolio investors.