Spurious trend switching phenomena in financial markets

TL;DR

This paper explains how apparent power-law behaviors in financial market data, like volatility and trade times, can arise from biased data selection and data formatting, rather than intrinsic market properties.

Contribution

It demonstrates that observed power laws in financial data are artifacts of biased sampling and data structure, not fundamental market phenomena.

Findings

Power laws result from biased subset selection.

Bias affects volatility, volume, and intertrade time statistics.

Data formatting influences observed power-law behaviors.

Abstract

The observation of power laws in the time to extrema of volatility, volume and intertrade times, from milliseconds to years, are shown to result straightforwardly from the selection of biased statistical subsets of realizations in otherwise featureless processes such as random walks. The bias stems from the selection of price peaks that imposes a condition on the statistics of price change and of trade volumes that skew their distributions. For the intertrade times, the extrema and power laws results from the format of transaction data.