Record statistics of financial time series and geometric random walks

Abstract

The study of record statistics of correlated series is gaining momentum. In this work, we study the records statistics of the time series of select stock market data and the geometric random walk, primarily through simulations. We show that the distribution of the age of records is a power law with the exponent $\alpha$ lying in the range $1.5 \le \alpha \le 1.8$. Further, the longest record ages follow the Fr\'{e}chet distribution of extreme value theory. The records statistics of geometric random walk series is in good agreement with that from the empirical stock data.