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MPIWG_PROJECTS:
Digital and Computational History of Science
Abstract:
Financial time series are usually analyzed by looking at the log-returns. This phenomeno-logical approach is justified by the apparent multiplicativity of stochastic noise in the process. In fact, it hides the non-stationarity of the data. Here we shift the focus to the interplay of return and volume instead of log returns. We analyze statistics and causal relationships between the squared price and the volume increments of S&P 500 data. A new quantity, namely the ratio of price increments and the square root of the traded volume shows particular non-stationarity giving rise to a Hurst exponent of 0.65 by the so-called Moses effect. (c) 2023 Elsevier B.V. All rights reserved.
