Wavelet analysis of Stock Market trends: Investigating behavioural patterns in the Johannesburg and London Stock Markets

Abstract

This research explores a view that considers price index movements as a reflection of the aggregate rational and sentiment psychological elements of market agents. This perspective asserts that both psychological elements of agent rational and sentiment influence choices that drive price movements in stock markets. To investigate this behavioural link between markets and market agents, the research caries out a time series analysis of Johannesburg and London stock market trends (JSE and FSTE indexes). In examining this link using index price information, the research considers its implications on the conceptualisation of market efficiency by interrogating the very meaning of information. The research employs a Morlet continuous wavelet transform as a special form of multiresolution analysis for resolving market price signals into information patterns. The research attempts to interpret these information patterns pragmatically in terms of market agents’ beliefs about the market through a hypothesis that maps price information to liquidity and agent psychology. The study verifies the plausibility of the research hypothesis by using cross-wavelet analysis to correlate index movements and volatility. Research results appear to confirm that price index patterns represent agents’ belief in the market as an aggregate of their rational and sentiment. Wavelet analysis of the FTSE 100 index demonstrates how changes in market belief or mind-set in 2008 (the global financial crisis) and 2012 (Greece debt crisis) closely relate to its volatility measure, the VIX. The research concludes that information transparency might not be adequate to qualify market efficiency. Beyond informational transparency is a subjective element of truth that brings market beliefs forth. Studying these beliefs through market rational and sentiment patterns might be key to understanding the market landscape of the future and understanding market horizons to enable better risk-returns forecasting.