Analysing stock market data—Market sentiment approach and its measures

Abstract

This paper states that market sentiments are central to any financial data analysis. A vivid distinction is made between studying financial data in terms of the concept of volatility and in rapport to analysing financial data in terms of market sentiments. The former is an existing approach that is extensively used and the latter is a proposed tactic. Methods of devising constructs for defining relative and absolute market sentiments are also discussed. Patterns of market sentiments in terms of the model parameters are discussed and a few new measures that capture the hypothesized market sentiments are proposed. As an application of the proposed line of approach, this study analyses weekly market sentiments that govern Domestic Company Indices of Botswana Stock Exchange.

Keywords:

• divergence measures
• equity price
• market sentiments
• multinomial model
• volatility
• weekly states

JEL classifications:

• C 19
• G13
• G 14

Public Interest Statement

Analysis of market sentiments is central to any financial data analysis. Rao and Moseki (2009) advocated market sentiments approach to analyse financial data as opposed to the time series based GARCH model approach which has been well researched over the past several decades. In their work, a clear distinction was made between the existing approach of studying financial data in terms of extensively used concept of volatility and the proposed approach in terms of market sentiments. In this paper, we further explore the types of market sentiments and device constructs for defining relative and absolute market sentiments. A few possible patterns of market sentiments in terms of the model parameters are discussed and new measures which capture the hypothesized market sentiments are proposed. As an application of the proposed line of approach, we analyse weekly absolute market sentiments that govern Domestic Company Indices of Botswana Stock Exchange.

Additional information

Funding

Funding. The authors received no direct funding for this research.

Notes on contributors

K.K. Moseki

K.K. Moseki is a lecturer in the Department of Statistics, University of Botswana. He is pursuing his PhD in Statistics at the same department. He has published research papers in regional journals. His research interests include financial data analysis, time series, among others.

K.S. Madhava Rao

K.S. Madhava Rao is a professor in the Department of Statistics, University of Botswana. He has published extensively in national, regional and international peer-reviewed journals with high-impact factors. His research areas include nonparametric inference, empirical likelihood, social sciences, agricultural and financial data analysis.