A Hidden Markov Model inference approach to testing the Random Walk Hypothesis: Empirical evidence from the Nigerian Stock Market

Journal of Economic and Financial Sciences

 
 
Field Value
 
Title A Hidden Markov Model inference approach to testing the Random Walk Hypothesis: Empirical evidence from the Nigerian Stock Market
 
Creator Nkemnole, Edesiri
 
Subject Hidden Markov Model; random walk theory; stochastic volatility; stock exchange
Description The movement of stock prices, in capital markets across the world, has been found to be both random and non-random. Basically, for a stock price to follow a random walk, its future price changes randomly based on all currently available information in the stock market, its price history inclusive. Some research findings have shown that the existing traditional unit root tests have low statistical power and hence cannot capture gradual changes over successive observations. Consequently, there is a need to revisit the random walk theory in stock prices using other tests. This study employs a Hidden Markov Model (HMM) with time-varying parameters to assess whether the stock price movements of the Nigerian Stock Exchange (NSE) follow a random walk process, or otherwise. Via hidden states, the HMM allows for periods with different volatility levels characterised by the hidden states. By simply accounting for the non-constant variance of the data with a two-state Hidden Markov Model and taking estimation into account via the Sequential Monte Carlo Expectation Maximisation (SMCEM) technique, this study finds no support of randomness. In conclusion, the stock price movements of the NSE do not follow the random walk process.
 
Publisher AOSIS
 
Contributor
Date 2016-12-03
 
Type info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion —
Format application/pdf
Identifier 10.4102/jef.v9i3.66
 
Source Journal of Economic and Financial Sciences; Vol 9, No 3 (2016); 696-713 2312-2803 1995-7076
 
Language eng
 
Relation
The following web links (URLs) may trigger a file download or direct you to an alternative webpage to gain access to a publication file format of the published article:

https://jefjournal.org.za/index.php/jef/article/view/66/63
 
Rights Copyright (c) 2016 Edesiri Nkemnole https://creativecommons.org/licenses/by/4.0
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