Computing the Investor Sentiment Index for Nigeria: Methodology and Applications
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Abstract
This study computed an Investor Sentiment Index (ISI) for the Nigerian stock market using the Hamilton Filter Decomposition method. The objective is to estimate an Index that reflect Nigerian investor sentiment over the period from January 15, 2009, to November 21, 2024. The Hamilton Filter allows for the separation of long-term trends from short-term cyclical fluctuations, which are then normalized using the min-max approach to create a sentiment index that spans from 0 to 1. The findings from the computed index suggest that investor sentiment generally follows the market’s movements, exhibiting greater volatility during periods of crises, such as the 2008-2011 Global Financial Crisis and the 2020-2021 COVID-19 pandemic. Additionally, sentiment reacts swiftly to news and market changes, making it a leading indicator of market trends, though it does not always align perfectly with the underlying stock index. This research highlights the significant role of investor sentiment in driving market volatility and offers insights into the psychological factors influencing stock prices.
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