Portfolio selection strategies and cognitive psychology biases: a behavioral evidence from the Nigerian equity market

  • Received May 24, 2018;
    Accepted August 14, 2018;
    Published September 14, 2018
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  • Article Info
    Volume 15 2018, Issue #3, pp. 267-282
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    1 articles

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The empirical evidence in the developed equity markets such as the United States, the United Kingdom, Germany, Japan and emerging markets had pronounced that there are institutional and individual investors’ cognitive psychology and mental biases in favor of the Growth Stocks, that is, the Growth Stocks are always preferred to the Value Stocks by the investors. The investors most times prefer the Growth Stocks to the Value Stocks irrespective of the stock fundamentals behavior in the equity market. The paper investigated whether Cognitive Psychology and Mental biases affect Portfolio Selection strategies using the Growth or the Value Stocks investment styles in the Nigerian Stock Market. In the study, the summary of the primary data was described and Multinomial Logistic Regression (MLR) models were adopted to make inferential decisions. The paper collected primary data through questionnaire administered to individual and institutional investors on the floor of Nigeria Stock Exchange (NSE). The findings from the analyses conducted confirmed a strong existence of Cognitive Psychology and mental biases in favor of the Growth Stocks in the Nigerian Equity Market. Investors had more belief in Growth Stocks than the Value Stocks notwithstanding the behavior of the market fundamentals. The study recommended that investors should seriously consider occurrences and performance fundamentals in Portfolio Selection in the Nigerian Equity Market.

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    • Table 1A. Gender
    • Table 2A. Age
    • Table 3A. Marital status
    • Table 1B. Occupational financial analysis
    • Table 2B. Highest qualification
    • Table 3B. Professional qualification
    • Table 4B. Level
    • Table 1C. Descriptive statistics
    • Table 2C. Goodness-of-Fit
    • Table 3C. Model fitting information (MFI)
    • Table 4C. Pseudo R-square
    • Table 5C. Likelihood ratio tests (LRT)
    • Table 6C. Parameter estimate
    • Table 7C. Classification
    • Table 1D. Case processing summary
    • Table 2D. Reliability statistics