The effect of behavioral bias and frame dependence on real estate prices in Nairobi county
Extreme volatility has plagued financial markets worldwide since the 2008 Global Crisis. Investor sentiment has been one of the key determinants of market movements. In this context, studying the role played by frame dependence and behavioral bias in shaping up investment decisions and real estate prizes seemed important. Behavioral Finance is an evolving field that studies how psychological factors affect decision making under uncertainty. This project seeked to find the influence of certain identified behavioral finance concepts (or biases), namely, emotional time line, herd instinct, mental accounting, loss aversion, behavioral portfolios and the shadow of the past on the effect of real estate prizes in Nairobi County. The study used survey questionnaire to collect data targeting real estate agents within Nairobi region the data analysis was done using descriptive statistics, in which mean, mode, standard deviations, and variances were used. The logistic regression was used to determine statistical relationship between the variables, SPSS application was used for the analysis. The study found out that frame dependence and behavioral bias plays a role in influencing investment decisions of the real estate investor. From the biases investigated Herd instinct and the Shadow of the past have had the most profound positive correlation with real estate prizes. Herd instinct could estimate 3.889 of the real estate prize while the Shadow of the past to an extent of 3.628. Mental accounting, Narrow Framing and Behavioral Portfolios had an effect on the real estate prizes but it was not significant. The study recommends that the real estate investors need to do an analysis of all the investment factors carefully using both traditional finance and behavioral biases before making an investment decision. The investors should also strive to interpret the market and economic indicators since they influence the performance targets of the real estate market.
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