Financial investment decisions under uncertainty: Heuristics and biases

Traditional finance theory assumes that individuals exhibit risk aversion with the intention of achieving the maximum utility and they make rational decisions consistently. The markets where investor behavior is assumed to be rational within the frame of efficient market hypothesis is considered as an efficient market that it is impossible to beat the market by getting excessive returns. On the other hand, behavioral finance investigates how individuals behave in fact in the process of financial decision making and which factors cause such behaviors. This study includes two empirical applications that examine the behavioral factors affecting the investing decisions of investors trading in various markets. In the first section, a brief information is given about the traditional finance theories and the genesis of behavioral finance and its historical process are explained. In the second section, several behavioral factors that affect the decisions of investors have been addressed. In the third section, herding behavior has been investigated in the cryptocurrency market by using the data of closing prices, market caps, trading volumes of 14 leading cryptos and economic policy uncertainty index. Moreover, two different regimes determined by applying regime switching approach where low and high volatility is observed and the effect of economic policy uncertainty on herding behavior under such regimes has been analyzed. Additionally, observation period has been splitted into sub-periods consideringly the results of structural break tests and analyses have been repeated. In the fourth section, for the purpose of examining the existence of overconfidence behavior in Istanbul Stock Exchange (ISE), by using the data of daily closing prices and trading volumes of BIST100 index, feedforward neural network non-linear Granger causality test and non-linear impulse response analysis have been applied.