Theoretically, investors are considered to be rational decision makers in regards to trading in stock markets, however, some empirical studies have statistically discredited this believe. Evidence shows that investors seem to act irrationally in the financial markets. This research, therefore, aims to empirically investigate investor's irrational behavior, specifically, overconfidence behavior in the Saudi stock market, Tadawul. The data under investigation is from 2007 to 2018, monthly based. According to previous research, positive past market returns influence the level of investors' overconfidence leading to higher trading turnover in stock markets. To test for overconfidence behavior, a market-wide Vector autoregression (VAR) model is designed to investigate the lead-lag relationship between market returns and market turnover. The results obtained in this research suggest that investors in the Saudi stock market are overconfident.

The main purpose of conducting this research is to investigate the impact of intellectual capital efficiency (ICE) and its components -human capital efficiency (HCE) and structural capital efficiency (SCE) -on bank credit and insolvency risks in the Saudi banking industry. To assess such a relationship, value added intellectual coefficient model (VAIC) along with a couple of panel data techniques were utilized by using quarterly observations spanning from the first quarter of 2009 to the fourth quarter of 2018. The carried out empirical results confirm the existence of a significant negative relationship between ICE, in particular HCE, and bank credit and insolvency risks.

This research paper investigates the impact of stock prices on real economic activity in the Saudi Arabian economy. We utilize various econometric techniques -Johansen and Juselius's (1990) cointegration tests and Granger's (1969) causality testto assess such a relationship, based on quarterly observations spanning the period from the first quarter of 2010 to the fourth quarter of 2018. Our empirical evidence indicates the presence of a significant cointegrating relationship between the two variables being examined; in other words, stock prices have a significant impact on real economic growth. Specifically, the estimated long-run relationship reveals that a 1 percent increase in stock prices would boost economic growth by 0.32 percent. In addition, the error correction model suggests that when the economy deviates from its steady state condition, it needs about a year and a half to return to its equilibrium condition. Lastly, this paper applies the most common Granger causality test, which confirms the essential role of stock prices in predicting changes in economic growth.