The cryptocurrency market has received immense consideration in media and academia since the beginning of 2013 because of its huge price fluctuation. This study focuses on Arab investors who invest in the cryptocurrency market by investigating the influence of behavioral finance factors on investment decisions in the cryptocurrency market. A quantitative approach was used by employing a snowball sampling method through 112 questionnaires. The results show that herding theory, prospect theory, and heuristic theory have a significant effect on investors’ investment decisions in the cryptocurrency market. This emphasizes the significant role of the proposed behavioral factors as determinants of the investors’ investment decisions. This study contributes to the existing research by consolidating the results of different researches in this study. It also contributes to the investors’ understanding of the dynamics of the cryptocurrency market and it enhances the ability to make informed decisions based on their understanding. The implication of the findings will prepare hit and run investors to be progressively prepared to stay in the cryptocurrency market and develop their abilities on the most proficient method to settle on sound venture choices. Furthermore, the findings of this study will encourage financial specialists to realize that information on the traditional finance theory is not adequate to excel in the cryptocurrency market.

The study aims to investigate the existence of overconfidence bias in Vietnam, Thailand, and Singapore. This paper focuses on the Vietnam Stock Market and other two countries of ASEAN, namely Singapore and Thailand. Data was collected over the period from January 1, 2014 to December 31, 2018, daily returns for each of the securities. This paper uses the time series method, namely ADF test, Granger Causality and VAR approach to find evidences of the overconfidence effect in Vietnam in relation to some ASEAN markets. The results show similarities between the observed countries with slight variations, with focus on Vietnam market. In general concrete evidences of overconfidence were found in both Vietnamese and Singaporean markets, in which Singaporean investors show higher degree of overconfidence than Vietnamese investors. Overconfidence is not as clear in Thai market, however a direct causal link from increased returns to increased investor confidence was found. From the model deployed in the paper, there are reasons to conclude that Thai investors are under-confident. The findings of the study shed lights into the existence of overconfidence bias in Vietnam, Thailand, and Singapore on a comparative basis, provide more insights and implications for future research in this new and rising field of research.

The paper aims to examine relationships between search-based sentiment and stock market reactions in Vietnam. This study constructs an internet search-based measure of sentiment and examines its relationship with Vietnamese stock market returns. The sentiment index is derived from Google Trends’ Search Volume Index of financial and economic terms that Vietnamese searched from January 2011 to June 2018. Consistent with prediction from sentiment theories, the study documents significant short-term reversals across three major stock indices. The difference from previous literature is that Vietnam stock market absorbs the contemporaneous decline slower while the subsequent rebound happens within a day. The results of the study suggest that the sentiment-induced effect is mainly driven by pessimism. On the other hand, optimistic investors seem to delay in taking their investment action until the market corrects. The study proposes a unified explanation for our findings based on the overreaction hypothesis of the bearish group and the strategic delay of the optimistic group. The findings of the study contribute to the behavioral finance strand that studies the role of sentiment in emerging financial markets, where noise traders and limits to arbitrage are more obvious. They also encourage the continuous application of search data to explore other investor behaviors in securities markets.