Influence of news on rational decision making by financial market investors

Efficient market hypothesis (EMH) states that financial markets are “informationally efficient”, implying that current prices fully reflect all available information. The present study aims at testing the weak form of market efficiency of the individual stocks listed on the Bahrain Bourse for the period 2011 to 2015. Weak form of EMH is tested using the Kolmogorov-Smirnov goodness of fit test, run test and autocorrelation test. The K-S test result concludes that in general the stock price movement does not follow random walk. The results of the runs test reveals that share prices of seven companies do not follow random walk. Autocorrelation tests reveal that share prices exhibit low to moderate correlation varying from negative to positive values. As the study shows mixed results, it is difficult to conclude the weak form of efficiency of Bahrain Bourse.

The biggest challenge facing countries, including India, is creating and managing an LCR (low carbon resilient) economy, which balances the need for high growth rates and is environmentally sustainable. The green bond market provides investors the means to help change the economy into an LCR economy. The study was undertaken to understand the key drivers and the factors influencing the individual retail investor’s decision to invest in green bonds. A survey instrument was designed and administered through the snowball sampling technique to 125 Indian respondents of various age groups who were eligible to invest in the Indian bond market. SPSS software was used to conduct a descriptive analysis followed by regression and conjoint analyses. The study results suggest that the Environmental, Social, and Governance (ESG) rating and credit rating of the green bond issuers are the key factors that influence an individual’s investment decision. The findings also highlight that incentives such as tax exemptions and awareness of green bonds also affect an investor’s decision. This research stands out as one of the first attempts to understand the Indian retail investors’ perception of a green bond.

The financial markets are found to be finite Hilbert space, inside which the stocks are displaying their wave-particle duality. The Reynolds number, an age old fluid mechanics theory, has been redefined in investment finance domain to identify possible explosive moments in the stock exchange. CNX Nifty Index, a known index on the National Stock Exchange of India Ltd., has been put to the test under this situation. The Reynolds number (its financial version) has been predicted, as well as connected with plausible behavioral rationale. While predicting, both econometric and machine-learning approaches have been put into use. The primary objective of this paper is to set up an efficient econophysics’ proxy for stock exchange explosion. The secondary objective of the paper is to predict the Reynolds number for the future. Last but not least, this paper aims to trace back the behavioral links as well.