The importance of downside risk cannot be denied. In this study, we have replaced beta in the five-factor model of using downside beta and have added a momentum factor to suggest a new six-factor downside beta capital asset pricing model (CAPM). Two models are tested—a beta- and momentum-based six-factor model and a downside-beta- (proxy of downside risk) and momentum-based six-factor model. Beta and downside beta are highly correlated; therefore, portfolios are double-sorted to disentangle the correlation. Factor loadings, i.e., size, value, momentum, profitability, and investment, are constructed. The standard methodologies are applied. Data for sample stocks from different non-financial sectors listed in the Pakistan Stock Exchange (PSX) are taken from January 2000 to December 2018. The PSX-100 index and three-month T-bills are taken as proxies for market and risk-free returns. The study uses three subsamples for robustness—period of very high volatility, period of stability, and period of stability and growth with volatility. The results show that the value factor is redundant in both models. The momentum factor is rejected in the beta-based six-factor model only. The beta-based six-factor model shows very low R² in periods of highly volatility. The R² is high for the other periods. In contrast, the downside beta six-factor model captures the downside trend of the market in an effective manner with a relatively high R². The risk–return relationship is stronger for the downside beta model. These reasons lead us to believe that, overall, the downside beta six-factor model is a better option for investors as compared to the beta-based six-factor model in the area of asset pricing models.

This study aims to test the adaptive market hypothesis by using the myopic behavior of investors as a new proxy. The data have been taken from New York Stock Exchange from December 1994 to December 2020. Following this collection of data, the companies’ stock prices were distributed into six different portfolios based on size, investment, a book-to-market value, and operating profit. Ordinal logistic regression was used to calculate the probability of recovery of losses after experiencing a decline in the market. As part of the robustness analysis, this study replaces the Sharpe ratio with a Lower Partial Moment ratio. Most of the results for the Sharpe ratio and Lower Partial Moment ratio are similar. During 1995–1999, 2002–2006, and 2010–2020, the investors have not shown myopic behavior towards losses, but from 2000–2001 and 2007–2009 the investors exhibited myopic characteristics. Furthermore, as investors move between myopic and non-myopic loss aversion, the study reports that the US market is both efficient and inefficient at various points in time, following the adaptive market hypothesis. Thus, such a finding could act as a basis for future investment models by adapting traditional models or by building and contributing to the development of new ones.

The role of family owners in the internal control environment is characterized by contradictory theoretical arguments i.e., entrenchment and alignment behavior. Therefore, the objective of this study is to investigate the behavior exhibited by family owners concerning the internal control environment in an underdeveloped regulatory setting. The study collected both primary and secondary data to use a multivariate regression research design to investigate the impact of family owners and CEOs on the internal control quality and disclosure of enterprises. The results of the current study demonstrated that family owners and family CEO have a negative impact on the internal control quality and disclosure, which validates the entrenchment behavior exhibited by family owners in the Pakistani setting. The results of the current study imply that policymakers should promote strict policy initiatives regarding the effectiveness of internal controls and their reporting so that companies are compelled to have better engagement in internal control practices for the protection of minority shareholders.

Greed plays an important in the fluctuations of stock prices because investors want profits irrespective of the risk taken by them. This study aims to determine, whether, in times of rising trends in the market, greediness is good for the investor or not. Secondly, investors can get high profits by beating the market or not. The already formed deciles portfolios of listed companies on NYSE, AMEX, and NASDAQ based on size and book to market value are taken from the Kenneth R. French data library from Dec 1994 to Dec 2021. Sharpe, Treynor, and Sortino ratios are used as the measure of the performance of portfolios. Ordinal logistic regression is used to calculate the probability at different benchmark levels to determine, whether the investor gets the profit by beating the market or not. The results show that the investor who used the Sharpe ratio has an average 85% probability of getting a profit of more than 75% of the benchmark of S&P-500 in all periods. Thus, the investors’ greediness is good in the long run if the investor considers total risk and can beat the market. By using the Sortino and Treynor ratio, there is an average 50% probability of achieving the profit up to the benchmark which is S&P-500. This means that the investors are not able to beat the market thus, support the efficient market hypothesis by considering the downside and market risk.