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This paper aims to use three proxy variables – initial public offerings, trading volume and business confidence index (BCI) to construct an investor sentiment index both for the USA and China, taking into account the challenging periods of the COVID-19 pandemic and the Russo-Ukrainian conflict.

Based on monthly data for a period from January 2009 to June 2022, this paper uses data of BCI, consumer confidence index (CCI), gross domestic product, trading volume and Fama and French (1993) factor data; linear regression of single and multifactor model; and EGARCH-M model for analyzing the effect of investor sentiment on stock market return and volatility, both in the USA and China.

The empirical results indicate the suitability of BCI over CCI as a measure of investor sentiment, both in the USA and China. The results indicate that investor sentiment has a significant positive effect on the excess returns in the stock market in both countries. Moreover, the effect of investor sentiment is higher in China than it is in the USA. Such an effect of investor sentiment is significant and fluctuates asymmetrically in the short run but loses its significance in the long run. Optimistic investor sentiment has a larger effect on the stock market volatility in the USA, while the pessimistic investor sentiment has a larger effect in the Chinese stock market.

This paper focuses on finding a more suitable proxy for investor sentiment from BCI or CCI. This paper also contributes by including both optimism and pessimism in explaining the stock return and volatility in both markets. The overall findings are important for understanding investor behavior in different market conditions.

Conventional theories of financial management are notably inconspicuous when considering the influence of heuristic-driven biases and fundamental and technical anomalies on institutional investors' investment decision-making performance and market efficiency, particularly, in emerging Asian economies. This study aims to explore the mechanism by which heuristic driven biases (i.e. cognitive heuristic biases and recognition-based heuristic biases) influence institutional investors' investment decision-making, investment performance and perceived market efficiency, with a mediating role of fundamental and technical anomalies and the moderating role of financial knowledge in Pakistan.

Data were collected through a survey completed by 180 institutional investors trading on the Pakistan Stock Exchange. Structural equation modeling was used to analyze the data and test the hypotheses.

The results suggest that heuristic-driven biases have a significant negative influence on perceived market efficiency and investment performance and a significant positive effect on investment decisions of institutional investors. Fundamental and technical anomalies appeared to mediate these relationships. The results also revealed that financial knowledge moderates these relationships.

This study pioneers research on the links among heuristic-driven biases, financial knowledge, fundamental and technical anomalies and institutional investors' decisions and performance. This adds to the understanding of the role that heuristic-driven bias plays in investment management activities and enhances the appreciation of various behavioral aspects and their influence on investment decision-making and performance in an emerging market. It also contributes to the literature on behavioral finance, specifically the role of heuristics in investment strategies, which is still in its initial stage in developed countries, let alone in developing countries. The current research contributes to the literature by defining heuristic-driven biases as antecedents and fundamental and technical anomalies as intervening variables for irrational investment decision-making and poor investment performance. In addition, this study underlines the significance of utilizing financial knowledge to manage the antecedents and repercussions of fundamental and technical anomalies.