We examine whether stock-level options information drives mutual fund performance. Our paper is motivated by existing studies indicating that options prices or implied volatilities predict stock returns. We find that stock-implied volatility innovations forecast mutual fund performance....

This study analyzes the impact of a newly emerging type of anti-money laundering regulation that obligates cryptocurrency exchanges to report suspicious transactions to financial authorities. We build a theoretical model for the reporting decision structure of a private bank or cryptocurrency...

This study investigates the economic and financial drivers of volatility changes and integrates them into stock market volatility forecasting. We first collect a diverse set of predictor variables and analyze them within a unified framework. We discover that only a small number of variables...

This study predicts stock market volatility and applies them to the standard problem in finance, namely, asset allocation. Based on machine learning and model averaging approaches, we integrate the drivers’ predictive information to forecast market volatilities. Using various evaluation...

This study suggests a portfolio theory encompassing various payment methods that are newly emerging as the development of the cryptocurrency market and central bank digital currencies (CBDCs) accelerates. We determine the payment methods chosen by an individual under given conditions by...

Incentive fees exist in the hedge fund industry to solve the principal-agent problem. However, due to indirect incentives, there continues to be a misalignment between fund managers’ and investors’ interests. This paper analyzes whether investors are able to mitigate this agency problem by...

This study predicts stock market volatility and applies them to the standard problem in finance, namely, asset allocation. Based on machine learning and model averaging approaches, we integrate the drivers’ predictive information to forecast market volatilities. Using various evaluation...