Despite ample evidence of ambiguity preferences in individual decision making, experimental studies of ambiguity effects in financial markets are scarce and inconclusive. Although a number of theoretical studies explain empirical puzzles in finance with ambiguity preferences, it is not a given...

The theory of fair geometric returns, F theory for short, rejects the generally accepted notion that volatility is the risk of risky assets. Instead, it claims that capital market volatility, in turn, constitutes the maximum achievable geometric return. In order to get to the point, F theory, in...

We propose a simple algorithm for the ex-ante valuation based on prospect theory. Our results reveal a strong and robust pricing effect associated with predicted values based on prospect theory (PV) in the US market, that is, higher ex-ante PV stocks associated with higher returns. Our findings...

The present paper evaluates whether the adaptive market hypothesis provides a better description of the behavior of Indian stock market using daily values of Sensex and Nifty, the two major indices of India from January 1991 to April 2013. We employed linear and nonlinear methods to evaluate the...

This study addresses the question of whether the adaptive market hypothesis provides a better description of the behaviour of emerging stock market like India. We employed linear and nonlinear methods to evaluate the hypothesis empirically. The linear tests show a cyclical pattern in linear...

In this paper we seek to demonstrate the predictability of stock market returns and explain the nature of this return predictability. To this end, we further develop the news-driven analytic model of the stock market derived in Gusev et al. (2015). This enables us to capture market dynamics at...

In this paper we seek to demonstrate the predictability of stock market returns and explain the nature of this return predictability. To this end, we further develop the news-driven analytic model of the stock market derived in Gusev et al. (2015). This enables us to capture market dynamics at...

In this paper we seek to demonstrate the predictability of stock market returns and explain the nature of this return predictability. To this end, we introduce investors with different investment horizons into the news‐driven, analytic, agent‐based market model developed in Gusev et al....

In this paper we seek to demonstrate the predictability of stock market returns and explain the nature of this return predictability. To this end, we introduce investors with different investment horizons into the news‐driven, analytic, agent‐based market model developed in Gusev et al....

This study examines the predictive power of textual information from S-1 filings in explaining IPO underpricing. Our empirical approach differs from previous research, as we utilize several machine learning algorithms to predict whether an IPO will be underpriced, or not. We analyze a large...