Given the process {X(t), t in T}, the definition of self-affinity is reformulated in terms of diameter of the space of the rescaled pdf's of X(t). Two necessary conditions are deduced which contribute to discriminate uniscaling processes. Furthermore, by properly choosing the distance, the...

The appropriate design of monetary policy in integrated financial markets is one of the most challenging areas for central banks. One hot topic is whether the increase in liquidity has contributed to the formation of price bubbles in asset markets in the years preceding the financial crisis. If...

We evaluate whether machine learning methods can better model excess portfolio returns compared to the standard regression-based strategies generally used in the finance and econometric literature. We examine 17 benchmark factor model specifications based on Expected Utility Theory and theory...

We apply machine learning techniques and use stock characteristics to predict the cross-section of stock returns in 33 international markets. We conduct a stringent out-of-sample test to examine concerns about overfitting: the models are trained with past U.S. data and used to predict...

The CAPM is commonly used for an introduction of the equity cost in practice to calculate the corporate value, which is composed by the risk-free rate, equity market return and each respective beta. However, there is a fundamental complication between the risk, cost and return for the equity...

Equity risk premiums are a central component of every risk and return model in finance and are a key input in estimating costs of equity and capital in both corporate finance and valuation. Given their importance, it is surprising how haphazard the estimation of equity risk premiums remains in...

This chapter focuses on the attitude of investors toward financial gains and losses and their decisions on wealth allocation, and how these changes are subject to behavioral factors. The focal point is the integration of behavioral elements into the classic portfolio optimization. Individual...

While existing asset pricing studies focus on macroeconomic variables to predict stock market risk premium, we find that an aggregate index of corporate activities has substantially greater predictive power both in- and out-of sample, and yields much greater economic gain for a mean-variance...

We show theoretically that when Bayesian investors face time-series uncertainty about assets' risk exposures, differences in their priors affect the pricing of risk in the cross-section: different priors for the same asset can generate differences in perceived risk exposures, and thereby...

We structurally estimate a model in which agents' information processing biases can cause predictability in firms' asset returns and investment inefficiencies. We generalize the neoclassical investment model by allowing for two biases -- overconfidence and over-extrapolation of trends -- that...