This paper introduces a unified parametric modeling approach for time-varying market betas that can accommodate continuous-time diffusion and discrete-time series models based on a continuous-time series regression model to better capture the dynamic evolution of market betas.We call this the...

Dynamic average correlations of stock returns are predicted by the volatility of the market excess return and moving average returns of value, size and momentum portfolios. While the influence of market volatility on average correlation is well-known, the role of value, size and momentum appears...

This study investigates the impact of the macroeconomic environment on South African industrial sector returns. Using standardized coefficients, we find that global influences are the most important drivers of returns and that industrial sectors are highly integrated with the global economy. We...

The simultaneous occurrence of jumps in several stocks can be associated with major financial news, triggers short-term predictability in stock returns, is correlated with sudden spikes of the variance risk premium, and determines a persistent increase (decrease) of stock variances and...

We propose a new estimator for the spot covariance matrix of a multi-dimensional continuous semi-martingale log asset price process which is subject to noise and non-synchronous observations. The estimator is constructed based on a local average of block-wise parametric spectral covariance...

We propose a new estimator for the spot covariance matrix of a multi-dimensional continuous semi-martingale log asset price process which is subject to noise and non-synchronous observations. The estimator is constructed based on a local average of block-wise parametric spectral covariance...

We propose a new estimator for the spot covariance matrix of a multi-dimensional continuous semi-martingale log asset price process which is subject to noise and non-synchronous observations. The estimator is constructed based on a local average of block-wise para- metric spectral covariance...

It is a well-known fact that most of the asset returns tend to be skewed and heavytailed. Heavy tailed distributions such as the Student’s t distribution and Stable distribution are commonly used in finance to model asset returns that areheavy tailed. Additionally, Stable distribution allows...

We develop a penalized two-pass regression with time-varying factor loadings. The penalization in the first pass enforces sparsity for the time-variation drivers while also maintaining compatibility with the no arbitrage restrictions by regularizing appropriate groups of coefficients. The second...

Asset pricing models implicitly assume that firm characteristics are context-free. At the same time, companies provide a substantial narrative context that helps investors to put numeric information in perspective. Management may discuss non-quantitative factors that influence performance, such...