This paper proposes a new discount rate that pension funds can use to discount their future obligations. If the payouts of a pension fund depend on the return of the fund's assets, then neither the risk-free rate nor the expected return is an equitable way to discount future liabilities. Using...

An n-variable structural vector auto-regression (SVAR) can be identified (up to shock order) from the evolution of the residual covariance across time if the structural shocks exhibit heteroskedasticity (Rigobon (2003), Sentana and Fiorentini (2001)). However, the path of residual covariances...

Do analysts add value and can they discover new information? I study the informativeness of reinitiations of coverage, which are defined as the resumption of coverage of a stock by a broker after more than six months of interruption. Reinitiations are associated with a significant short-term...

The study outlines fees and investment returns for state pension funds. The study concludes that states with the highest fees, as a percent of assets, had the lowest returns. The study shows a passive index mimicking state fund asset allocations provides higher returns. Private equity funds and...

Using individual-level data from the Survey on Household Income and Wealth (SHIW), we estimate the extra-returns to wealth earned by highly educated individuals (education premium). Importantly, we quantify the fraction of the premium due to the financial investments decisions, such as stock...

We investigate the causality between the real federal budget deficit returns and real stock market returns for the US economy. We divide the overall sample into two sub-samples running from 1968:1 to 1988:3 and from 1988:4 to 2011:3. In contrast to earlier studies, we find a significant positive...

We propose a new model for volatility forecasting which combines the Generalized Dynamic Factor Model (GDFM) and the GARCH model. The GDFM, applied to a large number of series, captures the multivariate information and disentangles the common and the idiosyncratic part of each series of returns....

A prediction model is any statement of a probability distribution for an outcome not yet observed. This study considers the properties of weighted linear combinations of n prediction models, or linear pools, evaluated using the conventional log predictive scoring rule. The log score is a concave...

We propose a new approach to model high and low frequency components of equity correlations. Our framework combines a factor asset pricing structure with other specifications capturing dynamic properties of volatilities and covariances between a single common factor and idiosyncratic returns....

Bayesian inference in a time series model provides exact, out-of-sample predictive distributions that fully and coherently incorporate parameter uncertainty. This study compares and evaluates Bayesian predictive distributions from alternative models, using as an illustration five alternative...