We use the MIDAS (Mixed Data Sampling) approach to study regressions of future realized volatility at low-frequency horizons (one to four weeks) on lagged daily and intra-daily (1) squared returns, (2) absolute returns, (3) realized volatility, (4) realized power and (5) return ranges. We...

This paper studies the ICAPM intertemporal relation between the conditional mean and the conditional variance of the aggregate stock market return. We introduce a new estimator that forecasts monthly variance with past daily squared returns - the Mixed Data Sampling (or MIDAS) approach. Using...

We consider a log-linearized version of a discounted rents model to price commercial real estate as an alternative to traditional hedonic models. First, we verify a key implication of the model, namely, that cap rates forecast commercial real estate returns. We do this using two different...

We explore Mixed Data Sampling (henceforth MIDAS) regression models. The regressions involve time series data sampled at different frequencies. Volatility and related processes are our prime focus, though the regression method has wider applications in macroeconomics and finance, among other...

We estimate the cross-sectional dispersion of returns and growth in net operating income (NOI) of apartments, industrial, retail and office properties using panel data for U.S. metropolitan areas over the period 1986 to 2002. Cross-sectional dispersion is a measure of the total volatility faced...

We use a parametric portfolio approach to estimate optimal commercial real estate portfolio policies. We do so using the NCREIF data set of commercial properties over the sample period 1984:Q2 to 2009:Q1. The richness of this extensive data set and the flexibility of the parametric portfolio...

We use a quantile-based measure of conditional skewness (or asymmetry) that is robust to outliers and therefore particularly suited for recalcitrant series such as emerging market returns. Our study is on the following portfolio returns: developed markets, emerging markets, the world, and...

We use a parametric portfolio approach to estimate optimal commercial real estate portfolio policies. We do so using the NCREIF data set of commercial properties over the sample period 1984:Q2 to 2009:Q1. The richness of this extensive data set and the flexibility of the parametric portfolio...

We analyze the effect of taxes and government spending on quarterly market returns of stocks, government bonds, and corporate bonds. In US data from 1960 to 2000, a one standard deviation increase in the share of tax receipts in GDP has a statistically and economically significant effect on...

We propose a novel approach to optimizing portfolios with large numbers of assets. We model directly the portfolio weight in each asset as a function of the asset's characteristics. The coefficients of this function are found by optimizing the investor's average utility of the portfolio's return...