Common statistical measures of bond risk premia are volatile and countercyclical. This paper uses survey data on interest rate forecasts to construct subjective bond risk premia. Subjective premia are less volatile and not very cyclical; instead they are high, only around the early 1980s. The...

Although a large number of recent studies employ the buy-and-hold abnormal return (BHAR) methodology and the calendar time portfolio approach to investigate the long-run anomalies, each of the methods is a subject to criticisms. In this paper, we show that a recently introduced calendar time...

The properties of an iterative procedure for the estimation of the parameters of an ARFIMA process are investigated in a Monte Carlo study. The estimation procedure is applied to stock returns data for 15 countries

Following recent advances in the non-parametric realized volatility approach, we separately measure the discontinuous jump part of the quadratic variation process for individual stocks and incorporate it into heterogeneous autoregressive volatility models. We analyze the distributional...

This paper studies the contemporaneous relationship between S&P 500 index returns and log-increments of the market volatility index (VIX) via a nonparametric copula method. Specifically, we propose a conditional dependence index to investigate how the dependence between the two series varies...

Volatility has been one of the most active and successful areas of research in time series econometrics and economic forecasting in recent decades. This chapter provides a selective survey of the most important theoretical developments and empirical insights to emerge from this burgeoning...

In this paper we introduce a new class of approaches to empirical asset pricing research, namely LASSO methods augmented by further penalties related to differences in adjacent coefficient estimates (at t and t+1) for a given characteristic. The economic motivation for this is that the...

A rapidly growing literature has documented important improvements in volatility measurement and forecasting performance through the use of realized volatilities constructed from high-frequency returns coupled with relatively simple reduced-form time series modeling procedures. Building on...