We present a new procedure for detecting multiple additive outliers in GARCH(1,1) models at unknown dates. The outlier candidates are the observations with the largest standardized residual. First, a likelihood-ratio based test determines the presence and timing of an outlier. Next, a second...

Taking advantage of a trades-and-quotes high-frequency database, we document the main stylized facts and dynamic properties of spot precious metals, i.e. gold, silver, palladium, and platinum. We analyze the behaviors of spot prices, returns, volume, and selected liquidity measures. We find...

This paper provides empirical evidence that combinations of option implied and time series volatility forecasts that are conditional on current information are statistically superior to individual models, unconditional combinations, and hybrid forecasts. Superior forecasting performance is...

We compare the performance of time-series (TS) and cross-sectional (CS) strategies based on past returns. While CS strategies are zero-net investment long/short strategies, TS strategies take on a time-varying net-long investment in risky assets. For individual stocks, the difference between the...

We investigate intermediary asset pricing theories empirically and find strong support for models that have intermediary leverage as the relevant state variable. A parsimonious model that uses detrended dealer leverage as a price-of-risk variable, and innovations to dealer leverage as a pricing...

We document that a theoretically founded, real-time, and easy-to-implement option-based measure, termed synthetic-stock difference (SSD), accurately estimates the part of stock's expected return arising from stock's transaction costs. We calculate SSD for U.S. optionable stocks. SSD can be more...

This paper documents that factors extracted from a large set of macroeconomic variables bear useful information for predicting monthly US excess stock returns and volatility over the period 1980-2005. Factor-augmented predictive regression models improve upon both benchmark models that only...

Density forecasts have become quite important in economics and finance. For example, such forecasts play a central role in modern financial risk management techniques like Value at Risk. This paper suggests a regression based density forecast evaluation framework as a simple alternative to other...

The S&P500 or DAX30 are important benchmarks for the financial industry. The first mimics the performance of the major US on the NYSE, AMEX and NASDAQ, while the second does the same for the German Prime Share sector. These and other indices describe different compositions of certain segments of...

Value-at-risk (VaR) is a useful risk measure broadly used by financial institutions all over the world. VaR has been extensively used to measure systematic risk exposure in developed markets like of the US, Europe and Asia. This paper analyzes the accuracy of VaR measure for Pakistan's emerging...