This paper addresses the open debate about the usefulness of high-frequency (HF) data in large-scale portfolio allocation. Daily covariances are estimated based on HF data of the S&P 500 universe employing a blocked realized kernel estimator. We propose forecasting covariance matrices using a...

This paper addresses the open debate about the effectiveness and practical relevance of highfrequency (HF) data in portfolio allocation. Our results demonstrate that when used with proper econometric models, HF data offers gains over daily data and more importantly these gains are maintained...

This paper addresses the open debate about the usefulness of high-frequency (HF) data in large-scale portfolio allocation. We consider the problem of constructing global minimum variance portfolios based on the constituents of the S&P 500 over a four-year period covering the 2008 financial...

The illiquidity of long-maturity options has made it difficult to study the term structures of option spanning portfolios. This paper proposes a new estimation and inference framework for these option-implied term structures that addresses long-maturity illiquidity. By building a sieve estimator...

This paper introduces several new Bayesian nonparametric models suitable for capturing the unknown conditional distribution of realized covariance (RCOV) matrices. Existing dynamic Wishart models are extended to countably infinite mixture models of Wishart and inverse-Wishart distributions. In...

This research investigates the presence of structural breaks in the indices of the Egyptian stock market using the Bai-Perron strcutural breaks test. The indices used are the EGX 30, the EGX 70, the EGX 100, and the EGX 20. The presence of long memory is then investigated using the GPH test and...

We analyze the dynamics of price jumps and the impact of the European debt crisis using the high-frequency data reported by selected stock exchanges on the European continent during the period January 2008 to June 2012. We employ two methods to identify price jumps: Method 1 minimizes the...

We analyze the behavior and performance of multiple price jump indicators across markets and over time. By using high-frequency stock market data we identify clusters of price jump indicators that share similar properties in terms of their performance in that they minimize Type I and Type II...

This paper compares the forecasting performance of three structural econometric models, namely the non-parametric, ARIMAX and the Kalman filter models, in predicting stock returns in an emerging market economy using South Africa as case study. The proposed models have different functional forms....

This paper examines sector specific volatility in order to determine how different sectors respond to volatility shocks within the same equity market. The Egyptian Exchange sector indices are used where firms are disaggregated and classified into twelve different sectors. Volatility is modeled...