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 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...

We employ parametric and non-parametric cointegration to investigate the extent of integration between African stock markets and the rest of the world. Long-run correlation estimates imply very low association between the two. The two distinct cointegration approaches confirm the latter through...

The paper explores the possibility of making investment decisions in emerging markets by using the trend analysis method on a particular example of the capital market in Serbia. The authors, starting from the common features of technical analysis, have analysed the common share index value in...

In this study, a vector autoregression (VAR) model with time-varying parameters (TVP) to predict the daily Indian rupee (INR)/US dollar (USD) exchange rates for the Indian economy is developed. The method is based on characterization of the TVP as an optimal control problem. The methodology is a...

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...

In this study, a vector autoregression (VAR) model with time-varying parameters (TVP) to predict the daily Indian rupee (INR)/US dollar (USD) exchange rates for the Indian economy is developed. The method is based on characterization of the TVP as an optimal control problem. The methodology is a...

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...

In this study, a vector autoregression (VAR) model with time-varying parameters (TVP) to predict the daily Indian rupee (INR)/US dollar (USD) exchange rates for the Indian economy is developed. The method is based on characterization of the TVP as an optimal control problem. The methodology is a...