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This article examines whether incorporating investors’ uncertainty, as captured by the conditional volatility of sentiment, can help forecasting volatility of stock markets. In this regard, using the Markov-switching ...
Using a machine-learning technique known as random forests, we analyze the role of investor confidence in forecasting monthly aggregate realized stock-market volatility of the United States (US), over and above a wide-array ...
We analyze the ability of a newspaper-based economic sentiment index of the United States to predict housing market movements using daily data from 2nd August, 2007 to 19th June, 2020. For this purpose, we use a nonparametric ...
We use an international dataset on 5-min interval intraday data covering nine leading markets and regions to construct measures of realized volatility, realized jumps, realized skewness, and realized kurtosis of returns ...
In this paper, we use a Quantile Structural Vector Autoregressive (QSVAR) model, estimated over the quarterly period of 1975:Q3 to 2017:Q3, to analyze whether the impact of monetary policy shocks on growth rate of real ...