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Full-Text Articles in Finance and Financial Management
Financial News And Cds Spreads, Paresh Kumar Narayan, Deepa Bannigidadmath
Financial News And Cds Spreads, Paresh Kumar Narayan, Deepa Bannigidadmath
Research outputs 2014 to 2021
© 2020 Elsevier B.V. This paper examines whether financial news moves CDS spreads for a large number of U.S. stocks sorted into 19 panels consisting of sectors, sizes and credit quality. Using a unique financial news data set, we discover that while both positive and negative news predicts CDS spread changes in most of the panels, annualised mean–variance profits and utility gains are dominated by forecasting models that use positive news as a predictor. At best, risk factors only account for around 31% of observed profits.
Stochastic Volatility And Garch: Do Squared End-Of-Day Returns Provide Similar Information?, David Edmund Allen
Stochastic Volatility And Garch: Do Squared End-Of-Day Returns Provide Similar Information?, David Edmund Allen
Research outputs 2014 to 2021
The paper examines the relative performance of Stochastic Volatility (SV) and GARCH(1,1) models fitted to twenty plus years of daily data for three indices. As a benchmark, I use the realized volatility (RV) for the S&P 500, DOW JONES and STOXX50 indices, sampled at 5-minute intervals, taken from the Oxford Man Realised Library. Both models demonstrate comparable performance and are correlated to a similar extent with the RV estimates, when measured by OLS. However, a crude variant of Corsi’s (2009) Heterogenous Auto-Regressive (HAR) model, applied to squared demeaned daily returns on the indices, appears to predict the daily RV of …
An Investigation Into The Use Of Neural Networks For The Prediction Of The Stock Exchange Of Thailand, Suchira Chaigusin
An Investigation Into The Use Of Neural Networks For The Prediction Of The Stock Exchange Of Thailand, Suchira Chaigusin
Theses: Doctorates and Masters
Stock markets are affected by many interrelated factors such as economics and politics at both national and international levels. Predicting stock indices and determining the set of relevant factors for making accurate predictions are complicated tasks. Neural networks are one of the popular approaches used for research on stock market forecast. This study developed neural networks to predict the movement direction of the next trading day of the Stock Exchange of Thailand (SET) index. The SET has yet to be studied extensively and research focused on the SET will contribute to understanding its unique characteristics and will lead to identifying …