Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 25 for “"Volatility Forecasting"”.
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Essays on Volatility Forecasting
… method that is tailored specifically for volatility. We then apply convolution neural network models on the transformed volatility images and find the forecasting performance is significantly better than both the econometrics and machine learning benchmark models in classification and …
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Essays on Commodity Price Shocks, Bank Risk and Market Volatility Forecasting
… studies how to better forecast the daily market volatility (VIX) index. We propose utilizing the ordinary least square post–least absolute shrinkage and selection operator (OLS post–Lasso) from Belloni and Chernozhukov (2013) to select the predictors and estimate the coefficients for a …
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Volatility Forecasting and Value-at-Risk: An Application to Cattle Feeding
… error criteria, the overall conclusion of the volatility forecasting exercise mirrors that found in the literature: performance of any volatility forecast is both data and horizon specific. However, composite techniques, especially simple composites that combine both conditional time series and …
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Volatility forecasting using Double-Markov switching GARCH models under skewed Student-t distribution
This thesis focuses on forecasting the volatility of daily returns using a double Markov switching GARCH model with a skewed Student-t error distribution. The model was applied to individual shares obtained from the Johannesburg Stock Exchange (JSE). The Bayesian approach which uses Markov Chain …
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Essays on economic value of intraday covariation estimators for risk prediction
… the economic value of incorporating intraday volatility estimators into the volatility forecasting process. The increased reliance on volatility forecasting in the nancial industry has intensied the need for more rigorous analysis from an economic perspective instead of merely statistical …
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Essays on the economic value of intraday covariation estimators for risk prediction
… the economic value of incorporating intraday volatility estimators into the volatility forecasting process. The increased reliance on volatility forecasting in the financial industry has intensified the need for more rigorous analysis from an economic perspective instead of merely statistical …
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Development and analysis of derivative trading systems using artificial intelligence
… option trading systems that incorporate both volatility and return forecasting. This study focuses on the S&P 500 stock index as a representative for the market. The three different trading methods are discussed: stock return forecasting using a simple call and put option strategy, volatility …
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Applications of Deep Learning to Financial Time Series Forecasting
… problems consists of predicting the future volatility of a given asset. In this thesis, we investigate how the Transformer architecture performs at the task of volatility forecasting by comparing its performance against that of previously explored deep learning architectures such as the LSTM.
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Application of GARCH Type Models in Forecasting Value at Risk
… dynamic VaR modeling using four conditional volatility forecasting models: GARCH, TGARCH, GJRGARCH, and IGARCH, and compares the forecasting output of the suggested GARCH-based volatility models. Since the predictive accuracy of Value-at-Risk (VaR) models is crucial for adequate …
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Forecasting and modelling the VIX using Neural Networks
This study investigates the volatility forecasting ability of neural network models. In particular, we focus on the performance of Multi-layer Perceptron (MLP) and the Long Short Term (LSTM) Neural Networks in predicting the CBOE Volatility Index (VIX). The inputs into these models includes the …
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Machine Learning with FEARS index: does the inclusion of investor sentiment improve a machine learning model's ability to predict volatility?
… methods to produce improved predictions of volatility in equity markets. Specifically, the investor sentiment measure is constructed as an index by using search volume data of different search terms obtained from Google Trends. The resulting Financial and Economic Attitudes Revealed by …
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A machine learning hybrid approach to forecasting equity returns volatility: A South African perspective.
… markets have been deeply interested in the forecasting of financial market return volatility. There are many methods for predicting the volatility of financial market returns, and various studies have indicated differing degrees of accuracy in this regard. Research on describing the …
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Essays on financial econometrics : variance and covariance estimation using price durations
… shorter durations are indicative of higher volatility. The duration-based approach provides a new angle to look at the high-frequency data, additionally, the duration based variance and covariance estimators are shown to be more efficient than competing time-domain high-frequency estimators. …
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Essays on the Modelling of S&P 500 Volatility
… the patterns of term-structure of implied volatility and examines the performance of different specifications of time-series and options-based volatility forecasting models under the influence of the observed market biases. Our research is based primarily upon the use of S&P 500 data for …
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Risk in Brazilian Stock and Futures Markets
… markets focusing on two questions: (i) Does volatility in emerging stock markets follow the time patterns observed in more traditional markets? and (ii) Can emerging futures markets in LDC's perform their classic functions of hedge provision and price discovery when operating under suboptimal …
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Volatility risk and stock return predictability on global financial crises
… empirical studies for investigating the role of volatility risk on stock return predictability specified on two global financial crises: the dot-com bubble and recent financial crisis. Using a broad sample of stock options traded at the American Stock Exchange and the Chicago Board Options …
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Volatility and return forecasting : time series and options-based methods
… to model and forecast returns and realized volatility using two different methods: time series models that exploit the historical information set and options-based approach that provides a natural forecast of return variation from listed option prices. Both univariate and multivariate …
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Price jumps and volatility in U.S. agricultural futures markets
… experienced by these markets affect prices and volatility dynamics. In the third essay, I investigate whether more flexible research approaches should be employed to provide market participants and policy markets more accurate volatility forecasts within the context of the new more heterogeneous …
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