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Support vector regression based GARCH model with application to forecasting volatility of financial returns
Chen, Shiyi (contributor); Jeong, Kiho (contributor);  … - 2008
financial forecasting. This paper deals with the application of SVR in volatility forecasting. Based on a recurrent SVR, a GARCH … 30, 2005. The experiment shows that, under both varying and fixed forecasting schemes, the SVR-based GARCH outperforms … examined to the free parameters. Keywords: recurrent support vector regression ; GARCH model ; volatility forecasting …
Persistent link: https://www.econbiz.de/10003636113
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Support Vector Regression Based GARCH Model with Application to Forecasting Volatility of Financial Returns
Chen, Shiyi - 2017
financial forecasting. This paper deals with the application of SVR in volatility forecasting. Based on a recurrent SVR, a GARCH … 30, 2005. The experiment shows that, under both varying and fixed forecasting schemes, the SVR-based GARCH outperforms …
Persistent link: https://www.econbiz.de/10012966267
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Forecasting stock market averages to enhance profitable trading strategies
Haefke, Christian; Helmenstein, Christian - 1995
In this paper we design a simple trading strategy to exploit the hypothesized distinct informational content of the arithmetic and geometric mean. The rejection of cointegration between the two stock market indicators supports this conjecture. The profits generated by this cheaply replicable...
Persistent link: https://www.econbiz.de/10010291049
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Forecasting stock market averages to enhance profitable trading strategies
Häfke, Christian; Helmenstein, Christian - 1995
In this paper we design a simple trading strategy to exploit the hypothesized distinct informational content of the arithmetic and geometric mean. The rejection of cointegration between the two stock market indicators supports this conjecture. The profits generated by this cheaply replicable...
Persistent link: https://www.econbiz.de/10009696690
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Prediction risk and the forecasting of stock market indexes
Häfke, Christian; Helmenstein, Christian - 1995
In most of the empirical research on capital markets, stock market indexes are used as proxies for the aggregate market development. In previous work we found that a particular market segment might be less efficient than the whole market and hence easier to forecast. In this paper we extend the...
Persistent link: https://www.econbiz.de/10009696691
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Stock Price Forecasting and Hypothesis Testing Using Neural Networks
Varaku, Kerda - 2020
In this work we use Recurrent Neural Networks and Multilayer Perceptrons, to predict NYSE, NASDAQ and AMEX stock prices from historical data. We experiment with different architectures and compare data normalization techniques. Then, we leverage those findings to question the efficient-market...
Persistent link: https://www.econbiz.de/10012834485
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Support vector regression based GARCH model with application to forecasting volatility of financial returns
Chen, Shiyi; Jeong, Kiho; Härdle, Wolfgang Karl - 2008
financial forecasting. This paper deals with the application of SVR in volatility forecasting. Based on a recurrent SVR, a GARCH … 30, 2005. The experiment shows that, under both varying and fixed forecasting schemes, the SVR-based GARCH outperforms … examined to the free parameters. Keywords: recurrent support vector regression ; GARCH model ; volatility forecasting …
Persistent link: https://www.econbiz.de/10010274143
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Prediction risk and the forecasting of stock market indexes
Haefke, Christian; Helmenstein, Christian - 1995
In most of the empirical research on capital markets, stock market indexes are used as proxies for the aggregate market development. In previous work we found that a particular market segment might be less efficient than the whole market and hence easier to forecast. In this paper we extend the...
Persistent link: https://www.econbiz.de/10010291063
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Predicting abnormal stock return volatility using textual analysis of news : a meta-learning approach
Myšková, Renáta; Hájek, Petr; Olej, Vladimír - In: Amfiteatru economic : an economic and business research … 20 (2018) 47, pp. 185-201
Textual analysis of news articles is increasingly important in predicting stock prices. Previous research has intensively utilized the textual analysis of news and other firm-related documents in volatility prediction models. It has been demonstrated that the news may be related to abnormal...
Persistent link: https://www.econbiz.de/10011881761
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Cascading logistic regression onto gradient boosted decision trees to predict stock market changes using technical analysis
Zhou, Feng; Zhang, Qun; Sornette, Didier; Jiang, Liu - 2018
In the data mining and machine learning fields, forecasting the direction of price change can be generally formulated …
Persistent link: https://www.econbiz.de/10011900252