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Covariance Forecasting in Equity Markets
Symitsi, Efthymia - 2018
while adjusting for the volatility risk premium. Relative model performance does not change during the global financial …
Persistent link: https://www.econbiz.de/10012915984
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Predictability of Bull and Bear Markets : A New Look at Forecasting Stock Market Regimes (and Returns) in the Us
Haase, Felix; Neuenkirch, Matthias - 2021
The empirical literature of stock market predictability mainly suffers from model uncertainty and parameter instability. To meet this challenge, we propose a novel approach that combines the documented merits of diffusion indices, regime-switching models, and forecast combination to predict the...
Persistent link: https://www.econbiz.de/10013250734
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Quantile Forecast Combinations in Realised Volatility Prediction
Meligkotsidou, Loukia - 2015
This paper tests whether it is possible to improve point, quantile and density forecasts of realized volatility by … more information for the evolution of the volatility distribution beyond that contained in its own past. The best …
Persistent link: https://www.econbiz.de/10013013804
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Forecasting Intraday Trading Volume : A Kalman Filter Approach
Chen, Ran - 2018
An accurate forecast of intraday volume is a key aspect of algorithmic trading. This manuscript proposes a state-space model to forecast intraday trading volume via the Kalman filter and derives closed-form expectation-maximization (EM) solutions for model calibration. The model is extended to...
Persistent link: https://www.econbiz.de/10012930388
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Beta Measurement and Forecasting with High Frequency Returns
Doan, Bao Huy - 2020
Analysis with high frequency returns has become a core part of modern financial econometrics. Particularly in the measurement and forecasting of variance, covariance, correlation and Capital Asset Pricing Model (CAPM) beta. This paper studies CAPM beta measurement and forecasting with high...
Persistent link: https://www.econbiz.de/10012848006
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The Limits to Volatility Predictability : Quantifying Forecast Accuracy Across Horizons
Zakamulin, Valeriy; Li, Xingyi - 2018
Volatility forecasting is crucial for portfolio management, risk management, and pricing of derivative securities …. Still, little is known about how far ahead one can forecast volatility. First, in this paper we introduce the notions of the … spot and forward predicted volatilities and propose to describe the term structure of volatility predictability by the spot …
Persistent link: https://www.econbiz.de/10014111954
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Can ChatGPT Forecast Stock Price Movements? Return Predictability and Large Language Models
Lopez-Lira, Alejandro; Tang, Yuehua - 2023
We examine the potential of ChatGPT, and other large language models, in predicting stock market returns using sentiment analysis of news headlines. We use ChatGPT to indicate whether a given headline is good, bad, or irrelevant news for firms' stock prices. We then compute a numerical score and...
Persistent link: https://www.econbiz.de/10014351271
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Are Stock Returns Predictable in China? A Machine Learning Approach
wu, huihang; wei, xingkong; Zhang, Xiaoyan - 2021
monthly volatility of 4.65% (6.88%), the annualized Sharpe ratio of 2.26 (1.48), and the significant monthly adjusted Alpha of …
Persistent link: https://www.econbiz.de/10013313205
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Informational Content of CEO Tweets and Stock Market Predictability
Lee, Kang-Pyo; Song, Suyong - 2022
volume, volatility, and stock price direction. We also find that the predictive power of CEO sentiments still stands after …
Persistent link: https://www.econbiz.de/10014239425
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The ARCH-in-Mean Dose Work : Out-of-Sample Predictability of US Stock Market
Xie, Haibin - 2015
The predictability of stock market is of great interest to both reseachers and investors. Despite voluminous evidence of in-sample predictability, the out-of-sample predictability of stock returns remains an ongoing debate. In this paper, motivated by both the financial theories and the well...
Persistent link: https://www.econbiz.de/10013029611