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Security Transaction Tax (STT) was introduced in the Indian capital market in 2004. It is a tax on transaction of equities as well as their derivatives. Despite the reduction in STT over the years, it constitutes a large percentage (next only to brokerage fee) of the total cost of trading. The...
Persistent link: https://www.econbiz.de/10010354157
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We propose a novel methodology for modeling and forecasting multivariate realized volatilities using graph neural networks. This approach extends the work of Zhang et al. [2022] (Graph-based methods for forecasting realized covariances) and explicitly incorporates the spillover effects from...
Persistent link: https://www.econbiz.de/10014265206
, we apply a classification problem based on long short-term memory neural networks to extract alternative proxies of …
Persistent link: https://www.econbiz.de/10012629835
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
We apply machine learning models to forecast intraday realized volatility (RV), by exploiting commonality in intraday volatility via pooling stock data together, and by incorporating a proxy for the market volatility. Neural networks dominate linear regressions and tree models in terms of...
Persistent link: https://www.econbiz.de/10013296651
This paper proposes a latent dynamic factor model for low- as well as high-dimensional realized covariance matrices of stock returns. The approach is based on the matrix logarithm and allows for flexible dynamic dependence patterns by combining common latent factors driven by HAR dynamics and...
Persistent link: https://www.econbiz.de/10010341025
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/10012416151
This study predicts stock market volatility and applies them to the standard problem in finance, namely, asset allocation. Based on machine learning and model averaging approaches, we integrate the drivers’ predictive information to forecast market volatilities. Using various evaluation...
Persistent link: https://www.econbiz.de/10013404229
Stock prices declined abruptly in the wake of the Covid-19, reflecting both the deterioration of investors’ expectations of economic activity as well as the surge in risk aversion. In the following months, however, economic activity remained sluggish while equity markets bounced back. This...
Persistent link: https://www.econbiz.de/10014258561