Reprint
Empirical Finance
Edited by
March 2019
276 pages
- ISBN978-3-03897-706-3 (Paperback)
- ISBN978-3-03897-707-0 (PDF)
This book is a reprint of the Special Issue Empirical Finance that was published in
Business & Economics
Computer Science & Mathematics
Summary
There is no denying the role of empirical research in finance and the remarkable progress of empirical techniques in this research field. This Special Issue focuses on the broad topic of “Empirical Finance” and includes novel empirical research associated with financial data. One example includes the application of novel empirical techniques, such as machine learning, data mining, wavelet transform, copula analysis, and TV-VAR, to financial data. The Special Issue includes contributions on empirical finance, such as algorithmic trading, market efficiency, market microstructure, portfolio theory and asset allocation, asset pricing models, liquidity risk premium, currency crisis, return predictability, and volatility modeling.
Format
- Paperback
License
© 2019 by the authors; CC BY-NC-ND license
Keywords
text similarity; text mining; machine learning; SVM; neural network; LSTM; credit risk; ensemble learning; deep learning; bagging; random forest; boosting; deep neural network; causality-in-variance; cross-correlation function; housing and stock markets; algorithmic trading; take profit; stop loss; MACD; ATR; city banks; dependence structure; copula; n/a; market microstructure; price discovery; latency; currency crisis; random forests; wavelet transform; predictive accuracy; housing price; bank credit; housing loans; real estate development loans; TVP-VAR model; exchange rate; volatility; exports; ARDL; Vietnam; crude oil futures prices forecasting; convolutional neural networks; short-term forecasting; utility of international currency; inertia; liquidity risk premium; US dollar; Japanese yen; cointegration; statistical arbitrage; natural gas; wholesale electricity; futures market; spark spread; earnings management; earnings manipulation; earnings quality; initial public offering; IPO; asset pricing model; data mining; bankruptcy prediction; financial and non-financial variables; institutional investors’ shareholdings; panel data model; piecewise regression model; global financial crisis; gold return; asymmetric dependence; financial market stress; robust regression; quantile regression; structural break; flight to quality