Search Results - subject:"Machine Learning"

An approach for variable selection and prediction model for estimating the Risk-Based Capital (RBC) based on machine learning algorithms

Park, Jaewon; Shin, Minsoo - In: Risks 10 (2022) 1, pp. 1-20

quarterly under regulation for transparent management information. This study employs a combination of Machine learning … least-squares regression (OLS). As a result of the findings from Machine learning techniques, a set of important predictors …

Persistent link: https://www.econbiz.de/10013200904

Text mining for U.S. pension de-risking analysis

Zhang, Limin; Tian, Ruilin; Chen, Jun - In: Risks 10 (2022) 2, pp. 1-18

identify different "de-risking" strategies that US-based companies have used. A combination of text mining, machine learning …

Persistent link: https://www.econbiz.de/10013200931

Exchange rate forecasting with advanced machine learning methods

Pfahler, Jonathan Felix - In: Journal of Risk and Financial Management 15 (2022) 1, pp. 1-17

Historically, exchange rate forecasting models have exhibited poor out-of-sample performances and were inferior to the random walk model. Monthly panel data from 1973 to 2014 for ten currency pairs of OECD countries are used to make out-of sample forecasts with artificial neural networks and...

Persistent link: https://www.econbiz.de/10013201306

Simulating multi-asset classes prices using Wasserstein Generative Adversarial Network: A study of stocks, futures and cryptocurrency

Han, Feng; Ma, Xiaojuan; Zhang, Jiheng - In: Journal of Risk and Financial Management 15 (2022) 1, pp. 1-21

Financial data are expensive and highly sensitive with limited access. We aim to generate abundant datasets given the original prices while preserving the original statistical features. We introduce the Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP) into the field of...

Persistent link: https://www.econbiz.de/10013201330

Machine-learning-based semiparametric time series conditional variance: Estimation and forecasting

Dang, Justin; Ullah, Aman - In: Journal of Risk and Financial Management 15 (2022) 1, pp. 1-12

parametric estimator and a nonparametric estimator based on machine learning. A popular kernel-based machine learning algorithm …

Persistent link: https://www.econbiz.de/10013201342

Machine learning the carbon footprint of Bitcoin mining

Calvo Pardo, Héctor F.; Mancini, Tullio; Olmo, Jose - In: Journal of Risk and Financial Management 15 (2022) 2, pp. 1-30

evidence (e.g., from climate-weather integrated models). We demonstrate how machine learning methods can contribute to not …

Persistent link: https://www.econbiz.de/10013201374

A study of the machine learning approach and the MGARCH-BEKK model in volatility transmission

Joshi, Prashant; Wang, Jinghua; Busler, Michael - In: Journal of Risk and Financial Management 15 (2022) 3, pp. 1-9

asymmetric volatility transmission on both markets. We apply MGARCH-BEKK and the algorithm-based GA2M machine learning model. The …

Persistent link: https://www.econbiz.de/10013201419

The impact of the U.S. macroeconomic variables on the CBOE VIX Index

Prasad, Akhilesh; Bakhshi, Priti; Seetharaman, Arumugam - In: Journal of Risk and Financial Management 15 (2022) 3, pp. 1-25

, classification problems from machine learning are constructed to predict the daily and weekly trends of the VIX Index. Data from May …

Persistent link: https://www.econbiz.de/10013201429

The crowdfunding of altruism

Faust, Luisa; Kolbe, Maura; Mansouri, Sasan; Momtaz, Paul P. - In: Journal of Risk and Financial Management 15 (2022) 3, pp. 1-29

This paper introduces a machine learning approach to quantify altruism from the linguistic style of textual documents …

Persistent link: https://www.econbiz.de/10013201441

Vereinfachtes Verfahren zur interaktiven Schätzung des Erfüllungsaufwands mittels maschinellen Lernens

Levagin, Bogdan; Lange, Kerstin; Walprecht, Sylvana; … - In: WISTA - Wirtschaft und Statistik 74 (2022) 3, pp. 53-67

. Employing machine learning, the Federal Statistical Office has trained a new estimation model to improve the accuracy of the …

Persistent link: https://www.econbiz.de/10013265557