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A neural network with shared dynamics for multi‐step prediction of value‐at‐risk and volatility
Baştürk, Nalan; Schotman, Peter C.; Schyns, Hugo - 2022
Persistent link: https://www.econbiz.de/10013539142
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Quantitative Verfahren im Finanzmarktbereich
Schröder, Michael (ed.) - 1996 - 1. Aufl.
Persistent link: https://www.econbiz.de/10000592147
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Datamining und computational finance : Ergebnisse des 7. Karsruher Ökonometrie-Workshops
Bol, Georg (ed.); Hann, Tae Horn (contributor) - 2000
Persistent link: https://www.econbiz.de/10001455393
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A machine learning approach to portfolio pricing and risk management for high-dimensional problems
Fernandez-Arjona, Lucio; Filipović, Damir - 2020
We present a general framework for portfolio risk management in discrete time, based on a replicating martingale. This martingale is learned from a finite sample in a supervised setting. The model learns the features necessary for an effective low-dimensional representation, overcoming the curse...
Persistent link: https://www.econbiz.de/10012219260
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A machine learning approach to portfolio pricing and risk management for high-dimensional problems
Fernandez-Arjona, Lucio; Filipović, Damir - In: Mathematical finance : an international journal of … 32 (2022) 4, pp. 982-1019
Persistent link: https://www.econbiz.de/10013463383
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Managing weather risk with a neural network-based index insurance
Chen, Zhanhui; Lu, Yang; Zhang, Jinggong; Zhu, Wenjun - In: Management science : journal of the Institute for … 70 (2024) 7, pp. 4306-4327
Persistent link: https://www.econbiz.de/10015045875
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Assessing asset-liability risk with neural networks
Cheridito, Patrick; Ery, John; Wüthrich, Mario V. - In: Risks : open access journal 8 (2020) 1/16, pp. 1-17
We introduce a neural network approach for assessing the risk of a portfolio of assets and liabilities over a given time period. This requires a conditional valuation of the portfolio given the state of the world at a later time, a problem that is particularly challenging if the portfolio...
Persistent link: https://www.econbiz.de/10012203982
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Künstliche neuronale Netze zur Risikomessung bei Aktien und Renten : am Beispiel deutscher Lebensversicherungsunternehmen
Rauscher, Markus - 2004 - 1. Aufl.
Persistent link: https://www.econbiz.de/10013420595
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Forward-looking volatility estimation for risk-managed investment strategies during the COVID-19 crisis
Di Persio, Luca; Garbelli, Matteo; Wallbaum, Kai - In: Risks 9 (2021) 2, pp. 1-16
, we focus our attention on estimating volatility levels of a risky asset to perform a VolTarget simulation over two …, investment levels have decreased over recent years. Moreover, the recent turbulence caused by the COVID-19 crisis has accelerated … the latter process. Within this scenario, we consider the so-called Volatility Target (VolTarget) strategy. In particular …
Persistent link: https://www.econbiz.de/10013200702
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Neural network predictive modeling on dynamic portfolio management : a simulation-based portfolio optimization approach
Yu, Jiayang; Chang, Kuo-Chu - In: Journal of risk and financial management : JRFM 13 (2020) 11/285, pp. 1-23
into their investment strategies and optimizing their portfolio performance in a timely manner. In this paper, we present a … simulation-based approach by fusing a number of macroeconomic factors using Neural Networks (NN) to build an Economic Factor …-based Predictive Model (EFPM). Then, we combine it with the Copula-GARCH simulation model and the Mean-Conditional Value at Risk (Mean …
Persistent link: https://www.econbiz.de/10012388728