Trading Signals in VIX Futures

DOI10.1080/1350486X.2021.2010584zbMath1490.91205arXiv2103.02016OpenAlexW4205223208MaRDI QIDQ5075243

Thomas Nanfeng Li, Gaozhan Wang, Andrew Papanicolaou, Marco Avellaneda

Publication date: 10 May 2022

Published in: Applied Mathematical Finance (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2103.02016

zbMATH Keywords

feedforward neural networkscross validationVIX futuresdeep learningcontangotrading signals

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Interest rates, asset pricing, etc. (stochastic models) (91G30) Derivative securities (option pricing, hedging, etc.) (91G20)

Related Items (1)

In memoriam: Marco Avellaneda (1955–2022)

Cites Work

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• A note on the validity of cross-validation for evaluating autoregressive time series prediction
• A survey of cross-validation procedures for model selection
• Perfect hedging in rough Heston models
• Surprises in high-dimensional ridgeless least squares interpolation
• STATISTICS OF VIX FUTURES AND APPLICATIONS TO TRADING VOLATILITY EXCHANGE-TRADED PRODUCTS
• MEAN-REVERTING STOCHASTIC VOLATILITY
• DATA-DEPENDENT ESTIMATION OF PREDICTION FUNCTIONS
• Stochastic Gradient Descent in Continuous Time
• Co-Integration and Error Correction: Representation, Estimation, and Testing
• Pricing under rough volatility
• Approximation by superpositions of a sigmoidal function

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