Statistical arbitrage trading with wavelets and artificial neural networks

Zapart, Christopher

doi:10.1109/cifer.2003.1196339

Cited by 7 publications

(1 citation statement)

References 8 publications

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“…Other important research in the area of statistical arbitrage was done by Pole (2007), Montana (2009), Burgess (2000), Avellaneda and Lee (2008), Thomaidis et al (2006), Zapart (2003), Hillier, Draper, and Faff (2006), Janda, Rausser, and Svarovska (2014), Cui, Qian, Taylor, and Zhu (2019). Technological developments in computational modelling have also facilitated the use of statistical arbitrage in high frequency trading and with the so-called machine learning methods, such as neural networks and genetic algorithms (Ortega & Khashanah, 2014;Brogaard et al, 2014;Chaboud et al, 2014;also Mahmoodzadeh et al, 2019).…”

Section: Literature Reviewmentioning

confidence: 99%

Interest Rates Sensitivity Arbitrage – Theory and Practical Assesment for Financial Market Trading

Stádník

2021

Business, Management and Economics Engineering

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Purpose – Nowadays popular algorithmic trading uses many strategies which are algoritmizable and promise profitability. This research assess if it is possible successfully use interest rates sensitivity arbitrage in bond portfolio (also known as convexity arbitrage) in financial praxis. This arbitrage is sparsely described in literature and an assessment about its practical success is missing. Research methodology – Methodology steps: mathematical definition of given arbitrage; construction of sufficient portfolio; backtesting on USD zero-coupon curves. Portfolio of two bonds is constructed (theoretically and practically) to have the same Macaulay duration and price, but a different convexity at certain YTM point. Therefore, being long the first bond while shorting the second (of higher convexity) would result in a market-directional bet for parallel zero-coupon yield curve shifts. Findings – To construct practically the portfolio which is sufficient for the convexity arbitrage could be unrealistic on markets with low liquidity; the presumptions necessary to practically succeed are not fulfilled enough to ensure the arbitrage is profitable. Research limitations – The backtesting is limited to USD market, testing other markets is recommended, but different result is not expected. Practical implications – The research helps practitioners considering this strategy for its implementation to algorithmic trading. Originality/Value – New important results for financial practitioners; states that practical and profitable utilization of convexity arbitrage is unrealizable and save costs during implementation of the strategy.

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Section: Literature Reviewmentioning

confidence: 99%

Interest Rates Sensitivity Arbitrage – Theory and Practical Assesment for Financial Market Trading

Stádník

2021

Business, Management and Economics Engineering

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Pricing and Hedging Short Sterling Options Using Neural Networks

Chen

Sutcliffe

2012

Intell. Sys. Acc. Fin. Mgmt.

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SUMMARY This paper compares the performance of artificial neural networks (ANNs) with that of the modified Black model in both pricing and hedging short sterling options. Using high‐frequency data, standard and hybrid ANNs are trained to generate option prices. The hybrid ANN is significantly superior to both the modified Black model and the standard ANN in pricing call and put options. Hedge ratios for hedging short sterling options positions using short sterling futures are produced using the standard and hybrid ANN pricing models, the modified Black model, and also standard and hybrid ANNs trained directly on the hedge ratios. The performance of hedge ratios from ANNs directly trained on actual hedge ratios is significantly superior to those based on a pricing model, and to the modified Black model. Copyright © 2012 John Wiley & Sons, Ltd.

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Convexity arbitrage – the idea which does not work

Stádník

2022

Cogent Economics & Finance

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Statistical arbitrage trading with wavelets and artificial neural networks

Cited by 7 publications

References 8 publications

Interest Rates Sensitivity Arbitrage – Theory and Practical Assesment for Financial Market Trading

Interest Rates Sensitivity Arbitrage – Theory and Practical Assesment for Financial Market Trading

Pricing and Hedging Short Sterling Options Using Neural Networks

Convexity arbitrage – the idea which does not work

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