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Computational Finance and Financial Econometrics
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Computational Finance and Financial Econometrics

A special issue of Journal of Risk and Financial Management (ISSN 1911-8074). This special issue belongs to the section "Mathematics and Finance".

Deadline for manuscript submissions: closed (28 February 2025) | Viewed by 6552

Special Issue Editor

Dr. Lars Stentoft

E-Mail Website
Guest Editor
Department of Economics, University of Western Ontario, Social Science Centre Room 4071, London, ON N6A 5C2, Canada
Interests: finance; financial econometrics; computational finance; econometrics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue focuses on the intersection of Computational Finance and Financial Econometrics in today’s complex financial markets. It will include novel research on the use of computational methods and techniques for modelling financial asset prices, returns, and volatility, on the pricing, hedging, and risk management of financial instruments, and the econometric challenges faced when considering financial markets in general and the markets for derivatives in particular.

Theoretical and empirical articles dealing with the application of novel computational techniques in estimation, simulation, optimization, and calibration with applications for asset pricing, derivative valuation, hedging, and risk management are welcome. Contributions focusing on multivariate or high-dimensional applications, on the use of machine learning techniques with large financial data sets, and on applications to new asset classes such as volatility indices such as, e.g., the VIX, are encouraged.

Dr. Lars Stentoft
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Risk and Financial Management is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • asset pricing models
  • calibration
  • derivatives
  • estimation
  • hedging and risk management
  • machine learning methods
  • multivariate and high-dimensional models
  • optimization
  • simulation
  • volatility models

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Published Papers (5 papers)

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Research

16 pages, 465 KiB  
Article
Multi-Period Portfolio Optimization Model with Cone Constraints and Discrete Decisions
by Ümit Sağlam and Hande Y. Benson
J. Risk Financial Manag. 2025, 18(4), 218; https://doi.org/10.3390/jrfm18040218 - 18 Apr 2025
Viewed by 77
Abstract
This work develops a practical multi-period optimization approach that incorporates real-world constraints, including discrete decisions and conic risk constraints. Expanding upon earlier single-period models, our framework employs a binary scenario tree derived from monthly returns of randomly selected S&P 500 stocks to represent [...] Read more.
This work develops a practical multi-period optimization approach that incorporates real-world constraints, including discrete decisions and conic risk constraints. Expanding upon earlier single-period models, our framework employs a binary scenario tree derived from monthly returns of randomly selected S&P 500 stocks to represent market evolution across multiple periods. The formulation captures essential portfolio constraints, such as transaction fees, sector diversification, and minimum investment thresholds, resulting in a robust and comprehensive optimization approach. To efficiently solve the resulting mixed-integer second-order cone programming (MISOCP) problem, we employ an outer approximation algorithm with a warmstart strategy, which significantly improves solution runtimes and computational efficiency. Numerical experiments demonstrate the model’s effectiveness, showing an average improvement of 10.71% in iteration count and 15.24% in computational time when using the warmstart approach. Full article
(This article belongs to the Special Issue Computational Finance and Financial Econometrics)
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28 pages, 1373 KiB  
Article
South African Government Bond Yields and the Specifications of Affine Term Structure Models
by Malefane Molibeli and Gary van Vuuren
J. Risk Financial Manag. 2025, 18(4), 204; https://doi.org/10.3390/jrfm18040204 - 9 Apr 2025
Viewed by 200
Abstract
This study adopts a three-factor approach to the affine term structure models, aiming to analyse South African (SA) government bond yields across various maturities. The primary objective is to evaluate whether these models offer robust pricing capabilities—being both admissible and flexible—while capturing the [...] Read more.
This study adopts a three-factor approach to the affine term structure models, aiming to analyse South African (SA) government bond yields across various maturities. The primary objective is to evaluate whether these models offer robust pricing capabilities—being both admissible and flexible—while capturing the conditional correlations and volatilities of yield factors specific to SA bond yields. For a model to be considered admissible, it must also demonstrate economic identification and maximal flexibility. We thus investigate the short-, medium-, and long-term dynamics of bond yields concurrently. Model estimation involves deriving joint conditional densities through the inversion of the Fourier transform applied to the characteristic function of the state variables. This enables the use of maximum likelihood estimation as an efficient method. We assume that the market prices of risk are proportional to the volatilities of the state variables. The analysis reveals negative correlations between factors. Among the models tested, the A1(3) model outperforms the A2(3) model in terms of fit, both in sample and out of sample. Full article
(This article belongs to the Special Issue Computational Finance and Financial Econometrics)
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14 pages, 504 KiB  
Article
Distortion Risk Measures of Increasing Rearrangement
by Joachim Paulusch, Thorsten Moser and Anna Sulima
J. Risk Financial Manag. 2024, 17(10), 461; https://doi.org/10.3390/jrfm17100461 - 10 Oct 2024
Viewed by 1136
Abstract
Increasing rearrangement is a rewarding instrument in financial risk management. In practice, risks must be managed from different perspectives. A common example is the portfolio risk, which often can be seen from at least two perspectives: market value and book value. Different perspectives [...] Read more.
Increasing rearrangement is a rewarding instrument in financial risk management. In practice, risks must be managed from different perspectives. A common example is the portfolio risk, which often can be seen from at least two perspectives: market value and book value. Different perspectives with different distributions can be coupled by increasing rearrangement. One distribution is regarded as underlying, and the other distribution can be expressed as an increasing rearrangement of the underlying distribution. Then, the risk measure for the latter can be expressed in terms of the underlying distribution. Our first objective is to introduce increasing rearrangement for application in financial risk management and to apply increasing rearrangement to the class of distortion risk measures. We derive formulae to compute risk measures in terms of the underlying distribution. Afterwards, we apply our results to a series of special distortion risk measures, namely the value at risk, expected shortfall, range value at risk, conditional value at risk, and Wang’s risk measure. Finally, we present the connection of increasing rearrangement with inverse transform sampling, Monte Carlo simulation, and cost-efficient strategies. Butterfly options serve as an illustrative example of the method. Full article
(This article belongs to the Special Issue Computational Finance and Financial Econometrics)
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20 pages, 1035 KiB  
Article
Optimal Market Completion through Financial Derivatives with Applications to Volatility Risk
by Matt Davison, Marcos Escobar-Anel and Yichen Zhu
J. Risk Financial Manag. 2024, 17(10), 457; https://doi.org/10.3390/jrfm17100457 - 8 Oct 2024
Viewed by 1348
Abstract
This paper investigates the optimal choices of financial derivatives to complete a financial market in the framework of stochastic volatility (SV) models. We first introduce an efficient and accurate simulation-based method applicable to generalized diffusion models to approximate the optimal derivatives-based portfolio strategy. [...] Read more.
This paper investigates the optimal choices of financial derivatives to complete a financial market in the framework of stochastic volatility (SV) models. We first introduce an efficient and accurate simulation-based method applicable to generalized diffusion models to approximate the optimal derivatives-based portfolio strategy. We build upon a double optimization approach, i.e., expected utility maximization and risk exposure minimization, already proposed in the literature, demonstrating that strangle options are the best choices for market completion within equity options. They lead to lower investors’ risk exposure for a wide range of strikes compared to the lesser flexibility of calls, puts, and strangles. Furthermore, we explore the benefit of using volatility index derivatives and conclude that they could be more convenient substitutes when short-term maturity equity options are not available. Full article
(This article belongs to the Special Issue Computational Finance and Financial Econometrics)
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15 pages, 1471 KiB  
Article
The Launch of a Night Trading Session and Currency Futures Market Liquidity: Evidence from the Thailand Futures Exchange
by Woradee Jongadsayakul
J. Risk Financial Manag. 2023, 16(10), 442; https://doi.org/10.3390/jrfm16100442 - 11 Oct 2023
Cited by 1 | Viewed by 1961
Abstract
The Thailand Futures Exchange launched USD Futures as the first currency futures contract on 5 June 2012. However, it has been available for night trading since 27 September 2021. This research aims to analyze the effect of adding a night trading session on [...] Read more.
The Thailand Futures Exchange launched USD Futures as the first currency futures contract on 5 June 2012. However, it has been available for night trading since 27 September 2021. This research aims to analyze the effect of adding a night trading session on USD Futures market liquidity and to make a liquidity comparison between day and night session trading. By adding a dummy variable into the vector autoregression model of order 5 to capture the effect of a night session introduction on market liquidity, the results show that market depth and breadth are even stronger after a longer trading session. In addition, the t-test results show the presence of lower tightness but stronger depth and breadth in day session trading than in night session trading, because of the availability of a large number of orders and the ability of the market to have smoother trading in day as opposed to night. Due to the positive effect of extended trading hours on market depth and breadth, TFEX should consider a longer night session in line with other global futures markets. Night traders should also be aware of liquidity risk due to low night session trading volume. Full article
(This article belongs to the Special Issue Computational Finance and Financial Econometrics)
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