Quantitative Finance

Quantitative Finance
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Published by: Taylor & Francis

Editor(s): Jim Gatheral - Baruch College, The City University of New York, USA and Michael Dempster - Centre for Mathematical Sciences, University of Cambridge

The frontiers of finance are shifting rapidly, driven in part by the increasing use of quantitative methods in the field. Quantitative Finance welcomes original research articles that reflect the dynamism of this area. The journal provides an interdisciplinary forum for presenting both theoretical and empirical approaches and offers rapid publication of original new work with high standards of quality. The readership is broad, embracing researchers and practitioners across a range of specialisms and within a variety of organizations. All articles should aim to be of interest to this broad readership.

  • Risk measures based on weak optimal transport
    By Michael Kupper Max Nendel Alessandro Sgarabottolo † Department of Mathematics and Statistics, University of Konstanz, Konstanz, Germany‡ Center for Mathematical Economics, Bielefeld University, Bielefeld, Germany
  • FuNVol: multi-asset implied volatility market simulator using functional principal components and neural SDEs
    By Vedant Choudhary Sebastian Jaimungal Maxime Bergeron † Department of Statistical Sciences, University of Toronto, Toronto, ON, M5G 1Z5, Canada‡ Riskfuel Analytics, Toronto, ON, Canada
  • Revisiting elastic string models of forward interest rates
    By Victor Le Coz Jean-Philippe Bouchaud † Quant AI Lab, 29 Rue de Choiseul, Paris, 75002, France‡ Chair of Econophysics and Complex Systems, École polytechnique, Palaiseau Cedex, 91128, France§ LadHyX UMR CNRS 7646 École polytechnique, Palaiseau Cedex, 91128, France¶ Laboratoire de Mathématiques et Informatique pour la Complexité et les Systèmes, CentraleSupélec, Université Paris-Saclay, Gif-sur-Yvette Cedex, 91192, France∥ Capital Fund Management, 23 Rue de l'Université, Paris, 75007, France** Académie des Sciences, Quai de Conti, Paris, 75006, France
  • Detecting rough volatility: a filtering approach
    By Camilla Damian Rüdiger Frey † Department of Mathematics, Vrije Universiteit Amsterdam, Amsterdam, Netherlands‡ Institute for Statistics and Mathematics, Vienna University of Economics and Business (WU), Vienna, Austria
  • Risk conscious investment¶
    By Dilip B. Madan Wim Schoutens King Wang † Department of Finance, Robert H. Smith School of Business, University of Maryland, College Park, MD, 20742, USA‡ Department of Mathematics, K.U. Leuven, Leuven, Belgium§ Derivative Product Strats, Morgan Stanley, 1585 Broadway, 2nd Floor, New York, NY, 10036, USA
  • Statistical inference for the first-order autoregressive process with the fractional Gaussian noise
    By Yinzhong Huang Weilin Xiao Xiaojian Yu † School of Management, Zhejiang University, Hangzhou, 310058, People's Republic of China‡ Center for Research on Zhejiang Digital Development and Governance, Hangzhou, Zhejiang, 310058, People's Republic of China§ Capital Market Research Center, Zhejiang University, Hangzhou, Zhejiang, 310058, People's Republic of China¶ Research Center of Financial Engineering, School of Economics and Commerce, South China University of Technology, Guangzhou, 510006, People's Republic of China
  • A common shock model for multidimensional electricity intraday price modelling with application to battery valuation
    By Thomas Deschatre Xavier Warin EDF Lab Paris-Saclay and FiMe, Laboratoire de Finance des Marchés de l'Energie, Palaiseau 91120, France
  • Higher order approximation of option prices in Barndorff-Nielsen and Shephard models
    By Álvaro Guinea Juliá Alet Roux † Comillas Pontifical University ICAI, Madrid, 28015, Spain‡ University of York, Heslington, YO10 5DD, UK
  • DeepVol: volatility forecasting from high-frequency data with dilated causal convolutions
    By Fernando Moreno-Pino Stefan Zohren † Oxford-Man Institute of Quantitative Finance, University of Oxford, Oxford, UK‡ Signal Processing and Learning Group, Universidad Carlos III de Madrid, Madrid, Spain§ Machine Learning Research Group, University of Oxford, Oxford, UK
  • Efficient option pricing in the rough Heston model using weak simulation schemes
    By Christian Bayer Simon Breneis Weierstrass Institute, Mohrenstr. 39, Berlin 10117, Germany
  • GDP-linked bonds as a new asset class
    By Ellie Papavassiliou Nikolas Topaloglou Stavros A. Zenios † Athens University of Economics and Business, 76, Patision Street, Athens GR10434, Greece‡ IPAG Business School, 10/12 rue du Théâtre, 75015 Paris, France§ Durham University Business School, Millhill Ln, Durham DH1 3LB, UK¶ University of Cyprus, P.O. Box 20537, Nicosia 1678, Cyprus‖ Cyprus Academy of Sciences, Letters, and Arts, Phaneromenis 60-68, 1011, Nicosia, Cyprus** Bruegel, Rue de la Charité, 1210 Brussel, Belgium
  • Neural network empowered liquidity pricing in a two-price economy under conic finance settings
    By Matteo Michielon Diogo Franquinho Alessandro Gentile Asma Khedher Peter Spreij † Quantitative Analysis and Quantitative Development, ABN AMRO Bank N.V., Gustav Mahlerlaan 10, Amsterdam, 1082 PP, The Netherlands‡ Korteweg-de Vries Institute for Mathematics, University of Amsterdam, Science Park 105-107, Amsterdam, 1098 XG, The Netherlands§ Department of Mathematics, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, 1049-001, Portugal¶ Energy Services B.V., Joan Muyskenweg 22, Amsterdam, 1096 CJ, The Netherlands∥ Institute for Mathematics, Astrophysics and Particle Physics, Radboud University Nijmegen, Huygens building, Heyendaalseweg 135, Nijmegen, 6525 AJ, The Netherlands
  • FX Open Forward
    By Julien Hok Alex S.L. Tse † Investec Bank, 30 Gresham St, London EC2V 7QN, UK‡ Department of Mathematics, University College London, London WC1H 0AY, UK
  • Asset prices when large investors interact strategically
    By Giuliano Curatola † Department of Economics and Statistics, University of Siena, Siena, Italy‡ Leibniz Institute for Financial Research SAFE, Frankfurt, Germany
  • Portfolio and reinsurance optimization under unknown market price of risk
    By Claudia Ceci Katia Colaneri † Department MEMOTEF, University of Rome Sapienza, Via del Castro Laurenziano 9, Roma 00161, Italy‡ Department of Economics and Finance, University of Rome Tor Vergata, Via Columbia 2, Roma 00133, Italy
  • Quantum Machine Learning and Optimisation in Finance
    By Tushar Vaidya Nanyang Technological University, SingaporeTushar Vaidya is a research fellow in quantum computing at Nanyang Technological University. His previous experience was in quantitative finance, working as a trader and quantitative strategist in fixed income derivatives. His current research encompasses algebraic AI and quantum algorithms for fundamental problems in machine learning.
  • Risk factor aggregation and stress testing
    By Natalie Packham Berlin School of Economics and Law, D-10825, Berlin, Germany
  • Pricing airbag option via first passage time approach
    By Zheng Liu Xiaosong Qian Jing Yao Yinghui Dong † Center for Financial Engineering and Department of Mathematics, Soochow University, Suzhou, People's Republic of China‡ Department of Mathematics and Physics, Suzhou University of Science and Technology, Suzhou, People's Republic of China
  • Regulating stochastic clocks§
    By Zhe Fei Weixuan Xia † Department of Finance, Boston University Questrom School of Business, 595 Commonwealth Ave, Boston, MA, 02215, USA‡ Department of Mathematics, University of Southern California, 3620 S. Vermont Ave, Los Angeles, CA, 90089, USA
  • Assessing network risk with FRM: links with pricing kernel volatility and application to cryptocurrencies
    By Ruting Wang Valerio Potì Wolfgang Karl Härdle † Business School, Sun Yat-sen University, Shenzhen, People's Republic of China‡ Smurfit Graduate Business School, University College Dublin, Dublin, Ireland§ IRTG 1792, Humboldt-Universität zu Berlin, Berlin, Germany¶ Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen, People's Republic of China|| Sim Kee Boon Institute for Financial Economics, Singapore Management University, Singapore, Singapore** Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic†† Yushan Scholar, National Yang Ming Chiao Tung University, Hsinchu, Taiwan‡‡ IDA Institute for Digital Assets, Bucharest University of Economic Studies, Bucharest, Romania
  • Covariance matrix filtering and portfolio optimisation: the average oracle vs non-linear shrinkage and all the variants of DCC-NLS
    By Christian Bongiorno Damien Challet Laboratoire de Mathématiques et Informatique pour la Complexité et les Systèmes, Université Paris-Saclay, CentraleSupélec, Gif-sur-Yvette, 91192, France
  • Spike and hike modeling for interest rate derivatives: with an application to SOFR caplets
    By Leif Andersen Dominique Bang Bank of America, New York, USA
  • Equity auction dynamics: latent liquidity models with activity acceleration
    By Mohammed Salek Damien Challet Ioane Muni Toke Laboratoire de Mathématiques et Informatique pour la Complexité et les Systèmes, Université Paris-Saclay, CentraleSupélec, Gif-sur-Yvette 91192, France
  • Valuation and hedging of cryptocurrency inverse options
    By V. Lucic A. Sepp † Imperial College and Marex, London, UK‡ LGT Bank, Zurich, Switzerland
  • When to efficiently rebalance a portfolio
    By Masayuki Ando Masaaki Fukasawa Graduate School of Engineering Science, Osaka University, Toyonaka, 560-8531, Japan
  • On joint marginal expected shortfall and associated contribution risk measures
    By Tong Pu Yifei Zhang Yiying Zhang Department of Mathematics, Southern University of Science and Technology, Shenzhen 518055, People's Republic of China
  • Introducing and testing the Carr model of default
    By Federico Maglione Department of Economics and Management, University of Florence, Via delle Pandette, 9, 50127 Florence, Italy
  • Weight bound constraints in mean-variance models: a robust control theory foundation via machine learning
    By Gilles Boevi Koumou Chaire Desjardins en Finance Responsable, École de Gestion, Université de Sherbrooke, 2500 Boulevard de l'Université, Sherbrooke, Québec, J1K 2R1, Canada
  • Causal Factor Investing
    By Luis Seco University of TorontoProf. Luis Seco is the Director of the Mathematical Finance Program, a Professor of Mathematics at the University of Toronto and the director of Risklab, a university research laboratory established in 1996, conducting research in quantitative finance, with a special focus on asset management. Prof. Seco's current activity is focused on sustainability, including climate risk, and is simultaneously the Chair of the Centre for Sustainable Development at the Fields Institute, and an affiliate Faculty member at the Vector Institute for Research in Machine Learning; Prof. Seco's core activity is bringing artificial intelligence into today's sustainability challenges to build a new better world for future. He has authored papers in artificial intelligence and environmental scores and currently is expanding that work to analyze CO2 emissions and carbon trades using machine learning. He was appointed ADIALab Fellow in 2022.His expertise has been in developing University–Industry relationships, which he has done since 1996. In October 2007, he won the NSERC – Natural Sciences and Engineering Research Council of Canada–Synergy Award for Innovation for his achievements. The award was delivered by Dr. Colin Carrie, Parliamentary Secretary to the Minister of Industry, on behalf of the Honourable Jim Prentice, Minister of Industry and Minister responsible for the Natural Sciences and Engineering Research Council of Canada (NSERC), and by Dr. Suzanne Fortier, President of NSERC. In 2011 he was admitted to Caballero de la Orden del Mérito Civil (Knight of the Order of Civil Merit), an award from the Government of Spain for his application of mathematics to foresee economic cycles.He was a co-founder and CEO of Sigma Analysis & Management Ltd., an asset management firm that invested institutional money in liquid alternative investments for 20 years.Today, Prof. Seco's business partners include several International pension and sovereign wealth funds, the FIT Centre, RiskLab Centre Inc., Metaversitas Inc. and JUMP S.a.r.l., to address challenges and achieve an innovation agenda. His vision is to leverage the University network worldwide to promote training and research broadly in the areas where technology and innovation join finance bringing them together, including education, climate risk and sustainability.Luis Seco's career started at Princeton University in 1985 and landed at the University of Toronto in 1992 after a short stay at the California Institute of Technology. Today, he holds adjunct appointments at Renmin University in Beijing, Florida International University, the Technical University of Munich, the University of Zurich and Kutaisi International University.
  • Earnings mean reversion and dynamic optimal capital structure
    By Elettra Agliardi Marios Charalambides Nicos Koussis † Department of Economics, University of Bologna, Piazza Scaravilli 2, 40126 Bologna, Italy‡ Department of Business Administration, Frederick University Cyprus, 7, Y. Frederickou Str. Pallouriotisa, Nicosia 1036, Cyprus
  • Trade co-occurrence, trade flow decomposition and conditional order imbalance in equity markets
    By Yutong Lu Gesine Reinert Mihai Cucuringu † Department of Statistics, University of Oxford, 24–29 St Giles', Oxford OX1 3LB, UK‡ Mathematical Institute, University of Oxford, Woodstock Rd, Oxford OX2 6GG, UK§ Oxford-Man Institute of Quantitative Finance, University of Oxford, Oxford, UK¶ The Alan Turing Institute, 96 Euston Rd, London NW1 2DB, UK
  • Predicting forward default probabilities of firms: a discrete-time forward hazard model with firm-specific frailty
    By Ruey-Ching Hwang Yi-Chi Chen † Department of Finance, National Dong Hwa University, Hualien, Taiwan‡ Department of Economics, National Cheng Kung University, Tainan, Taiwan
  • Interest rate convexity in a Gaussian framework
    By Antoine Jacquier Mugad Oumgari † Department of Mathematics, Imperial College London, London, UK‡ The Alan Turing Institute, London, UK§ University College London, London, UK¶ Lloyds Banking, London, UK
  • Neural network approach to portfolio optimization with leverage constraints: a case study on high inflation investment
    By Chendi Ni Yuying Li Peter Forsyth † Cheriton School of Computer Science, University of Waterloo, Waterloo, ON, N2L 3G1, Canada‡ Flap Technologies, 307 W 38th St, Floor 16, PMB 468, New York, NY, 10018, USA
  • Cross-section without factors: a string model for expected returns
    By Walter Distaso Antonio Mele Grigory Vilkov † Imperial College, South Kensington Campus, London SW7 2AZ, United Kingdom‡ USI Lugano, Swiss Finance Institute and CEPR, Via Buffi 13, 6900 Lugano, Switzerland§ Frankfurt School of Finance & Management, Adickesallee 32-34, Frankfurt, Germany
  • Counting jumps: does the counting process count?
    By Laura Ballotta Gianluca Fusai Daniele Marazzina † Bayes Business School (formerly Cass), City University of London, London, UK‡ Dipartimento DiSei, Università degli Studi del Piemonte Orientale, Novara, Italy§ Department of Mathematics, Politecnico di Milano, Milano, Italy
  • Market consistent bid-ask option pricing under Dempster-Shafer uncertainty
    By A. Cinfrignini D. Petturiti B. Vantaggi † Department MEMOTEF, “La Sapienza” University of Rome, Rome, Italy‡ Department Economics, University of Perugia, Perugia, Italy
  • ESG risk exposure: a tale of two tails
    By Runfeng Yang Massimiliano Caporin Juan-Angel Jiménez-Martin † Department of Economics, Ca' Foscari University of Venice, Venice, Italy‡ Department of Statistical Sciences, University of Padova, Padova, Italy§ Instituto Complutense de Análisis Económico (ICAE), Facultad de Ciencias Económicas y Empresariales, Universidad Complutense de Madrid, Madrid, Spain
  • On the implied volatility skew outside the at-the-money point
    By Michele Azzone Lorenzo Torricelli † Department of Mathematics, Politecnico di Milano, Milano, Italy‡ Department of Statistical Sciences “P. Fortunati”, University of Bologna, Bologna, Italy
  • Deep learning for enhanced index tracking
    By Zhiwen Dai Lingfei Li Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Hong Kong SAR, People's Republic of China
  • Consistent curves in the -world: optimal bonds portfolio
    By Gaddiel Y. Ouaknin Engineering Department, Stanford University, Stanford, CA, USA
  • Optimal trading and competition with information in the price impact model
    By Longjie Xu Yufeng Shi † Institute for Financial Studies, Shandong University, Jinan 250100, People's Republic of China‡ School of Mathematics, Shandong University, Jinan 250100, People's Republic of China
  • Do price trajectory data increase the efficiency of market impact estimation?
    By Fengpei Li Vitalii Ihnatiuk Yu Chen Jiahe Lin Ryan J. Kinnear Anderson Schneider Yuriy Nevmyvaka Henry Lam † Machine Learning Research, Morgan Stanley, New York, NY, USA‡ Quantitative Research, Morgan Stanley, New York, NY, USA§ Department of Economics, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine¶ Electrical and Computer Engineering, University of Waterloo, Waterloo, Canada‖ Department of IEOR, Columbia University, New York, NY, USA
  • Risk management under weighted limited expected loss
    By An Chen Thai Nguyen † Institute of Insurance Science, University of Ulm, Helmholtzstrasse 20, 89069 Ulm, Germany‡ École d'Actuariat, Université Laval, 2425, rue de l'Agriculture, Québec G1V 0A6, Canada§ School of Economic Mathematics – Statistics, University of Economics Ho Chi Minh City, 59C Nguyen Dinh Chieu Street, Ho Chi Minh City, Vietnam
  • Optimal reinsurance under a new design: two layers and multiple reinsurers
    By Dingjun Yao Jinxia Zhu † School of Finance, Nanjing University of Finance and Economics, Nanjing 210023, People's Republic of China‡ School of Risk and Actuarial Studies, Business School, The University of New South Wales, Sydney, NSW 2052, Australia
  • Mean-variance portfolio with wealth and volatility dependent risk aversion
    By Shican Liu School of Statistics and Mathematics, Zhongnan University of Economics and Law, Wuhan, China
  • A study on asset price bubble dynamics: explosive trend or quadratic variation?
    By Robert A. Jarrow Simon S. Kwok † Samuel Curtis Johnson Graduate School of Management, Cornell University, Ithaca, NY 14853, USA‡ Kamakura Corporation, Honolulu, HI 96815, USA§ School of Economics, The University of Sydney, Camperdown, NSW 2006, Australia
  • The contagion of extreme risks between fossil and green energy markets: evidence from China
    By Xiaohang RenYa XiaoFeng HeGiray Gozgor† School of Business, Central South University, Changsha, People’s Republic of China‡ School of Finance, Capital University of Economics and Business, Beijing, People’s Republic of China§ School of Management, University of Bradford, Bradford, UK
  • Dynamic partial (co)variance forecasting model
    By Zirong ChenYao Zhou† Department of Antai College of Economics and Management, Shanghai Jiao Tong University, Shanghai, People's Republic of China‡ The People's Bank of China, Beijing, People's Republic of China
  • Online learning of order flow and market impact with Bayesian change-point detection methods
    By Ioanna-Yvonni TsaknakiFabrizio LilloPiero Mazzarisi† Scuola Normale Superiore, Piazza dei Cavalieri 7, Pisa, 56126, Italy‡ Department of Mathematics, University of Bologna, Piazza di Porta San Donato 5, Bologna, 40126, Italy§ Department of Economics and Statistics, University of Siena, Banchi di Sotto 55, Siena, 53100, Italy
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