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 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
  • Speed and duration of drawdown under general Markov models
    By Lingfei LiPingping ZengGongqiu Zhang† Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR‡ Department of Mathematics, Southern University of Science and Technology, Shenzhen, People's Republic of China§ School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, Shenzhen, People's Republic of China
  • Optimal operation of a hydropower plant in a stochastic environment
    By Isabel Figuerola-FerrettiEduardo SchwartzIgnacio Segarra† ICADE and Center for Low Carbon Hydrogen Studies, Universidad Pontificia Comillas, Madrid, Spain‡ Beedie School of Business, Simon Fraser University, Vancouver, Canada§ Instituto de Investigación Tecnológica (IIT), Universidad Pontificia Comillas, Madrid, Spain
  • Tail risk aversion and backwardation of index futures
    By Jufang LiangDan YangQian Han† School of Finance and Statistics, Hunan University, 109 Shijiachong Road, Yuelu District, Changsha, Hunan 410079, People's Republic of China‡ Lingnan College, Sun Yat-Sen University, 135 Xingang Xi Road, Haizhu District, Guangzhou, Guangdong 510275, People's Republic of China
  • Narrative triggers of information sensitivity
    By Kim RistolainenDepartment of Economics, Turku School of Economics, University of Turku, FI-20014, Turku, Finland
  • Deep calibration with random grids
    By Fabio BaschettiGiacomo BormettiPietro Rossi† Scuola Normale Superiore, Pisa, Italy‡ Department of Mathematics, University of Bologna, Bologna, Italy§ Prometeia S.p.A., Bologna, Italy¶ Department of Statistical Sciences, University of Bologna, Bologna, Italy
  • A modified CTGAN-plus-features-based method for optimal asset allocation
    By José-Manuel Pe naFernando SuárezOmar LarréDomingo RamírezArturo Cifuentes† Fintual Administradora General de Fondos S.A. Santiago, Chile, Fintual, Inc.‡ Clapes UC, Pontificia Universidad Católica de Chile, Santiago, Chile
  • Interactions between monetary and macroprudential policies
    By Gustavo Libório Rocha LimaRegis Augusto ElyDaniel Oliveira Cajueiro† Department of Economics, University of Brasilia, Brasilia, Brazil‡ Department of Economics, Federal University of Pelotas, Pelotas, Brazil§ National Institute of Science and Technology for Complex Systems (INCT-SC), Rio de Janeiro, Brazil¶ Machine Learning Laboratory in Finance and Organizations (LAMFO), Brasilia, Brazil
  • Interactions between monetary and macroprudential policies
    By Gustavo Libório Rocha LimaRegis Augusto ElyDaniel Oliveira Cajueiro† Department of Economics, University of Brasilia, Brasilia, Brazil‡ Department of Economics, Federal University of Pelotas, Pelotas, Brazil§ National Institute of Science and Technology for Complex Systems (INCT-SC), Rio de Janeiro, Brazil¶ Machine Learning Laboratory in Finance and Organizations (LAMFO), Brasilia, Brazil
  • 15 years of Adjoint Algorithmic Differentiation (AAD) in finance
    By Luca CapriottiMike Giles† Department of Mathematics & Department of Industrial Engineering and Operations Research, Columbia University, New York, NY, 10027, USA‡ Mathematical Institute, Oxford University Mathematical Institute, Woodstock Road, Oxford, OX2 6GG, UK
  • 15 years of Adjoint Algorithmic Differentiation (AAD) in finance
    By Luca CapriottiMike Giles† Department of Mathematics & Department of Industrial Engineering and Operations Research, Columbia University, New York, NY, 10027, USA‡ Mathematical Institute, Oxford University Mathematical Institute, Woodstock Road, Oxford, OX2 6GG, UK
  • Asymptotics for short maturity Asian options in jump-diffusion models with local volatility
    By Dan PirjolLingjiong Zhu† School of Business, Stevens Institute of Technology, Hoboken, NJ 07030, USA‡ Department of Mathematics, Florida State University, 1017 Academic Way, Tallahassee, FL 32306, USA
  • Asymptotics for short maturity Asian options in jump-diffusion models with local volatility
    By Dan PirjolLingjiong Zhu† School of Business, Stevens Institute of Technology, Hoboken, NJ 07030, USA‡ Department of Mathematics, Florida State University, 1017 Academic Way, Tallahassee, FL 32306, USA
  • GPT's idea of stock factors
    By Yuhan ChengKe Tang† School of Management, Shandong University, Jinan, China‡ Institute of Economics, Tsinghua University, Beijing, China
  • GPT's idea of stock factors
    By Yuhan ChengKe Tang† School of Management, Shandong University, Jinan, China‡ Institute of Economics, Tsinghua University, Beijing, China
  • A static replication approach for callable interest rate derivatives: mathematical foundations and efficient estimation of SIMM–MVA
    By J. H. HoencampS. JainB. D. Kandhai† Computational Science Lab, University of Amsterdam, Science Park 904, Amsterdam 1098XH, Netherlands‡ Department of Management Studies, Indian Institute of Science, Bangalore, India§ Quantitative Analytics, ING Bank, Foppingadreef 7, Amsterdam, 1102 BD, Netherlands
  • A static replication approach for callable interest rate derivatives: mathematical foundations and efficient estimation of SIMM–MVA
    By J. H. HoencampS. JainB. D. Kandhai† Computational Science Lab, University of Amsterdam, Science Park 904, Amsterdam 1098XH, Netherlands‡ Department of Management Studies, Indian Institute of Science, Bangalore, India§ Quantitative Analytics, ING Bank, Foppingadreef 7, Amsterdam, 1102 BD, Netherlands
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