Research activities

QFinLab promotes research in quantitative finance, combining rigorous mathematical, statistical and computational methods with applications that are central to financial markets, risk management, regulation, innovation and sustainability. The Lab aims to be a reference point for academic research, advanced education, outreach and collaborations with institutions and industry.

Topics

The research activity of QFinLab covers core areas of quantitative finance and emerging domains at the intersection of finance, technology and sustainability.

Activities

QFinLab supports research dissemination and community building through seminars, workshops, conferences, training initiatives and outreach activities. These initiatives connect researchers, students, institutions and financial-industry practitioners.

• QFinLab Seminar. A scientific seminar series devoted to current research topics in quantitative finance, fintech, risk management and related areas.
• Climate Risk Seminar. A thematic seminar series on climate risk and its implications for economic activity, financial assets, insurance products, risk management, transition policies and incentive mechanisms.
• ALGODEFI Conference. A conference on Algorithmic Trading, Decentralized Finance and Artificial Intelligence in Capital Markets, designed to foster discussion between academia and industry on trading, market microstructure, machine learning, digital assets, smart contracts and cryptocurrencies.
• International Fintech Research Conference. QFinLab researchers are among the promoters of this annual research initiative. The first edition took place at Politecnico di Milano on October 27-28, 2022, and aimed to bring together researchers working across fintech, including banking, asset management, insurance, payments, capital markets, digital currencies, cybersecurity, blockchain and artificial intelligence.
• Green Finance Workshop. QFinLab and the Department of Mathematics promote this initiative on quantitative methods for green finance. The first workshop was held in Milan on February 1-2, 2024, at Politecnico di Milano.
• FinRiskAlert and outreach initiatives. QFinLab also contributes to dissemination and financial education through initiatives aimed at institutions, schools, practitioners and the wider public. Click here for details.

Main Recent Financed Projects

• Securing Decentralized Finance and Remote Healthcare Systems – SHIELD (2024-2025). PNRR project PE7 Security and rights in the cyberspace (SERICS). The SHIELD project aims to develop protective measures to safeguard users of DeFi systems from cyber fraud, as well as tools to prevent, detect and respond to cyber threats targeting medical devices and patients’ personal information.
• Measuring, managing and hedging indirect climate-transition risk (2023-2025). 2022 PNRR PRIN. The project studies transition risk for firms and societies, focusing mainly on indirect risks arising from supply chains and from the interconnections among economic activities.
• Caccia al Tesoro Finanziaria – Financial Education Gamification (2023). The project supported the creation of an online event for secondary school students on financial education, exploiting gamification.
• MUSA – Multilayered Urban Sustainability Action (2022-2025). PNRR Project.  MUSA aims to transform the metropolitan area of Milan into an ecosystem of innovation for urban regeneration, intervening in fields ranging from social innovation to technology, with the goal of becoming a national and European model.
• EMFI – Emergency Finance (2021-2022). Research project proposed by Politecnico di Milano, Cefriel and University of Stirling, financed by the Algorand Foundation. The project focused on research and development of a special purpose digital currency on the Algorand blockchain.
• FIN-TECH – A FINancial supervision and TECHnology compliance training programme (2019-2021). H2020 project. The project provided training for Consob staff on fintech topics, including big data, machine learning and blockchain.
• IMPACT EDUFIN (2020-2022). Bank of Italy “Contributo liberale”. The project supported financial education activities in Italian secondary schools and an impact analysis aimed at assessing their effectiveness.
• EDUFIN@POLIMI (2018-2020). Fondazione Cariplo project on financial education in schools. The project funded the creation of financial education material and its dissemination in secondary schools in Milan.

Research Output

• Jun 30 2026 Returns under the lens: the importance of ESG factors Returns under the lens: the importance of ESG factors by Gabriele Ginestroni, Daniele Marazzina, Nico Rosamilia. Published in Decisions in Economics and Finance Abstract: Environmental, Social, and Governance (ESG) factors have become increasingly relevant in financial markets, influencing investment strategies and risk assessments. This article explores the role of raw ESG metrics in predicting the direction of future stock returns, framing return forecasting as a classification problem. We analyse MSCI ACWI index components from 2016 to 2022, focusing on the manufacturing, information, and financial sectors in the USA and Europe. We propose an ESG-oriented data cleaning pipeline and evaluate various machine learning models, finding that XGBoost outperforms other approaches. To assess the predictive power of ESG metrics, we conducted an ablation study, comparing their contribution to benchmark financial variables and past returns. Our results show that ESG and financial variables independently improve classification performance comparably, suggesting a complementary role in return forecasting. Through a SHAP-based feature importance analysis, we examine ESG contributions at the sector-region level, revealing that Environmental and Governance factors are generally the most influential in predictive performance. Our findings suggest that raw ESG metrics contain meaningful predictive value that should not be overlooked.

• May 29 2026 Carbon-Penalised Portfolio Insurance Strategies in a Stochastic Factor Model with Partial Information Carbon-Penalised Portfolio Insurance Strategies in a Stochastic Factor Model with Partial Information by Katia Colaneri, Federico D’Amario, Daniele Mancinelli. Published in Scandinavian Acturial Journal Abstract: We investigate optimal proportional portfolio insurance (PPI) strategies aimed at reducing exposure to carbon intensive stocks. PPI strategies enable investors to mitigate downside risk while retaining the potential for upside gains. In this paper we determine the PPI strategies to maximise the expected utility of the terminal cushion, where the terminal cushion is penalised proportionally to the realised volatility of stocks issued by firms operating in carbon-intensive sectors. We model the risky assets’ dynamics using geometric Brownian motions whose drift rates are modulated by an unobservable common stochastic factor to capture market-specific or economy-wide state variables that are typically not directly observable. Using the classical stochastic filtering theory, we formulate a suitable optimisation problem and solve it for the CRRA utility function. We characterise optimal carbon-penalised PPI strategies and optimal value functions under full and partial information. We also carry a numerical analysis showing that the proposed strategy reduces carbon-emissions intensity without compromising financial performance.

• May 15 2026 Short-rate models with stochastic discontinuities: A PDE approach Short-rate models with stochastic discontinuities: A PDE approach by Alessandro Calvia, Marzia De Donno, Chiara Guardasoni, Simona Sanfelici. Published in Mathematics and computers in simulation. Abstract: With the reform of interest rate benchmarks, interbank offered rates (IBORs) like LIBOR have been replaced by risk-free rates (RFRs), such as the Secured Overnight Financing Rate (SOFR) in the U.S. and the Euro Short-Term Rate (€STR) in Europe. These rates exhibit characteristics like jumps and spikes which correspond to specific market events, driven by regulatory and liquidity constraints. To capture these characteristics, this paper considers a general short-rate model that incorporates discontinuities at fixed times with random sizes. Within this framework, we introduce a PDE-based approach for pricing interest rate derivatives and establish, under suitable assumptions, a Feynman-Kač representation for the solution. For affine models, we derive (quasi) closed-form solutions, while for the general case, we develop numerical methods to solve the resulting PDEs.

• Apr 30 2026 The additive Bachelier model with an application to the oil option market in the Covid period The additive Bachelier model with an application to the oil option market in the Covid period by Roberto Baviera and Michele Domenico Massaria Published in the Journal of Computational and Applied Mathematics Abstract: In April 2020, the Chicago Mercantile Exchange temporarily switched the pricing formula for West Texas Intermediate oil market options from the Black model to the Bachelier model. In this context, we introduce an additive Bachelier model that provides a simple closed-form solution and a good description of the implied volatility surface. This new additive model exhibits several notable mathematical and financial properties. It ensures the no-arbitrage condition, a critical requirement in highly volatile markets, while also enabling a parsimonious synthesis of the volatility surface. The model features only three parameters, each with a clear financial interpretation: the volatility term structure, the vol-of-vol, and a parameter for modelling skew. Model calibration can follow a cascade procedure: first, it accurately replicates the term structures of forwards and At-The-Money volatilities observed in the market; second, it fits the smile of the volatility surface. The proposed model also supports efficient pricing of path-dependent exotic options via Monte Carlo simulation, using a straightforward and computationally efficient approach. Overall, this model provides a robust and parsimonious description of the oil option market during the exceptionally volatile first period of the Covid-19 pandemic.

• Apr 27 2026 Temperature Anomalies and Climate Physical Risk in Portfolio Construction Temperature Anomalies and Climate Physical Risk in Portfolio Construction by Michele Azzone, Carlo Bechi, Gabriele Sbaiz Preprint Abstract: Driven by the increasing frequency and intensity of natural disasters and chronic climate threats, we investigate the impact of physical climate risk on global equity portfolios. By employing a panel regression analysis on sectoral returns, we provide statistical evidence that extreme temperature events exert a negative effect on most sectors. We introduce two novel metrics based on these temperature anomalies, Climate Risk Exposure and Climate Exposure Volatility, in order to measure the environmental vulnerability of a portfolio. Unlike available static country-level indices, these metrics incorporate the time varying probability of extreme events and their relations with firm-specific asset intensity. We integrate these measures into a multi-objective portfolio optimization framework. This approach extends the traditional Mean-Variance paradigm, allowing investors to construct portfolios that are resilient to physical climate shocks without sacrificing diversification. Finally, we conduct a backtesting analysis to show the practical benefits of incorporating these climate risk metrics into the investment process, evaluating how climate-aware strategies perform relative to traditional benchmarks.