In a nutshell

This webpage outlines my research activities (Ph.D., post-doc, EDF R&D). 

I moved to JP Morgan at the end of 2022, the webpage is no longer updated, but the contacts below still work!

Contact (e-mail).  You can contact me at matteo31415 (usual symbol) gmail (dot) com

Contact (LinkedIn).  My LinkedIn page is here

Curriculum

• Most recent positions

  • • JP Morgan Chase, Paris  -  VP - Quantitative analyst

    • EDF R&D, Paris  -  Quantitative researcher and project lead

    • University of California, Berkeley  -  Post-doc researcher

• Education

  • • Ph.D. in Computational Mathematics  -  University of Padua, Italy  

    • MS in Probability and Finance (DEA El Karoui)  -  Univ. Paris VI and École Polytechnique

    • MS in Mathematics -  University of Padua, Italy

• For more details, please see my LinkedIn page here

Published papers

(i) Machine learning

• M. Basei, X. Guo, A. Hu, Y. Zhang, Logarithmic regret for episodic continuous-time linear-quadratic reinforcement learning over a finite-time horizon, J. Mach. Learn. Res. (JMLR) 23, 1-34

We study finite-time horizon continuous-time linear-quadratic reinforcement learning problems in an episodic setting, where both the coefficients in the SDE are unknown to the controller. We propose a least-squares algorithm and establish a logarithmic regret bound of order O((ln M)(ln ln M)), with M being the number of learning episodes.

(ii) Stochastic control and games

• M. Basei, H. Pham, A weak martingale approach to linear-quadratic McKean-Vlasov stochastic control problems, J. Optim. Theory Appl. 181, no. 2, 347-382

We propose an original approach to solve linear-quadratic mean-field stochastic control problems. We study both finite-horizon and infinite-horizon problems, and allow some coefficients to be stochastic. We illustrate our results through an application to the production of an exhaustible resource. 

• M. Basei, H. Cao, X. Guo, Nonzero-sum stochastic games and mean-field games with impulse controls, Math. Oper. Res. 47, no. 1, 341-366

We consider nonzero-sum N-player stochastic games with impulse controls. Then, we consider the limit situation $N \to \infty$, i.e., mean-field games with impulse controls. Under appropriate conditions, the MFG is an $\epsilon$-NE approximation to the N-player game, with $\epsilon=\frac{1}{\sqrt{N}}$. As an example, we propose a cash management problem.  

• R. Aïd, M. Basei, G. Callegaro, L. Campi, T. Vargiolu, Nonzero-sum stochastic differential games with impulse controls: a verification theorem with applications, Math. Oper. Res. 45, no. 1, 205-232

We consider a general nonzero-sum impulse game with two players. The main contribution is a verification theorem which provides a suitable system of quasi-variational inequalities for the value functions. As an application, we consider a one-dimensional example and provide explicit expressions for a Nash equilibrium.

(iii) Models and options in commodities markets

• R. Aid, M. Basei, G. Ferrari, A stationary mean-field equilibrium model of irreversible investment in a two-regime economy, Operations Research, to appear

We consider a mean-field model of firms competing on a commodity market, where the commodity price is given in terms of a power inverse demand function of the industry-aggregate production. We prove existence, uniqueness and characterization of the stationary mean-field equilibrium of the model. The equilibrium investment strategy is of barrier-type and is triggered by a couple of endogenously determined investment thresholds, one per state of the economy.

• M. Basei, G. Ferrari, N. Rodosthenous, Uncertainty over uncertainty in environmental policy adoption: Bayesian learning of unpredictable socioeconomic costs, J. Economic Dynamics and Control JEDC 161, 104841

We consider the timing problem of a decision maker who aims at reducing the current emissions rate. By keeping track of the actual evolution of the costs, the decision maker is able to learn the unknown drift of the socioeconomic costs. We characterise the solution in terms of a threshold function, unique solution to a nonlinear integral equation. We numerically illustrate our results and perform comparative statics to understand the role of the relevant model's parameters.

• C. Alasseur, M. Basei, C. Bertucci, A. Cecchin, A mean-field model for the development of renewable capacities, Math. Financ. Econ. 17, 695-719

We propose a model based on a large number of small competitive producers of renewable energies, to study the effect of subsidies on the aggregate level of capacity. The analysis is based on a master equation and we get explicit formulae for the long-time equilibria.

• R. Aïd, M. Basei, H. Pham, A McKean-Vlasov approach to distributed electricity generation development, Math. Methods Oper. Res. 91, 269-310

Consumers satisfy their electricity demand by self-production (solar panels) and centralized production (energy companies). We consider the point of view of a consumer, an energy company, a social planner: we characterize the production strategies which minimize the costs and look for an equilibrium price.

• M. Basei, Optimal price management in retail energy markets: an impulse control problem with asymptotic estimates, Math. Methods Oper. Res. 89, no. 3, 355-383

We consider a retailer who buys energy in the wholesale market, resells it to final consumers, and looks for the price strategy maximizing his profit. We formulate a suitable infinite-horizon stochastic impulse control problem, characterize an optimal price strategy, and provide asymptotic estimates for the action region.

• M. Basei, A. Cesaroni, T. Vargiolu, Optimal exercise of swing contracts in energy markets: an integral constrained stochastic optimal control problem, SIAM J. Finan. Math. 5, no. 1, 581–608

We characterize the value of swing contracts in continuous time as the unique viscosity solution of a Hamilton–Jacobi–Bellman equation. The case of contracts with strict constraints gives rise to a control problem with nonstandard state constraints. 

Teaching

• [responsible instructor, in English] Financial engineering systems I (45 students), Spring 2019, Master of Engineering (MEng), IEOR department, University of California, Berkeley

Markov chains, Poisson and Hawkes processes, Markov decision processes (dynamic programming, value iteration, Q-learning

• [responsible instructor, in English] Introduction to financial engineering (65 students), Fall 2018, Master of Engineering (MEng), IEOR department, University of California, Berkeley

Introduction to finance (interest rates, financial instruments, arbitrage), discrete-time models (Markowitz problem, binomial model, no-arbitrage pricing), continuous-time models (stochastic calculus, martingales, Ito’s lemma, Black-Scholes model), Monte Carlo methods

• [exercises, in French] Financial mathematics (48h, 25 students),  Spring 2017, Master 1 ISIFAR, Université Paris Diderot

Interest rates, financial instruments, no-arbitrage assumption, discrete-time martingales, binomial model, no-arbitrage pricing, American options