David Evangelista

David Evangelista
Getúlio Vargas Foundation | FGV · School of Applied Mathematics "EMAp"

Post-Doctoral Researcher

About

16
Publications
3,092
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119
Citations
Introduction
David Evangelista is a Postdoctoral Researcher at the School of Applied Mathematics (EMAP) in FGV. David does research in Analysis and Applied Mathematics. His most recent publication is 'Optimal inventory management and order book modeling'.

Publications

Publications (16)
Preprint
Full-text available
In a fixed time horizon, appropriately executing a large amount of a particular asset -- meaning a considerable portion of the volume traded within this frame -- is challenging. Especially for illiquid or even highly liquid but also highly volatile ones, the role of "market quality" is quite relevant in properly designing execution strategies. Here...
Preprint
Full-text available
We propose two novel frameworks to study the price formation of an asset negotiated in an order book. Specifically, we develop a game-theoretic model in many-person games and mean-field games, considering costs stemming from limited liquidity. We derive analytical formulas for the formed price in terms of the realized order flow. We also identify a...
Article
A large proportion of market making models derive from the seminal model of Avellaneda and Stoikov. The numerical approximation of the value function and the optimal quotes in these models remains a challenge when the number of assets is large. In this article, we propose closed-form approximations for the value functions of many multi-asset extens...
Preprint
Full-text available
We investigate finite population games of optimal execution, taking place at a market with friction. The models over which we develop our results are akin to the standard Almgren-Chriss model with linear price impacts. On the one hand, at a temporary level, our perspective is rather similar to that of the aforementioned model. On the other hand, al...
Article
Full-text available
Mean-field games (MFGs) are models of large populations of rational agents who seek to optimize an objective function that takes into account their location and the distribution of the remaining agents. Here, we consider stationary MFGs with congestion and prove the existence of stationary solutions. Because moving in congested areas is difficult,...
Preprint
Full-text available
The job of market makers is to provide liquidity to other market participants. The main source of risk for market makers is holding inventory and the uncertainty of future price variation. In many cases, the market makers are in charge of a large range of assets. However, managing the risk in multiple asset cases is an important task. We propose in...
Article
Full-text available
We model the behavior of three agent classes acting dynamically in a limit order book of a financial asset. Namely, we consider market makers (MM), high-frequency trading (HFT) firms, and institutional brokers (IB). Given a prior dynamic of the order book, similar to the one considered in the Queue-Reactive models [14, 20, 21], the MM and the HFT d...
Preprint
We model the behavior of three agent classes acting dynamically in a limit order book of a financial asset. Namely, we consider market makers (MM), high-frequency trading (HFT) firms, and institutional brokers (IB). Given a prior dynamic of the order book, similar to the one considered in the Queue-Reactive models [14, 20, 21], the MM and the HFT d...
Presentation
Full-text available
Mean-field games (MFGs) are models for large populations of competing, rational agents that seek to optimize a suitable functional. In the case of congestion, this functional takes into account the difficulty of moving in high-density areas. In this talk, I will present a recent contribution on MFGs with congestion with power-like Hamiltonians. Our...
Article
Full-text available
Mean-field games (MFGs) are models for large populations of competing rational agents that seek to optimize a suitable functional. In the case of congestion, this functional takes into account the difficulty of moving in high-density areas. Here, we study stationary MFGs with congestion with quadratic or power-like Hamiltonians. First, using explic...
Preprint
Mean-field games (MFGs) are models for large populations of competing rational agents that seek to optimize a suitable functional. In the case of congestion, this functional takes into account the difficulty of moving in high-density areas. Here, we study stationary MFGs with congestion with quadratic or power-like Hamiltonians. First, using explic...
Preprint
Here, we study radial solutions for first- and second-order stationary Mean-Field Games (MFG) with congestion on $\mathbb{R}^d$. MFGs with congestion model problems where the agents' motion is hampered in high-density regions. The radial case, which is one of the simplest non one-dimensional MFG, is relatively tractable. As we observe in this paper...
Conference Paper
Full-text available
Here, we study radial solutions for first-and second-order stationary Mean-Field Games (MFG) with congestion on R^d. MFGs with congestion model problems where the agents' motion is hampered in high-density regions. The radial case, which is one of the simplest non one-dimensional MFG, is relatively tractable. As we observe in this paper, the Fokker...
Preprint
Mean-field games (MFGs) are models of large populations of rational agents who seek to optimize an objective function that takes into account their location and the distribution of the remaining agents. Here, we consider stationary MFGs with congestion and prove the existence of stationary solutions. Because moving in congested areas is difficult,...
Article
Full-text available
Here, we consider a regularized mean-field game model that features a low-order regularization. We prove the existence of solutions with positive density. To do so, we combine a priori estimates with the continuation method. Since low-order regularizations are easier to implement numerically, our methods give a theoretical foundation for their use.

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