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20182024
most citedConditionally Elicitable Dynamic Risk Measures for Deep Reinforcement Learning

2 citations · 3 across the 5 of their papers we have counts for

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7 papers · 1 filter

q-fin.TR2024

Nash Equilibrium between Brokers and Traders

Álvaro Cartea, Sebastian Jaimungal, Leandro Sánchez-Betancourt

We study the perfect information Nash equilibrium between a broker and her clients -- an informed trader and an uniformed trader. In our model, the broker trades in the lit exchang…

q-fin.TR2023

Decentralised Finance and Automated Market Making: Execution and Speculation

Álvaro Cartea, Fayçal Drissi, Marcello Monga

Automated market makers (AMMs) are a new prototype of decentralised exchanges which are revolutionising market interactions. The majority of AMMs are constant product markets (CPMs…

q-fin.TR2023

Optimal execution and speculation with trade signals

Peter Bank, Álvaro Cartea, Laura Körber

We propose a price impact model where changes in prices are purely driven by the order flow in the market. The stochastic price impact of market orders and the arrival rates of lim…

q-fin.TR2020

Trading Foreign Exchange Triplets

Álvaro Cartea, Sebastian Jaimungal, Tianyi Jia

We develop the optimal trading strategy for a foreign exchange (FX) broker who must liquidate a large position in an illiquid currency pair. To maximize revenues, the broker consid…

q-fin.TR2019

Latency and Liquidity Risk

Álvaro Cartea, Sebastian Jaimungal, Leandro Sánchez-Betancourt

Latency (i.e., time delay) in electronic markets affects the efficacy of liquidity taking strategies. During the time liquidity takers process information and send marketable limit…

q-fin.TR2018

Trading Cointegrated Assets with Price Impact

Alvaro Cartea, Luhui Gan, Sebastian Jaimungal

Executing a basket of co-integrated assets is an important task facing investors. Here, we show how to do this accounting for the informational advantage gained from assets within…