Zobrazeno 1 - 10
of 105
pro vyhledávání: '"Saporito, Yuri"'
Phylogenetic trees constitute an interesting class of objects for stochastic processes due to the non-standard nature of the space they inhabit. In particular, many statistical applications require the construction of Markov processes on the space of
Externí odkaz:
http://arxiv.org/abs/2410.17919
Instrumental variables (IVs) provide a powerful strategy for identifying causal effects in the presence of unobservable confounders. Within the nonparametric setting (NPIV), recent methods have been based on nonlinear generalizations of Two-Stage Lea
Externí odkaz:
http://arxiv.org/abs/2402.05639
We define and develop an approach for risk budgeting allocation - a risk diversification portfolio strategy - where risk is measured using a dynamic time-consistent risk measure. For this, we introduce a notion of dynamic risk contributions that gene
Externí odkaz:
http://arxiv.org/abs/2305.11319
This article explores the optimisation of trading strategies in Constant Function Market Makers (CFMMs) and centralised exchanges. We develop a model that accounts for the interaction between these two markets, estimating the conditional dependence b
Externí odkaz:
http://arxiv.org/abs/2304.02180
Modeling social interactions is a challenging task that requires flexible frameworks. For instance, dissimulation and externalities are relevant features influencing such systems -- elements that are often neglected in popular models. This paper is d
Externí odkaz:
http://arxiv.org/abs/2210.15712
Autor:
Fonseca, Yuri R., Saporito, Yuri F.
Inverse problems are paramount in Science and Engineering. In this paper, we consider the setup of Statistical Inverse Problem (SIP) and demonstrate how Stochastic Gradient Descent (SGD) algorithms can be used in the linear SIP setting. We provide co
Externí odkaz:
http://arxiv.org/abs/2209.14967
This paper proposes a classification model for predicting the main activity of bitcoin addresses based on their balances. Since the balances are functions of time, we apply methods from functional data analysis; more specifically, the features of the
Externí odkaz:
http://arxiv.org/abs/2202.12019
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 der
Externí odkaz:
http://arxiv.org/abs/2202.11416
Trading frictions are stochastic. They are, moreover, in many instances fast-mean reverting. Here, we study how to optimally trade in a market with stochastic price impact and study approximations to the resulting optimal control problem using singul
Externí odkaz:
http://arxiv.org/abs/2101.10053
Autor:
Ludkovski, Mike, Saporito, Yuri
We investigate a machine learning approach to option Greeks approximation based on Gaussian process (GP) surrogates. The method takes in noisily observed option prices, fits a nonparametric input-output map and then analytically differentiates the la
Externí odkaz:
http://arxiv.org/abs/2010.08407