Zobrazeno 1 - 10
of 4 477
pro vyhledávání: '"Garcin, A."'
Autor:
Angelini, Daniele, Garcin, Matthieu
The Fractional Stochastic Regularity Model (FSRM) is an extension of Black-Scholes model describing the multifractal nature of prices. It is based on a multifractional process with a random Hurst exponent $H_t$, driven by a fractional Ornstein-Uhlenb
Externí odkaz:
http://arxiv.org/abs/2409.07159
Starting from a basic model in which the dynamic of the transaction prices is a geometric Brownian motion disrupted by a microstructure white noise, corresponding to the random alternation of bids and asks, we propose moment-based estimators along wi
Externí odkaz:
http://arxiv.org/abs/2407.17401
Autonomous agents trained using deep reinforcement learning (RL) often lack the ability to successfully generalise to new environments, even when these environments share characteristics with the ones they have encountered during training. In this wo
Externí odkaz:
http://arxiv.org/abs/2402.03479
A key limitation preventing the wider adoption of autonomous agents trained via deep reinforcement learning (RL) is their limited ability to generalise to new environments, even when these share similar characteristics with environments encountered d
Externí odkaz:
http://arxiv.org/abs/2310.03494
Autor:
Brouty, Xavier, Garcin, Matthieu
Considering that both the entropy-based market information and the Hurst exponent are useful tools for determining whether the efficient market hypothesis holds for a given asset, we study the link between the two approaches. We thus provide a theore
Externí odkaz:
http://arxiv.org/abs/2306.13371
Autor:
Garcin, Matthieu
We are interested in the nonparametric estimation of the probability density of price returns, using the kernel approach. The output of the method heavily relies on the selection of a bandwidth parameter. Many selection methods have been proposed in
Externí odkaz:
http://arxiv.org/abs/2305.13123
Average-K classification is an alternative to top-K classification in which the number of labels returned varies with the ambiguity of the input image but must average to K over all the samples. A simple method to solve this task is to threshold the
Externí odkaz:
http://arxiv.org/abs/2303.18118
Autor:
Brouty, Xavier, Garcin, Matthieu
We determine the amount of information contained in a time series of price returns at a given time scale, by using a widespread tool of the information theory, namely the Shannon entropy, applied to a symbolic representation of this time series. By d
Externí odkaz:
http://arxiv.org/abs/2208.11976
Autor:
Ahmed, Ibrahim H., Brewitt, Cillian, Carlucho, Ignacio, Christianos, Filippos, Dunion, Mhairi, Fosong, Elliot, Garcin, Samuel, Guo, Shangmin, Gyevnar, Balint, McInroe, Trevor, Papoudakis, Georgios, Rahman, Arrasy, Schäfer, Lukas, Tamborski, Massimiliano, Vecchio, Giuseppe, Wang, Cheng, Albrecht, Stefano V.
The development of autonomous agents which can interact with other agents to accomplish a given task is a core area of research in artificial intelligence and machine learning. Towards this goal, the Autonomous Agents Research Group develops novel ma
Externí odkaz:
http://arxiv.org/abs/2208.01769
Autor:
Julius Jara‐Muñoz, Amotz Agnon, Jens Fohlmeister, Sara Tomás, Jürgen Mey, Norbert Frank, Birgit Schröder, Andrea Schröder‐Ritzrau, Yannick Garcin, Yaniv Darvasi, Daniel Melnick, Maria Mutti, Manfred R. Strecker
Publikováno v:
Geochemistry, Geophysics, Geosystems, Vol 25, Iss 8, Pp n/a-n/a (2024)
Abstract To date, the most complete paleolake‐level reconstructions for the late Pleistocene water bodies that once occupied the Dead Sea depression have been based on the combination of dating of lake sediments and terrestrial materials. However,
Externí odkaz:
https://doaj.org/article/3f4a3ce2156346e98b6be7976229e099
