Zobrazeno 1 - 10
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pro vyhledávání: '"Tegnér, Martin"'
The Gaussian Process Convolution Model (GPCM; Tobar et al., 2015a) is a model for signals with complex spectral structure. A significant limitation of the GPCM is that it assumes a rapidly decaying spectrum: it can only model smooth signals. Moreover
Externí odkaz:
http://arxiv.org/abs/2203.06997
Autor:
Tegner, Martin, Roberts, Stephen
Local volatility is a versatile option pricing model due to its state dependent diffusion coefficient. Calibration is, however, non-trivial as it involves both proposing a hypothesis model of the latent function and a method for fitting it to data. I
Externí odkaz:
http://arxiv.org/abs/2112.03718
This paper advocates privacy preserving requirements on collection of user data for recommender systems. The purpose of our study is twofold. First, we ask if restrictions on data collection will hurt test quality of RNN-based recommendations. We stu
Externí odkaz:
http://arxiv.org/abs/2106.11218
Consider the empirical measure, $\hat{\mathbb{P}}_N$, associated to $N$ i.i.d. samples of a given probability distribution $\mathbb{P}$ on the unit interval. For fixed $\mathbb{P}$ the Wasserstein distance between $\hat{\mathbb{P}}_N$ and $\mathbb{P}
Externí odkaz:
http://arxiv.org/abs/1907.02006
The non-storability of electricity makes it unique among commodity assets, and it is an important driver of its price behaviour in secondary financial markets. The instantaneous and continuous matching of power supply with demand is a key factor expl
Externí odkaz:
http://arxiv.org/abs/1903.09536
Autor:
Tegnér, Martin, Roberts, Stephen
The local volatility model is a widely used for pricing and hedging financial derivatives. While its main appeal is its capability of reproducing any given surface of observed option prices---it provides a perfect fit---the essential component is a l
Externí odkaz:
http://arxiv.org/abs/1901.06021
We consider the problem of inferring a latent function in a probabilistic model of data. When dependencies of the latent function are specified by a Gaussian process and the data likelihood is complex, efficient computation often involve Markov chain
Externí odkaz:
http://arxiv.org/abs/1807.04932
Autor:
Cohen, Samuel N., Tegnér, Martin
We consider stochastic volatility models under parameter uncertainty and investigate how model derived prices of European options are affected. We let the pricing parameters evolve dynamically in time within a specified region, and formalise the prob
Externí odkaz:
http://arxiv.org/abs/1807.03882
Publikováno v:
In Energy Economics October 2017 68:490-514
Publikováno v:
In Energy Economics October 2017 68:423-439