Speaker: Assoc. Prof. Malick Fall, Center for Research in Economics and Management, Univ. of Rennes, Fr. Abstract: The expected return and covariance matrix are commonly calculated on a calendar time scale (e.g. daily or monthly data). In this article, we assess the relevance of calculating them on a new time scale derived from traded volume. […]
Speaker: Prof. Miloš Kopa, Dept. Probability & Mathematics, Charles University, Prague Abstract: Stochastic dominance rules are well-characterized and widely used. This work aims to describe and better understand the situations when they do not hold by developing measures of stochastic non-dominance. They quantify the error caused by assuming that one random variable dominates another one […]
Speaker: Prof. Dr. Dirk Soehnholz, CEO: Soehnholz ESG GmbH and Soehnholz Asset Management GmbH; Prof. of Asset Management, Leipzig University Abstract: Responsible investments are booming, but criticism has been growing, too. I start by outlining the different dimensions and characteristics of responsible investments. I also describe a free tool to develop bespoke, responsible investment policies […]
Speaker: Prof. Álvaro Guinea Julia, Dept. Industrial Org., Comillas Pontifical University ICADE-ICAI, Madrid Abstract: This work introduces a new stochastic volatility model with delay parameters in the volatility process, extending the Barndorff–Nielsen and Shephard model. It establishes an analytical expression for the log price characteristic function, which can be applied to price European options. Empirical […]
Speaker: Dr. Hirbod Assa, Founding team | Quantitative researcher, Edge Technologies; Director and founder, Model Library Ltd. Abstract: In this paper, we utilize data from the IPCC to develop a predictive model for the Palmer Drought Severity Index (PDSI). Our approach involves a two-step modeling process: initially applying a random forest regression, followed by a […]
Speaker: Prof. Riza Demirer, Dept. Economics & Finance, School of Business, Southern Illinois University, Edwardsville, IL Abstract: Recent years have seen that institutional investors simultaneously crowd in (buy) the ESG stock market. The aim of this study is to investigate the underlying motivations and their economic consequences. The empirical results are consistent with the hypothesis […]
Speaker: Prof. Maciej Augustyniak, Dept. of Mathematics & Statistics, University of Montreal Abstract: Basis risk arises when hedging a financial derivative with an instrument different from its underlying asset. This risk can significantly impair hedging effectiveness and must therefore be properly managed. This article develops a discrete-time hedging framework for European-style derivatives that explicitly accounts […]
Speaker: Prof. Elisa Alos, Dept. of Economics and Business, University of Pompeu Fabra, Barcelona Abstract: We introduce the main tools of Malliavin calculus and show how to use them to study the short-end behavior of skew and curvature of the implied volatility surface. This methodology allows us to obtain general formulas in terms of Malliavin […]
Speaker: Dr. Jean-Phillipe Aguilar, Head of Pricing Models Audit, Societe Generale, Paris La Defense Abstract:Stochastic Volatility Jump Diffusion (SVJ) models combine the advantages of both stochastic volatility and jump models, while addressing some of their well-known limitations; moreover, they often calibrate well in equity and FX markets. In this talk we will focus on a […]
Speaker: Prof. Marta Malecka, Dept. of Statistical Methods, Univ. of Lodz, Lodz, Poland Abstract: The reformed Basel framework has left value at risk (VaR) as a basic tool of validating risk models. Within this framework, VaR independence tests have been regarded as critical to ensuring stability during periods of financial turmoil. However, until now, there […]
Speaker: Dr. Alejandro Rodriguez Dominguez, Director of Quantitative Analysis and Artificial Intelligence, Miralta Finance Bank, Madrid. Abstract: We introduce a novel framework for portfolio construction, covering both selection and optimization, based entirely on ensemble learning theory. A portfolio is modelled as an ensemble in a multi-hypothesis prediction setting, with each constituent (base learner) focused on […]