Speaker: Prof. Piotr Fiszeder, Dept. Econ. & Stat., Nicolaus Copernicus Univ., Torun, Poland Abstract: Traditional volatility models do not work well when volatility changes rapidly and in the presence of outliers. Therefore, two lines of improvements have been developed separately in the existing literature. Range-based models benefit from efficient volatility estimates based on low and […]

Speaker: Jason Bailey, Dept. of Mathematics & Statistics, Texas Tech University Abstract:</abstract} Using data from 2000 through 2022, we analyze the predictive capability of the annual numbers of new home constructions and four available environmental, social, and governance (ESG) factors on the average annual price of homes sold in eight major U.S. cities. We contrast […]

Speaker: Prof. Aurelio Bariviera, Dept. of Business, Universitat Rovira i Virgili, Reus, Spain Abstract: This paper adopts a versatile conditional correlation approach to explore daily seasonality in the major cryptocurrencies. Given the lack of clear fundamental value in this market and the active online profile of investors, the study also relates cryptocurrency cross-correlations to online […]

Speaker:</strong? Dr. Christian Laudagé, Dept. Mathematics, RPTU Kaiserslautern-Landau Abstract: We revisit the recently introduced concept of return risk measures (RRMs). We extend it by allowing risk management via multiple so-called eligible assets. The resulting new risk measures are called multi-asset return risk measures (MARRMs). We analyze properties of these risk measures. In particular, we prove […]

Speaker: Prof. Eduardo Schwartz, Beedie School of Business, Simon Fraser Univ. Abstract: The increased impact of extreme weather events and draughts has prompted the rapid growth of the water market. This paper analyzes the optimal operation of a reservoir that generates electricity and manages the water by trading water rights. We extend the framework introduced […]

Speaker: Prof. Giuseppe Storti, Dept. Econ & Stat., University of Salerno, Fisciano, IT Abstract: This paper compares the accuracy of tail risk forecasts with a focus on including realized skewness and kurtosis in ”additive” and ”multiplicative” models. Utilizing a panel of 960 US stocks, we conduct diagnostic tests, employ scoring functions, and implement rolling window […]

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 […]