Speaker: Dr. Yossi Shvimer, Research Associate, School of Finance and Management, SOAS University of London Abstract: A novel hybrid option pricing model using a deep learning neural network has been developed. The hybrid model keeps the traditional option pricing model with the same input parameters while simultaneously adjusting the model with neural network methods to […]
Speaker: Prof Stylianos Perrakis, John Molson School of Business, Concordia Univ, Montreal Abstract: The stochastic dominance (SD) approach is applied to the valuation of index options in frictionless markets for a wide class of stochastic volatility (SV) processes. SD allows for the derivation of a unique, exponential option pricing kernel based on the physical underlying […]
Speaker: Dr. Kirill Golubnichiy, Dept of Math & Statistics, Texas Tech University Abstract: We present a new heuristic mathematical model for accurate forecasting of prices of stock options for 1-2 trading days ahead of the present one. This new technique uses the Black-Scholes equation supplied by new intervals for the underlying stock and new initial […]
Speaker: Prof. Aihua (Eva) Zhang, College of Science, Math & Tech., Wenzhou-Kean University, Wenzhou China Abstract: In order to obtain the optimal portfolio strategy maximizing the accumulated terminal wealth with transaction costs, in this paper, we propose a new prediction-based portfolio method combining with a long short-term memory (in short, LSTM) network which is an […]
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. […]
