BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Mathematical Finance - ECPv5.7.0//NONSGML v1.0//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-WR-CALNAME:Mathematical Finance X-ORIGINAL-URL:https://www.math.ttu.edu/mathematicalfinance X-WR-CALDESC:Events for Mathematical Finance BEGIN:VTIMEZONE TZID:America/Chicago BEGIN:DAYLIGHT TZOFFSETFROM:-0600 TZOFFSETTO:-0500 TZNAME:CDT DTSTART:20240310T080000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0500 TZOFFSETTO:-0600 TZNAME:CST DTSTART:20241103T070000 END:STANDARD BEGIN:DAYLIGHT TZOFFSETFROM:-0600 TZOFFSETTO:-0500 TZNAME:CDT DTSTART:20250309T080000 END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0500 TZOFFSETTO:-0600 TZNAME:CST DTSTART:20251102T070000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTART;TZID=America/Chicago:20240126T120000 DTEND;TZID=America/Chicago:20240126T130000 DTSTAMP:20260429T044846 CREATED:20231114T173732Z LAST-MODIFIED:20231115T151421Z UID:1214-1706270400-1706274000@www.math.ttu.edu SUMMARY:On subordinated generalizations of 3 classical models of option pricing DESCRIPTION:Speaker: Dr. Grzegorz Krzyżanowski\, Hugo Steinhaus Center\, Faculty of Pure and Applied Mathematics\, Wroclaw University of Science and Technology \nAbstract: We will investigate the relation between Bachelier and Black-Scholes models driven by the infinitely divisible inverse subordinators. Such models\, in contrast to their classical equivalents\, can be used in markets where periods of stagnation are observed. We will introduce the subordinated Cox-Ross-Rubinstein model and prove that the price of the underlying in that model converges in distribution and in Skorokhod space to the price of underlying in the subordinated Black-Scholes model. Motivated by this fact we will price the selected option contracts using the binomial trees. The comparison to other numerical methods will be provided. URL:https://www.math.ttu.edu/mathematicalfinance/event/on-subordinated-generalizations-of-3-classical-models-of-option-pricing/ LOCATION:via Zoom CATEGORIES:Seminars,Spring 2024 ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2023/11/gk-scaled.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20240209T140000 DTEND;TZID=America/Chicago:20240209T150000 DTSTAMP:20260429T044846 CREATED:20230809T162110Z LAST-MODIFIED:20231128T225520Z UID:1140-1707487200-1707490800@www.math.ttu.edu SUMMARY:Good for the Planet\, Good for the Wallet: The ESG Impact on Financial Performance in India DESCRIPTION:Speaker: Prof. Tauhidul Islam Tanin\, EGADE Business School\, Technologico de Monterrey \nAbstract: We examine the impact of ESG practices on financial performance among Nifty 50 companies in India from 2015 to 2022. Utilizing fixed-effects panel quantile regression\, we observe that the relationship between ESG practices and financial profitability varies across the ROE distribution. While the environmental pillar score and the governance pillar score negatively impact ROE across almost all quantiles with high statistical significance\, the social pillar score exhibits mostly an insignificant relationship. Its impact is negative\, but only mildly statistically significant at the lower end of the ROE distribution. The findings and their implications are important for investors\, corporate executives\, and policymakers. URL:https://www.math.ttu.edu/mathematicalfinance/event/good-for-the-planet-good-for-the-wallet-the-esg-impact-on-financial-performance-in-india/ LOCATION:Department of Mathematics & Statistics\, TTU CATEGORIES:Seminars,Spring 2024 ATTACH;FMTTYPE=image/png:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2023/08/Tauhidul-Islam-TANIN.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20240216T120000 DTEND;TZID=America/Chicago:20240216T130000 DTSTAMP:20260429T044846 CREATED:20231114T173843Z LAST-MODIFIED:20231116T214834Z UID:1217-1708084800-1708088400@www.math.ttu.edu SUMMARY:On the implied volatility of European and Asian call options under the stochastic volatility Bachelier model DESCRIPTION:Speaker: Makar Pravosud\, Department of Economics and Business\, Universitat Pompeu Fabra \nAbstract: In this paper we study the short-time behavior of the at-the-money implied volatility for European and arithmetic Asian call options with fixed strike price. The asset price is assumed to follow the Bachelier model with a general stochastic volatility process. Using techniques of the Malliavin calculus such as the anticipating Itô’s formula we first compute the level of the implied volatility when the maturity converges to zero. Then\, we find a short maturity asymptotic formula for the skew of the implied volatility that depends on the roughness of the volatility model. We apply our general results to the SABR and fractional Bergomi models\, and provide some numerical simulations that confirm the accurateness of the asymptotic formula for the skew. URL:https://www.math.ttu.edu/mathematicalfinance/event/on-the-implied-volatility-of-european-and-asian-call-options-under-the-stochastic-volatility-bachelier-model/ LOCATION:via Zoom CATEGORIES:Seminars,Spring 2024 ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2023/11/Pravosud-1.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20240223T140000 DTEND;TZID=America/Chicago:20240223T150000 DTSTAMP:20260429T044846 CREATED:20231114T173948Z LAST-MODIFIED:20231115T145502Z UID:1220-1708696800-1708700400@www.math.ttu.edu SUMMARY:Unpacking the ESG ratings: Does one size fit all? DESCRIPTION:Speaker: Prof. Monica Billio\, Department of Economics\, Ca’ Foscari University of Venice \nAbstract: As ESG investing goes mainstream\, investors increasingly rely on ESG ratings when making investment decisions. This study aims to delve into the overall ESG ratings provided by four prominent ESG data providers\, focusing on their accounting methodologies\, the relevance of the three pillars (environment\, social\, and governance)\, and the key performance indicators (KPIs) that drive these ratings. By examining a sample of European and UK companies\, we question the significance of the governance and social pillars in explaining the overall ESG scores. Our findings highlight a subset of indicators that exhibit the highest correlation with ESG scores\, including the presence of external audits\, an environmental supply chain policy\, and target emissions. This letter contributes to the ongoing ESG credibility debate and emphasizes the need for further transparency of ESG ratings. URL:https://www.math.ttu.edu/mathematicalfinance/event/unpacking-the-esg-ratings-does-one-size-fit-all/ LOCATION:via Zoom CATEGORIES:Seminars,Spring 2024 ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2023/11/billio.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20240308T140000 DTEND;TZID=America/Chicago:20240308T150000 DTSTAMP:20260429T044846 CREATED:20231127T155729Z LAST-MODIFIED:20231212T162216Z UID:1259-1709906400-1709910000@www.math.ttu.edu SUMMARY:On the Bachelier implied volatility at extreme strikes DESCRIPTION:Speaker: Dr. Fabien Le Floc’h\, Nasdsaq\n\nAbstract: Roger Lee proved that the Black-Scholes implied variance can not grow faster than linearly in log-moneyness. This paper investigates what happens in the Bachelier (or Normal) implied volatility world\, making sure to cover the various aspects of vanilla option arbitrages. URL:https://www.math.ttu.edu/mathematicalfinance/event/on-the-bachelier-implied-volatility-at-extreme-strikes/ LOCATION:via Zoom CATEGORIES:Seminars,Spring 2024 ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2023/12/lefloch.jpg END:VEVENT BEGIN:VEVENT DTSTART;VALUE=DATE:20240315 DTEND;VALUE=DATE:20240316 DTSTAMP:20260429T044846 CREATED:20231115T152205Z LAST-MODIFIED:20231115T152205Z UID:1238-1710460800-1710547199@www.math.ttu.edu SUMMARY:No Seminar - Spring Break DESCRIPTION: URL:https://www.math.ttu.edu/mathematicalfinance/event/no-seminar-spring-break/ CATEGORIES:Seminars,Spring 2024 ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2023/01/unhappy.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20240318T120000 DTEND;TZID=America/Chicago:20240318T130000 DTSTAMP:20260429T044846 CREATED:20231122T185234Z LAST-MODIFIED:20231122T185234Z UID:1256-1710763200-1710766800@www.math.ttu.edu SUMMARY:Bayesian Optimization of ESG Financial Investments DESCRIPTION:Speaker: Prof Eduardo César Garrido Merchán\, Faculty of Economics and Business Sciences\, Comillas Universidad Pontificia \nAbstract: Financial experts and analysts seek to predict the variability of financial markets. In particular\, the correct prediction of this variability ensures investors successful investments. However\, there has been a big trend in finance in the last years\, which are the ESG criteria. Concretely\, ESG (Economic\, Social and Governance) criteria have become more significant in finance due to the growing importance of investments being socially responsible\, and because of the financial impact companies suffer when not complying with them. Consequently\, creating a stock portfolio should not only take into account its performance but compliance with ESG criteria. Hence\, this paper combines mathematical modelling\, with ESG and finance. In more detail\, we use Bayesian optimization (BO)\, a sequential state-of-the-art design strategy to optimize black-boxes with unknown analytical and costly-to compute expressions\, to maximize the performance of a stock portfolio under the presence of ESG criteria soft constraints incorporated to the objective function. In an illustrative experiment\, we use the Sharpe ratio\, that takes into consideration the portfolio returns and its variance\, in other words\, it balances the trade-off between maximizing returns and minimizing risks. In the present work\, ESG criteria have been divided into fourteen independent categories used in a linear combination to estimate a firm total ESG score. Most importantly\, our presented approach would scale to alternative black-box methods of estimating the performance and ESG compliance of the stock portfolio. In particular\, this research has opened the door to many new research lines\, as it has proved that a portfolio can be optimized using a BO that takes into consideration financial performance and the accomplishment of ESG criteria. URL:https://www.math.ttu.edu/mathematicalfinance/event/bayesian-optimization-of-esg-financial-investments/ LOCATION:via Zoom CATEGORIES:Seminars,Spring 2024 ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2023/11/merchan.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20240412T140000 DTEND;TZID=America/Chicago:20240412T150000 DTSTAMP:20260429T044846 CREATED:20231114T173107Z LAST-MODIFIED:20240305T220124Z UID:1209-1712930400-1712934000@www.math.ttu.edu SUMMARY:Supermartingale Brenier's Theorem with full-marginals constraint DESCRIPTION:Speaker: Prof. Dominykas Norgilas\, Department of Mathematics\, North Carolina State University \nAbstract: We explicitly construct the supermartingale version of the Fréchet-Hoeffding coupling in the setting with infinitely many marginal constraints. This extends the results of Henry-Labordere et al. obtained in the martingale setting. Our construction is based on the Markovian iteration of one-period optimal supermartingale couplings. In the limit\, as the number of iterations goes to infinity\, we obtain a pure jump process that belongs to a family of local Lévy models introduced by Carr et al. We show that the constructed processes solve the continuous-time supermartingale optimal transport problem for a particular family of path-dependent cost functions. The explicit computations are provided in the following three cases: the uniform case\, the Bachelier model and the Geometric Brownian Motion case. URL:https://www.math.ttu.edu/mathematicalfinance/event/supermartingale-breniers-theorem-with-full-marginals-constraint/ LOCATION:via Zoom CATEGORIES:Seminars,Spring 2024 ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2023/11/norgilas-1.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20240419T120000 DTEND;TZID=America/Chicago:20240419T130000 DTSTAMP:20260429T044846 CREATED:20231129T190232Z LAST-MODIFIED:20231130T170131Z UID:1263-1713528000-1713531600@www.math.ttu.edu SUMMARY:Semi-analytic pricing of American options in some time-dependent jump-diffusion models DESCRIPTION:Speaker: Prof. Andrey Itkin\, Department of Risk and Financial Engineering\, Tandon School of Engineering\, NYU \nAbstract: In this paper we propose a semi-analytic approach to pricing American options for some time-dependent jump-diffusions models. The idea of the method is to further generalize our approach developed for pricing barrier\, [Itkin et al.\, 2021]\, and American\, [Carr and Itkin\, 2021; Itkin and Muravey\, 2023]\, options in various time-dependent one factor and even stochastic volatility models. Our approach i) allows arbitrary dependencies of the model parameters on time; ii) reduces solution of the pricing problem for American options to a simpler problem of solving an algebraic nonlinear equation for the exercise boundary and a linear Fredholm-Volterra equation for the the option price; iii) the options Greeks solve a similar Fredholm-Volterra linear equation obtained by just differentiating Eq. (25) by the required parameter. URL:https://www.math.ttu.edu/mathematicalfinance/event/semi-analytic-pricing-of-american-options-in-some-time-dependent-jump-diffusion-models/ LOCATION:via Zoom CATEGORIES:Seminars,Spring 2024 ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2023/11/itkin.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20240419T140000 DTEND;TZID=America/Chicago:20240419T140000 DTSTAMP:20260429T044846 CREATED:20231115T154042Z LAST-MODIFIED:20240408T172908Z UID:1241-1713535200-1713535200@www.math.ttu.edu SUMMARY:Portfolio selection under non-gaussianity and systemic risk: A machine learning based forecasting approach DESCRIPTION:Speaker: Prof. Abderrahim Taamouti\, Management School\, University of Liverpool \nAbstract: The Sharpe-ratio-maximizing portfolio becomes questionable under non-Gaussian returns\, and it rules out\, by construction\, systemic risk\, which can negatively affect its out-of-sample performance. In the present work\, we develop a new performance ratio that simultaneously addresses these two problems when building optimal portfolios. To robustify the portfolio optimization and better represent extreme market scenarios\, we simulate a large number of returns via a Monte Carlo method. This is done by obtaining probabilistic return forecasts through a distributional machine learning approach in a big data setting and then combining them with a fitted copula to generate return scenarios. Based on a large-scale comparative analysis conducted on the US market\, the backtesting results demonstrate the superiority of our proposed portfolio selection approach against several popular benchmark strategies in terms of both profitability and minimizing systemic risk. This outperformance is robust to the inclusion of transaction costs. URL:https://www.math.ttu.edu/mathematicalfinance/event/portfolio-selection-under-non-gaussianity-and-systemic-risk-a-machine-learning-based-forecasting-approach/ LOCATION:via Zoom CATEGORIES:Seminars,Spring 2024 ATTACH;FMTTYPE=image/png:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2023/11/taamouti.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20240426T120000 DTEND;TZID=America/Chicago:20240426T130000 DTSTAMP:20260429T044846 CREATED:20231212T161814Z LAST-MODIFIED:20231212T161836Z UID:1278-1714132800-1714136400@www.math.ttu.edu SUMMARY:Hedging with temporary price impact DESCRIPTION:Speaker: Prof. Peter Bank\, Department of Mathematics\, Technical University of Berlin \nAbstract: We consider the problem of hedging a European contingent claim in a Bachelier model with temporary price impact as proposed by Almgren and Chriss (J Risk 3:5–39\, 2001). Following the approach of Rogers and Singh (Math Financ 20:597–615\, 2010) and Naujokat and Westray (Math Financ Econ 4(4):299–335\, 2011)\, the hedging problem can be regarded as a cost optimal tracking problem of the frictionless hedging strategy. We solve this problem explicitly for general predictable target hedging strategies. It turns out that\, rather than towards the current target position\, the optimal policy trades towards a weighted average of expected future target positions. This generalizes an observation of Gârleanu and Pedersen (Dynamic portfolio choice with frictions. Preprint\, 2013b) from their homogenous Markovian optimal investment problem to a general hedging problem. Our findings complement a number of previous studies in the literature on optimal strategies in illiquid markets as\, e.g.\, Gârleanu and Pedersen (Dynamic portfolio choice with frictions. Preprint\, 2013b)\, Naujokat and Westray (Math Financ Econ 4(4):299–335\, 2011)\, Rogers and Singh (Math Financ 20:597–615\, 2010)\, Almgren and Li (Option hedging with smooth market impact. Preprint\, 2015)\, Moreau et al. (Math Financ. doi:10.1111/mafi.12098\, 2015)\, Kallsen and Muhle-Karbe (High-resilience limits of block-shaped order books. Preprint\, 2014)\, Guasoni and Weber (Mathematical Financ. doi:10.1111/mafi.12099\, 2015a; Nonlinear price impact and portfolio choice. Preprint\, 2015b)\, where the frictionless hedging strategy is confined to diffusions. The consideration of general predictable reference strategies is made possible by the use of a convex analysis approach instead of the more common dynamic programming methods. URL:https://www.math.ttu.edu/mathematicalfinance/event/hedging-with-temporary-price-impact/ LOCATION:via Zoom CATEGORIES:Seminars,Spring 2024 ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2023/12/bank.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20240501T080000 DTEND;TZID=America/Chicago:20240501T170000 DTSTAMP:20260429T044846 CREATED:20240501T160730Z LAST-MODIFIED:20240501T160730Z UID:1401-1714550400-1714582800@www.math.ttu.edu SUMMARY:Gold-backed cryptocurrencies: A hedging tool against categorical and regional financial stress DESCRIPTION:Speaker: Prof. Md. Rayfayet Alam\, Dept. of Finance and Economics\, University of Tennessee at Chattanooga \nAbstract: This study evaluates the potential of gold-backed cryptocurrencies\, such as Tether Gold and PAX Gold\, as a hedge and safe haven against global\, regional\, and categorical financial stresses. Hedge and safe haven properties of gold-backed cryptocurrencies are also compared with those of gold and Bitcoin. For the analyses\, dynamic conditional correlation (DCC) and quantile coherency techniques are applied to daily data from February 2020 to March 2023. The results show that Tether Gold and PAX Gold are strong safe havens against the US and equity-valuation-related financial stress but weak safe havens against global financial stress. Tether Gold is a weak safe haven against credit-related financial stress as well. Tether Gold is a strong hedge against US financial stress but a weak hedge against aggregate financial stress of developed economies and that of emerging economies. In our sample\, gold-backed cryptocurrencies usually outperform gold and Bitcoin as a hedge and safe haven against financial stresses. The Quantile coherency analysis shows that Tether Gold is a hedge against low to moderate financial stress and a safe haven against extreme financial stresses. These findings have important implications for investors\, risk-managers and policy makers. URL:https://www.math.ttu.edu/mathematicalfinance/event/gold-backed-cryptocurrencies-a-hedging-tool-against-categorical-and-regional-financial-stress/ LOCATION:via Zoom CATEGORIES:Fall 2024,Seminars END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20240503T120000 DTEND;TZID=America/Chicago:20240503T130000 DTSTAMP:20260429T044846 CREATED:20231114T174101Z LAST-MODIFIED:20240408T172725Z UID:1223-1714737600-1714741200@www.math.ttu.edu SUMMARY:Elementary function solutions to the Bachelier model generated by Lie point symmetries DESCRIPTION:Speaker: Dr. Evangelos Melas\, Department of Mathematics\, University of Thessaly \nAbstract: Under the recent negative interest rate situation\, the Bachelier model has been attracting attention and adopted for evaluating the price of interest rate options. In this paper we find the Lie point symmetries of the Bachelier partial differential equation (PDE) and use them in order to generate new classes of denumerably infinite elementary function solutions to the Bachelier model from elementary function solutions to it\, which we derived in a previous publication. URL:https://www.math.ttu.edu/mathematicalfinance/event/elementary-functions-solutions-to-the-bachelier-model-generated-by-lie-point-symmetries/ LOCATION:via Zoom CATEGORIES:Seminars,Spring 2024 ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2023/11/melas.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20240823T140000 DTEND;TZID=America/Chicago:20240823T150000 DTSTAMP:20260429T044846 CREATED:20240430T211647Z LAST-MODIFIED:20240430T211647Z UID:1374-1724421600-1724425200@www.math.ttu.edu SUMMARY:Quanto Option Pricing on a Multivariate Lévy Process Model with Generative Artificial Intelligence DESCRIPTION:Speaker: Prof. Aaron YS Kim\, College of Business\, Stony Brook University \nAbstract: In this study\, we discuss a machine learning technique to price exotic options with two underlying assets based on a non-Gaussian Levy process model. We introduce a new multivariate Levy process model named the generalized normal tempered stable (gNTS) process\, which is defined by time-changed multivariate Brownian motion. Since the gNTS process does not provide a simple analytic formula for the probability density function (PDF)\, we use the conditional real-valued non-volume preserving (CRealNVP) model\, which is a type of flow-based generative network. Then\, we discuss the no-arbitrage pricing on the gNTS model for pricing the quanto option whose underlying assets consist of a foreign index and foreign exchange rate. We present the training of the CRealNVP model to learn the PDF of the gNTS process using a training set generated by Monte Carlo simulation. Next\, we estimate the parameters of the gNTS model with the trained CRealNVP model using the empirical data observed in the market. Finally\, we provide a method to find an equivalent martingale measure on the gNTS model and to price the quanto option using the CRealNVP model with the risk-neutral parameters of the gNTS model. URL:https://www.math.ttu.edu/mathematicalfinance/event/quanto-option-pricing-on-a-multivariate-levy-process-model-with-generative-artificial-intelligence/ LOCATION:via Zoom CATEGORIES:Fall 2024,Seminars ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2024/04/youngskim.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20240830T140000 DTEND;TZID=America/Chicago:20240830T150000 DTSTAMP:20260429T044846 CREATED:20240501T161202Z LAST-MODIFIED:20240501T161202Z UID:1404-1725026400-1725030000@www.math.ttu.edu SUMMARY:Gold-backed cryptocurrencies: A hedging tool against categorical and regional financial stress DESCRIPTION:Speaker: Prof. Md. Rayfayet Alam\, Dept. of Finance and Economics\, University of Tennessee at Chattanooga \nAbstract: This study evaluates the potential of gold-backed cryptocurrencies\, such as Tether Gold and PAX Gold\, as a hedge and safe haven against global\, regional\, and categorical financial stresses. Hedge and safe haven properties of gold-backed cryptocurrencies are also compared with those of gold and Bitcoin. For the analyses\, dynamic conditional correlation (DCC) and quantile coherency techniques are applied to daily data from February 2020 to March 2023. The results show that Tether Gold and PAX Gold are strong safe havens against the US and equity-valuation-related financial stress but weak safe havens against global financial stress. Tether Gold is a weak safe haven against credit-related financial stress as well. Tether Gold is a strong hedge against US financial stress but a weak hedge against aggregate financial stress of developed economies and that of emerging economies. In our sample\, gold-backed cryptocurrencies usually outperform gold and Bitcoin as a hedge and safe haven against financial stresses. The Quantile coherency analysis shows that Tether Gold is a hedge against low to moderate financial stress and a safe haven against extreme financial stresses. These findings have important implications for investors\, risk-managers and policy makers. URL:https://www.math.ttu.edu/mathematicalfinance/event/gold-backed-cryptocurrencies-a-hedging-tool-against-categorical-and-regional-financial-stress-2/ LOCATION:via Zoom CATEGORIES:Fall 2024,Seminars ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2024/05/alam-scaled.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20240913T140000 DTEND;TZID=America/Chicago:20240913T150000 DTSTAMP:20260429T044846 CREATED:20240729T183816Z LAST-MODIFIED:20240729T195839Z UID:1488-1726236000-1726239600@www.math.ttu.edu SUMMARY:Optimal Portfolios with Sustainable Assets - Aspects for Life Insurers DESCRIPTION:Speaker: Prof. Ralf Korn\, Dept. of Mathematics\, RPTU Kaiserslautern-Landau\nAbstract: Since August 2022 customers have to be asked if they are interested in sustainable investment when entering a pension contract. Hence\, the provider has to be prepared to offer suitable investment opportunities. Further\, the provider has to manage the new risks and chances of those assets in the whole portfolio. We therefore especially look at possible consequences for optimal portfolio decisions of a life insurer and suggest modeling approaches for the evolution of the demand and the sustainability ratings for sustainable assets. We will solve various portfolio problems under sustainability constraints explicitly and suggest further research topics. As a special feature for a life insurer\, we particularly look at the role of the actuarial reserve fund and the annual declaration of its return. URL:https://www.math.ttu.edu/mathematicalfinance/event/optimal-portfolios-with-sustainable-assets-aspects-for-life-insurers/ LOCATION:via Zoom CATEGORIES:Fall 2024,Seminars ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2024/07/Ralf_Korn.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20240920T120000 DTEND;TZID=America/Chicago:20240920T130000 DTSTAMP:20260429T044846 CREATED:20240430T213543Z LAST-MODIFIED:20240508T155354Z UID:1385-1726833600-1726837200@www.math.ttu.edu SUMMARY:To hedge or not to hedge? Cryptocurrencies\, gold and oil against stock market risk DESCRIPTION:Speaker: Prof. Agata Kliber\, Dept of Applied Mathematics\, Poznan University of Economics & Business\nco-Authors: Prof. Krzysztof Echaust\, Dept. of Operations Research & Mathematical Economics\, Poznan University of Economics & Business\nProf. Małgorzata Just\, Dept. of Finance & Accounting\, Poznan University of Life Sciences \nAbstract: The article aims to determine whether any hedging strategy against stock market risk\, performed using instruments popular in the literature (gold\, cryptocurrencies and oil)\, can beat index futures. As a hedging strategy\, we understand a pair-wise portfolio consisting of a long position in stocks and a short position in a hedging instrument put together to minimise the portfolio variance. As a benchmark\, we analyse optimal and naive hedging strategies with futures contracts. We demonstrate that\, regardless of the stock market\, the best hedging strategy focused on variance minimisation requires using index futures. Both strategies: the optimisation-based one and the naive one\, beat the dynamic strategies utilising the remaining hedging assets. Therefore\, from a risk-minimisation point of view\, investors have no motivation to implement cryptocurrencies\, gold or oil in hedging strategy against stock market risk. The results are robust with respect to hedging against tail risk. URL:https://www.math.ttu.edu/mathematicalfinance/event/to-hedge-or-not-to-hedge-cryptocurrencies-gold-and-oil-against-stock-market-risk/ LOCATION:via Zoom CATEGORIES:Fall 2024,Seminars ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2024/04/Kliber.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20240927T120000 DTEND;TZID=America/Chicago:20240927T130000 DTSTAMP:20260429T044846 CREATED:20240501T152309Z LAST-MODIFIED:20240501T152309Z UID:1396-1727438400-1727442000@www.math.ttu.edu SUMMARY:ESG performance and investment efficiency: The impact of information asymmetry DESCRIPTION:Speaker: Prof. Seda Erdogan\, Dept. International Trade & Finance\, Kadir Has University \nAbstract: This paper investigates the relationship between firms’ engagement in environmental\, social\, and governance (ESG) activities and corporate investment efficiency\, using 1\,094 firms from 21 countries in Europe\, covering the years 2002–2019. We conduct our estimations using fixed effects panel data techniques and address potential endogeneity with instrumental variables (IV) estimations. We provide evidence that overall ESG engagement is positively and significantly associated with investment efficiency. Analyzing overinvestment and underinvestment scenarios shows that ESG engagement decreases only overinvestment problems. Within the underinvestment scenario\, we observe that ESG engagement is beneficial only for firms with higher information asymmetries. Thus\, information asymmetry matters in the underinvestment case. We next show that four firm-level channels—information asymmetry\, financial constraints\, cash flows\, and risk—link ESG performance to investment inefficiency. Additional analysis shows that firms with extreme ESG scores (i.e.\, very low and very high) do not experience significant reductions in investment inefficiency. Altogether\, our findings draw attention to the critical role of ESG performance and information asymmetry in determining corporate investment efficiency. URL:https://www.math.ttu.edu/mathematicalfinance/event/esg-performance-and-investment-efficiency-the-impact-of-information-asymmetry/ LOCATION:via Zoom CATEGORIES:Fall 2024,Seminars ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2024/05/erdogan.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20241004T140000 DTEND;TZID=America/Chicago:20241004T150000 DTSTAMP:20260429T044846 CREATED:20240430T214605Z LAST-MODIFIED:20240430T214605Z UID:1391-1728050400-1728054000@www.math.ttu.edu SUMMARY:Option Pricing under a Generalized Black–Scholes Model with Stochastic Interest Rates\, Stochastic Strings\, and Lévy Jumps DESCRIPTION:Speaker: Prof. Steven P. Clark\, Dept. of Finance\, UNC Charlotte \nAbstract: We introduce a novel option pricing model that features stochastic interest rates along with an underlying price process driven by stochastic string shocks combined with pure jump Lévy processes. Substituting the Brownian motion in the Black–Scholes model with a stochastic string leads to a class of option pricing models with expiration-dependent volatility. Further extending this Generalized Black–Scholes (GBS) model by adding Lévy jumps to the returns generating processes results in a new framework generalizing all exponential Lévy models. We derive four distinct versions of the model\, with each case featuring a different jump process: the finite activity lognormal and double–exponential jump diffusions\, as well as the infinite activity CGMY process and generalized hyperbolic Lévy motion. In each case\, we obtain closed or semi-closed form expressions for European call option prices which generalize the results obtained for the original models. Empirically\, we evaluate the performance of our model against the skews of S&P 500 call options\, considering three distinct volatility regimes. Our findings indicate that: (a) model performance is enhanced with the inclusion of jumps; (b) the GBS plus jumps model outperform the alternative models with the same jumps; (c) the GBS-CGMY jump model offers the best fit across volatility regimes. URL:https://www.math.ttu.edu/mathematicalfinance/event/option-pricing-under-a-generalized-black-scholes-model-with-stochastic-interest-rates-stochastic-strings-and-levy-jumps/ LOCATION:via Zoom CATEGORIES:Fall 2024,Seminars ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2024/04/SClark.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20241011T140000 DTEND;TZID=America/Chicago:20241011T150000 DTSTAMP:20260429T044846 CREATED:20240501T154246Z LAST-MODIFIED:20240920T182126Z UID:1399-1728655200-1728658800@www.math.ttu.edu SUMMARY:Seminar Cancelled DESCRIPTION:Title: Time changes\, Fourier transforms and the joint calibration to the S&P500/VIX smiles \nSpeaker: Prof. Laura Ballotta\, Bayes Business School\, City University of London \nAbstract: We develop a model based on time changed Lévy processes and study its ability of reproducing the joint S&P500/VIX implied volatility smiles and the VIX futures prices – a problem known in the literature as the `joint calibration problem’. The model admits semi-analytical characteristic functions for the key quantities\, and therefore efficient Fourier based pricing schemes can be deployed. We focus on a specification of the proposed general setting which uses purely discontinuous processes. Results from the application to market data show satisfactory performances in solving the joint calibration problem\, and therefore demonstrate that the class of affine processes can provide a workable fit. URL:https://www.math.ttu.edu/mathematicalfinance/event/time-changes-fourier-transforms-and-the-joint-calibration-to-the-sp500-vix-smiles/ LOCATION:via Zoom CATEGORIES:Fall 2024,Seminars ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2024/05/Ballotta.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20241018T130000 DTEND;TZID=America/Chicago:20241018T140000 DTSTAMP:20260429T044846 CREATED:20240502T142834Z LAST-MODIFIED:20240502T142834Z UID:1410-1729256400-1729260000@www.math.ttu.edu SUMMARY:Elicitability and identifiability of tail risk measures DESCRIPTION:Speaker: Dr. Tobias Fissler\, Department of Mathematics\, ETH Zurich \nAbstract: Tail risk measures are fully determined by the distribution of the underlying loss beyond its quantile at a certain level\, with Value-at-Risk and Expected Shortfall being prime examples. They are induced by law-based risk measures\, called their generators\, evaluated on the tail distribution. This talk establishes joint identifiability and elicitability results of tail risk measures together with the corresponding quantile\, provided that their generators are identifiable and elicitable\, respectively. As an example\, we establish the joint identifiability and elicitability of the tail expectile together with the quantile. The corresponding consistent scores constitute a novel class of weighted scores\, nesting the known class of scores of Fissler and Ziegel for the Expected Shortfall together with the quantile. For statistical purposes\, our results pave the way to easier model fitting for tail risk measures via regression and the generalized method of moments\, but also model comparison and model validation in terms of established backtesting procedures. \nThe talk is based on joint work with Ruodu Wang\, Fangda Liu and Linxiao Wei. URL:https://www.math.ttu.edu/mathematicalfinance/event/elicitability-and-identifiability-of-tail-risk-measures/ LOCATION:via Zoom CATEGORIES:Fall 2024,Seminars ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2024/05/fissler.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20241025T100000 DTEND;TZID=America/Chicago:20241025T110000 DTSTAMP:20260429T044846 CREATED:20240801T143537Z LAST-MODIFIED:20240801T143642Z UID:1512-1729850400-1729854000@www.math.ttu.edu SUMMARY:Estimation and backtesting of risk measures with emphasis on distortion risk measures DESCRIPTION:Speaker: Prof. Hideatsu Tsukahara\, Dept.. of Economics\, Seijo University\, Tokyo \nAbstract: Statistical methodology has an important role to play in risk measurement. In this paper\, we will review and discuss some statistical issues on risk measures. Examples we consider are value-at-risk\, expected shortfall\, expectiles\, and distortion risk measures. Several methods of estimating these risk measures based on time series data have been proposed\, and we will try to explain in some detail. Another main issue we would like to address is a problem of backtesting: the evaluation of risk measurement procedures using historical data\, by comparing ex ante estimates of loss distributions or risk measures with the ex post realized losses. There have been several suggestions concerning backtestability of risk measures\, which will be discuss in detail. We also examine and suggest backtesting procedures for predictive distributions\, expected shortfall and distortion risk measures. URL:https://www.math.ttu.edu/mathematicalfinance/event/estimation-and-backtesting-of-risk-measures-with-emphasis-on-distortion-risk-measures/ LOCATION:via Zoom CATEGORIES:Fall 2024,Seminars ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2024/08/Tsukahara.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20241104T120000 DTEND;TZID=America/Chicago:20241104T130000 DTSTAMP:20260429T044846 CREATED:20240729T184309Z LAST-MODIFIED:20240729T195746Z UID:1491-1730721600-1730725200@www.math.ttu.edu SUMMARY:Pricing options with a new hybrid neural network model DESCRIPTION:Speaker: Dr. Yossi Shvimer\, Research Associate\, School of Finance and Management\, SOAS University of London \nAbstract: 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 improve accuracy when applied to real market data\, especially in OTM options. The new hybrid model demonstrates superior accuracy compared to both traditional parametric and non-parametric option pricing models for both Call and Put options across all moneyness levels. The empirical results of the hybrid model provide an explanation for the deviation from the Put-Call parity observed in real market data. URL:https://www.math.ttu.edu/mathematicalfinance/event/pricing-options-with-a-new-hybrid-neural-network-model/ LOCATION:via Zoom CATEGORIES:Fall 2024,Seminars ATTACH;FMTTYPE=image/png:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2024/07/Yossi_Shvimer.png END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20241115T140000 DTEND;TZID=America/Chicago:20241115T150000 DTSTAMP:20260429T044846 CREATED:20240729T184547Z LAST-MODIFIED:20240816T214112Z UID:1493-1731679200-1731682800@www.math.ttu.edu SUMMARY:Stochastic dominance\, stochastic volatility\, and jump risk: new theory interprets old results DESCRIPTION:Speaker: Prof Stylianos Perrakis\, John Molson School of Business\, Concordia Univ\, Montreal \n 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 return and volatility dynamics. A lower bound and an upper bound on option prices are obtained\, for a wide class of stochastic volatility jump (SVJ) processes that feature jumps in addition to diffusion. Using parameter estimates for the physical process from high-profile studies\, the bounds are shown to be remarkably tight\, especially for the empirically important class of short-term near-the-money options. The bounds are in many cases inconsistent with separate parameter estimates for the risk-neutral process that are extracted from observed option prices: for many option series\, the risk-neutral value exceeds the SD upper bound. This inconsistency points at the possibility that the distributional shape of the risk-neutral process is mis-specified or that the parameters are estimated without properly taking the option bid-ask spread into account. URL:https://www.math.ttu.edu/mathematicalfinance/event/stochastic-dominance-stochastic-volatility-and-jump-risk-new-theory-interprets-old-results/ LOCATION:via Zoom CATEGORIES:Fall 2024,Seminars ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2024/07/perrakis.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20241122T140000 DTEND;TZID=America/Chicago:20241122T150000 DTSTAMP:20260429T044846 CREATED:20240430T212747Z LAST-MODIFIED:20240903T172510Z UID:1379-1732284000-1732287600@www.math.ttu.edu SUMMARY:Inverse Problem for Forecasting Stock Options Prices DESCRIPTION:Speaker: Dr. Kirill Golubnichiy\, Dept of Math & Statistics\, Texas Tech University \nAbstract: 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 and boundary conditions for option prices. The Black-Scholes equation was solved in the positive direction of the time variable\, This ill-posed initial boundary value problem was solved by the so-called Quasi-Reversibility Method (QRM). This approach with an added trading strategy was tested on the market data for 368 stock options and good forecasting results were demonstrated. In the current paper\, we use the geometric Brownian motion to provide an explanation of that effectivity using computationally simulated data for European call options. We also provide a convergence analysis for QRM. The key tool of that analysis is a Carleman estimate. URL:https://www.math.ttu.edu/mathematicalfinance/event/inverse-problem-for-forecasting-stock-options-prices/ LOCATION:via Zoom CATEGORIES:Fall 2024,Seminars ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2024/04/Golubnichiy.jpeg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20250117T090000 DTEND;TZID=America/Chicago:20250117T100000 DTSTAMP:20260429T044846 CREATED:20241216T170525Z LAST-MODIFIED:20250110T185141Z UID:1643-1737104400-1737108000@www.math.ttu.edu SUMMARY:Deep learning-based portfolio optimization with transaction costs DESCRIPTION:Speaker: Prof. Aihua (Eva) Zhang\, College of Science\, Math & Tech.\, Wenzhou-Kean University\, Wenzhou China \nAbstract: 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 extended type of recurrent neural networks in deep learning. Our proposed method\, named as LSTM-Prediction-based Portfolio (LSTM-PbP) with transaction costs\, consists of two technical steps: finding the optimal portfolio strategy and predicting the future relative prices. For the price prediction\, we use multi-layer LSTM; while for the optimal portfolio strategy\, we solve the constraint maximization problem via relative entropy. We then update the future portfolio weights using the predicted prices and past portfolio weights. We iterate the process until the final investment period. Numerical experiments are also provided to show the accumulated wealth by following the obtained optimal portfolio strategy in comparison with the accumulated wealth under buy-and-hold strategy. The numerical results show that our model consistently outperforms the buy-and-hold strategy. URL:https://www.math.ttu.edu/mathematicalfinance/event/to-be-provided/ LOCATION:via Zoom CATEGORIES:Seminars,Spring 2025 ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2024/12/zhang.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20250124T130000 DTEND;TZID=America/Chicago:20250124T140000 DTSTAMP:20260429T044846 CREATED:20241216T170921Z LAST-MODIFIED:20241216T172221Z UID:1651-1737723600-1737727200@www.math.ttu.edu SUMMARY:Robust estimation of the range-based GARCH model: Forecasting volatility\, value at risk and expected shortfall of cryptocurrencies DESCRIPTION:Speaker: Prof. Piotr Fiszeder\, Dept. Econ. & Stat.\, Nicolaus Copernicus Univ.\, Torun\, Poland \nAbstract: 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 high prices\, while robust methods deal with outliers. We propose a range-based GARCH model with a bounded M-estimator\, which combines these two improvements with a third new improvement: a modified robust method\, which adds elasticity in treating the outliers. We apply this model to Bitcoin\, Ethereum Classic\, Ethereum\, and Litecoin and find that it forecasts variances\, value at risk\, and expected shortfall more accurately than the standard GARCH model\, the standard range-based GARCH model\, and the GARCH model with the robust estimation. Utilization of high and low prices joined with a novel treatment of outliers makes our model perform well during extreme periods when traditional volatility models fail. \nThis work is joint with\nProf. Marta Malecka\, Faculty of Economics and Sociology\, University of Łódź\, Łódź\, Poland\nand\nPeter Molnár\, UiS Business School\, University of Stavanger\, Stavanger\, Norway. URL:https://www.math.ttu.edu/mathematicalfinance/event/robust-estimation-of-the-range-based-garch-model-forecasting-volatility-value-at-risk-and-expected-shortfall-of-cryptocurrencies/ LOCATION:via Zoom CATEGORIES:Seminars,Spring 2025 ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2024/12/fiszeder.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20250131T140000 DTEND;TZID=America/Chicago:20250131T150000 DTSTAMP:20260429T044846 CREATED:20241216T171218Z LAST-MODIFIED:20241216T171717Z UID:1653-1738332000-1738335600@www.math.ttu.edu SUMMARY:Hedonic Models Incorporating Environmental\, Social\, and Governance Factors for Time Series of Average Annual Home Prices DESCRIPTION:Speaker: Jason Bailey\, Dept. of Mathematics & Statistics\, Texas Tech University \nAbstract: URL:https://www.math.ttu.edu/mathematicalfinance/event/hedonic-models-incorporating-environmental-social-and-governance-factors-for-time-series-of-average-annual-home-prices/ LOCATION:via Zoom CATEGORIES:Seminars,Spring 2025 ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2021/06/Screen-Shot-2021-06-29-at-10.18.41-PM.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20250207T120000 DTEND;TZID=America/Chicago:20250207T130000 DTSTAMP:20260429T044846 CREATED:20241216T171540Z LAST-MODIFIED:20241216T171630Z UID:1655-1738929600-1738933200@www.math.ttu.edu SUMMARY:Do online attention and sentiment affect cryptocurrencies’ correlations? DESCRIPTION:Speaker: Prof. Aurelio Bariviera\, Dept. of Business\, Universitat Rovira i Virgili\, Reus\, Spain \nAbstract: 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 market attention and sentiment. Our results highlight that while investor attention has a positive effect\, sentiment has a much stronger negative impact on the correlations. These findings can offer interesting insights for investors and regulators\, as the influence of market attention and sentiment on the correlations has important implications for portfolio diversification and market stability. URL:https://www.math.ttu.edu/mathematicalfinance/event/do-online-attention-and-sentiment-affect-cryptocurrencies-correlations/ LOCATION:via Zoom CATEGORIES:Seminars,Spring 2025 ATTACH;FMTTYPE=image/jpeg:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2024/12/bariviero-scaled.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=America/Chicago:20250221T120000 DTEND;TZID=America/Chicago:20250221T130000 DTSTAMP:20260429T044846 CREATED:20241216T171945Z LAST-MODIFIED:20241216T172028Z UID:1662-1740139200-1740142800@www.math.ttu.edu SUMMARY:Multi-asset return risk measures DESCRIPTION:Speaker: URL:https://www.math.ttu.edu/mathematicalfinance/event/multi-asset-return-risk-measures/ LOCATION:via Zoom CATEGORIES:Seminars,Spring 2025 ATTACH;FMTTYPE=image/png:https://www.math.ttu.edu/mathematicalfinance/wp-content/uploads/2024/12/Laudage.png END:VEVENT END:VCALENDAR