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X-WR-CALNAME:Mathematical Finance
X-ORIGINAL-URL:https://www.math.ttu.edu/mathematicalfinance
X-WR-CALDESC:Events for Mathematical Finance
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DTSTART:20240310T080000
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DTSTART:20241103T070000
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DTSTART;TZID=America/Chicago:20240308T140000
DTEND;TZID=America/Chicago:20240308T150000
DTSTAMP:20260417T070149
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
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BEGIN:VEVENT
DTSTART;VALUE=DATE:20240315
DTEND;VALUE=DATE:20240316
DTSTAMP:20260417T070149
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
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DTSTART;TZID=America/Chicago:20240318T120000
DTEND;TZID=America/Chicago:20240318T130000
DTSTAMP:20260417T070149
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
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