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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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TZOFFSETFROM:-0600
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TZNAME:CDT
DTSTART:20240310T080000
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DTSTART:20241103T070000
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DTSTART;TZID=America/Chicago:20241122T140000
DTEND;TZID=America/Chicago:20241122T150000
DTSTAMP:20260520T082616
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
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