Abstract

Whether it's building dams to control rivers, crafting garments to withstand cold, or the simple act of carrying an umbrella, these actions reflect humanity's precautionary behavior to adapt to nature. Weather derivatives are an extension of this adaptive behavior of the humankind seeking to hedge against weather related risks. A recent example that motivated this work is the loss of revenue incurred by Egypt during the six- day closure of the Suez Canal caused by the wedging of large vessel due to bad weather conditions. In this thesis, we model and price a temperature-based weather contract, using a dataset of historical weather metrics from Cairo, Egypt. We employ a stochastic approach based on the Ornstein-Uhlenbeck process, incorporating seasonal trends, mean reversion, and assuming monthly volatilities to model temperature dynamics. Our work extends the foundational methodology found in (Alaton et al., 2002), using Monte Carlo simulation and enhanced with a variance reduction technique using the control variate approach, leveraging a correlated Asian option under a Geometric Brownian Motion framework which significantly improves computational efficiency. Findings show that these methods could be effective when pricing temperature-based instruments and hence offering practical implications for industries like agriculture, energy, transportation, tourism, data center, etc. This research also aims to contribute to the broad understanding of the topic of Weather Derivatives as we explore use cases that fit different local economies, and we touch upon the challenges faced when pricing such instruments in the incomplete markets’ framework.

School

School of Business

Department

Management Department

Degree Name

MS in Finance

Graduation Date

Fall 2-16-2025

Submission Date

2-16-2025

First Advisor

Rim Cherif

Second Advisor

Malek Ben Abdel-latif

Committee Member 1

Tarek El Domiaty

Committee Member 2

Wael Abdullah

Extent

81 p.

Document Type

Master's Thesis

Institutional Review Board (IRB) Approval

Not necessary for this item

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