Yasmin Kalhor

About me

I hold an MSc in Financial Engineering from HEC Montréal, where I maintained 'Great Distinction' on my transcript for all semesters, reflecting my commitment to academic excellence. Previously, I earned a Bachelor's degree in Applied Mathematics, with a major in Financial Mathematics and a minor in Industrial Engineering, from Amirkabir University of Technology (Tehran Polytechnic), graduating with Dean's Honours.

Outputs

A reduced-order model based on cubic B-spline basis function and SSP Runge–Kutta procedure to investigate option pricing under jump-diffusion models

The purpose of this research is to develop a numerical method that can be used to deal with option pricing in jump-diffusion models. The proposed model is made up of a backward partial integro-differential equation with diffusion and advection factors. For the first and second order derivatives, the pseudo-spectral technique is used in conjunction with cubic B-spline functions. As a consequence, the first- and second-order derivative matrices are constructed, and an ODE system is created. Second-order Strong Stability Preserved Runge–Kutta (SSP) procedure is used to solve the ODE problem. According to what has been stated, the main model falls under the advection–diffusion classification. As a result, in order to reach the ultimate time, we need to increase both the number of collocations and the number of time steps in order to improve our results. That is why the final algebraic system of equations has been condensed using a technique known as proper orthogonal decomposition (POD). The POD-cubic B-Spline (POD-CB-S) function collocation approach can be used to describe this numerical procedure. Finally, a number of test cases are conducted to demonstrate the proposed method’s efficiency and accuracy.

Conditional Pricing of Macroeconomic Risk Factors Using Attention

My thesis examines the applicability and robustness of the Arbitrage Pricing Theory (APT) with macroeconomic factors in explicating risk premia in the context of financial markets. Grounded in the seminal works of Chen et al. [1986] and Fisher et al. [2022], this study integrates the innovative concept of attention to macroeconomic risk factors with the established APT framework. The prior literature has failed to find that macroeconomic risk factors are priced, which is a puzzle. The principal objective of the research is to ascertain whether risk premia estimations during heightened periods of investor attention can be effectively priced by macroeconomic factors. However, the findings align with existing literature, demonstrating a statistically insignificant relationship. The results also point to the role of attention, and those factors “might” be priced when attention is high (the average absolute lambda increases with attention for most risk factors).