The Valuation of Basket-lookback Option

DOI

10.2991/aebmr.k.220307.346How to use a DOI?

Keywords

Lookback options; Portfolio; Driverless car; Monte Carlo method

Abstract

Exotic options have becoming more popular in the markets. We designed a new over-the-counter product by working on a combination of basket and lookback options and explained its rationale. To value the derivative, we constructed a pricing model in Python using the Monte Carlo method. For a sample simulation, we chose a portfolio of 10 stocks from the driverless technology sector. After collecting the historical data, we estimated the covariance matrix. To perform the valuation, we applied the Cholesky decomposition and moment matching and simulated correlated price paths. Finally, a sensitivity analysis was conducted to evaluate the impact of variations in the parameters on the option value and seek the practical significance of the new product intuitively. With stable and reasonable simulated pricing results, we concluded that our product could play a good role in helping investors grasp the potential value of one specific sector and providing psychological comfort by minimizing regrets. This paper effectively provides a new financial product that will be of great practical significance.

Copyright

© 2022 The Authors. Published by Atlantis Press International B.V.

Open Access

This is an open access article under the CC BY-NC license.

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TY  - CONF
AU  - Jiayi Li
AU  - Xinwen Xu
PY  - 2022
DA  - 2022/03/26
TI  - The Valuation of Basket-lookback Option
BT  - Proceedings of the 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022)
PB  - Atlantis Press
SP  - 2110
EP  - 2115
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.220307.346
DO  - 10.2991/aebmr.k.220307.346
ID  - Li2022
ER  -