Option Pricing and Delta Hedging for Moderna Inc. on Different
Models
Wuyu Wei
Department of Statistical Sciences University of Toronto, Toronto, Canada
Keywords: Delta Hedging, Black-Scholes Model, Binomial Model, Calibration, Option Pricing.
Abstract: The aim of this paper is to compare the performance of the same delta hedging strategies using three different
models in the process of pricing options for Moderna Inc., which has reference value for investors to compare
such models and build their hedging portfolios. Historical volatility is estimated from past open prices and
two implied volatilities are calibrated utilizing the selected 10 options on the Moderna Inc.’s stock. Then the
delta hedging strategy using three different models with volatilities above, containing one unit of a specific
option with different maturity and delta shares of the stock, is applied to obtain daily profit/loss. Finally, the
trends of daily gain/loss for such three models are visualized compared with the trends without hedging. To
conclude, the hedging strategy performs all well for the three models. This results in this study benefits
investors and researchers in choosing the relatively suitable option pricing model and the best-fit hedging
strategy for specific companies or sectors.
1 INTRODUCTION
Option pricing has been a focus of mathematical
research in finance since the publication of the Black-
Scholes formula in 1973 (Davis, 1993). Basically, it
provides an evaluation of an option’s value, which
would be involved into investors’ strategies. Options
are used for hedging and speculation (Amir, 2018).
Hedging is a term used nowadays primarily in
conjunction with financial markets (Rata, 2009),
which refers to the entrepreneur’s financial strategy of
mitigating market price risks through selling or
buying futures contracts for the commodity that is the
object of his activity (Rata, 2009). Hedging strategies
limit the losses to a great extent and meanwhile,
provide a flexible price mechanism. In recent years,
hedging with options, no matter what kind of options,
has been a crucial part in mathematical finance and
widely used. The related topics have been
continuously studied.
To demonstrate, on the one hand, researchers have
improved classical model and hedging strategy to fit
them better in realistic situations. First, based on the
exist theory under the model without considering
liquidity, Gueant, Olivier, and J. Pu modeled a new
framework which considers stochastic optimal control
to price and hedge a call option with execution costs
and market impact (Gueant, 2017). Also, to improve
delta hedging for options, Hull, J., and A. White
determined empirically a model for minimizing the
variance of changes in the value of a trader’s position
(Hull, 2017). Moreover, Ye, M., et al. improved
Black-Scholes model for crop price insurance
premium (Ye, 2017). Also, Imaki et al. proposed a
new neural network to facilitate fast training and
accurate optimal hedging strategies. In addition, Kim
et al. extended binomial model in two ways,
developed the one with time-dependent parameters
and derived a hedging strategy for a trinomial model
(Kim, 2017).
On the other hand, there are also some scholars
who try to test the performance of different models for
specific companies or fields, or for different kind of
options. Lassance, Nathan and Vrins, Frederic
compared the hedging ability of several popular
models on the Apple stock (Lassance, 2017). Also,
Doffou tested three parametric models in pricing and
hedging higher-order moment swaps (Doffou, 2019).
Besides, Bollin and Lepaczuk explored the
performance of several option pricing models in
hedging the exotic options (Bollin, 2020)
To sum up, this topic is of interest to the
researchers in the financial field. This paper also
focuses on this topic and two main parts are included
in the entire study. First, the three volatilities are