Understanding stock options is an essential part of managing a portfolio or investing in the stock market. A stock option is an agreement that gives the owner the right, but not the obligation, to buy or sell a stock at a specific price within a specific time frame. Excel is a powerful application used to build models and calculate complex calculations. In this blog post, we will look at how to use Excel to model stock options effectively.

Key Takeaways

  • Understand the basics of stock options.
  • Learn how to Calculate complex calculations using Excel.
  • Discover tips and tricks for modeling stock options.
  • Gain insight into how to use Excel to gain a competitive edge in the stock market.

Comprehending Option Types

Understanding option types is the first step to modelling stock options in Excel. There are three main kinds of options; calls, puts, and combinations of both.


A call option gives the buyer the right, but not the obligation, to buy the underlying asset at a fixed price, on or before a predetermined date. As the buyer, you pay an upfront premium to hold the option, and collect any returns from any difference in the market value and the fixed predetermined price if the buyer chooses to exercise the option.


A put option is essentially the opposite of a call option. The buyer is given the right to sell the underlying asset at a fixed price, on or before a predetermined date. As the buyer, they must also pay an upfront premium to hold the option, and any return will be the difference between the market price of the underlying asset and the fixed price determined by the option, if the option is exercised.


Combining call and put options together creates a strategy known as a straddle. A straddle involves purchasing both a call and a put option with the same strike and expiration date, but with different underlying assets. This creates a risk- and profit-neutral that enables a market neutral position, as the market move will result in either a pay-off or a break-even situation.

Pricing Options

Options pricing is the process of determining the fair value of an option contract. This can be done mathematically by using the Black-Scholes methods, or by using binomial tree models. While the Black-Scholes model is a simpler, more widely accepted approach, binomial models can provide higher accuracy for certain stock options.

Black-Scholes Methods

The Black-Scholes model is used to price European call and put options. This is done by calculating the option’s current or intrinsic value, as well as its time value. The time value is determined by the option’s strike price and the current price of the underlying stock, volatility of the stock, risk-free rate, and time until expiration. With Excel, these factors can be input into a formula to quickly price the option.

Binomial Models

Binomial models are a more complex way to price stock options. While they are more difficult to set up and understand, they are more accurate in certain cases. For example, if the option has a long-term expiration or is a deep-out-of-the-money option, the Black-Scholes model may not be sufficiently accurate for pricing. In such cases, a binomial model can be used to gain a more precise option price.

When using a binomial model in Excel, the stock price is tracked at each point in time over the life of the option, instead of looking at a single time frame, as is done with the Black-Scholes model. Over the entire time horizon, the stock’s up and down movements are tracked and, from that, a price is determined for the option.

Hedging Options

Hedging is a strategy used to reduce risk by offsetting the possible losses of a transaction. This can be done through buying and selling of financial products, such as options or futures contracts, in order to protect against market movements. Hedging requires some knowledge of how and when to manage the risks of a security or transaction. In general, the idea of hedging is to reduce the risks associated with the movement in the prices of stock or options.

Defining Hedging

Hedging is essentially a form of financial insurance, where traders take measures to protect themselves and their portfolios against potential losses. This can be done through buying insurance, such as put or call options, or futures contracts, which allow them to protect against downside risk. Hedging also applies to other types of investments, such as currencies and commodities.

Put options are a type of option contract which gives its holder the right, but not the obligation, to sell a particular asset at a specified price on or before a specified date. Call options, on the other hand, are contracts offering the right to purchase an asset at a given price before a specified date. By purchasing either a put or call option, traders can protect their position against changes in the price of an underlying asset.

Calculation Methods

Calculating hedging positions can be complicated and requires an understanding of derivatives and basic accounting principles. The most accurate and reliable way to calculate hedging positions is to use Excel. With Excel, traders can use various formulas to analyze the data and establish their position. For example, the Black-Scholes model, a popular method for pricing options and executing hedging trades, can be calculated with an Excel spreadsheet.

Some of the other Excel options for calculating hedging positions include Monte Carlo Simulation, VB macro and function, and the Binomial Model. Each of these methods can help traders to understand their underlying position, the potential risks associated with it, and the ways in which they can hedge against those risks.

Calculating Portfolio Returns

Calculating portfolio returns is an essential skill for any investor and modelling stock options with Excel provides an easy-to-use platform for evaluating the performance of a portfolio. By understanding the calculations that go into assessing portfolio returns, investors can better understand the tools available to them and make smarter decisions when making investments.

Value at Risk (VaR)

Value at Risk (VaR) is a useful measure for understanding the maximum potential loss on a portfolio over a given time period. VaR is calculated by summing the possible losses of individual stocks in the portfolio and then deducting the profits. This calculation can be used to get an accurate measure of risk and help investors decide whether to buy or sell a certain stock.

VaR is also a useful measure for evaluating the performance of a portfolio over time, as it can help identify trends in the market and pinpoint opportunities for investment. With Excel, investors can easily create models that take into account all the variables associated with particular investments and use the VaR calculation to understand the risk level of each portfolio.

Applying Excel

Excel enables users to easily calculate a portfolio's VaR by providing a comprehensive range of features. Investors only need to input their data and then use the built-in functions to calculate the value of their portfolio at the end of any given period. Excel also provides powerful tools such as currency conversion calculators to help investors understand the differences between different currencies and gauge the value of their investments.

Additionally, Excel offers tools for automating the VaR calculation process, which can save investors considerable time and effort. For example, Excel's Data Analysis Tools can be used to quickly analyze a portfolio's performance with VaR and other relevant metrics. This makes it easier for investors to determine which stocks to buy or sell and identify opportunities for investing in the stock market.

Strategies for Modeling

Modeling stock options with Excel can be done effectively by considering both the short and long-term, as well as leveraging the software’s built-in features. Investors are able to construct their own stock analysis models with precision and accuracy to anticipate potential trends and identify potential opportunities.

Short vs. Long Term

When building models to track stock options using Excel, it is important to consider both the short and long-term performance of the stock. For example, by identifying the historical highs and lows of the stock, investors can estimate the potential of the stock over the course of the future. Furthermore, by projecting the stock's values over the short and long-term, investors can determine whether it is a viable investment and potentially capitalize on market movements.


Excel provides a number of useful built-in features and formulas which can be used to generate stock option models quickly and accurately. For example, Excel’s “VLOOKUP” feature allows investors to quickly identify stock values for various points in time and develop a comparison for what the stock should be worth at various points going forward. Additionally, formulas such as the “IF” statement can be used to develop more complex models which consider a range of potential outcomes. Examining these features allows investors to leverage their stock option modeling to make the most of their investment.


Modelling stock options with Excel can be a great way to gain insight into your investments. Excel provides users with an array of different tools to work with, all of which are easily accessible and user friendly. Through the use of formulas, pivot tables, and data visualization capabilities, you can accurately assess risks and make informed decisions about trading stock options.


In this post, we discussed how Excel can be used to model stock options. We went over the basics of setting up the environment and downloading the necessary data. We explored the various formulas and pivot tables available, followed by an examination of data visualization features.

Best Practices

The following best practices should be followed when modelling stock options with Excel:

  • Use formulas to accurately test the conditions of stock options and assess potential risks.
  • Explore the different types of Excel pivot tables and use the data to your advantage.
  • Utilize the data visualization capabilities in Excel to gain a better understanding of the data and make informed decisions.
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