Black-Scholes in C# Options Pricing Model

Understanding the Black Scholes Model

The Black Scholes Model is a mathematical model used for pricing options contracts. It helps traders and investors determine the fair price of options based on various factors such as underlying asset price, strike price, time to expiration, risk-free interest rate, and volatility.

Setting Up the Environment

To get started, ensure you have Visual Studio installed on your machine. We’ll be using C# with Winforms to create a user-friendly interface for our Black Scholes Model calculator.

Creating the Winforms Application

Begin by creating a new Winforms project in Visual Studio. Once the project is set up, you can design your form layout with text boxes, labels, buttons, and dropdowns to capture user input and display results.

Implementing the Black Scholes Model Logic

Now, let’s go deep into the heart of our application — the Black Scholes Model logic. We’ll need functions to calculate both call and put options prices based on the provided inputs: current stock price, strike price, time to expiration, risk-free interest rate, and volatility.

Key components include:

• Form1 Class: The main form class responsible for handling user inputs and triggering calculations.
• Input Validation: Ensuring that user inputs are valid is crucial. The IsvalidInput method safeguards against erroneous inputs.
• Black-Scholes Calculation: The Call_bsm and put_bsm methods implement the Black-Scholes formula for call and put options, respectively.
• Cumulative Distribution Function (CDF): The CDF method is employed for calculating the cumulative distribution function, a crucial part of the Black-Scholes calculation.

In our C# code, we define methods Call_bsm and put_bsm to compute the option prices using the Black Scholes formulas. We also implement the Cumulative Distribution Function (CDF) to calculate the probability distribution.

        private double Call_bsm( double StockPrice, double StrikePrice , double TimePeriod , double RateofIntrest , double roh_Volatility  )
        {
            //ref https://www.codearmo.com/python-tutorial/options-trading-black-scholes-model
            double model = -1;
            try
            {
                //d1 denote Get 
                double d1 = (Math.Log(StockPrice / StrikePrice) + (RateofIntrest + Math.Pow(roh_Volatility, 2) / 2) * TimePeriod) / (roh_Volatility * Math.Sqrt(TimePeriod));

                //d2 denote Pay 
                double d2 =  d1 - roh_Volatility * Math.Sqrt(TimePeriod);

                model = StockPrice * CDF(d1) - StrikePrice * Math.Exp(-RateofIntrest * TimePeriod) * CDF(d2);
                return model;
            }
            catch(Exception ex)
            {
                Debug.WriteLine($"Error Ocurred(s) {ex.Message}");
            }
            return model;
        }

        private double put_bsm(double StockPrice, double StrikePrice, double TimePeriod, double RateofIntrest, double roh_Volatility)
        {
            //ref https://www.codearmo.com/python-tutorial/options-trading-black-scholes-model
            double model = -1;
            try
            {
                //d1 denote Get 
                double d1 = (Math.Log(StockPrice / StrikePrice) + (RateofIntrest + Math.Pow(roh_Volatility, 2) / 2) * TimePeriod) / (roh_Volatility * Math.Sqrt(TimePeriod));

                //d2 denote Pay 
                double d2 = d1 - roh_Volatility * Math.Sqrt(TimePeriod);

                model = StrikePrice * Math.Exp(-RateofIntrest * TimePeriod) * CDF(-d2) - (StockPrice * CDF( -d1) );
                return model;
            }
            catch (Exception ex)
            {
                Debug.WriteLine($"Error Ocurred(s) {ex.Message}");
            }
            return model;
        }

Running the Application

To use the application, enter the required parameters such as stock price, strike price, interest rate, time to expiry, and implied volatility. Select the type of option (Call or Put) from the dropdown, and the application will compute the Black-Scholes price.

Black Scholes Model to Calculate Options Premium

Handling User Input and Error Validation

It’s essential to handle user input carefully to ensure the application functions smoothly. We implement error validation to check for valid input data before processing the Black Scholes Model calculations. This helps prevent runtime errors and enhances user experience.

Conclusion

In this article, we’ve explored how to code the Black Scholes Model using C# and WinForms. By following these steps, you can create a powerful tool for options pricing and financial analysis.

Reference :

Khan Academy Video: https://youtu.be/pr-u4LCFYEY

Access the Full Solution

To explore the complete C# solution implementing the Black-Scholes Model using WinForms, you can access the GitHub repository provided by the author. Dive into the code, experiment with different parameters, and expand your knowledge of quantitative finance and C# programming.

https://github.com/Coderixc/BlackScholesModel.git

If you are seeking assistance in developing this project, please do not hesitate to contact me.

Thanks For Reading.

Feel free to integrate this into your quantitative trading projects . Happy coding! 🚀📈

📊You can also read my other Post Like:BackTesting Strategy Setup: Building a Python Trading Strategy Analyzer

📊Explore the full potential of this project by visiting our GitHub repository.

LinkedIn : https://www.linkedin.com/in/kamalchanchal

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