Monte Carlo Simulation for Option Pricing with Python (Basic Ideas Explained)
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2 سال پیش
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In this tutorial we will
In this tutorial we will investigate the Monte Carlo simulation method for use in valuing financial derivatives.
Monte Carlo simulations is a way of solving probabilistic problems by numerically simulating many possible scenarios so that you may calculate statistical properties of the outcomes, such as expectations, variances of probabilities of certain outcomes. In the case of Financial Derivatives, this gives us a handy tool for which to price complex derivatives for which and analytical formulae is not possible.
First used by Boyle in 1977, Monte Carlo simulation provides an easy way to deal with multiple random factors and the incorporation of more realistic asset price processes such as jumps in asset prices. Valuation of Financial Derivatives through Monte Carlo Simulations is only possible by using the Financial Mathematics of Risk-Neutral Pricing and simulating risk-neutral asset paths.
The mathematic notation and examples are from Les Clewlow and Chris Strickland's book Implementing Derivatives Models.
★ ★ Code Available on GitHub ★ ★
GitHub: https://github.com/TheQuantPy
Specific Tutorial Link: https://github.com/TheQuantPy/youtube...
00:00 Intro
01:05 What is Monte Carlo?
05:56 Accuracy Improvements
07:27 Valuation by Monte Carlo Simulation
10:00 European Call Option Modelling
14:38 Real World Example
27:02 Visualising your results
★ ★ QuantPy GitHub ★ ★
Collection of resources used on QuantPy YouTube channel. https://github.com/thequantpy
★ ★ Discord Community ★ ★
Join a small niche community of like-minded quants on discord. Discord: discord
★ ★ Support our Patreon Community ★ ★
Get access to Jupyter Notebooks that can run in the browser without downloading python.
Patreon: quantpy
★ ★ ThetaData API ★ ★
ThetaData's API provides both realtime and historical options data for end-of-day, and intraday trades and quotes. Use coupon 'QPY1' to receive 20% off on your first month.
https://www.thetadata.net/
★ ★ Online Quant Tutorials ★ ★
WEBSITE: https://quantpy.com.au
★ ★ Contact Us ★ ★
EMAIL: [email protected]
Disclaimer: All ideas, opinions, recommendations and/or forecasts, expressed or implied in this content, are for informational and educational purposes only and should not be construed as financial product advice or an inducement or instruction to invest, trade, and/or speculate in the markets. Any action or refraining from action; investments, trades, and/or speculations made in light of the ideas, opinions, and/or forecasts, expressed or implied in this content, are committed at your own risk an consequence, financial or otherwise. As an affiliate of ThetaData, QuantPy Pty Ltd is compensated for any purchases made through the link provided in this description.
Monte Carlo simulations is a way of solving probabilistic problems by numerically simulating many possible scenarios so that you may calculate statistical properties of the outcomes, such as expectations, variances of probabilities of certain outcomes. In the case of Financial Derivatives, this gives us a handy tool for which to price complex derivatives for which and analytical formulae is not possible.
First used by Boyle in 1977, Monte Carlo simulation provides an easy way to deal with multiple random factors and the incorporation of more realistic asset price processes such as jumps in asset prices. Valuation of Financial Derivatives through Monte Carlo Simulations is only possible by using the Financial Mathematics of Risk-Neutral Pricing and simulating risk-neutral asset paths.
The mathematic notation and examples are from Les Clewlow and Chris Strickland's book Implementing Derivatives Models.
★ ★ Code Available on GitHub ★ ★
GitHub: https://github.com/TheQuantPy
Specific Tutorial Link: https://github.com/TheQuantPy/youtube...
00:00 Intro
01:05 What is Monte Carlo?
05:56 Accuracy Improvements
07:27 Valuation by Monte Carlo Simulation
10:00 European Call Option Modelling
14:38 Real World Example
27:02 Visualising your results
★ ★ QuantPy GitHub ★ ★
Collection of resources used on QuantPy YouTube channel. https://github.com/thequantpy
★ ★ Discord Community ★ ★
Join a small niche community of like-minded quants on discord. Discord: discord
★ ★ Support our Patreon Community ★ ★
Get access to Jupyter Notebooks that can run in the browser without downloading python.
Patreon: quantpy
★ ★ ThetaData API ★ ★
ThetaData's API provides both realtime and historical options data for end-of-day, and intraday trades and quotes. Use coupon 'QPY1' to receive 20% off on your first month.
https://www.thetadata.net/
★ ★ Online Quant Tutorials ★ ★
WEBSITE: https://quantpy.com.au
★ ★ Contact Us ★ ★
EMAIL: [email protected]
Disclaimer: All ideas, opinions, recommendations and/or forecasts, expressed or implied in this content, are for informational and educational purposes only and should not be construed as financial product advice or an inducement or instruction to invest, trade, and/or speculate in the markets. Any action or refraining from action; investments, trades, and/or speculations made in light of the ideas, opinions, and/or forecasts, expressed or implied in this content, are committed at your own risk an consequence, financial or otherwise. As an affiliate of ThetaData, QuantPy Pty Ltd is compensated for any purchases made through the link provided in this description.
2 سال پیش
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