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Python for Finance

You're reading from   Python for Finance Apply powerful finance models and quantitative analysis with Python

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Product type Paperback
Published in Jun 2017
Publisher
ISBN-13 9781787125698
Length 586 pages
Edition 2nd Edition
Languages
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Author (1):
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Yuxing Yan Yuxing Yan
Author Profile Icon Yuxing Yan
Yuxing Yan
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Toc

Table of Contents (17) Chapters Close

Preface 1. Python Basics FREE CHAPTER 2. Introduction to Python Modules 3. Time Value of Money 4. Sources of Data 5. Bond and Stock Valuation 6. Capital Asset Pricing Model 7. Multifactor Models and Performance Measures 8. Time-Series Analysis 9. Portfolio Theory 10. Options and Futures 11. Value at Risk 12. Monte Carlo Simulation 13. Credit Risk Analysis 14. Exotic Options 15. Volatility, Implied Volatility, ARCH, and GARCH Index

Capital budgeting with Monte Carlo Simulation

As we mentioned at the beginning of this chapter, we can use Monte Carlo Simulation to capital budgeting when the number of variables has many different values. Our objective is to estimate the NPV for a given budget by discounting all of its future free cash flow:

Capital budgeting with Monte Carlo Simulation

Here, NPV is the Net Present Value of one proposal, FCF0 will be the free cash flow at time zero, FCFt will be free cash flow at the end of year I, R is the discount rate. The formula to calculate free cash flows at the end of year t is given here:

Capital budgeting with Monte Carlo Simulation

Here, FCTt is Free Cash Flow at year t, Dt is depreciation of year t, CaptExt is the net capital expenditure at year t, NWC is for Net working capital, which is the current asset minus current liability, Δ means change. Let's look at a simple one. Assume that the company buys one price of long term equivalent with a total cost of 0.5 million with a life of five years:

Items

0

1

2

3

4

5

Price

0

28

28

28

28

28

Unit

...
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