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Python for Finance

Python for Finance

3.5 (33)
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Python for Finance

Python for Finance

3.5 (33)

Overview of this book

This book uses Python as its computational tool. Since Python is free, any school or organization can download and use it. This book is organized according to various finance subjects. In other words, the first edition focuses more on Python, while the second edition is truly trying to apply Python to finance. The book starts by explaining topics exclusively related to Python. Then we deal with critical parts of Python, explaining concepts such as time value of money stock and bond evaluations, capital asset pricing model, multi-factor models, time series analysis, portfolio theory, options and futures. This book will help us to learn or review the basics of quantitative finance and apply Python to solve various problems, such as estimating IBM’s market risk, running a Fama-French 3-factor, 5-factor, or Fama-French-Carhart 4 factor model, estimating the VaR of a 5-stock portfolio, estimating the optimal portfolio, and constructing the efficient frontier for a 20-stock portfolio with real-world stock, and with Monte Carlo Simulation. Later, we will also learn how to replicate the famous Black-Scholes-Merton option model and how to price exotic options such as the average price call option.
Table of Contents (17 chapters)
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16
Index

Adjusted beta

Many researchers and professionals find that beta has a mean-reverting tendency. It means that if this period's beta is less than 1, there is a good chance that the next beta would be higher. On the other hand, if the current beta is higher than 1, the next beta might be smaller. The adjusted beta has the following formula:

Adjusted beta

Here, βadj is the adjusted beta and β is our estimated beta. The beta of a portfolio is the weighted beta of individual stocks within the portfolio:

Adjusted beta

Here Adjusted beta is the beta of a portfolio, wi (βi) is the weight (beta) of its stock, and n is the number of stocks in the portfolio. The weight of wi is calculated according to the following equation:

Adjusted beta

Here vi is the value of stock i, and summation of all vi, the denominator in the preceding equation is the value of the portfolio.

Scholes and William adjusted beta

Many researchers find that β would have an upward bias for frequently traded stocks and a downward bias for infrequently traded stocks...

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