8. Working with Options | Mastering Pandas for Finance

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Table Of Contents

Mastering Pandas for Finance

By : Michael Heydt

3.7 (6)

Mastering Pandas for Finance

3.7 (6)

By: Michael Heydt

Overview of this book

If you are interested in quantitative finance, financial modeling, and trading, or simply want to learn how Python and pandas can be applied to finance, then this book is ideal for you. Some knowledge of Python and pandas is assumed. Interest in financial concepts is helpful, but no prior knowledge is expected.

Preface

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Free Chapter

1. Getting Started with pandas Using Wakari.io

1. Getting Started with pandas Using Wakari.io

What is Wakari?

Creating a Wakari cloud account

Installing the samples in Wakari

Summary

2. Introducing the Series and DataFrame

2. Introducing the Series and DataFrame

Notebook setup

The main pandas data structures – Series and DataFrame

The basics of the Series and DataFrame objects

Reindexing the Series and DataFrame objects

Summary

3. Reshaping, Reorganizing, and Aggregating

3. Reshaping, Reorganizing, and Aggregating

Notebook setup

Loading historical stock data

Reorganizing and reshaping data

Grouping and aggregating

Summary

4. Time-series

4. Time-series

Notebook setup

Time-series data and the DatetimeIndex

Creating time-series with specific frequencies

Representing intervals of time using periods

Shifting and lagging time-series data

Frequency conversion of time-series data

Resampling of time-series

Summary

5. Time-series Stock Data

5. Time-series Stock Data

Notebook setup

Obtaining historical stock and index data

Visualizing financial time-series data

Fundamental financial calculations

Moving windows

Volatility calculation

Comparing stocks to the S&P 500

Summary

6. Trading Using Google Trends

6. Trading Using Google Trends

Notebook setup

A brief on Quantifying Trading Behavior in Financial Markets Using Google Trends

Data collection

Generating order signals

Computing returns

Cumulative returns and the result of the strategy

Summary

7. Algorithmic Trading

7. Algorithmic Trading

Notebook setup

The process of algorithmic trading

Moving averages

Technical analysis techniques

Algo trading with Zipline

Summary

8. Working with Options

8. Working with Options

Introducing options

Notebook setup

Calculating payoff on options

Profit and loss calculation

The pricing of options

Summary

9. Portfolios and Risk

9. Portfolios and Risk

Notebook setup

An overview of modern portfolio theory

Modeling a portfolio with pandas

Constructing an efficient portfolio

Constructing an optimal portfolio

Visualizing the efficient frontier

Value at Risk

Summary

Index

Index

Introducing options

An option is a contract that gives the buyer the right, but not the obligation, to buy or sell an underlying security at a specific price on or before a certain date. Options are considered derivatives as their price is derived from one or more underlying securities. Options involve two parties: the buyer and the seller. The parties buy and sell the option, not the underlying security.

There are two general types of options: the call and the put. Let's look at them in detail:

Call: This gives the holder of the option the right to buy an underlying security at a certain price within a specific period of time. They are similar to having a long position on a stock. The buyer of a call is hoping that the value of the underlying security will increase substantially before the expiration of the option and, therefore, they can buy the security at a discount from the future value.
Put: This gives the option holder the right to sell an underlying security at a certain price within...

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