An intuitive way to think about price volatility is investor confidence in the specific instrument, that is, how willing the investors are to invest money into the specific instrument and how long they are willing to hold on to a position in that instrument. As price volatility goes up, because prices make bigger swings at faster paces, investor confidence drops. Conversely, as price volatility goes down, investors are more willing to have bigger positions and hold those positions for longer periods of time. Volatility in a few asset classes often spills over into other asset classes, thus slowly spreading volatility over to all economic fields, housing costs, consumer costs, and so on. Obviously, sophisticated strategies need to dynamically adjust to changing volatility in trading instruments by following...
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Book Overview & Buying
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Table Of Contents
Learn Algorithmic Trading
By :
Learn Algorithmic Trading
By:
Overview of this book
It’s now harder than ever to get a significant edge over competitors in terms of speed and efficiency when it comes to algorithmic trading. Relying on sophisticated trading signals, predictive models and strategies can make all the difference. This book will guide you through these aspects, giving you insights into how modern electronic trading markets and participants operate.
You’ll start with an introduction to algorithmic trading, along with setting up the environment required to perform the tasks in the book. You’ll explore the key components of an algorithmic trading business and aspects you’ll need to take into account before starting an automated trading project. Next, you’ll focus on designing, building and operating the components required for developing a practical and profitable algorithmic trading business. Later, you’ll learn how quantitative trading signals and strategies are developed, and also implement and analyze sophisticated trading strategies such as volatility strategies, economic release strategies, and statistical arbitrage. Finally, you’ll create a trading bot from scratch using the algorithms built in the previous sections.
By the end of this book, you’ll be well-versed with electronic trading markets and have learned to implement, evaluate and safely operate algorithmic trading strategies in live markets.
Table of Contents (17 chapters)
Preface
Free Chapter
Section 1: Introduction and Environment Setup
Algorithmic Trading Fundamentals
Section 2: Trading Signal Generation and Strategies
Deciphering the Markets with Technical Analysis
Predicting the Markets with Basic Machine Learning
Section 3: Algorithmic Trading Strategies
Classical Trading Strategies Driven by Human Intuition
Sophisticated Algorithmic Strategies
Managing the Risk of Algorithmic Strategies
Section 4: Building a Trading System
Building a Trading System in Python
Connecting to Trading Exchanges
Creating a Backtester in Python
Section 5: Challenges in Algorithmic Trading
Adapting to Market Participants and Conditions
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