In this project-based course, expert Python programmer and consultant Jose Portilla teaches you how to apply the programming language to financial analysis and algorithmic trading.
In this Python for Finance Course, Jose Portilla will teach you how to code basic financial trading algorithms. You’ll learn step-by-step how to develop a full backtesting and risk management system using Python so you can create automated trading systems and backtesting the strategies that are based purely on your own ideas and research.
Python for Financial Analysis and Algorithmic Trading is an in-depth, hands-on guide to applying Python to trading algorithms and data analysis with the financial industry.
Python is one of the most popular languages for financial analysis and algorithmic trading. In this course you will learn how to use Python for data analytics, backtesting, and automating trading strategies. You will set up a Python environment on your computer so you can start using it right away. You’ll also learn about different libraries in order to do data analysis from scratch or use third party tools available online.
In this course, you will learn the most important concepts around financial analysis and algorithmic trading using Python. You will cover topics like data visualization, statistical modeling, time series analysis, mathematical programming and numerical optimization. Apply these skills to real-world problems such as portfolio simulation and prediction or risk assessment
Build anything you can imagine with Python. It’s powerful and its versatility makes it the C# of scripting languages: a great all-around tool. Learn to build web apps, data analyses programs, games, image filters – even games.
Python for Financial Analysis and Algorithmic Trading will teach you how to use Python programming to create practical, high-performance software for the financial markets. You will learn about the tools and technologies used by traders, as well as their real-world applications. You’ll explore Python’s ecosystem through an in-depth analysis of different libraries commonly used in finance, such as NumPy, Pandas, Plotly and scikit-learn. Along the way, you’ll use these libraries to build fully-fledged programs that can be put into production right away
Python for Financial Analysis and Algorithmic Trading is designed for intermediate coders that want to take their Python skills to the next level by applying them to financial analysis.
Python for Financial
This Python for Financial Analysis and Algorithmic Trading course is designed to help you learn how to program in Python, one of the most popular languages used in finance. The course will teach you the basics of financial theory, and how to apply it through Python programming techniques. Complete with an additional set of lectures on using finance together with Linux, this course will walk you through a comprehensive curriculum of learning how to use Python for investment analysis and algorithmic trading.
This Python for Algorithmic Trading course covers the basics of Python programming and financial analysis, to expose students to the tools and techniques used by professional quant traders. You’ll start by learning how to get started with Python 3, and then review all the basic elements of the language. Then, you’ll learn how to perform two-dimensional data visualizations with matplotlib. Following that, we’ll tackle how to acquire and clean financial data, so that we can start modeling our own trading algorithms. The next section covers risk management, which will familiarize you with concepts such as Value at Risk (VaR), Conditional Value At Risk (CVaR), Shortfall Probability (SF), and Expected Shortfall. We end with a discussion on optimizing your trading system from both theoretical as well as practical perspectives.
The Python & Algorithmic Trading Course is designed to take you from beginner to advanced levels of finance analytics, development and trading. You’ll be introduced to an incredible array of tools, big data libraries and frameworks that will prepare you for life as an algorithmic trader. There are no prerequisites for this course so anyone can learn algorithmic trading; including those with no previous experience!
This course is for those who want to get started in financial trading using python, machine learning and market data. You will learn how to write your own strategies and backtest them with the most popular Python libraries such as pandas, numpy, scikit-learn or quantopian. I will show you all the steps needed to go from a blank sheet of paper to an automated trading strategy running on paper trading account.
Python for Financial Analysis and Algorithmic Trading is a fast-paced, hands-on course to get you started programming algorithms in Python. You’ll learn how to use Python for financial analysis and develop scalable and efficient trading systems, covering topics like:
Python for Financial Analysis and Algorithmic Trading is an introductory course focused on teaching you how to use Python for large financial datasets.
Python for Financial Analysis and Algorithmic Trading is a practical course that teaches you how to create your own trading algorithm using real-world applications. You will learn the basics of Python, which is used by many financial institutions, including Bloomberg. You will then go on to discover how Python works with Excel and incorporate its functionality into your own algorithms. Finally, you will learn how to programmatically trade using Python and analyze data using pandas and matplotlib.
Analysis and Algorithmic
This course is about using Python for Financial Analysis and Algorithmic Trading. We start with the basics of installing Python, then go over easy to use libraries such as SciPy, Numpy, Pandas, Matplotlib and PyAlgoTrade. Once you have installed everything you will use it to undertake real world examples related to obtaining historical data from Bloomberg and Forex data from Oanda. The financial analysis part of this class focuses on fundamental analysis using 10 year corporate stocks data to estimate dividend yields using regression models. Additionally we look at simple moving averages and exponential moving averages. In the last section we examine technical analysis with a focus on candlestick patterns and how they relate to volatility.
This is an expert level course on financial analysis and algorithmic trading with Python. The goal of this class is for you to learn how to use Python to write short sell high and buy low algorithms, analyze live financial data and trade on their own. This is not a class on programming but rather a class on financial analysis and algorithmic trading. This course is perfect for somebody who is interested in making money through trading, investing or creating their own hedge fund (or at least have an idea of what traders do).
In this course Python basics and its use in the financial industry are discussed. The course then illustrates how to analyze stock market data by using Python packages such as numpy and pandas. Algorithmic trading, building custom indicators with python, ideas described in high frequency and algorithmic trading books with code examples are discussed. The course provides a comprehensive overview of all aspects of Python for finance including: Why use Python for financial analysis?
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