[Update Course] Performance Optimization and Risk Management for Trading | Udemy

Generate Income and make a living with Day Trading / Algorithmic Trading. A quantitative & data-driven Python course.

What you’ll learn
How to make a living with Trading (and what it requires)
How to optimize the Performance of Trading Strategies
How to manage & control the Risk of Trading Strategies
How to find the optimal degree of Leverage for Margin Trading
How to measure the Performance and Risk of Trading Strategies and Financial Instruments
How to make proper use of Stop Loss (SL) and Take Profit (TP) Orders
Advanced Python Coding (OOP, Pandas, Numpy, Scipy, Matplotlib, Seaborn)
How to optimize Trading Performance with single/multiple Parameter Optimization
How to optimize Trading Performance with Smoothing
How to calculate Risk, Return and the Sharpe Ratio (Mean-Variance Analysis)
How to calculate Downside Risk and the Sortino Ratio
How to calculate Maximum Drawdown, Maximum Drawdown Duration and the Calmar Ratio
How to calculate CAGR, Investment Multiple, compound Returns and more.
How to generate a sustainable income with Trading

(Latest course update and full code review in May 2023!)

(How) Can I generate sustainable Income and make a living with Trading? – That is one of the most frequently asked questions in Day Trading / Algorithmic Trading.

This unique course provides the skills, knowledge, and techniques required to (realistically!) answer that question. The course uses rigorous quantitative methods and is 100% data-driven (Python coding required!).

You will learn how to make use of the most powerful trading features and techniques:

Path-dependent Simulation techniques to find a sustainable level of Trading Income

Taking into account Taxation, Inflation and Shortfall Risk

Strategy Backtesting and Forward Testing

Strategy Optimization techniques (One/Many Parameter Optimization, Multi-Period Optimization, Smoothing, and more…)

Finding the optimal Degree of Leverage in Margin Trading (Kelly Criterion and more advanced techniques)

Improving Trading Performance and mange Risk with Stop Loss and Take Profits Orders

and more…

Important: these techniques and skills are highly relevant and must-knows for any Trader and any Trading activity:

for Assets like Forex (Currencies), Cryptocurrencies, Stocks, Indexes, Commodities, and more…

for Strategies based on Technical/Fundamental Analysis, Artificial Intelligence (Machine Learning & Deep Learning), Statistical Arbitrage, and more…

for Trading with Brokers like Interactive Brokers (IBKR), Binance, TD Ameritrade, Oanda, FXCM, and more…

Performance Optimization and Risk Management require… rigorous Performance and Risk Measurement. The course covers the following Metrics and Methods:

Mean-Variance Analysis

Risk-adjusted Return Metrics (e.g. Sharpe Ratio)

Downside Deviation and Sortino Ratio

Tail Risk Metrics

Maximum Drawdown, Maximum Drawdown Duration, and Calmar Ratio

Deep Analysis of Levered Trading and the Kelly Criterion

Compound Annual Growth Rate (CAGR)

Investment Multiple

and many more…

You´ll have the opportunity to practice what you have learned in various Coding Exercises/Challenges (real data and meaningful questions!).

This is not only a course on Performance and Risk Management for Trading. It´s an in-depth coding course on Python and its Data Science Libraries Numpy, Pandas, Matplotlib. You will learn how to use and master these Libraries for (Financial) Data Analysis, Optimization, and Trading.

Please note: This is not a course for complete Python Beginners (check out my other courses!)

What are you waiting for? Join now and start improving your Trading Performance!

As always, there is no risk for you as I offer a 30-Days-Money-Back Guarantee!

Thanks and looking forward to seeing you in the Course!

Who this course is for:
Traders who are dissatisfied with their Trading Performance
Those who want to generate sustainable Income with Trading
Traders and Investors who want to professionalize their Business.
Traders who want to improve their work/analysis with powerful Python Coding

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