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Algorithmic Cryptocurrency Trading (Last update)
Learn Algorithmic Trading in Python, Think like a Quant
What you'll learn
Learn how to think about quantitative strategies in a robust manner.
Implement and test your ideas against market data like a professional.
Learn how to do risk management and portfolio allocation with empirical observations.
Build the pipeline from data, simulation, to exchange integrations.
Algorithmic Cryptocurrency Trading teaches the in-and-outs of building robust quantitative frameworks for testing and simulating your ideas for quantitative trading.
Learn about various approaches to testing your quantitative strategies, from statistical models to simulations and industry standards in risk management such as volatility targeting. Combine arbitrary, multiple signals/strategies and walk away with an end-to-end trading system that goes from collecting data to order submission on exchanges.
Learn how to think like about trading strategies like a quant trader. There are two monetizable effects - inefficiencies and risk premiums. An Ichimoku Cloud, Fibonacci Retracement and Stochastic Oscillators are neither of them.
Quantitative trading is not a hobby, and do not treat it as one. The content is designed for aspiring quants, and an introduction into the science and discipline of trading that practitioners contest with.
This course is not a beginner course; financial literacy, and programming methodology is expected. Students are expected to be able to understand code without being prompted, or at least learn how to comprehend medium-sized code systems of hundreds~thousands of lines of code.
Those without programming experience are encouraged to first undergo courses in Python / Programming Methodology / Data Science for Finance courses.
Note:
- this is not intended for high frequency trading (market-making, latency arbitrage)
- this course is not part of the Udemy Deals program, and no Udemy promotions are available. We believe that the material within is highly valuable and the cost price is cost de minimis in your quant journey.
Who this course is for:
This is for traders who wish to learn about automation, or programmers to learn about trading.
Serious students who wish to think about quant trading in a robust framework.
Learn Algorithmic Trading in Python, Think like a Quant
What you'll learn
Learn how to think about quantitative strategies in a robust manner.
Implement and test your ideas against market data like a professional.
Learn how to do risk management and portfolio allocation with empirical observations.
Build the pipeline from data, simulation, to exchange integrations.
Algorithmic Cryptocurrency Trading teaches the in-and-outs of building robust quantitative frameworks for testing and simulating your ideas for quantitative trading.
Learn about various approaches to testing your quantitative strategies, from statistical models to simulations and industry standards in risk management such as volatility targeting. Combine arbitrary, multiple signals/strategies and walk away with an end-to-end trading system that goes from collecting data to order submission on exchanges.
Learn how to think like about trading strategies like a quant trader. There are two monetizable effects - inefficiencies and risk premiums. An Ichimoku Cloud, Fibonacci Retracement and Stochastic Oscillators are neither of them.
Quantitative trading is not a hobby, and do not treat it as one. The content is designed for aspiring quants, and an introduction into the science and discipline of trading that practitioners contest with.
This course is not a beginner course; financial literacy, and programming methodology is expected. Students are expected to be able to understand code without being prompted, or at least learn how to comprehend medium-sized code systems of hundreds~thousands of lines of code.
Those without programming experience are encouraged to first undergo courses in Python / Programming Methodology / Data Science for Finance courses.
Note:
- this is not intended for high frequency trading (market-making, latency arbitrage)
- this course is not part of the Udemy Deals program, and no Udemy promotions are available. We believe that the material within is highly valuable and the cost price is cost de minimis in your quant journey.
Who this course is for:
This is for traders who wish to learn about automation, or programmers to learn about trading.
Serious students who wish to think about quant trading in a robust framework.
