Tradingmarkets – Programming in For Traders

  • Do you already program in Python?
  • Do you program in TradeStation?
  • Do you program in Amibroker?
  • Would like to learn to program?

Python has become the hottest programming language on Wall Street and is now being used by the biggest and best quantitative trading firms in the world. We’re going to teach you the benefits of and how it can make you a more successful trader and allow you to build better trading strategies.

Why Is The Language of Choice By Many Of The Biggest and Best Firms In the World

The best trading firms in the world have the resources and capabilities to program in any language.

They also have the ability to hire the best and smartest traders in the world. When you look at who they’re hiring, there’s one major theme; they’re hiring traders with Programming skills.

You only have to look at the professional job boards to see this.

Many of the top firms are now all requiring their traders and researchers to program in Python.

The reason they’re doing this is they obviously believe is leading to greater trading profits.

“The Best Coding Languages to Learn for Traders in Banks, Hedge Funds and HFT Firms” by Rob Carver - former head of fixed income at multi-billion dollar quantitative hedge fund AHL, and the author of the two books, Systematic and Smart Portfolios.

Python is the preferred language of many quantitative traders because of the extensive availability of packages for data analysis

We can show you dozens of these examples, and now tens of thousands of professionals at the top trading firms around the world do their programming in (not in retail products like TradeStation, Amibroker, etc.).

If you’re serious about your trading, and want to join the elite trading professionals around the world, (and not a bunch of retail traders) then learning is a must.

If not, you’re falling behind!

Briefly Our Story

I started doing backtesting on TradeStation in 1991 and it was the primary language I relied upon to develop trading strategies.

I then moved to Amibroker in the early 2000’s and it along with Excel have been good to me and my clients for years.

In 2019 I realized in order to keep up with the professional quant trading firms, we needed to upgrade to an open source professionally used language.

That language, as so many major quant firms have found, is Python.

Here is Why Many of The Top Firms Use and Why You Should Too

There are many reasons why has become the go-to programming language for these multi-billion dollar fund companies. This includes…

1. It’s easy to learn - You can learn how to program in under 10 hours. In 10 hours, you will be able to do in-depth research, code more complicated trading strategies, and analyze your backtested results better and faster than ever before!

2. It’s faster than most languages. You will spend less time writing your code which leads you to having more time analyzing your results and improving your strategies.

3. It’s Open Source - This means you’ll have access to the same trading code and tools created by many of the best researchers, programmers and traders in the world.

There’s also a global community available 24/7 to answer any questions you may have. Python is widely used and well documented, making solving coding issues a breeze. If you’re stuck on a coding problem, many people out there will be able to help you.

In fact, even a quick Google search usually answers your questions!

4. has the best libraries for data analyses and quantitative trading. This means again you will be using the same tools as professional quant trading desks and hedge fund managers do. This can’t be said for other languages like TradeStation and Amibroker.

This means you’ll find edges in the market faster and more efficiently than ever before.

How To Program With The Same Tools As The Best Quantitative Firms

If you’re interested in joining the ranks of the best quantitative trading firms in the world including multi-billion dollar trading firms like Tudor Investments, Point 72, Millennium, Citadel, and hundreds of other professional trading firms, we are offering a proprietary 10 hour “Programming in For Traders” course beginning on Tuesday, June 23.

“Programming in For Traders”

Here is What You Will Receive

Week One - You'll gain the foundation in order to do your backtesting, research and signal generation.

This foundation will lay the groundwork for you to scale into the upcoming weeks.

Your homework will include learning how to do technical analysis calculations in including moving averages, RSI, and the other major technical indicators used by professionals.

Week Two - You're going to be backtesting in Python!

You'll be writing code in and testing strategies and signals to find market edges. For example, you’ll be writing code using a 2, 3, or 4 period RSI on various levels, such as RSI below 30, RSI below 20, etc.

By the end of week 2, you'll be able to test various market conditions (for example overbought and oversold conditions) and calculate the historical edges that exist in those conditions.

Week Three - You'll be writing full fledged trading strategies. This includes allocating capital to trades, adding risk management tools, and analyzing portfolio returns.

At the end of Week 3, you will be able to run more advanced backtests of your trading ideas and strategies.

Week Four - In Week 4 you'll be analyzing your backtests. This includes analyzing your cumulative returns, analyzing your risk (drawdowns, volatility, etc.), analyzing correlations through time, and a deep dive into analyzing individual signals in order for you to see when and how to best optimize your trading strategies.

Week Five - In Week 5 you'll be writing more advanced backtests. This includes creating signal list generation and managing a portfolio of multiple securities. You'll also learn advanced concepts on position sizing in order for you to optimize the edges you are finding in your strategies.

By the end of this course you will have the ability to find your own market edges, build your backtest, and do a deep analysis of the test results.

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