QuantStart Explains Algorithmic Trading

Over at QuantStart is an article on algorithmic trading for beginners, broken down into sections explaining strategy identification, strategy backtesting, execution, and risk management.  It’s a broad overview without much in the way of specifics, but a good first read if you’re interested in algorithmic trading and want to learn more.  Afterwards, you can visit The Algorithmic Trading and Autotrading Universe to see the myriad tools available to the algorithmic trader.

I like to reference these sorts of articles for beginners both because I’m a recent convert to algorithmic trading myself, and still have much to learn, but also because there is a steep learning curve to enter the world of algorithmic trading.  Few sites formally explain how to formulate trading rules, test them, and execute them.  I myself traded on a fundamental/discretionary basis for years before stumbling across technical analysis and then some of the more quantitative techniques.  But even then, how to get started?  Excel is a great tool to start, as everyone is familiar with it, but it’s not the most robust framework for testing and trading.  Yet the robust tools are difficult to use for the beginner.

Thankfully, we have a new generation of sites emerging attempting to “democratize algorithmic trading,” as the rallying cry goes, but we’re not there yet.  Rizm Equametrics–and before that, Prodigio RTS–seemed like the answer to me, but I’ve been frustrated with the laborious process of building blocks of strategies using their graphical user interfaces (Rizm especially seems more work, as the configuration blocks reset with every misplaced mouse drag).  Quantopian and QuantConnect seem like the next best thing, but still require major investment in learning Python or C#, respectively.  In that sense, “democratizing algorithmic trading” really means providing inexpensive but industrial-strength tools to those who are already familiar with the field, but doesn’t particularly help the beginner who would like to enter the field.  I have no experience with Tradestation’s EasyLanguage, but it seems to me that there’s still an optimal solution out there that uses a trading-aware programming language with a robust back-testing and execution platform in the cloud.  I think traders should be able to trade, not worry about variable types, event handlers, threads, and memory management.  I’m doing well enough with C# and ForexConnect the ib-csharp wrapper for the Interactive Brokers API that this isn’t a direct concern for me anymore, but I would still like to see a better solution for the non-professional / non-programmer crowd.

I will continue to update The Algorithmic Trading and Autotrading Universe as I find new tools.  Perhaps one will emerge which will address this under-served market.

One thought on “QuantStart Explains Algorithmic Trading”

  1. Totally agree that algo-trading is here to say, but I’d love to get more info and details on the partnership. Who will be handling what aspects of things? Who’s doing the backtesting, or will it be a joint venture that both groups participate in?

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