August 6

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Getting Down To Business!

By Kevin Davey

August 6, 2018

Algorithmic Trading, beginners, Kevin Davey

In the previous parts of this 3-part article (see part 1 and part 2), I introduced you to algo trading, and then discussed features of algo trading, along with advantages and disadvantages.

Algo trading can definitely help you compete with the “big boys,” but it is not automatically a “supertrader” creator. There is no easy way to trade, and algo trading is no exception. Rest assured there are retail algo traders out there surviving against the hedge funds, commodity trading advisors, etc.

At this point, it is time to set aside theory and words, and get down to business: the business of actually starting to algo trade. In this final section, I’ll give some tips on:

  •             Testing
  •              Selecting A Trading Platform
  •              Info On Popular Platforms

Testing

One key feature of algo trading is testing. The idea is you historically test an idea to prove its profitability BEFORE you actually trade it live. There are a few different ways to test. You could manually test your approach by recording entries and exits on a chart by hand. You could also hire a programmer to code and test your idea. You could even create your own backtester, using a computer language like Python or R. While all of those are possible alternatives, I like retail trading software.

Trading software is probably the best one for most retail traders. In today’s market, there are literally dozens of trading software packages designed for the retail trader. All have pros and cons, obviously, but the best of them allow traders with little programming knowledge to successfully develop their own trading algorithms.

The great thing about the retail software option is that once you know how to operate the software, and do some simple strategy programming, your focus can be on developing algorithms – exactly where it should be.

Retail Trading Software – Pros

  •              Most platforms are easy to use and learn
  •              Used and debugged by other traders, so you can trust results
  •              Relatively inexpensive, some platforms are even free
  •              Easy to share strategies with other traders using same software

Retail Trading Software – Cons

  •              Easy to trick most packages into giving false results
  •              With so many choices, hard to pick “right” platform
  •              If software company goes out of business, algos might be useless

This is why I recommend standard trading software for most retail traders. The available software is just too powerful and convenient to disregard.

In case you are wondering, I started out my trading career with the first option, manual backtesting. What a pain! As soon as I had access to a personal computer at night, outside of my regular career working hours, I switched to option 3 – building my own backtesting platform. I did that for a number of years, and had more success in programming the platform than I did in building the algorithms.

I had a few decent algos – or so I thought – but after talking to some more experienced traders, I realized there were issues with my bespoke platform that I was not accounting for properly (for example, some of the intricacies of rollovers). I realized I had to make a drastic change.

Eventually, I decided to go the retail platform route, and I got a copy of Tradestation. I was very scared and intimidated at first by the package (for example, for years I trusted only “buy/sell next bar at market” orders), but eventually I came to understand and felt comfortable with strategy development. And guess what? The algo strategies I started to build became a lot better!

Today, I have been using Tradestation for over 10 years. And baring some unforeseen circumstances, I see myself using it for years to come.

Selecting A Trading Platform

Back when I started using a retail trading platform (Tradestation), there really weren’t too many choices out there. And Tradestation was far and away the best; it had the most features, its backtesting was the most accurate, support was superb and its user group was active and helpful.

Fast forward to today, and the retail software platform landscape is a bit different. Now, there are dozens of trading platforms, and most are pretty good. Each one has some specific “niche” areas it tries to address, usually areas that Tradestation was traditionally not as good at. Of course, Tradestation has responded, and is continually building a better platform. The competition is raising the standard for all platforms, which is tremendous.

This is all great for the retail trader – more competition, better features, lower costs – but it can be overwhelming! Which platform is the best? Which platform has the features you are looking for? Which platform is the easiest to build with? The list of questions goes on and on.

So, I’m not going to try to tell you which platform to, but I will identify some “must haves” that you want for algo trading. In the section after this, I’ll also tell you the most popular platforms, based on trader surveys I have done in the past few years. You might think popularity is a poor criteria to use, but I think it is important. You want a trading platform that will be around for years and years, since transferring your algos from a defunct platform will be cumbersome.

Here are some of the features that are important to an algo trader:

Charting Capabilities - Many times, during the idea creation phase, an algo trader will want to see his or her idea – an indicator, histogram, bar patterns, whatever – in action. A good charting module in the software will help with that.

Figure - Charts Can Help You Visualize Aspects Of Your Algorithms

Broker Integration - Some retail platforms, such as Tradestation, are tied directly to one brokerage (in this case, Tradestation Brokerage). Other platforms, such as NinjaTrader, have a few limited choices in brokers. Finally, some platforms (like Multicharts) have a huge selection of brokers to choose from.  There are pros and cons to each approach.

So, searching for a trading platform might also be a search for the proper broker. 

Ease of Programming - Most good platforms offer you the ability to create your own indicators, strategies, etc. – in addition to providing standard indicators with parameters you can change and optimize. Of all the topics discussed in this section, I think this is the most important. Having a programming language you can easily learn, and feel comfortable with, is a big deal. Spend a lot of time upfront investigating what is best for you, and it will pay dividends down the road.

Integrating With Market Data - Most of the premier trading platforms these days integrate well with market data. Make sure the platform you choose connects with the data you need.

Standard Indicators and Studies - Before selecting a platform, make sure it has a long list of indicators and functions already programmed in. Most platforms do, but it is always good to check first.

Optimization - If your code has any parameters or numbers in it, for example the number of bars in a moving average, or the buy threshold in an RSI calculation, chances are at some point you will want to optimize that number. While too much optimization is definitely a bad thing, you at least will want the capability to do it in the software.

Walkforward Analysis - In my algo development work, I use a technique called walkforward testing to create “out-of-sample” results. These results tend to mimic live trading better than traditional “plug and chug” backtest optimizations.

Walkforward testing is an advanced topic, one that a new algo trader might not need right away. But it is a good feature for trading software to have. 

Trader Community - Having a large and active trading community is critical for any software platform you choose. A vibrant community is a definite plus, and should be a very important part of your search criteria.

Live Trading & Automation - Once you create and test your algo, the last thing you want to do is convert it or move it to a different platform in order to trade it live or automate it. You want a package that does it all: development, test, and automated trading. 

Info On Popular Platforms

​In 2017-8, I asked readers of my blog to tell me which trading platform was their favorite. Here are the latest results:
- Worldwide Survey, Trading Platforms

Figure - Worldwide Survey, Trading Platforms

Depending on your needs, my guess is one of these platforms will be sufficient for your algo trading. Contact info for each of the major ones is given below:

Conclusion

This 3-part article (see part 1 and part 2) has covered a lot of ground about the basics of algo trading for the retail trader. Trading is a tough world, but algo trading may just be a good route for your trading success. If you follow the steps in detailed article series, you might actually become as good as the professional traders you are competing against! It is hard work though, and never seem to get very easy. Remember that. I always tell prospective traders, “Trading is the hardest way to make easy money!”

​-- by Kevin Davey from KJ Trading Systems

Kevin Davey

About the author

Kevin Davey is a professional trader and a top performing systems developer. Kevin is the author of “Building Algorithmic Trading Systems: A Trader's Journey From Data Mining to Monte Carlo Simulation to Live Trading” (Wiley Trading, 2014.) . He generated triple digit annual returns 148 percent, 107 percent, and 112 percent in three consecutive World Cup of Futures Trading Championships® using algorithmic trading systems.

His web site, www.kjtradingsystems.com, provides trading mentoring, trading signals, and free trading videos and articles. He writes extensively in industry publications such as Futures Magazine and Active Trader and was featured as a “Market Master” in the book The Universal Principles of Successful Trading by Brent Penfold (Wiley, 2010).
Active in social media, Kevin has over 15,000 Twitter followers. An aerospace engineer and MBA by background, he has been an independent trader for over 20 years. Kevin continues to trade full time and develop algorithmic trading strategies.

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