How I Found Success in Trading Through Automation after the Long Suffering
There’s no shortage of “90% of traders lose money” type articles floating around the internet. The kind that tells you why traders fail and what you can do to avoid being one of them. I hope this anecdote isn’t another one of those, but I wanted to share my personal experience of how I found success in trading through automation. (This is 12/9 post for Trading API Advent Calendar 2018)
The Well-Trodden Path of Failed Traders
Having built a career in the investment industry, I thought I had a leg up when I decided to give trading my personal account a shot. I networked with day traders, posted on online trading forums, read trading books, and studied technical analysis. How hard could it be?
I already had a brokerage account for my IRA, so I was able to trade right away. Drawing lines on stock charts and applying technical indicators, I made buying and selling decisions throughout the day. If you asked me what my edge was, I’d probably have told you that I was able to predict short-term prices by reading charts and order flow, or that I was able to determine how much news or earnings should affect a stock better than the market could. It seems unlikely in hindsight. And so I followed the well-trodden path of failed traders. In the post-mortem, I suffered from:
(1) Lack of discipline
- My profits and losses (P&L) affected my emotions and caused me to override predefined stops and targets and average down or chase prices arbitrarily.
(2) Lack of quantifiable edge and accountability
- Using technical analysis to make discretionary decisions, I was able to justify my trading based on moving targets and the benefit of hindsight. I lacked a definable edge that could be observed over a large number of trades.
(3) Commissions
- I often traded fearfully, constantly entering and exiting on tiny price moves. Some days I’d have traded hundreds of times, and even though my gross P&L would be positive, my net P&L would be negative.
(4) Slow reaction time
- I simply could not react fast enough. Whether it was entering a trade based on news or earnings, or exiting a short-term technical trade, I often submitted limit orders too slowly and missed fills because of it, or I submitted market orders and suffered significant slippage.
(5) Screen burnout
- Looking at stock charts, order books, time and sales, and news all day is tiring. I had to process a continuous flow of information and be ready to act on it at any moment. It was exhausting.
(6) Lack of scalability
- I only had so much time and energy during the day to trade. I couldn’t possibly monitor thousands of stocks and actively trade all opportunities.
Down but not out, it wasn’t long before I again found myself drawn in by the intellectual challenge and potential financial gain of trading. But I knew something had to change to avoid suffering the same fate as before. It seemed all too obvious that automation was the answer, and thus I began the journey toward becoming an algorithmic trader.
Automation isn’t a Silver Bullet
I’ll be the first to admit that automation isn’t a silver bullet. It doesn’t guarantee success or profitability whatsoever, and it’s filled with its own “gotchas”, risks, and limitations. But automation provided me with much-needed structure and discipline.
I was forced to define strategies using hard rules, expressed as algorithms comprised of many conditional if-then-else statements. And it allowed me to scale in a way I could never have achieved otherwise. The computer could monitor thousands of stock prices in real-time and act on all opportunities, regardless of how short-lived they were. Lastly, regardless of my P&L, the computer would continue to faithfully execute trades based on the instructions that it was given.
There was no hiding from an automated strategy’s results. No rationalizing losses that might grow over a large number of trades. Automation didn’t solve the burden of trading commissions, but then again I didn’t have access to alpaca.markets (brokerage services are offered through Alpaca Securities LLC) at the time!
Strategy Logic in Tens of Lines of Code
I’ll save the story about how I learned (and continue to learn!) to program and analyze data in Python for another time. Along the way, I grew my toolkit to include backtesting/trade simulation, statistical analysis, and machine learning. While there are many uses for such tools, for me personally I found success first and foremost by capturing relatively simple trading edges with automation. Strategy logic that even a child could understand. Strategy logic that could be represented in tens of lines of code.
Your journey probably won’t be the same as mine, and trading is difficult no matter how it’s done, but if you are struggling as a trader or investor, I urge you to explore whether automated trading can help you (even if you can’t program, nowadays it’s pretty easy to find a contract developer to do this for you).
Technology and services are offered by AlpacaDB, Inc. Brokerage services are provided by Alpaca Securities LLC (alpaca.markets), member FINRA/SIPC. Alpaca Securities LLC is a wholly-owned subsidiary of AlpacaDB, Inc.
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