Dr Ernest ChanTrader Dozen: Dr Ernest Chan. Photo: EPChan.com

Trader Dozen: Dr Ernest Chan

Since 1994 Dr Ernest Chan has worked on developing statistical models and computer algorithms to find patterns in large quantities of data. It wasn’t until the late nineties, and the lure of Manhattan's bright lights, that he started to apply these models to the markets.

Now a Managing Member of QTS Capital Management, Dr Chan shares his thoughts from over two decades in the industry by fielding our Trader Dozen questions from interviewer Chris Johnston. Read why he started trading his own money in 2006, why he wants to work until aged 85, and the two key things to look for when deciding on your first job...

The importance of luck is underestimated – so I try to help others less luckyDr Ernest Chan

1. Can you remember when and why you got into trading? (and what do you trade?)

There are two phases of my trading career: working in the institutional world starting at Morgan Stanley, and then working as an independent trader and fund manager. Joining Morgan Stanley in 1997 was a naïve decision of a young man: I wanted to live among the bright lights of Manhattan (and Morgan Stanley’s Times Square headquarters certainly looks flashy). Becoming an independent trader in 2006 was because I didn’t think I could trade profitably with all the institutional constraints. I started my independent trading by trading ETFs, stocks, and futures.

2. What’s your trading style and how do you fit this into your other life activities? Do you trade around your life or does your life/job fit around trading?

My trading is fully quantitative and automated. Hence the actual trading takes little personal time – I am fortunate to be able to work with an amazing partner who is a software whiz, and a very dedicated staff member. That means I can spend my time on research and teaching, and take time off as I see fit.

3. What motivates you to constantly work on improving your trading systems and enjoy what you’re doing?

Intellectual challenge and excitement, a sense of duty to my investors, and a need to provide for my family!

4. Throughout your journey, are you able to pinpoint a moment or a routine that you started doing that then made all the difference to your trading and/or life?

I started trading with my own money in 2006. There is nothing that focuses one’s attention more than risking your own money.

5.I’m presuming that you’ve come up against failure in the past. What has been your approach on getting past these failures and has this evolved since?

Do not make the same mistake twice is my motto. I am very emotionally stable – partly because of my age! Temporary setbacks do not faze me. I intend to live until 100, and work until at least 85. So there is plenty of chance to recover from mistakes.

6. What would you put your success down to? Just being lucky, your intellect and smarts or just consistent hard work? Or possibly a combination?

I thank my parents for their genes and their hard work in putting me through the best schools available. With that foundation, added to some of my own hard work and good luck, I have been able achieve modest success as a trader. The importance of luck is underestimated – so I try to help others less lucky.

7. What do you think sets you apart from others who are trying to be succeed in the algorithmic trading space?

Emotional stability, intellect, and curiosity.

8. What advice do you have for those who fail, give up or never get started? For either trading or something else in life.

Find your edge: Programming? Mathematics? Accounting? Market intuition? Wealth? Social network? And focus on using that edge to succeed. Also, it may make it more fun and productive if you partner with someone else with a complementary edge.

9. Do you set yourself goals? And do you feel that it is a good way to achieve what you want?

My goal is to be Jeff Bezos. No, seriously, I don’t think goals help. I just do my best every day.

10. Knowing what you know now and how you got to where you are today. Is there anything you would like to have done differently, maybe done something earlier in life (or later)?

I wish I were more patient in looking for the right institutional environment when I first started in this business. Morgan Stanley is a great firm, but I think I will learn more by joining a proprietary trading group or quantitative hedge fund. I was unskilled in politics in big sell-side investment banks.

11. You’ve now written three books on the subject of quantitative trading. Can you tell us a bit about why you decided to write these?

Writing, teaching, and generally explaining something in a systematic way is the best way to really know something well. I always derive trading ideas from this process.

12. You’ve had quite the career, starting out at IBM and joining firms like Morgan Stanley, Credit Suisse and various hedge funds. What would you say is the one take away from all your work across these firms that would most useful to someone looking to get into systematic trading or even someone who’s had some experience in this area?

To decide on the first job, the most important criterion is if you feel your boss is a good mentor, and whether the group you join has great potential for growth. Monetary compensation is secondary. I love my group at IBM, which, as many people know, spawned such hedge fund luminaries as Bob Mercer and Peter Brown. Also, lifelong continuous learning is a must, no matter where you are. As an example, I just learned to become a decent Python programmer within the space of about two months, after starting with my high school Basics, then C, Mathematica, C++, Perl, Java, Matlab, and R. You are never too old to learn a new trick!

13. Do you think discretionary trading is going to become a less common practice with beginner traders, as they have access to many resources and tools to create their own systematic strategies, whether that is in Excel, Python, R or through brokers' own proprietary language and platform?

Discretionary trading is like driving. Just because a human decides when to turn right doesn’t mean we won’t benefit from assisted driving technologies (e.g. blind spot detection). Conversely, not everyone needs a self-driving car to get where they want to go. One key ingredient in trading success is market knowledge and intuition. You can’t learn that through programming and AI/ML alone.

Follow Dr Chan on Twitter @ChanEP or head to his website EPChan.com