@ Trader's Expo: A Day in the Life of a Trader

The recent Trader's Expo was held in New York. I went as a reporter for seeking alpha. Trader's expo is a mostly retail trader event. Many of the products and promises sounded like they did when I first started trading futures when I was in high school in Iowa. I would go to sleep with a Soybean and one lot yen position on hoping not to get a margin call after delivering pizza all day. My risk control wasn’t the best.

The banners and booths shout, “Make a million, signals that ride the trend, instant quotes, faster, better cheaper and free.” The computers are faster, the displays show thousands of indicators and the transaction speeds and spreads have gotten better as the costs have gone down…and yet.

And yet, the average “trader” still probably gets taken to the cleaners. I remember reading a study in the late 80s that indicated 80% of futures traders lose money or shut down their accounts, this is probably the same for active ETF and currency traders. The reason is simple: the deck is stacked against them. Most mutual fund investors actually get returns below the average of the funds the invest in. They buy high and sell low, it is the comfortable psychology.

Without a process or plan it may be cheaper and more sensible to go the local dog or horse track than be a retail trader. Here are a few reasons why.

With zero transaction costs, zero commissions and zero slippage your actively traded mean expected return is negative. Yes you read that correctly. The more leverage you put on based on Siegel’s paradox, the faster you will sink.

It works like this: assume your trading results are IID (independent and identically distributed) what most people think of as random. Let's also assume that these variables have a mean variance of 20%.

You Mr. Day Trader will start with $10,000. Now what happens if our first trade / gamble loses 20%? We are sitting with $8,000 in our account. Lo and behold your next position returns 20% on your new portfolio, you may believe you are back to break even….hold on there partner, you just got back to $8,000x1.20=$9,600 a 4% loss. Hey that’s not very fun. This is known as Siegel’s paradox and it gets amplified with leverage. The inflection point in the relationship is around 13% loss or draw down. Using lots of small leveraged bets or thin slicing the exposure leads to the same result.

When one piles on transactions cost, slippage etc. and the short term vs. long term tax situation, the retail trader is swimming against a swift current and most likely doesn’t know it.

Add in slippage and commissions which put further drag on a portfolio and the average retail trader doesn’t stand a chance as they don’t have a plan or understand that maximizing terminal wealth is a disciplined marathon.

Many look for systems, signals and information that will make them millions. As Henry Ford said, “many times opportunity is missed because it shows up in coveralls disguised as work.”

Trading for a living or beating the indexes is challenging to say the least unless one has a process, a deep understanding for the nature of risk and the long term mechanics of increasing terminal wealth.

There were some interesting prosumer tools and talks at the show and I would like to highlight those. www.ac-markets.com gave an interesting talk on the carry trade in forex, I am still waiting for Melvin to get back to me with the White paper.

Fidelity showed off Wealth lab 5.0 which is starting to look like a real professional tool. This isn’t another moving average back testing toy, but rather a system that supports full c# and allows portfolio level back testing, analysis and execution. Wealthlab 5.0 is supposed to release fundamental data sets in the near future, but until then if you are comfortable with a little C# then some more robust analysis could be done.

For the high frequency professional crowd, executing through fidelity wouldn’t cut it, but if you develop fundamental screens, end of day technicals or want to try out portfolio ranking systems Wealth lab may be for you. Again, the fundamental dataset isn’t supported yet, but they have said it will be soon. Another important weakness in wealth lab is the lack of a built in optimizer. Typically optimizers succeed in only giving you a high ordered polynomial curve fit and are more trouble than they are worth. Having used Genetic algorithms and Neural nets in the past, I can only offer a big 'be careful' that your sample size is big enough and that whatever approach you use works across multiple markets and regimes.

If you are a retail trader, I would suggest extending your time horizons and studying the underlying investments looking for long term value. If you insist on being a trader, think about the long term and work back from there. Ernest Chan’s new book is a great start and remember the current is very strong.