Trading on the (Super)Fast Lane

A New York Times article I read recently that describes high-frequency trading.

I was a little worried after reading this at first, but I don’t think that small traders need to be too concerned. Given that my holding periods may last from a few days to a couple of months, I doubt that any high frequency market manipulation could do any serious damage to my positions, other than costing me a few additional points of slippage. It might seriously impact day-traders though, since their performances matter largely on their fill prices. Any thoughts?

The Real Story Behind Airline Ops

Two interesting articles from the NYT Freakonomics site: one about pilots, and the other answering your airline questions.

The first one in particular is pretty much a slap in the face. How safe are these so-called “budget carriers” anyway? It’s true that the incentives for a qualified, safe pilot don’t seem to exist in the current system. Then again, I might be wrong – maybe they are getting incentives from sources other than pure revenue, but I highly doubt it.

And from the second article: “The airline business has never really been able or allowed to operate under a truly free market environment. The government continues to meddle in the business. It doesn’t let airlines go out of business as a rule, though several of the current airlines should have been allowed to die. Trust the market.”

Mean Reversion Techniques

Apologies for the long absence from blogging. I’ve spent the last week moving everything I’ve owned for the past 3 years to Singapore, and I’m still suffering from jetlag – hence my blogging at this ridiculously early hour.

Just before I left the United States, I purchased a book by Larry Connors after reading one of his articles on his proprietary Double 7s Strategy in an issue of Stocks and Commodities. The book, Short Term Trading Strategies That Work, includes a number of high-probability strategies that relate to stocks and ETFs. From what I gather, the underlying philosophies are:

1) Trade in the direction of the long-term trend.

2) Stocks and ETFs are mean-reverting.

3) Stops hurt the performance of a mean-reversion strategy.

He claims that his strategies are backed up by rigorous statistical testing, and includes a number of statistics to demonstrate the robustness of his strategies. He seems to focus mainly on hitting high-probability trades. However, after running a few tests of my own, I’ve discovered that:

1) These strategies work wonderfully with most stock indices, but strangely not for futures, forex, interest rates, and commodities. I’m hypothesizing that perhaps equities are truly mean-reverting, while other securities seem to be subject to large, defined trends. I didn’t have any ETF data to test his strategies on, but I suppose that his strategies would have worked well on them as well.

2) The parameters given are not always ideal – they can sometimes generate a high percentage of “right” trades, but the drawdown of any one single trade could possibly be fairly large – something most traders might not be comfortable trading. This also results in a relatively poorer Net Profit/Max Drawdown ratio.

3) In contrast to Mr Connors, I still believe that stops improve performance. To test this, I included some stops and re-optimized the parameters using both in and out-sample periods. To my delight, stops dramatically improved the Profit/Drawdown ratio, and sometimes even increased gross profit. The only trade off was that it lowered the probability of right trades. Even then, the percentage remained relatively high (> 50%)

This might be a good, diversified technique to trade equities with, given that my other trend-following strategies do not seem to work very well in this one area.

I Actually Find This Hilarious

Taken from the Facebook fan page of my favorite economics blog:

Q: How many Chicago School economists does it take to change a lightbulb?

A: None. If the lightbulb needed changing the market would have done it already.

Words Of Wisdom

Paul Tudor Jones gave an excellent 9th grade Commencement speech. (taken from Michael Covel’s blog)

The focus of his speech was on failure: how to deal with it and how it makes you better (harder, faster, stronger), but one particular paragraph that wasn’t related to the topic struck me:

“Don’t get me wrong – serving others is really, really important. It truly is the secret to happiness in life. I swear to God. Money won’t do it. Fame won’t do it. Nor will sex, drugs, homeruns or high achievement. But now I am getting preachy.”

… What? Money and sex won’t do it? Damn. (just kidding, just kidding..)

And The Search Goes On…

An update on my research:

Research is becoming a sort of an obsession lately. I’ve been doing it almost every day, from after lunch to the early hours of the morning, with a few breaks in between for meals and the gym. After a morning on Atlantic City beach last weekend, the guys went to play volleyball, the girls went shopping… and I planted myself at a Starbucks to do research. It’s that intense. And exhausting.

I don’t think I’m a workaholic. It’s just that I hate the feeling of going through an entire day’s worth of research and not be able to show anything for it, which has happened several times now. Coming up with trading ideas is easy, testing a system out is easy, but trying to find a system that meets all of my criteria is hell:

1) The system needs to have Net Profit/Max Drawdown ratios of above 3 in both my in-sample and out-sample periods (out-sample periods need to be at least 2 years)

2) The system equity curve should be relatively smooth and upward sloping, and not marked by many flat/negative periods and a few big upward moves. (I know of some trading styles that adopt this sort of equity curve: losing a little for many periods and then locking in the rare, huge upward moves, but that isn’t my style.)

3) The system should have a stop in place at all times whenever I have an open position.

4) There should be at least 30 trades in the entire sample period in order for me to gauge the statistical significance of each trade’s expectancy.

5) The system should still yield a Net Profit/Max Drawdown ratio of at least 2 for both in-sample and out-sample periods even after taking away the trade with the biggest gain. This is to ensure that the good performance wasn’t due entirely to luck.

The first three criteria were relatively easy to meet. I think I have close to a hundred examples of supposedly “good” market-system pairings, but very few that meet criteria #4 and #5. In fact, I spent an entire day last week testing out criteria #5 only to realize that… I had less than 3 market-system pairings, from an initial 50-ish. Bummer.

Things have since improved since then. My ATR system seems to be the most robust compared to other systems – after a week’s worth of testing, I found that it could trade 5 markets so far: the SGD/USD, the EUR/JPY, T-Notes, the HSI, and the Nikkei 225.

Just today, from a sheer stroke of luck or brute force of will, (or maybe I’m just getting better at this), I found 2 additional markets for my Donchian Breakout system to trade. It now trades 4 markets in total (the same markets at the ATR system, with the exception of the Nikkei, which I have yet to test out).

Some things I’ve noticed/thought of:

1) I’m not sure if the amazing performance of my ATR system is due to it having a high number of parameters – there might be a danger of overfitting. However, an out-of-sample test is one of the best defenses against overfitting, and the system performs well in both in and out-of-sample test periods. Still, I’ve optimized different parameters for each market, so I must expect that the actual performance might be slightly lower than what I’ve tested.

2) It’s always good to optimize based on “normal” times (such as the run-up from year 2000 to 2007), since those are the conditions under which the market normally operates. However, it is almost critical to include fat-tailed events (such as October 2008 to present) in the out-of-sample period to see if the system can withstand such conditions. I’ve cheated a bit in this area by using Neuroshell’s papertrade function, which gives me the best performance in the out-of-sample period based on in-sample optimization. However, I guarded against this by ensuring that the in-sample period performs well too.

3) Sometimes, less rules help to improve performance. I was stuck on my Donchian system for the longest time. Today, I experimented removing the exit rule of exiting on breakouts, and simply relied on a trailing percentage stop to exit my trades, and I found that it was much easier for me to generate trades that performed well. Perhaps I should experiment removing some parameters from my ATR systems, though I don’t see how that can be done. Hmmmm.

Ok I think I’ve been working too hard. I need to take a break and watch Friends or something before I go insane.

Risk

“Many people share the view that risk is bad. As they see it, risk should be avoided – even shunned.

I don’t.

I like risk. I embrace risk.

If your goal is to make small, incremental improvements, then you don’t need to play with risk, If you want to make giant leaps forward, you cannot avoid it.”

- from “Inside the Mind of the Turtles”, by Curtis Faith.

Goldman Holdem

Apparently, Goldman Sachs has been behind every major market manipulation since the Great Depression.

My favorite line of the article describes Goldman as “a great vampire squid wrapped around the face of humanity, relentless jamming its blood funnel into anything that smells like money.” Talk about strong imagery.

… No wonder it’s THE choice employer for every Whartonite sheep I know.