About Me

For most of my life, I traded the news.

Actually, my wife did the trading and I gave her my brilliant insights about what we might want to trade. She’s a buy-and-hold investor, otherwise known as a “buy-and-hope” investor.** Every once in awhile, maybe every year or so, I would have some “fabulous” idea of something to buy. Usually because I’d read about something in the Economist or connected two things that aren’t super obvious. Hardly a great investment plan.

Fast forward to the future. I read Tim Ferriss’ blog a lot. He’s an ardent advocate of hacking your life to get more out of it. Unlike me though, he’s got lots of money, very little time, and needs to leverage his time. I have less money, more time, and less real need to hack my life. I remain ever hopeful though that I’ll need those skills soon.

Tim suggests books by other authors from time to time. One book that sounded interesting was What I learned Losing a Million Dollars, by Brendan Moynihan. The story of Brendan’s early hubris in the commodities markets makes for a fun tale (at his expense). But the trading advice can be summed up very simply. Spoiler alert: don’t bet the farm, let your winners run, and cut your losses early. My wife and I had been doing two of those three things. The whole “cut your losses though,” that was a new one. I mean it made total sense to ME, but I only get 48% of the voting rights.

Now fast forward to the height of the Ebola panic. CNN’s website lists a number of pharmaceutical companies with promising drugs. “Investment Bonanza!” I shout (to myself, in my head, where no one can hear me). I get permission from the wife to invest in one of these companies. The stock is up, the product sounds promising, and I can use one of these new-fangled “trailing stops” I’ve just heard about to keep me from getting screwed.

One of the patients died who was being treated with this experimental drug. The stock takes a nose-dive, and my trailing stop kicks in and we lose a little money, but not that much. Hey at least I was on the right side of the ethnical equation. I was betting the guy would live, as well as hoping to make money! It would have been just a little horrible to short the stock in case he didn’t make it.

That experience made me want to find out more about investing. I went from “news” trading to fundamentals trading to technical analysis…well ok I pretty much looked at TA for about five minutes and yelled “BS!” and moved on. It looks too much like reading tea leaves and palm reading.

Rules-based trading, with hard numbers and out-of-sample testing is very important to me. I consider myself a “quant-a-be”. I’m not a real “quant” because everything I know is self-taught, and I’m just never going to go back to college for four years of a statistics degree (or whatever those people major in).

Sometimes at night I even dream about bar charts. That’s a little weird.

But hey, I have some good ideas from time to time. Even without the fancy financial pedigree. Which is why I call this blog “throwing good money after bad”.

** She’s coming around though, and we’ve parted with some real dogs and even some profitable long-term trades after they dropped below thresholds. Progress!

3 thoughts on “About Me”

  1. Hi Matt

    I do appreciate the humor, and I agree you were on the moral side of the trade with that long pharmaceutical stock position, but regarding your ‘day job’, I would say the moral thing to do is to try to stop the poor man in probably his most difficult day of his entire life.

    Ok, enough with the easy jokes on the misery of married men, and let’s get back to our own misery: Mr. Market. 1 question: What data do you use for backtesting? You wrote somewhere that you tested all stocks that were members of russell 1000 at moment X. How do you know that info? You also mentioned AmiBroker; I am not familiar with that; AmiBroker provides you this info (the members of stock index X at point Y in the past)?

    1. Hah! 🙂

      As for data…

      I use Norgate Premium Data for my end-of-day data, and recently subscribed to the delisted stocks portion of it as well as the currently listed stocks. I don’t have data for historic index constituents. As a time-saver, I will usually develop using the current list of Russell 3000 members, but test at a point in the past when some of them might not be members. It speeds up processing time for me to limit to a subset. But then when I think I’ve got a good system, I will then test on ALL stocks in the database, including delisted stocks. I can’t select for historical index members, so I must winnow them out another way. I’ll usually restrict my test to a historical price being over X and average 10day volume being over Y. This is actually a tougher test to pass, since it might pull in some stocks that weren’t in an index at the time. At the very least, it doesn’t skew the data toward false positives.

      There are backtest systems that allow you to specify historical index membership, along with historical fundamental data etc. Portfolio123 is a good example of an online backtester that looks pretty rigorous. Many of these systems though have safeguards in place that try to prevent future leaks, but at the expense of not being able to test certain styles of trading. For example, many of my systems buy or sell at the close, if the close is less than or greater than some value. Technically you can’t know the closing price before it happens, so these systems won’t allow a system like that. But in reality, you can look at a price 15 minutes before the close and say to yourself, yes that’s way over the minimum so I’m going to trade it. Amibroker will allow you to test that way if you want. For me, Amibroker is just enough nerdy coding to do what I want, without going the Python/R route and falling down the rabbit hole of automated quant trading.

      Hope that helps!


      1. I see, thanks. I use the free end-of-day data from Quandl, and I use my custom code written in Ruby to test (read: invalidate) my ideas. I use Ruby because at the moment I started this journey, and now too, Ruby was the language I preferred. I have my small library of indicators, and I can code new ones when I find something that may look interesting, and of course my library is not even close to the existing Python or R open source libraries, but for now at least, I don’t want to switch to Python/R because I don’t think that 1 extra indicator is what’s missing me in order to beat Mr. Market. Still, I won’t recommend anyone use Ruby, because based on my experience so far, I can say Ruby is incompatible with profitable strategies :D.

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