Sunday, March 30, 2014

03/30/2014 End of Quarter report

End of quarter. Time to take a peek at the Sector Fund being managed by Gold Coast Advisors LLC.

The current return, year to date, on the Sector Fund is 11.32%.

The model it is based on shows an ideal return of 11.72%.

That’s a reasonable margin for error, and well above both the market and the benchmark (from the average return rate in the 15 year backtest).

The Sector Model is based on the observation that sectors take turns outperforming each other.  The sector rotation metrics are proprietary, but the logic is rather basic: breadth, volume, and price go together more often than not.  When they don’t, the model looks for the greatest disagreement between the three and invests in the sector most likely to mean revert.

On occasion it will whipsaw, but the average holding period is a month.

The Sector Fund follows the model in a timing window that allows for free trades, so whipsaws don’t cost investors anything in the exchange.

This offers small investors two advantages normally reserved for large institutional investors:

1)     Since there is no trading cost, a 300 dollar investment will get the same return rate as a 300,000 dollar investment.

2)     Since the model is defensive, it offers greater outperformance in bearish times than in bullish times, which serves as a kind of hedge.

I’m quite pleased that Gold Coast has found a way to give the same value to the little guy as to the big guy, and they’re off to a good start.




  1. Tim, the sector model is indeed performing ridiculously lately (here, I just jinxed it, didn't I). Would you attribute most of that to the mean-reverting concept or to the machine learning optimization?

  2. Probably a little of both. The caveat is that mean reversion works both ways.

    But the backtest actually performs worse than real time experience because ETF constituency data gets less accurate the further you go back (some of the former holdings no longer exist, for instance).

  3. There are survivorship-bias free databases, but they aren't cheap. What timeframe accuracy do you need for market data?

  4. True. I've accessed Compustat in the past. For now I'm content to use it as a benchmark to be beaten, especially since I've been using earlier drafts of this model live for the past three years.

  5. Ditto, Compustat Xpressfeed which was rather expensive but data accuracy was good. The market data was EOD only, so it's inadequate for intraday trading signals, unless you only use it for constituency info and source the intraday data from another feed? At least for S&P 500 equities, it's not like companies "disappeared" but merely left the index, etc.

  6. There's also the problem of constituency itself (which you just mentioned). I tried to get the monthly histories from SDRS, but their histories were not that granular, and (which is worse) were corrupted. They sometimes had stocks in the wrong sectors entirely. When I tried to get corrected data, they were unable to do so.

    The nearest I could get for the backtest was a reconstruction I had to piece together myself for which of the presently existing stocks were most likely to have been in or near the top holdings for any given time period.

    After weeks of work I got something that was good enough for a sanity check, but in no way could be considered a pristine reproduction of what would have occurred.

    The good news, though, is that the worse the data was, the worse the returns were. The OPPOSITE would have been a problem. I'd much rather under promise and over deliver than over promise and under deliver.