What has Worked in January?

After my calendar analysis of the Russell 2000 proved to be right on target (up more than 5% since that point), I couldn’t resist but to take a similar look at the month of January. My universe was my list of futures. On the long side, the top three (sorting done by winning months) were:

Read More

Is the Russell 2000 primed for a Long?

Today over a coffee, me and a friend did a quick analysis on the Russell 2000. The reason was that I was holding a short, and was debating whether to close it or not. Not only the outcome of this analysis made my action clear, but it also surprised me quite a bit. Here are the monthly statistics for the month of December.

Read More

Parallelism via “parSapply”

In an earlier post, I used mclapply to kick off parallel R processes and to demonstrate inter-process synchronization via the flock package. Although I have been using this approach to parallelism for a few years now, I admit, it has certain important disadvantages. It works only on a single machine, and also, it doesn’t work on Windows.

Read More

Went Long on the S&P 500

It has been a while since my system had a position in the S&P 500, but it’s back. Went long at the close today.

Max-Sharpe Allocations for December

December is going to be interesting, mostly from a performance point of view. Based on seasonality, emotions and gut feeling, I’d go mostly into stocks, mostly US. My Max-Sharpe approach tells me otherwise, and I will stick with the boss’s allocations. Here they are:

Read More

Storing Forecasts in a Database

In my last post I mentioned that I started using RSQLite to store computed results. No rocket science here, but my feeling is that this might be useful to others, hence, this post. This can be done using any database, but I will use (R)SQLite as an illustration.

Read More

Synchronization for R with the flock Package

Have you tried synchronizing R processes? I did and it wasn’t straightforward. In fact, I ended up creating a new package – flock.

One of the improvements I did not too long ago to my R back-testing infrastructure was to start using a database to store the results. This way I can compute all interesting models (see the “ARMA Models for Trading” series for an example) once and store the relevant information (mean forecast, variance forecast, AIC, etc) into the database. Then, I can test whatever I want without further heavy lifting.

Read More

Grouping of Commodity Futures

The volatility seems to be leaking quickly out of the stock market, and it seems to be back to its pre-dominantly bull-mode, which has been going on for a while now. So time to go long and wait for the next opportunity for more trading?

Read More

Max-Sharpe Allocations for November

At the beginning of October, this strategy went heavily into treasuries (TLT), to the tune of 70%. The rest was SPY. With all the turbulence in October, this proved to be a good setup – yielding about 2.3% for the month.

For November, the strategy allocations deviate a little bit from the original strategy (which implementation was posted originally on the Systematic Investor Blog).

Read More