Monthly vs. Daily Trading – updated

2011 offered challenging market conditions for trend followers (as illustrated by both the State of Trend Following and the Trend Following Wizards reports). The second half of the year in particular threw a few “curve balls”, in the form of wild volatile moves with inter-market correlations spiking up.

With this backdrop, I wanted to revisit the daily vs. monthly trading comparison run a bit over a year ago, to check the impact of these volatile moves against a system trading on a monthly basis (2008 had proven “costly” to the monthly trader; would 2011 be similar?).

DAILY V. MONTHLY GOLDEN CROSS

As a reminder, in that post, I compared two versions of a moving average cross-over system (Golden Cross) tested on daily data. Both versions generated the same trading signals, but the first instance executed signals on a daily basis (as new signals were generated) while the second instance executed them at the end of the month.

The results did show that there was little difference in the monthly version versus the daily one, with alternating periods of under-performance and over-performance; the daily version ultimately coming out on top.

Re-running the test with updated data (until the end of last month) still gives similar results:

Note that I “deleveraged” the system to reduce the drawdown (from 50%+ in previous test) to more manageable levels, so the performance numbers are not directly comparable.

IMPACT OF EXTREME MARKET CONDITIONS – ZOOM INTO 2011

One of the empirical observations from last year’s run was the impact of 2008 and its dramatic market action, on the two systems. During that time, the daily system clearly over-performed the monthly one. One possible interpretation is that the monthly system was “too slow” to follow the extreme moves of that period.

Did the same thing happen in 2011?

By zooming in on the 2011 performance, it appears that the answer is.. No.

Well, let’s declare it as a tie between the two: similar results for both systems, but the monthly edges out the daily on the CAGR stat, while it is the other way around for the Max Drawdown stat.

As I was preparing this article, I came across this video from Mebane Faber about his Tactical Asset Allocation Model. In one of the points, he highlights a similar over-performance of his monthly model vs. the daily and weekly ones.

A possible explanation could be that monthly trading allows the system to side-step some of the whipsaws brought by short volatile trend reversals (although – surprisingly… or not – the trade count does not vary a lot between the two versions).

MONTHLY TRADING A VIABLE OPTION?

So it seems that “monthly trading” still held up as a viable option through 2011. Of course the same caveats from last year’s post still applies: most importantly that these results are only derived from a single test for example.

Additionally, a very good point made in a comment by reader Pumpernickel on the original post highlighted the fact that the futures back-adjusted contract time series used in the back-test did imply daily “roll-over” monitoring and trading, since they can roll any time in the month (whenever liquidity shifts). Additionally, monthly roll-over might be all but impossible for these financial instruments that completely roll over a few days every month.

So, monthly trading of futures might not be a practically viable option. However, the main take-away from this comparison is that the trading signal execution frequency does not seem to have a strong impact on the results.
It could be assumed that the same stands for weekly trading, which was suggested by other readers and might represent a better compromise for futures trading

Yet, another alternative could be to switch from trading futures and trade ETFs instead, a subject covered in Anthony Garner’s practical guide to ETF trading systems. Futures act as good proxies to their corresponding ETFs – something discussed in the book and tested here – so the monthly-versus-daily comparison in this post should be transposable in the world of ETFs.