Above is a diagram by Andy Lo, illustrating how alpha morphs into beta over time, as the initial strategy becomes more common/popular. Could the phenomenon affect Trend Following? And could the 2/20 fee structure charged by CTAs now be inappropriate?
This Beta of Managed Futures paper (PDF) from the Conquest Group hints that Yes, the original alpha provided by Trend Followers has taken the path down the beta-fication route.
Further along these lines the paper claims that Trend Following Managers sell Beta disguised in Alpha clothes:
CTAs: Alpha or Expensive Beta?
Returns can be broken down into alpha (excess returns due to skill), beta and the risk free rate.
Beta is ubiquitous and easily replicable and therefore cheap, while alpha is rare, hard to replicate and therefore expensive. It makes sense to pay a premium for alpha, but there is no need to do so to access beta, as it is available from multiple, competing sources. CTAs purport to provide alpha and justify their fees on that basis. It is clear, however, that there is a good deal of beta in the returns of many alternative investments, which raises the possibility that alternative investments are providing beta but charging alpha prices for it.
In order to measure the baseline for Trend Following (and derive each CTA’s beta to it), the first step is to establish the benchmark and measure its performance.
Instead of taking an index of Trend Following CTAs, the authors build an index representing investing like a CTA. They do this by implementing a simple mechanical Trend Following system (Donchian reversal system) that covers multiple timeframes (20: from 5-day to 200-day) and a wide range of diversified markets (55 markets with exposure to all asset classes and geographical locations). The system also implements volatility-based position sizing and sector allocations (reflecting average allocation from a sample group of long-term Trend Following managers – possibly a flaw in the benchmark construction as it does not make it completely independent from the CTAs).
Correlating the benchmark to CTA indices
After applying fees, slippage and interest, the returns of the benchmark were compared to the returns of well-known CTA indices (S&P Managed Future Index, CSFB Tremont Managed Futures Index, etc.). The correlation between the benchmarks and these indices range from 0.75 to 0.9 indicating that the benchmark seems to do its job of… well, providing a benchmark for Trend Following.
Measuring CTA alpha
The next step is to calculate each CTA’s beta and alpha to the benchmark. The correlations are still fairly high (between 60% and 90%) and most CTA exhibit negative alpha over the testing period. For example, Rabar and Millburn’s calculated alpha since 1990 is around -2,000%.
Fourteen of the twenty largest CTAs failed to demonstrate alpha to the Conquest Managed Futures Beta benchmark from their inception until December 31, 2004. Six of these CTAs did demonstrate alpha over this period. Alpha, of course, [...] represents merely unexplained variation which can represent either skill, random fluctuation or some combination of the two.
CTAs: Trend Following Wizards or Not?
It is not explicitly stated from the paper but it is safe to assume that the results from CTAs are net of fees. It is arguable which performance to use for comparison (before-fees or net-of-fees). It would be interesting to see a comparison of CTA returns with the benchmark on a before-fees basis.
Since most CTAs charge (much) more than a 1% fee, a before-fees performance comparison should prove more to their advantage. One could speculate that most would actually display some alpha to this benchmark.
2/20 Fee Structure obsolete for CTAs?
If CTAs can display before-fees over-performance to the benchmark despite their net-of-fees under-performance, it simply points to CTAs over-charging for their fund management services and that they must evolve to adapt to the new market environment. In order to become more competitive (from a pricing point of view) and stay attractive to investors, CTAs must keep producing net-of-fees alpha to the benchmark. This can either be done by:
- lowering fees
- improve their returns
Option 1 is surely the easier way, but understandably less desirable for CTAs – nobody said free competition was good for everybody (that’s probably why we have all the current interventionism and protectionism in global markets!). But as more competition arises, they will have to – in a Darwinian fashion- adapt to this betafication of alpha or die out.
A probably fair approach would be to differentiate the beta performance from the alpha performance of the fund and charge fees accordingly. Possibly a combination of a flat fee to cover costs of the beta-tracking strategy (similar to a passive management fund) and a variable fee to charge the true “value-add” from the fund (i.e. alpha). The latter fee could be based on the Information Ratio using the Trend Following benchmark.
Obviously, this is based on the assumption that there can be a widely-accepted and valid benchmark for Trend Following (including variables such as slippage, roll yield, asset selection and allocation, etc.); or each fund could possibly designate their own benchmark for this calculation – to be agreed with investors.
There are a few good points to take away, as an investor:
Second, for those not inclined to build their own system, there should be more products and funds available charging a much more competitive fee – when the launch of a Trend Following ETF?
However, this could also be bad news for Trend Following in general: if there is only a finite amount of alpha/profit available in the markets for Trend Following, and if the Trend Following space becomes more crowded there will be less opportunities for each player.
This is also in line with another Darwinian market theory, from Andy Lo: the Adaptive Market Theory (AMH), whose papers are an interesting read. The AMH theory tries to reconcile the Efficient Market Hypothesis (EMH) with its numerous flaws, as described by behavioral investing theory. The main premise of the AMH theory is that markets’ target and ideal model is the EMH model. However inefficiences (profit opportunities) arise from behavioral biases and as a result markets oscillate towards/away from the EMH model. The level of inefficiency in a market is related to that market’s “ecology” – with more competition bringing on more efficiency.
Could too much Trend Following kill Trend Following?…