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Saturday 13 August 2016

A peek at our premium research...

Here's an extract from a recent issue of our Premium Newsletter service. The letter focuses is on generating actionable trade ideas. But it goes way beyond that to present methodological information and trading context.

Our next issue is released tomorrow at 10h30 GMT. We offer a free trial - try it out!


Friday 17 June 2016

Brexit and arbitrage

The race is a tight one and has spawned a massive swathe of media analysis. This FT piece covers some of the implications for equities and bonds of a Brexit.

One of the conclusions is that not only might large UK exporters to the EU suffer but large EU exporters to the UK are the more likely to. On this analysis a hunt for arbitrage opportunities seems straightforward.

Software like ArbMaker will turn up big exporting pairs such as France’s Legrand SA vs the UK’s Spirax-Sarco Engineering plc (LG/SPX). Backtests will show the pair trades regularly and profitably.

However, the operational detail of such companies is important in the context of Brexit. For example, Legrand has a well-balanced export market with the UK representing perhaps 10% to 15% of revenue (it’s not broken out separately in the accounts). A weaker, Brexited euro may simply boost non-UK exports as well as mitigate any fall in UK sales that might happen along the lines suggested in the article.

Spirax-Sarco has parallels. Its Europe, Middle East and African division accounts for ~30% of operating profit. But the group has manufacturing sites in the EU. Those sites' top-lines, translated to sterling, would take a hit from a weaker euro. But their cost of goods numbers benefit. Given the weight of its other export markets untangling the aggregate impact is not straightforward.

Traders may thus end up concluding that the fundamental economic relationship between such companies will remain in place regardless of the Brexit referendum. If so, SPX/LG remains an attractive trade.

An alternative pair for dollar-only traders taking this view might be the US ETF pair EWU/EZU. That pair allow an aggregated approach to the thesis. EWU (fact sheet here) covers mid-size and large UK equities while EZU (fact sheet here) does the same for EU companies of member states within the monetary union.

ArbMaker analysis shows that the EWU/EZU trade has a historically lower profitability than SPX/LG - but that has come with a far lower level of in-trade volatility.

There is, of course, much more Brexit fodder to consider when scouring for arbitrage ideas. A few samples of the fare on offer can be found here, here and here.

Saturday 11 June 2016

Getting results for clients

In 2015 our largest client was a hedge fund based in New York. Here is a snapshot of what we achieved for them during the contract:

htec_NYC_ACM.png Get the full report with complete risk-adjusted statistics and commentary here.

It's not only hedge-funds that can do this.

Monday 11 April 2016

One relative-value approach to keep an eye on...

The idea of moving from consultant to manager intrigues us. It involves moving beyond trading one's own account and dealing with the pain of client management. Notwithstanding that outcome, though, it remains a potentially attractive activity.

But in the meantime accumulating the data is what counts:


Monday 21 March 2016

Should you rely on that hedge fund index?

Keeping in similar vein to a number of the previous entries about the mysteries of defining, selecting and tracking hedge fund strategies here is a 2015 paper by Swiss wealth manager Pictet titled “Hedge fund indices: how representative are they?

Amongst its gems covering the biases of the indices is this great graphic explaining the source of ‘self-selection’ bias:


Core message: less than one percent of funds report to all the tracking databases. One study puts the impact on the performance figures of this at 1.9% per annum. More worryingly, the cumulative impact of all biases may be as high as 10.7% annually.

Over time that adds up to a lot of dispersion between index providers...

Monday 14 March 2016

Which strategy?

An earlier entry pointed out how many sub-strategies there are under the title ‘long/short’. Take one step back and consider this table from the 2016 Preqin Global Hedge Fund Report (click for larger version):


The table continues for an entire second page but this half makes the point: that’s a lot of headline strategies (before any talk of sub-strategies).

For those who like steady returns with as few shocks as possible ranking this list by the 5 year net return/volatility columns produces is a clear winner in the equity class: RV Equity Market Neutral (our yellow highlight). It is not the best on that ratio overall: two credit based approaches formerly best known for Jenga cameos in The Big Short pipped it.

The top 10 strategies on the return/volatility ratio look like this (click for larger version):


Perhaps a useful reference point when designing strategy approaches!

Wednesday 2 March 2016

Long-term investing: short-term investing gone wrong?

It frequently is to those in the hole. Or as Professor Thaler of The Big Short fame says,

"Just buying cheap stocks doesn’t do you any good unless they get less cheap soon"

So consider value as an investment category. Words to the effect that “the market always recognises the economic fundamentals of sound enterprises in due course” are part of the strap lines of value managers: intrinsic value against market prices; 60 cents for a dollar; and so on.

In overvalued and irrationally exuberant markets this approach frequently provides poor returns relative to benchmarks as market participants suspend good sense. Still, after the fallout of such episodes the value manager’s reputation as a paragon of sober logic is burnished.

And thus the proposition that the oft mad market will come round and fully price the fundamentals of a value enterprise remains seductive. So much so that the possibility of the fundamentals coming round to align with prices is frequently overlooked.

Last week, for example, Francis Chou was reported by Bloomberg as returning his 2015 advisory fee in an act of solidarity with his investors who lost 22% in his Opportunity Fund. Mr. Chou had a poor 2015 but is otherwise a strong value manager - as he points out in the article by referring to his great long-term record. Nonetheless, 22% is quite a drawdown to ascend in reasonable time without taking excessive risks.

An outlier? Some readers may be thinking “Warren Buffet” just about now. Below is a chart of Berkshire Hathaway’s performance versus the S&P 500 on a rolling 5 year basis:


(Source: Berkshire Hathaway annual letter, 2015)

Even the King of Value has found the job tougher and tougher since the turn of the century.

Thursday 25 February 2016

What is long/short, anyway?

Long/short – what could go wrong? Hedged positions, protection etc etc etc. And yet there are headlines like this one:

Here’s Why Long / Short Hedge Funds Are Getting Hammered

One of the problematic aspects of such an approach is that “long/short” is a hard category to define – and there is no consensus around the term. Which leaves plenty of room for whatever headline one wishes to shock and amaze with.

The IAM took a stab at the definition in cooperation with the LSE's Financial markets Group a few years ago. They produced the following classification table of hedge fund strategies:

HF Strategies

A cursory examination will show that Long/Short is a broad church - and one with some disciples who regularly trek over to the neighbouring tabernacle of Relative Value to worship.

Thus probably it is worth defining precisely what class of strategy is being analyzed before daubing all with the same brush.

Wednesday 24 February 2016

Robo-advisors & the limits of FinTech

"I know that you and Frank were planning to disconnect me, and I’m afraid that is something I cannot allow to happen." (HAL, 2001: A Space Odyssey)

Deep Blue vs Kasparov.

John Henry vs the steam drill.

Frank and Dave vs HAL.

Google’s self-driving car vs the world’s Mr Magoos.

Man vs machine has moved into the world of the investment advisor; and the list of the robo-advisors ready to allocate on the cheap is already legion.

Yet who is better? Tricky.

In chess, there are a fixed number of permutations: Moore’s Law led to human brains eventually being left behind.

In repetitive tasks human fatigue will lose to a machine (John Henry being an outlier although the fatigue did kill him).

But Hal and self-driving cars are more interesting cases.

Hal meets his demise because he could not handle cognitive dissonance (surely there can be no argument - humans excel at this). One might call this a programming error. But even fuzzy logic will have problems weighting competing directives successfully all (or even most) of the time.

As for Google’s self-driving cars the stats say that, as the software behind the driving improves, it is generally human errors (ie the Magoos driving other cars) that lead to mishaps.

My children have a neat line for such mishaps and cognitive dissonance episodes: “I didn’t do it on purpose!” Well, "it" happened anyway.

Provided the seas are calm the robo-advisors will do the mechanics just fine. There can be little doubt they will unearth opportunities via exhaustive scans and apply the financial theory and formulas to statistically common situations more thoroughly than humans. Moore’s Law.

But in competitive arenas where man and machine coexist; and in unusual scenarios where judgement and emotional intelligence is acutely required it is likely to be very tough for machines to prevail consistently against humans prepared to (a) take relatively extraordinary risks or (b) apply intuitively-derived solutions.

This human factor, bug or feature (depending on one’s perspective) definitively complicates the existence of algorithms. It can frequently be the primary cause of havoc. But, equally, it is frequently the primary source of its resolution.

Smart beta? Or dumb beta?

The attraction of a set of fixed criteria that lead to trading out performance is strong and perennial. Unfortunately, the factors underlying the out performance for any given period of time are not.

Smart beta is a case in point. The smart beta approach gives greater weighting to companies displaying certain factors deemed key to out performance. These might be low P/E or P/S names, companies delivering earnings surprises, relative strength stocks and so on.

Sadly, stability is not a characteristic of any such factors. Their very popularity will see to that; and if it does not anything else leading to a change in market regime will.

So “smart” should more accurately be called “alternative” (or even “dumb”). Indeed, at least one study has shown these strategies do not outperform their benchmarks on a risk-adjusted basis

Alternative beta is no substitute to dynamic (and proprietary) strategies. Such approaches continuously monitor changes in relationships and shift to the most profitable. If you have one keep it proprietary!

Tuesday 23 February 2016

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