Is six the ‘magic’ number? AQR’s extension of the Fama-French Five Factor Model to Six.


I didn’t realise until recently that Eugene Fama & Keneith French had extended their famous three factor model to five factors. They have added RMW, the return spread of the most profitable firms minus the least profitable stocks and  CMA, the return spread of firms that invest conservatively minus aggressively to the standard size spread SMB and value spread of HML. You can find a piece discussing it in a Forbes article.

Following on from the five factor model there is an interesting piece on the AQR website at the end of last year which considers extending the five factor model to six, by adding in UMD, momentum winners and losers. It’s is well worth a read.


Adding back in noise to model private market assets

Multi Asset Investing


A lot of effort is being done on how to incorporate private markets into a public market risk framework, as more and more institutions are trying to look at multi-asset risk holistically.

I recently came across the catchily titled ‘Fisher-Geltner Unsmoothing methodology’, which I have to confess I’d never heard of before. It appears to use first order auto-correlation to recover the underlying market values from a smoothed series. Initially it was applied to commercial property, though now people are using it range of illiquid assets, except Mezzanine debt which doesn’t seem to exhibit auto-correlation in the returns.

However the downside is you still need a time series history. This implies generally a listed benchmark or fund history, which limits it use in more bespoke, innovative  and direct investments, that usually don’t have a time series history. You could use a ‘similar asset’ database to template it, but the jury is out how representative…

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GIPS compares apples with apples, but does it stifle innovation?

Multi Asset Investing

I first came across GIPS a few years ago when I was at Gulf International Bank and have recently had need to revisit it. There are clearly many benefits to being GIPS compliant as it allows a like-for- like comparison of different managers, and removes uncertainty around the calculation methodology. For a fund/strategy to be GIPS compliant, the fund requires a minimum of five years of audited performance. Furthermore some people may say that it separates the ‘wheat form the chaff’, as in a Darwinian view of the world, it means that the fund has ‘survived’ for five to ten years. Clearly several UK pension fund consultants in particular use GIPS as part of their manager selection processes.

However from another perspective one could say that in a changing world, even five years is a long time and the head wind of of a five year record, stifles innovation. A growing…

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Has passive become passé in the Multi-Asset space?

Multi Asset Investing


More and more pension funds, sovereign wealth funds and endowments are looking to move away from having passive full replication of equities in their multi-asset portfolios to a variety of proxies either to enhance performance, lower cost, increase liquidity or a combination of all three. Amongst the alternatives people are looking at are:

Blended Smart Beta

Ive written about this on the quant blog. It’s becoming ever more popular as a diversifier, risk reducer and a potential source of alpha. A lot of attention has been drawn recently to blending different alternative indexation strategies, wether load weighted (such as risk parity or fundamental weighting) or via optimisation (as in minimum variance or maximum diversification). In addition there is the potential of netting rebalance trades to reduce turnover, compared to having each strategy in a separate portfolio.

Explicit risk premia/factor overlays

Smart Beta largely works through the manifestation of indirect…

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Smart Beta benchmarks compared to their real world implementation

Everybody seems to be looking at smart beta these days, particularly within the equity space as an alternative to pure passive. I’m not a great fan of the term smart beta, as if your definition is ‘a non free float cap weighted index’ then price weighted indices such as the Dow 30 and Nikkei 225 are smart beta. Alternative indexation is a better term, but a bit of a mouthful.

Given cap weighted indices by their very nature have a fairly low turnover, a big issue with smart beta is the difference between a smart beta benchmark as calculated by an index provider that everyone looks at and a real world portfolio implementation of that benchmark, which may have a very significant two way turnover when rebalanced. Take for example a minimum variance portfolio, which can have a very significant turnover. The problem becomes progressively worse as the investable universe becomes less liquid, as transaction costs increase and as more non major fx’s are involved. An example of this is the potentially significant difference between benchmark performance and the implementation drag of say an S&P 500 minimum variance portfolio and a minimum variance broad emerging markets portfolio.