- 31 DecVector 2019 Annual Review
- 17 DecFama/French going through its second biggest drawdown since 1963
- 15 NovThe Alpha Lifecycle
- 16 OctVector 2019 Q3 Review
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- 10 JulVector 2019 Semi-annual Review
- 14 JunAre factor premia disappearing?
- 21 MayHow persistent is regional outperformance?
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- 31 DecVector 2018 Annual Review
- 14 Dec2019 (outrageous) predictions!
- 20 AugTemperatures and stock markets heat up
- 18 JulVector 2018 Semi-annual Review
- 14 JunDo exporters suffer during trade wars?
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Fama/French going through its second biggest drawdown since 1963
17 Dec 2019
November was a good month for equity markets. With a possible trade deal in sight, developed markets returned 4%. Emerging markets on the other hand were plagued by weak manufacturing and consumer data, which caused them to end the month just 1% higher. Nevertheless, if investor sentiment doesn’t collapse, like it did last December, then the global index is set to end the year with double-digit gains – a feat not many investors would have predicted around the turn of the year.
Since January Vector Navigator returned 21.30%, which is nice but nevertheless a bit less than we had hoped for. With the benefit of hindsight, it is clear that Vector Flexible hedged too much market risk in 2019. Combined with the fact that we made the strategic choice not to hold bonds, which had a very good year, we recognize that the relative performance of our allocation strategy (+5.60%) was not on par with the returns we delivered during the previous years. Keep in mind though that the long-term returns on bonds are very much linked to their current yields, and that the pendulum swings both ways. We might have underperformed as interest rates fell in 2019, but we won’t be hit as hard when interest rates inevitably start to rise again…
In this month’s edition of the newsletter we’re going to take a look at the headwind that quant investors have faced these past couple of years. We try to find out what is causing this, and whether it’s exceptional when placed into historical context.
The idea is relatively simple, we proxy for an average quant fund by using the 4 factors of Fama & French, which are publicly available through this data library. The advantage of this approach is that we have a US dataset going back all the way to 1963. The Fama & French factors are:
- Small minus Big (Market Capitalization): Size premium, where small caps outperform large caps.
- High minus Low (Book to Market ratio): Value premium, where cheaply priced stocks outperform expensively priced companies.
- Robust minus Weak (Operating Profitability): Profitability premium, where more profitable stocks outperform less profitable (or even unprofitable) companies.
- Conservative minus Aggressive (change in investments): Investments premium, where companies that invest less outperform companies that invest a lot (and often too much).
If in 1963 you would have invested 25% of your assets in each of these market-neutral factor portfolios while keeping this portfolio’s riskiness broadly in line with the market risk (Beta = 1) then you would have ended up with a performance of 14.16% p.a., with a volatility of 14.86%. This risk-adjusted performance is significantly better than the market over this period, which had a return of 10.95% p.a. (with a volatility of 15.16%).
Below you can visually see the merit of adding factor exposures to your arsenal. After 55 years the portfolio of a factor investor was more than 6 times larger than the portfolio of somebody who held his money in a pure index fund - 1493 USD instead of 242 USD.
However, there is no such thing as a free lunch. While the volatility of factor investing strategy was slightly lower over the entire sample, there have clearly been periods where factor investors underperformed the broad market. This is displayed in the graph below, which plots the drawdown (the maximum loss since its previous high) of a market-neutral factor investing strategy, which invests equally in the four factors mentioned above.
What is clear from the graph is that quant investing is currently having a difficult time. In fact, the Fama/French factors are going through their second biggest drawdown since 1963! With this particular form of factor investing the underperformance w.r.t. the broad equity market adds up to 12% over the last 3-year period.
Many of the reasons that drove factor investing to its biggest drawdown ever (during the preamble of the dotcom crisis) are reoccurring today: money is once more flowing towards growth potential despite the already bloated valuations of these companies. This means that value, profitability and conservative investments, three pillars of quant investing, are currently not being valued in the market – on the contrary, the short side of these equations are currently in vogue. Moreover, many of the companies that show the most promising growth potential in this digital era are not necessarily small caps, but giant caps (i.e. Amazon), which means that the small cap premium has also largely stopped working.
Quant investing has always tried to impose market rationality by defining some factors that should be economically priced in within a company’s valuation. Markets are not always rational however, or at least not according to this way of measuring rationality, and there are periods when valuations of sectors/countries deviate due to temporary changes in investor preferences and/or news driving the markets. Over the long-term though, the evidence is clear: quant investing works, but just like investing itself it is not for the faint of heart – if you want extra active return you must take on a little bit of additional active risk and have the tenacity to stick with your investment plan.
Werner, Thierry and Nils