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MPI details how hot smart beta low volatility funds are doing

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Investment research firm Markov Processes International (MPI) has published a paper entitled ‘Lower Volatility Smart Beta Funds – A Safe Haven in Turbulent Times?’, commenting that smart beta funds are hot at the moment. 

The firm writes that according to ETF.com, more than half of the 150 funds launched in 2016 implemented smart beta strategies.  For the year to June 30, 2016, ETFGI’s most recent data show that assets in smart beta funds have a five-year annual compound growth rate of 31.3 per cent. And, low volatility funds, up USD15.1 billion in the first seven months of the year are the most popular. BlackRock’s Holly Framsted called minimum volatility funds the ‘fastest growing’ smart beta segment.
 
“But critics have cautioned against low volatility strategies citing sector concentration, rate sensitivity and potential crowding risks. And the prospect of rate rises, currently, may be contributing to withdrawals from low volatility funds after a long period of inflows.
 
“Low volatility funds seek to take advantage of the ‘low volatility anomaly’ – the empirical observation that lower risk (as measured by beta or volatility) securities outperform their higher volatility counterparts, the firm writes. 
 
“Researchers have advanced several reasons for this anomaly – investor preference for lottery-like payoffs combined with leverage or other investment constraints.  Some question the existence of the anomaly at all, citing instances where the observations are not robust to changes in data frequency, horizon or some other change in methodology. Whether one believes in the low volatility anomaly or not, there is also the draw implicit in the name.  Post-financial crisis, the simple promise of mitigating losses has its own appeal.
 
MPI says that there are a number of easily investible low-volatility products, both mutual funds and ETFs on the market and focuses on the PowerShares S&P Low Volatility fund (SPLV), started in 2011, and the index it tracks, the S&P 500 Low Volatility Index.
 
“The S&P 500 Low Volatility Index was launched in April, 2011, with history backfilled to 1990.  While experience (and providers’ disclaimers) teach us to be wary of back-tested results, a look at the longer term behavior of the indexes helps establish expectations for the strategy.
 
 
MPI reports the following observations:
 
S&P 500 Low Volatility Index vs S&P 500 Index Nov 1991 – Aug 2016
•             Using the S&P 500 Index as a benchmark, the index tends to deliver on the promise of lower volatility on average, although there are some periods of volatility higher than that of the index, where the relative standard deviation values on the plot are greater than one.
•             Outperformance claims are less supported. While the index does outperform over the full period, there are extended periods of underperformance observed.
 
S&P 500 Low Volatility Index: Dynamic Sector Exposures Dec 1990 – Aug 2016
•             The SPLV index can be tracked with high accuracy with an R-Squared value over 95 per cent and predictability, as measured by MPI’s proprietary measure of Predicted R-Squared of over 90 per cent using a portfolio of sector indices.
•             The fund’s implied sector exposures change over time, in particular post-crises. Note that in 2009, prior exposure to financials is reduced, for obvious reasons.  The index’s exposure to Utilities also fell following 2013’s ‘taper tantrum’.
•             Sector concentration is clearly visible, and it confirms the intuition that the strategy is highly focused in defensive sectors, more so since 2008.
 
S&P 500 Low Volatility Index: Dynamic Factor Exposures Dec 1990 – July 2016[g]
•             Exposures have changed since 2008, with Value (High-Low) exposure becoming negative and momentum increasing.
•             Rate sensitivity also increases, as does the magnitude on the quality (profitability and the firm’s capital investment level) factors. These reinforce the picture painted by the sector analysis.”
 
The firm writes that higher frequency analysis of the ETF product, the only out-of-sample test, supports the longer term analysis of the index, with total risk and return numbers reported and similar exposures. 
 
“Higher frequency analysis also observes periods such as the taper tantrum and recent weeks where the low volatility products can be in fact both as or more volatile than the market and underperform as well. 
SPLV (S&P Low Volatility Index) lost -5.2 per cent between July 25, 2016 and Sept 9, 2016, while SPY (S&P 500) returned a loss of -1.9 per cent with lower daily volatility than SPLV.
Between May 20, 2013 and June 20, 2013 SPLV returned -7.1 per cent, compared to a loss of -4.6 per cent for SPY with the same daily volatility,” the paper says. 
 
Implications for investors from the research are that low volatility investing is an active strategy with active sector and factor tilts.  MPI writes that while these tilts do change over time, they appear persistent over moderately long periods, changing rapidly only with regime changes. 
 
“Recent experience has shown that current tilts are sensitive to interest rate shocks, and long term experience suggests that defensive sectors tend to underperform the market in a rising rate environment; this is reinforced by the negative relationship with rising rates on a factor basis.  Positive exposures to momentum, which itself is subject to periodic crashes as well as recently limited value exposure supports the contention that the strategy is relatively more expensive than it has been historically.  For those interested in tactical allocation, we’ll leave it at that.”
 
On a longer term basis, low volatility tends to deliver on the only characteristic it truly targets, which is a lower standard deviation of returns than its parent index, albeit with high sector concentration and higher turnover, MPI says.
 
“As a component of a multi-factor portfolio, the strategy’s exposures to other targeted factors should be a major consideration.  While significant interest rate exposure might be unique to this particular strategy, the quality and momentum factor exposures could possibly result in an unintentional ‘doubling down’ of factors in a multi-factor portfolio.”

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