Periods of heightened volatility are expected in every investment strategy. For hedge funds, the raison d’etre is to provide access to investment strategies that “hedge” out this volatility. In most cases, the hedge fund will use leverage and negatively correlated assets to provide alpha with lower volatility than the S&P 500, or any other benchmark.
When markets dip and cause the “tide to go out”, many HF’s suffer because of losses proportional to the leverage used and positive correlation that sneaks into the model. Most retail investors understand what happens with margin accounts when the market turns against them. Losses can quickly multiply.
Correlation effect is something less widely understood and this requires constant monitoring and analysis. It causes a rise in volatility it negatively affects returns. It is important to understand why it happens and whether or not it will affect the longer term results of the model. Ideally, a model should be robust enough in its construct or philosophy, so much so that tweaks to the formula are unnecessary.
First a word about low volatility exchange traded funds. There are two principally recognized ETF’s that cater to those looking for stability and dividends, the PowerShares S&P 500 Low Volatility (SPLV) and PowerShares S&P 500 High Dividend Low Volatility (SPHD). SPLV was conceived in May of 2011 and SPHD began in October of 2012. As you can see in the following performance graph, SPLV has returned +82.42% in price performance since inception, while the SPHD has returned +68.4%. For comparisons sake, QQQ has returned +100.62% in the same period as SPLV.
If I utilize the same starting point for all three, QQQ is up +77.78%, versus SPHD’s +68.4% and SPLV’s +57.92%. Therein lies the reason for my utilization of QQQ in the Absolute Return model.
Now, if I examine the longer term price returns of related indices, beginning in December of 1999, I find that the S&P High Yield Dividend Aristocrats Index has returned +174.24%, versus the S&P 500 +50.97% and Nasdaq +48.32%. Note also the return of the 30 Year US Treasury Bond, up +79.92%.
Therefore, it is plausible that I could use an S&P high yield dividend ETF in Absolute Return, instead of QQQ. Fortunately, it is clear in the last graph that the three equity indexes follow similar paths during stock market crises. In spite of this, since May 1 of 2007 the Nasdaq has significantly outperformed lower volatility indices, gaining +95.96%, versus the +41.46% in S&P 500, +38.92% in S&P HY Dividend Aristocrats, and +46.26% in the US long bond (USB).
Here lies the reason why I use the TLT and QQQ in the Absolute Return strategy. Over the longer term, there may be excellent alternatives for a buy and hold strategy, but I have yet to meet someone that does not attempt to time the market to avoid draw downs. If the Absolute Return model is capable of detecting a negative turn in the stock market, it would behoove me to allocate to a negatively correlated asset, the US Long Bond.
This takes me to the correlation factor that can present itself in the Absolute Return model. Last week, the model indicated a return to QQQ was required. Today, the first day of the trading week, TLT rose +0.24% and the QQQ rose +0.19%. As I mentioned in a previous post, one day does not make a trend, but with the Dow down almost half a percent on the day, readers surely must wonder what may be wrong with the markets and if the model can withstand oddly positive correlations.
Between September 28, 2012 – June 21, 2013, the model dropped -15.47%, wile the S&P 500 rose +10.53% and the Nasdaq rose +7.73%. Even more importantly, while the median weekly return of Absolute Return was -0.11% and QQQ was -0.15%, the Nasdaq had a median return of +0.14%!
The reason for this anomaly is simple, a major component of the Nasdaq 100 (for which the QQQ is the proxy) fell -38.27%, Apple Inc. (AAPL). Other components helped a bit, but it is easy to point the finger at Apple. Can such a thing happen again? Yes, though it is part of the business of index investing, trusting that the yearly rebalancing of indices will appropriately reflect the risk reward parameters that one is looking for. In the case of QQQ and the Nasdaq 100, my view is that it best represents the innovation, growth and liquidity that the US markets can provide. Small and medium cap companies can grow into the top 100, but until then they have market liquidity risks that are accentuated in market draw downs.
As I said before, model construction requires analysis of factors that may cause changes in expected returns. As long as the factors that underlie this model’s construction remain supportive, there should be no need to tweak it. Still, it requires constant vigilance, that is key to being anti-fragile.