A Strategy With A 3.42 Sharpe Ratio This Year

Includes: SPLV, SPY, TMF
by: Harry Long


Stock picking has been tough this year.

Strategy indices can provide less correlated returns.

Today we will examine an elegantly simple example.

The Ultra-Low Volatility Strategy Index has reached a new all-time high. YTD, the strategy is hitting a Sharpe Ratio of 3.42, and has vastly outpaced the market (NYSEARCA:SPY).

Here are the Ultra-Low Volatility Index's rules:

  1. Buy the PowerShares S&P 500 Low Volatility Portfolio ETF (NYSEARCA:SPLV) with 80% of the dollar value of the portfolio.
  2. Buy the Direxion Daily 30-Year Treasury Bull 3x Shares ETF (NYSEARCA:TMF) with 20% of the dollar value of the portfolio.
  3. Rebalance annually to maintain the 80%/20% dollar value split between the positions.

In addition to the extremely high Sharpe ratio, the max drawdown of 2.37% YTD is spectacular. This has been a tough YTD for many investors. The fact that an elegantly simple ETP strategy index has only had a 2.37% drawdown YTD is notable.

Almost any strategy looks good when the markets are up. It is far more difficult for a strategy to shine when markets are turbulent. This index performs remarkably well across a variety of market conditions.

Here is the index vs. the SPY ETF in a log scale:

The index beats the SPY ETF by over 5 percentage points per year, while having a max drawdown which is over 5 percentage points less.

The index performs well because of the advantages of low volatility investing. The low volatility anomaly has been exhaustively, empirically documented by Dr. Robert Haugen and others. Simply put, low volatility stocks tend to outperform high volatility stocks - totally contrary to the popular notion that higher risk denotes higher potential return.

My approach in creating the Ultra-Low Volatility Index has been to add a second asset class (3X leveraged long duration U.S. government bonds) in an effort to further reduce the volatility of the entire portfolio, and to reduce the portfolio's correlation to the U.S. stock market.

Our index is not achieving long-term outperformance by rising more than the broader market during strong up years. The index is achieving outperformance across a cycle by adhering to the general pattern of underperforming during strong up years and outperforming during strong down years.

This leads to the happy result, which we have observed, of strong returns combined with low volatility.

Standard & Poors reports that over a "10-year investment horizon, 82.14% of large-cap managers, 87.61% of mid-cap managers, and 88.42% of small-cap managers failed to outperform on a relative basis."

Clearly, the answer is not more reckless emotional decision making. The answer is the creation of quantitative indices which exploit market inefficiencies and combine diversification with ingenuity and discipline.

Our Ultra-Low Volatility Index is not complex, but its performance is powerful.

On an intuitive level, it's important that investors understand that an index doesn't need to be a collection of 500 large companies. An index can be an index of ETPs chosen for their risk/reward, correlation and diversification attributes. At ZOMMA, we call this a strategy index.

We believe that strategy index technology will beat most human investors over time. Rather than guessing about market direction, we are finding robust quantitative advantages to incorporate into index-based solutions.

The evidence is clear - multi asset class indices can beat stock market performance across a cycle. And the mechanism is clearly defined quantitative insights into the long-term drivers of robust, sustainable outperformance.

Thanks for reading. We feature even more impressive strategy indices in our subscription service. If this post was useful to you, consider giving it a try.

Hypothetical performance results have many inherent limitations, some of which are described below. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown; in fact, there are frequently sharp differences between hypothetical performance results and the actual results subsequently achieved by any particular trading program. One of the limitations of hypothetical performance results is that they are generally prepared with the benefit of hindsight. In addition, hypothetical trading does not involve financial risk, and no hypothetical trading record can completely account for the impact of financial risk of actual trading. For example, the ability to withstand losses or to adhere to a particular trading program in spite of trading losses are material points, which can also adversely affect actual trading results. There are numerous other factors related to the markets in general or to the implementation of any specific trading program, which cannot be fully accounted for in the preparation of hypothetical performance results and all which can adversely affect trading results.

Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours.

I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.

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