Now that the new year is approaching, many publications and market pundits are making all kinds of predictions about the markets in 2018. These kinds of forecasts are seldom accurate, and trying to time the markets based on opinions and speculation is generally an expensive mistake.
On the other hand, we can rely on quantitative systems to measure and evaluate how different asset classes are performing. The evidence shows that investing in the asses with superior relative performance can produce above-average returns over time. Perhaps more important, these kinds of systems can be remarkably effective at protecting investors’ capital during bear markets.
The selection universe includes three massively liquid and well-known exchange traded funds: iShares 1-3 Year Treasury Bond ETF (SHY), SPDR S&P 500 Trust ETF (SPY), and iShares MSCI Emerging Markets ETF (EEM).
The rationale for including these instruments is quite simple, yet effective according to the data.
The iShares 1-3 Year Treasury Bond ETF offers exposure to short-term Treasury bonds. In times of economic hardship and market uncertainty, these assets are seen as a safe haven for investors in search for protection. The system will rotate into this ETF when stocks are under pressure, which can be remarkably effective at reducing volatility and downside risk.
SPDR S&P 500 Trust ETF is a widely-known ETF that tracks the S&P 500 index. For many U.S. investors the S&P 500 is the most representative benchmark to watch, and it’s certainly one of the most important indexes in the world. When compared versus other stock indexes, the S&P 500 is relatively safe and stable. This index is focused on big capitalization companies based on the U.S., so it’s safer than other indexes that invest in small companies or emerging market stocks, for example.
iShares MSCI Emerging Markets ETF invests in a portfolio of nearly 850 large capitalization stocks in emerging markets. These kinds of companies are generally more volatile than the ones in the S&P 500 index, and they tend to outperform in times of strong global economic growth and rising risk appetite around the world. Emerging markets also have considerable exposure to commodity prices. When inflation is accelerating and commodity prices are strong, this can be a powerful tailwind for emerging markets stocks.
The quantitative algorithm ranks these three ETFs based on their relative performance over three and six months. The algorithm also considers volatility as a negative factor, so we are looking at relative performance adjusted for volatility. The portfolio is completely allocated to the ETF that has superior relative performance, and it’s rebalanced monthly.
Performance data is quite promising. Since December of 2003 the quantitative system gained 12.6% per year versus 8.7% annually for the SPDR S&P 500 Trust ETF. In cumulative terms, this means the system gained 422.4% versus 219.6% for the index-tracking ETF.
Data and charts and from ETFreplay, and the quantitative trading system is available for members in my research service: The Data Driven Investor.
Even more important, the system did a rock-solid job at protecting the portfolio during bear markets. While the SPDR S&P 500 Trust ETF suffered a maximum drawdown of 55.2% during the backetsing period, the system did considerably better, with a maximum drawdown of only 17.7%. Note: Maximum drawdown measures the largest percentage drop from the high.
A big part of this outperformance, especially in terms of reducing downside risk, is due to the fact that the quantitative system was mostly invested in the safe asset, meaning the iShares 1-3 Year Treasury Bond ETF, during the worst times of the financial crisis in 2008 and 2009.
The system bought the iShares 1-3 Year Treasury Bond ETF in January of 2008, and it mostly held the position until May of 2009. It only changed to emerging markets during one month over that 17-months period, and this is the key reason why the system produced remarkably solid returns in a period when the stock market went through one of its biggest losses in history.
This doesn't mean that the system will necessarily outperform in all market environments. Far from that, chances are that systems like this one will do worse than the benchmark for long periods of time. That acknowledged, it makes sense to expect the quantitative system to provide protection during the most challenging bear markets.
If history is any valid guide, the system is well designed to invest in safe assets when the market environment is deteriorating. This can be a bad trade when the market retracement is ultimately shallow and the system goes for safety at the time when risky assets are about to rebound. On the other hand, when the bear market is deep and long, the system could be enormously valuable in terms of protecting investors’ capital.
In addition to representing sound quantitative trading strategies, these models can also provide substantial informational value. Relative strength is a powerful force, when a particular asset class or sector is outperforming, chances are that it will continue outperforming over the middle term. For this reason, it makes a lot of sense to watch relative strength for different markets and sectors when making investment decisions, even if the investor is not directly implementing a quantitative trading strategy.
When picking winning stocks or trying to time the markets, investing decisions based on quantified data are far superior to those based on subjective opinions. My research service, The Data Driven Investor, offers multiple systems with market-beating backtested performance. You can take a free trial for limited time on this link.
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.