Relying purely on human intuition is very difficult when it comes to making educated investment decisions, especially when the market is constantly reaching new highs.
Historically, market peaks have signaled hard times ahead. Following the peak in 1929, America faced the Great Depression and a drawdown of 87%. In 2001, the technology bubble burst, and the market dropped 43% over the next 30 months. A third familiar example is the housing bubble of 2007. After the market peaked in May 2007, it dropped 48% to its bottom in March 2009.
The most memorable market losses, however, do not mirror the actual trend. In fact, historical data show that market peaks are usually followed by positive returns once the drawdown has been weathered. The graph below tracks the three-year period following market peaks in 1926, 1995, and 1996. 
Following peaks in 1926 and 1995, the market increased more than 100% over the subsequent three years. After a peak in 1996, the market increased 94%. Based on monthly historical data from 1900, the probability that a market high is followed by a three-year positive return has been 71% with an average return of 22%. An investor has been much more likely to gain over the three years following any market high.
Human intuition might encourage an investor to flee from the market following a peak since the prospect of sharp drawdowns is ever in mind, but this decision could cause the investor to miss out on substantial gains. At Newfound, our momentum models filter out noise and identify market trends through rule-based, quantitative investment strategies, rather than human intuition. In this way, we can identify signals in the market to determine whether it is appropriate to remain invested or to protect capital.
Nathan Faber
Nathan is a Portfolio Manager at Newfound Research, a quantitative asset manager offering a suite of separately managed accounts and mutual funds. At Newfound, Nathan is responsible for investment research, strategy development, and supporting the portfolio management team. Prior to joining Newfound, he was a chemical engineer at URS, a global engineering firm in the oil, natural gas, and biofuels industry where he was responsible for process simulation development, project economic analysis, and the creation of in-house software. Nathan holds a Master of Science in Computational Finance from Carnegie Mellon University and graduated summa cum laude from Case Western Reserve University with a Bachelor of Science in Chemical Engineering and a minor in Mathematics.
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