Dollar Cost Averaging vs. Lump Sum Investing

Uncertainty is a constant in investing. Recency bias makes the current time, whenever that may be, feel more uncertain than ever. At the time of writing this paper the COVID-19 pandemic may be presenting us with truly unprecedented economic and health-related uncertainty, but stepping back to any point in history there is always a reason that this time is different; this is true in both bull markets and bear markets.

Uncertainty is not necessarily a bad thing – if investing felt certain we would not expect to collect a meaningfully positive risk premium from owning risky assets. For long-term investors stocks should deliver on their positive expected returns. The concept of hanging on through tough markets to benefit from long-term expected returns is relatively easy for most investors to understand. The tricky part is doing it, and it doesn’t get any trickier than making the decision to invest a lump sum of cash.

The nagging uncertainty that comes with investing in the stock market seems to be particularly pronounced when it comes to investing “new money.” New money could be a windfall from selling a home or business, receiving an inheritance, or winning the lottery. Whatever its source, shifting from cash into stocks can be a nerve-racking experience. In the case of new money, it doesn’t help to know that long-term expected returns are positive when you are deciding to invest a large sum at a single point in time.

Instead of investing a lump sum all at once, you might choose to enter the market gradually over some pre-determined period. This is commonly referred to as dollar-cost averaging. It seems intuitive that dollar cost averaging would lead to a better average outcome. You are buying more stocks when stocks are down and less when they are up, and you are avoiding the potential timing error of investing right before a crash. As usual, intuition and investment decisions don’t mix.

This paper aims to compare dollar-cost averaging (DCA) to lump sum investing (LSI) through time for six stock markets. We will examine average historical outcomes, the worst LSI outcomes, historical bear markets, and historically expensive markets. Neither this analysis nor its broad findings are new. A 1979 paper in the Journal of Financial and Quantitative Analysis by George Constantinides, A Note on the Suboptimality of Dollar-Cost Averaging as an Investment Policy, regards DCA as suboptimal through two propositions. A 2012 paper from Vanguard, Dollar-cost averaging just means taking risk later, found that LSI beats DCA about two-thirds of the time in the United States, the United Kingdom, and Australia.

This paper extends the analysis to include a closer look at the distribution of outcomes on average and under special circumstances commonly believed to be suboptimal for LSI.

Table of contents

• Introduction
• Analysis
• The Nature of Stock Returns
• Average LSI vs. DCA Results
• Results in the LSI Tail
• DCA in Bear Markets
• DCA When Stock Prices are High
• Psychological Risk
• Conclusion
• References