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Here’s a fun thought experiment: **What if you only invested in stocks after the stock market had a down year?**

For example, suppose you have $1,000 to invest each year. On the first trading day of each year you can either invest that $1,000 into a stock market index fund like the S&P 500 or you can simply hold your $1,000 in cash.

To determine if you should invest your money, you look at how the S&P 500 performed in the previous year. If the S&P 500 experienced positive returns in the previous year, you keep your money in cash. If the S&P 500 experienced negative returns in the previous year, you invest your $1,000 into an S&P 500 index fund.

This is a simple market-timing strategy. The logic behind this strategy is that if the stock market experienced a negative return in the previous year, perhaps it’s more likely to experience a positive return in the coming year.

Likewise, the market doesn’t always increase each year indefinitely, so perhaps it’s more likely that the market will experience a decline following a positive year.

To find out how well this strategy worked historically, I downloaded data for the annual S&P 500 returns dating back to 1928. Then, I looked at how the following two strategies performed over every 40-year period:

**Dollar-Cost Averaging:** Invest $1,000 into an S&P 500 index fund at the beginning of each year, regardless of how the market performed in the prior year.

**Market-Timing: **Invest $1,000 into an S&P 500 index fund at the beginning of the year *only if *the market experienced a negative return in the prior year. Otherwise, hold the $1,000 in cash.*

*****If the market has several positive years in a row, keep accumulating $1,000 in cash each year until the market experiences a negative year, then deploy all of the cash savings into an S&P 500 index fund. Also note that all numbers are inflation adjusted for this analysis.

Let’s check out the results.

**Example: Investing Only After Down Years**

First I’ll show an example of how I calculated the returns for both the dollar-cost averaging and the market-timing strategy.

*If you’re not interested in the math behind these calculations, feel free to skip down to a lower section in the post where I summarize the results.*

Suppose the year is 1929.

- Using
**the dollar-cost averaging strategy**you invest $1,000 into an S&P 500 index fund since you invest $1,000 each year regardless of how the market performed in the prior year. - Using
**the market-timing strategy**, you*do not*invest $1,000 since the S&P 500 returned 45.56% in the prior year of 1928. Thus, you hold $1,000 in cash.

It turns out that the S&P 500 returned -8.85% in 1929. Thus, the next year in 1930 the following would occur:

- Using
**the dollar-cost averaging strategy**you invest $1,000 into an S&P 500 index fund since you invest $1,000 each year regardless of how the market performed in the prior year. - Using
**the market-timing strategy**, you invest $1,000 along with the additional $1,000 you had saved in cash since the S&P 500 experienced a negative return in the prior year of 1929.

For every year from 1929 to 1968, we repeat this process. Here are the final results:

By following a dollar-cost averaging strategy and investing $1,000 at the beginning of each year, you would have accumulated** $369,719** after 40 years compared to **$355,554** for the market-timing strategy.

It’s interesting to note that although the DCA strategy outperformed, the two strategies actually produced very similar results for the first 20 years. However, the DCA strategy took the lead around year 23 and never looked back until the end of the 40-year period:

**DCA vs. Market-Timing for All 40-Year Periods**

I repeated the same analysis for all 40-year periods dating back to 1929. Here are the final ending amounts for each strategy for all 40-year periods:

Here are some summary stats:

- Dollar-cost averaging
**outperformed in****34 of the 51**total 40-year periods. - The average final ending amount for the dollar-cost averaging strategy was
**2.5% higher**than the market-timing strategy. - Dollar-cost averaging
**outperformed****in all 17**of the most recent 40-year periods.

The following chart shows how the final ending amount for DCA relative to the market-timing strategy:

**Why Dollar-Cost Averaging Tends to Outperform**

In this analysis we saw that dollar-cost averaging outperformed a simple market-timing strategy during most long-term investment periods.

The main explanation for this outperformance is the fact that the stock market experiences more positive years than negative years.

This means that sitting on the sideline with cash is likely to result in underperformance since the stock market is likely to deliver higher returns in any given year compared to cash.

While it seems like a good idea in theory to sit on the sidelines after the stock market has a positive year, it’s a simple fact that the stock market tends to climb higher slowly over the course of several years, with occasional recessions every decade or so.

This means that the market has a tendency to string together several positive years in a row, which means investors who are waiting for a negative year are often left waiting for longer than they expect.

To me, the results of this analysis weren’t too surprising. The stock market is surprisingly difficult to time and thus nearly all market-timing strategies underperform a dead simple dollar-cost averaging strategy.

For most investors, it’s possible to outperform complex market-timing strategies by following a simple dollar-cost averaging strategy. No matter how the market performs in the previous year, keep diligently investing each year. More than likely you’ll be left with more money several decades later than if you attempted to time the market.

**Further Reading: **

The Math & Psychology Behind Lump Sum vs. Dollar-Cost Average Investing

Can Historical Stock Market Returns Predict Future Returns?

**Note:** All charts used in this post were created in Excel. To find out how to create similar charts yourself, grab a copy of the Excel Genius Toolkit.

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