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Figure 2 – Historical Monthly US Equity Risk Premium

Data source: Dimensional Returns Web, CRSP, PWL Capital Inc.

The monthly US equity premium has been remarkably consistent, within a range, throughout history. It has an arithmetic average of 0.65%, and it has been positive 60% of the time. There tend to be periods, visible in Figure 2, where the monthly premium becomes more volatile; volatility clustering is a well-known phenomenon. Over periods longer than one month we also observe characteristic negative skewness - frequent small gains and a few extreme losses.

Given the nature of stock returns, we would expect a stock investor to achieve positive returns with roughly the same frequency as the equity risk premium being positive. For the remainder of this paper, we will be comparing lump sum investing to dollar-cost averaging in terms of absolute returns, as opposed to observing their risk premiums. US stock returns have been positive in absolute terms 63% of the time in the historical data.

Data source: Dimensional Returns Web, CRSP, MSCI, S&P Dow Jones Indices, PWL Capital Inc.

Comparing average outcomes is interesting but it does not speak to the dispersion of outcomes. Even if DCA is worse on average in terms of expected average outcomes, maybe it offers some protection on the downside. To assess this, we calculate the difference in annualized returns for LSI and DCA over 10-year periods and sort the data into percentiles. The 10th percentile is the bottom 10% of outcomes, the 50th percentile is the median, and the 90th percentile is the top 10%.

Table 4 – Difference in Annualized Returns (LSI – DCA)

Data source: Dimensional Returns Web, CRSP, MSCI, S&P Dow Jones Indices, PWL Capital Inc.

It should be clear from Table 4 that LSI is beating DCA by a healthy margin on average. In the best 10% of outcomes (90th percentile), more has been gained by LSI over DCA than what has been lost in the worst 10% of outcomes. The median outcome is positive, and the distribution is negatively skewed. None of this should be a surprise considering the positive expected risk premium of stocks over treasury bills, and the left-skewed distribution of stock returns. Figure 3 shows the shape of the distribution of the differences in outcomes for LSI less DCA in terms of 10-year annualized returns.

Figure 3 – Distribution of Differences in 10-Year Annualized Outcomes (LSI - DCA)

Data source: Dimensional Returns Web, CRSP, MSCI, S&P Dow Jones Indices, PWL Capital Inc.

At the most extreme, the far left and right tails of the distribution, LSI does look worse than DCA. This observation is consistent with a negatively skewed distribution; we see that most of the outcomes are good, but the worst outcomes are more extreme than the best outcomes. This validates the idea that DCA might be able to offer protection from the worst outcomes, but it comes at a significant cost in terms of expected returns.

Sorting by the difference between LSI and DCA lets us think about the total distribution of outcomes for DCA relative to LSI, but we are now interested in how DCA does when LSI does poorly relative to the full set of LSI outcomes. To examine this, we sort historical outcomes by LSI ending assets and observe how DCA performs when LSI has its worst 10% of historical outcomes. Framed differently, if we knew that the next 10 years would be among the worst in history for a lump sum investment, could we count on DCA to improve the outcome?

Table 5 – LSI vs. DCA in the 10th Percentile LSI Historical Periods

Data source: Dimensional Returns Web, CRSP, MSCI, S&P Dow Jones Indices, PWL Capital Inc.

In half of our markets, LSI still beats DCA most of the time even when LSI has delivered its worst historical outcomes; this is also true with an equal-weighted average of all markets in the sample. The results are not as strongly in favor of LSI as the full data series but remember that we have intentionally selected the worst LSI outcomes for this sample. While the number of outcomes is evenly matched, the bad outcomes in this case are worse in magnitude than the good ones. The result is a negative difference in annualized 10-year performance. This should not be surprising considering our intentional selection of the worst LSI outcomes in the sample.

Table 6 – Difference in Annualized Returns for 10th Percentile LSI Outcomes (LSI – DCA)

Data source: Dimensional Returns Web, CRSP, MSCI, S&P Dow Jones Indices, PWL Capital Inc.

Even under artificial conditions of a known bad future outcome for LSI, DCA offers less than a 50% shot at an improvement. DCA does however offer an edge when the magnitude of positive and negative outcomes is considered – despite the roughly even split between good and bad outcomes, the bad outcomes are worse than the good outcomes are good. This seems to give credence to the mythical ability of DCA to improve an extremely bad LSI outcome. An important nuance in the data is that the worst LSI outcomes relative to other LSI outcomes do not correspond with the worst LSI outcomes relative to DCA outcomes. The most extreme instances of underperformance for LSI relative to DCA have less to do with the LSI outcome being extremely bad and more to do with the DCA outcome being extremely good. In other words, lucky timing for DCA, as opposed to avoiding unlucky timing for LSI, drives the difference in the most extreme cases.

Given that it is impossible to predict which time periods will result in the worst outcomes for a lump sum investment, we next turn to two signals commonly believed to offer forward-looking insight into future investment returns.

Table 7 – LSI vs. DCA in Historical Bear Markets

Data source: Dimensional Returns Web, CRSP, MSCI, S&P Dow Jones Indices, PWL Capital Inc.

We again find that LSI produces a better outcome than DCA most of the time in most countries in the sample. Aetna employees and retirees should note that the US experience is significantly impacted by the enormous volatility and seemingly perpetual market drops in the 1930s. We find that, on average, LSI beats DCA by a 10-year annualized 0.25% when the investment period begins with the month after a drop of 20% or more has occurred. Echoing the experience of the full data series we also see that there has historically been more to gain from LSI in the 90th percentile of outcomes than there has been to lose in the 10th percentile. DCA is not offering protection from bad outcomes without also exposing us to a greater risk of missing good outcomes.

Table 8 – Difference in Annualized Returns Starting at Bear Markets (LSI – DCA)

Data source: Dimensional Returns Web, CRSP, MSCI, S&P Dow Jones Indices, PWL Capital Inc.

It's important for Aetna employees to keep in mind that our trigger to begin the investment period is a 20% drop. In some cases, a 20% drop is followed by more drops, while in other cases it is followed by a rebound. Based on the data in Tables 7 and 8 we can see that rebounds are more impactful, on average than further drops. This results in LSI delivering a better result than DCA most of the time, even during periods of market volatility.

Table 9 – LSI vs. DCA when Stock Prices are High Relative to all History

Data source: Dimensional Returns Web, CRSP, Barclays Research, PWL Capital Inc.

While it may seem concerning, this observation suffers from a massive bias: at any point in time we do not have the full set of past and future Shiller CAPE data to base a decision - we only have past data in our possession. We adjust for this by measuring the market’s expensiveness only relative to historical data for each data point. For example, for January 1926 we are comparing the Shiller CAPE to the set of data from February 1872 to January 1926, not from February 1872 to May 2020 to test for expansiveness. In this case, LSI beats DCA 63.70% of the time.

Table 10 – LSI vs. DCA when Stock Prices are High Relative to Backward-looking History

This exercise is to remind Aetna employees and retirees that while valuations may look high at a point in time, they can always get higher. Japan might be a particularly interesting case study on the usefulness of market valuations in making the LSI vs. DCA decision. We have less data for Japan, so instead of comparing historical Japanese data, we will compare Japanese valuations to US data to determine expensiveness. The highest level of the monthly Shiller CAPE for the full US historical data series is 44.19 which occurred in December 1999. Japan exceeded this level in May 1986 with a Shiller CAPE of 44.31. While the Japanese market did eventually crash in 1990, there are 29 monthly observations following May 1986 where LSI beats DCA by a wide margin. Even starting in November 1988, with a Shiller CAPE of 72.07, LSI beats DCA in Japan in terms of 10-year annualized returns.

It is well-known that future returns tend to be relatively low when valuations are relatively high. Despite this, using valuation as a signal to time the LSI vs. DCA decision has historically resulted in unfavorable outcomes most of the time.

Despite the statistical evidence in favor of LSI, there is a meaningful psychological risk to investing in a lump sum. For many Aetna investors, losing money in the stock market is psychologically, and in some cases physiologically painful. There is evidence from behavioral finance suggesting that acts of commission are more painful than acts of omission. Making the decision to buy stocks today is an act of commission while deciding not to buy stocks is an act of omission. Buying stocks on a given day and then watching them fall is more psychologically painful than not buying stocks and watching them rise, even if the economic impact is identical. DCA could be viewed as diversifying acts of commission over time to reduce the potential for a psychologically painful outcome.

If DCA seems like a solution to avoiding pain when investing new money, we think that it is a reasonable strategy. However, we also think that if the fear of loss is so great that DCA needs to be employed to make an asset allocation decision palatable, that asset allocation may be too aggressive. It should feel comfortable to invest a lump sum in a risk-appropriate portfolio. We do not want to imply that DCA should never be employed, but we do believe that if it feels necessary to use DCA in order to implement an asset allocation decision, it may be wise to revisit the portfolio altogether.

TRG takes a teamwork approach in providing the best possible solutions for our clients’ concerns. The Team has a conservative investment philosophy and diversifies client portfolios with laddered bonds, CDs, mutual funds, ETFs, Annuities, Stocks and other investments to help achieve their goals. The team addresses Retirement, Pension, Tax, Asset Allocation, Estate, and Elder Care issues. This document utilizes various research tools and techniques. A variety of assumptions and judgmental elements are inevitably inherent in any attempt to estimate future results and, consequently, such results should be viewed as tentative estimations. Changes in the law, investment climate, interest rates, and personal circumstances will have profound effects on both the accuracy of our estimations and the suitability of our recommendations. The need for ongoing sensitivity to change and for constant re-examination and alteration of the plan is thus apparent.

Therefore, we encourage you to have your plan updated a few months before your potential retirement date as well as an annual review. It should be emphasized that neither The Retirement Group, LLC nor any of its employees can engage in the practice of law or accounting and that nothing in this document should be taken as an effort to do so. We look forward to working with tax and/or legal professionals you may select to discuss the relevant ramifications of our recommendations.

Throughout your retirement years we will continue to update you on issues affecting your retirement through our complimentary and proprietary newsletters, workshops and regular updates. You may always reach us at (800) 900-5867.