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Market Timing: More Evidence Why It Doesn't Work

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In 2018's tumultuous December, U.S. investors pulled $143 billion from actively managed funds -- the biggest monthly outflow from this group ever recorded by Morningstar. And their timing couldn't have been worse.

Those billions of dollars in assets sent to the sidelines or churned between managers came during a particularly violent three-week swing. From around Christmas through late-January, however, the S&P 500 Index shot up by nearly double-digits.

It's also worth noting that in December, passive funds generated net inflow of nearly $60 billion, per Morningstar. For all of 2018, such passive strategies collected a net $458 billion of investment money. Meanwhile, actively managed funds had some $301 billion of net outflow for the year, just shy of 2016's high-water mark of $320 billion.

But a growing sense of buyer's remorse by traders shouldn't come as a surprise. A host of academic and industry research points to a really bad tendency by active investors: they panic and bail out at just the wrong times. Indeed, a typical stock mutual fund investor has lost almost two percentage points a year in total returns from ill-timed trading activities, according to data compiled over extended periods by market researcher Dalbar Inc. 

At IFA, we call them "Time Pickers." Too often, these do-it-yourself investors are led by "star" active managers. The evidence shows, however, that such so-called investment gurus don't show any greater propensity to time markets than anyone else. A study by CXO Advisory Group, for example, found during a 12-year stretch (2000-2012) that not one of the 28 well-known managers tracked was able to meet basic accuracy and consistency criteria suggested through earlier research by Nobel Laureate William Sharpe and others.

That's just one study. In the most recent edition of his book on investing, Mark Hebner and his staff at IFA put together updated tables breaking down opportunity costs related to distinct market-timing objectives. (See Step 4 of "Index Funds: The 12-Step Program for Active Investors.")

As he notes, avoiding big sell-offs can be alluring. "The predicament, however, is that the worst days are equally concentrated and just as difficult to identify in advance as the best days," Hebner writes.

The chart below shows that missing the 40 worst days in the S&P 500 Index during a 20-year period (1998-2017) would've increased investment returns by 952% as compared to a buy-and-hold investor's gains.

The_Allure_of_Market_Timing_Missing_the_Worst_Days

By contrast, investors who weren't on the right side of trades in both instances -- jumping in and out -- faced even more damage. As illustrated below, the flip side of the coin is that missing out on 40 of blue chip stocks' best days would've resulted in a triple-digit percentage loss during this extended timeframe.

The_Problem_With_Market_Timing_Missing_The_Best_Days

To look into how a diversified portfolio involving both types of assets works together when market-timing is added to such a mix, Dimensional Fund Advisors has crunched data to compare outcomes for S&P 500 Index stocks and one-month U.S. Treasury bills over 91 years (1926-2016).

The short-term T-bills, of course, represent fairly low-risk fixed-income markets. The S&P 500 benchmark stands on the other end of the spectrum as a proxy for blue-chip equity market risk.

In order to understand how counter-productive market-timing can be to long-term investors, allocations between those two different types of assets were switched back-and-forth on a monthly basis, ultimately spending 60% of the time in equity and 40% in fixed-income.

The chart below presents how such a comparison using 1,000 market-timing outcomes -- generated by randomly assigning months to be allocated to fixed-income or equity -- plays out over this extended period to a static 60/40 allocation.

Summary-Statistics-for-Static-Balanced

Not surprisingly, the monthly average return was the same in each instance (0.68%). But notice how much of a difference market-timing hiked monthly standard deviation rates. Such trading activities increased standard deviation, a measure of volatility, during a typical month by nearly a full percentage point (0.95%). 

"The higher volatility acted as a performance hurdle," concludes Dimensional, "resulting in a lower compound return of about 43 basis points per year on average (7.35% vs. 7.78%)."

Further study by Dimensional reveals that over longer timeframes, market-timing also produced more extreme return patterns. "Market timing therefore may expose investors to dramatic shifts in risk profiles over time," researchers point out, "and add uncertainty in the outcomes."