Market timing

Market timing is the strategy of making buying or selling decisions of financial assets (often stocks) by attempting to predict future market price movements. The prediction may be based on an outlook of market or economic conditions resulting from technical or fundamental analysis. This is an investment strategy based on the outlook for an aggregate market, rather than for a particular financial asset.

The Efficient-market hypothesis is an assumption that asset prices reflect all available information meaning that it is impossible to systematically "beat the market."

Government, University, & SSRN PublicationsEdit

Poor PerformanceEdit

Market timing can cause poor performance.[1] Select sound, quality managers and give them a reasonable period of time.[2]

Trend FollowingEdit

After fees, the average "trend follower" does not show skills or abilities compared to benchmarks. "Trend Tracker" reported returns are distorted by survivor bias, selection bias, and fill bias.[3]

Trend-following investments have done well in every decade for more than a century.[4]

Return-Chasing BehaviorEdit

At the Federal Reserve Bank of St. Louis, YiLi Chien, Senior Economist wrote about return-chasing behavior. The average equity mutual fund investor tends to buy MUTUAL FUNDS with high past returns and sell otherwise. Buying MUTUAL FUNDS with high returns is called a “return-chasing behavior.” Equity mutual fund flows have a positive correlation with past performance, with a return-flow correlation coefficient of 0.49. Stock market returns are almost unpredictable in the short term. Stock market returns tend to go back to the long-term average. The tendency to buy MUTUAL FUNDS with high returns and sell those with low returns can reduce profit.[5]

Using Sentiment and Momentum to Predict Stock ReturnsEdit

The Federal Reserve Bank of San Francisco found one can expect a below-average stock return over the next month, when

  • For weeks, there is negative return momentum and
  • For the past year, there the sentiment is less than in the previous year.[6]
  • The GoogleTrends interest over time for the terms "stock market" and “stock market crash” increases when stock prices and consumer confidence are diminishing. Those serve as something of a pessimistic indicator for investors. The sentiment variable appears to help predict episodes of below-average equity returns.[7],[8],[9]

Consumer Confidence, Conference Board’s Present Situation IndexEdit

The Federal Reserve Bank of New York found that major turns in the Conference Board’s Present Situation Index tend to precede corresponding turns in the unemployment rate—particularly at business cycle peaks (that is, going into recessions). Major upturns in the index also tend to foreshadow cyclical peaks in the unemployment rate, which often occur well after the end of a recession. Another useful feature of the index that can be gleaned from the charts is its ability to signal sustained downturns in payroll employment. Whenever the year-over-year change in this index has turned negative by more than 15 points, the economy has entered into a recession. [10]

Spread between "stock index Price–Earnings ratio” and "short term interest rate"Edit

The Federal Reserve Bank of Kansas City found that a "Very low spread" between the Earnings/Price ratio of the stock market index and the yield of 3-month Treasury bills. Very low spread" happened during the times the spread fell below its 10th percentile, and

  • Seemed to predict higher frequency of subsequent market downturns in monthly data
  • Even with trading costs built in, it comfortably and reliably outperformed the stock index.[11]

VIX rising above 23 to a peak VIX valueEdit

The stock market performance is negative, while the VIX rises above 23 until the VIX reaches a peak.

The market has big positive returns, while the VIX falls a VIX peak back to 23.

You might consider selling when VIX is high and buying again when VIX is low, but that's a mistake.[12]

VIX futures marketEdit

The VIX term structure refers to the relationship of the VIX, VIX3M, VIX6M etc. Changes in the VIX Term Structure have a correlation between future price and volatility.[13][14]

An unexpected increase in volatility lowers current stock prices.[15]

Although the VIX futures market predicts future stocks returns, the predictability, measured by the regression R squared, is in the low single digits.[16]

Signals for trades can be based on

  • The VIX level relative to VXV, CBOE-3 monthly volatility index
  • The difference between VIX and its moving average of any length (usually 12-20 days).[17]

Changes in the cost of equity and growth rate of earningsEdit

Changes in change in the cost of equity and growth rate of earnings are related to equity returns, not the rate of inflation or the uncertainty of inflation.[18]

Total factor productivityEdit

Total factor productivity (TFP) growth volatility is negatively associated with the value of U.S. corporations. An increase of 1% in the standard deviation of TFP growth is associated with a reduction in the value-output ratio of 12%.[19] Changes in uncertainty can explain business cycle fluctuations, stock prices, and banking crises.[20]

News Articles and Paid Financial AdvisorsEdit

Stock Buybacks That Make CEOs Rich But Impoverish Their FirmsEdit

After the 2008 financial crisis, Corporate stock buybacks became a ‘dominant’ source of stock market demand.[21] Companies significantly increased the use of performance indicators as a prerequisite for awarding executive compensation. Corporate stock buybacks increase S&P 500 CEO executive compensation while also increasing the risks of bankruptcy caused by increased corporate debts used to pay for buybacks.[22]

Evidence for market timingEdit

Mutual fund flows are published by organizations like Investment Company Institute, Lipper, Morningstar, and TrimTabs.[23] They show that flows generally track the overall level of the market: investors buy stocks when prices are high, and sell stocks when prices are low. For example, in the beginning of the 2000s, the largest inflows to stock mutual funds were in early 2000 while the largest outflows were in mid-2002. These mutual fund flows were near the start of a significant bear (downtrending) market and bull (uptrending) market respectively. A similar pattern is repeated near the end of the decade.[24][25][26][27][28]

This mutual fund flow data seems to indicate that most investors (despite what they may say) actually follow a buy-high, sell-low strategy.[29][30] Studies confirm that the general tendency of investors is to buy after a stock or mutual fund price has increased.[31] This surge in the number of buyers may then drive the price even higher. However, eventually, the supply of buyers becomes exhausted, and the demand for the stock declines and the stock or fund price also declines. After inflows, there may be a short-term boost in return, but the significant result is that the return over a longer time is disappointing.[31]

Researchers suggest that, after periods of higher returns, individual investors will sell their value stocks and buy growth stocks. Frazzini and Lamont find that, in general, growth stocks have a lower return, but growth stocks with high inflows have a much worse return.[31]

Studies find that the average investor's return in stocks is much less than the amount that would have been obtained by simply holding an index fund consisting of all stocks contained in the S&P 500 index.[32][33][34][35][36]

For the 20-year period to the end of 2008, the inflation-adjusted market return was about 5.3% on average per year. The average investor managed to turn $1 million into $800,000, against $2.7 million for the index (after fund costs).[37]

Studies by the financial services market research company Dalbar say that the retention rate for bond and stock funds is three years. This means that in a 20-year period the investor changed funds seven times. Balanced funds are a bit better at four years, or five times. Some trading is necessary since not only is the investor return less than the best asset class, it is typically worse than the worst asset class, which would be better.[38] Balanced funds may be better by reason of investor psychology.[39]

Financial advisors often agree that investors have poor timing, becoming less risk averse when markets are high and more risk averse when markets are low, a strategy that will actually result in less wealth in the long-term compared to someone who consistently invests over a long period regardless of market trends.[40][41] This is consistent with recency bias and seems contrary to the acrophobia explanation. Similarly, Peter Lynch has stated that "Far more money has been lost by investors preparing for corrections or trying to anticipate corrections than has been lost in the corrections themselves."[42]

Proponents of the efficient-market hypothesis (EMH) claim that prices reflect all available information. EMH assumes that investors are highly intelligent and perfectly rational. However, others dispute this assumption. "Of course, we know stocks don't work that way".[43] In particular, proponents of behavioral finance claim that investors are irrational but their biases are consistent and predictable.

Difference in views on the viability of market timingEdit

Whether market timing is ever a viable investment strategy is controversial. Some may consider market timing to be a form of gambling based on pure chance, because they do not believe in undervalued or overvalued markets. The efficient-market hypothesis claims that financial prices always exhibit random walk behavior and thus cannot be predicted with consistency.

Some consider market timing to be sensible in certain situations, such as an apparent bubble. However, because the economy is a complex system that contains many factors, even at times of significant market optimism or pessimism, it remains difficult, if not impossible, to predetermine the local maximum or minimum of future prices with any precision; a so-called bubble can last for many years before prices collapse. Likewise, a crash can persist for extended periods; stocks that appear to be "cheap" at a glance, can often become much cheaper afterwards, before then either rebounding at some time in the future or heading toward bankruptcy.

Proponents of market timing counter that market timing is just another name for trading. They argue that "attempting to predict future market price movements" is what all traders do, regardless of whether they trade individual stocks or collections of stocks, aka, mutual funds. Thus if market timing is not a viable investment strategy, the proponents say, then neither is any of the trading on the various stock exchanges. Those who disagree with this view usually advocate a buy-and-hold strategy with periodic "re-balancing".[citation needed]

Others contend that predicting the next event that will affect the economy and stock prices is notoriously difficult. For examples, consider the many unforeseeable, unpredictable, uncertain events between 1985 and 2013 that are shown in Figures 1 to 6 [pages 37 to 42] of Measuring Economic Policy Uncertainty.[44] Few people in the world correctly predicted the timing and causes of the Great Recession during 2007–2009.[citation needed]

Market-timing software and algorithmsEdit

Institutional investors often use proprietary market-timing software developed internally that can be a trade secret. Some algorithms, like the one developed by Nobel Prize–winning economist Robert C. Merton, attempts to predict the future superiority of stocks versus bonds (or vice versa),[45][46] have been published in peer-reviewed journals and are publicly accessible.

Moving averageEdit

Market timing often looks at moving averages such as 50- and 200-day moving averages (which are particularly popular).[47] Some people believe that if the market has gone above the 50- or 200-day average that should be considered bullish, or below conversely bearish.[48] Technical analysts consider it significant when one moving average crosses over another. The market timers then predict that the trend will, more likely than not, continue in the future. Others say, "nobody knows" and that world economies and stock markets are of such complexity that market-timing strategies are unlikely to be more profitable than buy-and-hold strategies.

Moving average strategies are simple to understand, and often claim to give good returns, but the results may be confused by hindsight and data mining.[49][50]

Curve fitting and over-optimizationEdit

A major stumbling block for many market timers is a phenomenon called "curve fitting", which states that a given set of trading rules tends to be over-optimized to fit the particular dataset for which it has been back-tested. Unfortunately, if the trading rules are over-optimized they often fail to work on future data. Market timers attempt to avoid these problems by looking for clusters of parameter values that work well[51] or by using out-of-sample data, which ostensibly allows the market timer to see how the system works on unforeseen data. Critics, however, argue that once the strategy has been revised to reflect such data it is no longer "out-of-sample".

Independent review of market-timing servicesEdit

Several independent organizations (e.g., Timer Digest and Hulbert Financial Digest) have tracked some market timers' performance for over thirty years. These organizations have found that purported market timers in many cases do no better than chance, or even worse.

A 2004 study suggested that the best predictor of a fund's consistent outperformance of the market was low expenses and low turnover, not pursuit of a value or contrarian strategy.[52]

Bull Bear SpreadEdit

The Investors Intelligence Advisors Sentiment[53] Survey reports the attitudes of U.S. advisors. A large difference between the percentage bullish vs. bearish indicates more risk.

  • The 30% difference is increased risk.
  • At 40% difference, consider defensive measures.[54]

On January 16, 2018, Peter Boockvar said that the Investors Intelligence had the highest bull bear spread since 1986. Boockvar said that there was an extraordinary level of overboughtness.[55]

See alsoEdit

ReferencesEdit

  1. ^ Metcalfe, Guy (18 July 2018). "The mathematics of market timing". PLOS ONE. 13 (7): e0200561. arXiv:1712.05031. Bibcode:2018PLoSO..1300561M. doi:10.1371/journal.pone.0200561. PMC 6051602. PMID 30021021.
  2. ^ Board Of Trustees Of The City Of Atlanta | General Employees Pension Fund | Minutes Of Meeting | November 2, 2011
  3. ^ [1] Yale ICF Fooling Some of the People All of the Time: The Inefficient Performance and Persistence of Commodity Trading Advisors | Working Paper No. 08-21 October 2008 | Geetesh Bhardwaj AIG Financial Products; Rutgers University - Department of Economics Gary B. Gorton Yale School of Management; National Bureau of Economic Research (NBER) K. Geert Rouwenhorst Yale School of Management, International Center for Finance
  4. ^ A Century of Evidence on Trend-Following Investing | Brian Hurst | Yao Hua Ooi | AQR Capital Management, LLC | Lasse Heje Pedersen | AQR Capital Management, LLC; Copenhagen Business School - Department of Finance; New York University (NYU); Centre for Economic Policy Research (CEPR) | 26 Pages Posted: 28 Jun 2017
  5. ^ "Chasing Returns Has a High Cost for Investors | St. Louis Fed On the Economy".
  6. ^ Using Sentiment and Momentum to Predict Stock Returns | Kevin J. Lansing and Michael Tubbs | SENTIMENT * MOMENTUM variable | FRBSF Economic Letter 2018-29 December 24, 2018
  7. ^ Using Sentiment and Momentum to Predict Stock Returns | Kevin J. Lansing and Michael Tubbs | SENTIMENT * MOMENTUM variable | FRBSF Economic Letter 2018-29 December 24, 2018
  8. ^ https://trends.google.com/trends/explore?date=today%205-y&geo=US&q=stock%20market GoogleTrends | “stock market”
  9. ^ https://trends.google.com/trends/explore?geo=US&q=stock%20market%20crash GoogleTrends | “stock market crash”
  10. ^ Federal Reserve Bank of New York, Consumer Confidence: A Useful Indicator of . . . the Labor Market? Jason Bram, Robert Rich, and Joshua Abel ... Conference Board’s Present Situation Index   This article incorporates text from this source, which is in the public domain.
  11. ^ Federal Reserve Bank of Kansas City | Shen, Pu | Market Timing Strategies That Worked | May 2002 | pages=1–39
  12. ^ [2] Bonaparte, Yosef, The VIX is Your FIX: a Flexible Strategy to Timing the Stock Market (July 3, 2020). Available at SSRN
  13. ^ Zhu, Yunying (May 2018). Comparison of Three Volatility Forecasting Models (Thesis). hdl:1811/84909.
  14. ^ Bardgett, Chris; Gourier, Elise; Leippold, Markus (1 March 2019). "Inferring volatility dynamics and risk premia from the S&P 500 and VIX markets". Journal of Financial Economics. 131 (3): 593–618. doi:10.1016/j.jfineco.2018.09.008.
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  18. ^ [3] The Spurious Relation between Inflation Uncertainty and Stock Returns: Evidence from the U.S. Samih Antoine Azar Faculty of Business Administration & Economics, Haigazian University Mexique Street, Kantari, Beirut, LEBANON
  19. ^ Bocola, Luigi; Gornemann, Nils (March 2013). Risk, Economic Growth and the Value of U.S. Corporations (PDF) (Report). SSRN 2243705.
  20. ^ Orlik, Anna; Veldkamp, Laura (22 October 2015). Understanding Uncertainty Shocks and the Role of Black Swans (Report). SSRN 2754317.
  21. ^ [4] Buybacks are the ‘dominant’ source of stock-market demand | Chris Matthews | Published: Nov. 9, 2019 at 11:48 a.m. ET
  22. ^ [5] The real effects of share repurchases | Heitor Almeida, Vyacheslav Fos, Mathias Kronlunda | Journal of Financial Economics | Volume 119, Issue 1, January 2016, Pages 168-185
  23. ^ "Estimated Long-Term Mutual Fund Flows - Data via Quandl". www.quandl.com. Retrieved 2015-10-01.
  24. ^ Kinnel, Russel (15 February 2010). "Bad Timing Eats Away at Investor Returns". Morningstar.com. Archived from the original on 26 September 2017.
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  32. ^ Anderson, Tom. "Fund Investors Lag As S&P 500 Nears All-Time High".
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  40. ^ Lieber, Ron (8 October 2008). "Switching to Cash May Feel Safe, but Risks Remain". The New York Times.
  41. ^ "Emotions And Market Timing, Emotions and Timing". www.fibtimer.com.
  42. ^ As quoted in "The Wisdom of Great Investors: Insights from Some of History’s Greatest Investment Minds, by Davis Advisers, p. 7
  43. ^ Jim Cramer's Getting Back to Even, pp. 63-64
  44. ^ Baker, Scott R.; Bloom, Nicholas; Davis, Steven J. (1 November 2016). "Measuring Economic Policy Uncertainty*". The Quarterly Journal of Economics. 131 (4): 1593–1636. doi:10.1093/qje/qjw024.
  45. ^ Merton, Robert C. (1981). "On Market Timing and Investment Performance. I. An Equilibrium Theory of Value for Market Forecasts". The Journal of Business. 54 (3): 363–406. doi:10.1086/296137. JSTOR 2352345.
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  48. ^ Hulbert, Mark. "Good enough".
  49. ^ Zakamulin, Valeriy (August 2014). "The real-life performance of market timing with moving average and time-series momentum rules". Journal of Asset Management. 15 (4): 261–278. doi:10.1057/jam.2014.25. S2CID 195333197.
  50. ^ Zakamulin, Valeriy (11 December 2015). "A Comprehensive Look at the Empirical Performance of Moving Average Trading Strategies". SSRN 2677212. Cite journal requires |journal= (help)
  51. ^ Pruitt, George, & Hill, John R. Building Winning Trading Systems with TradeStation(TM), Hoboken, N.J: John Wiley & Sons, Inc. ISBN 0-471-21569-4, p. 106-108.
  52. ^ Malkiel, Burton G. (31 January 2004). "Can Predictable Patterns in Market Returns be Exploited Using Real Money?". The Journal of Portfolio Management. 30 (5): 131–141. doi:10.3905/jpm.2004.442638. S2CID 154981913.
  53. ^ [6] Yardeni Research, Inc. | Stock Market Indicators: Fundamental, Sentiment, & Technical |Investors Intelligence Sentiment
  54. ^ Bush Wealth Management | MARKET COMMENTARY 11/28/2017 | Stacy Bush & Kent Patrick | November 28, 2017
  55. ^ Stock market’s wild flip flop comes as warning signs build | JANUARY 16, 2018 | Patti Domm, NBR, CNBC.com

External linksEdit