Introduction to Market timing models

By Sandra Makumbirofa

The study of stock market trading is synonymous for its random walk properties, yet there is still a strong controversial school of thought that supports the idea of ‘market timing’. Detemple and Rindisbacher (2013:2492) describe market timing as the ability to extract information about future market returns of an investment. These market timing models aim to provide a lower-risk strategy for growing portfolios by shifting assets during periods of high risk and low risk.

Since trading on the stock market involves constant buying and selling of stock to increase one’s profitability, traders have long been looking for the key to effectively anticipate the market ahead of other traders. The disadvantage of discovering this key is that a truly successful market timing method is not sustainable in the long-run because as more and more traders discover it, it ceases to be effective (Dickson & Knudsen, 2012:1).

Proponents against market timing back their arguments with the efficient market hypothesis. A market is said to be efficient if prices adjust quickly and, on average, without bias, to new information. Profiting from predicting price movements in an efficient market would be very difficult and unlikely. As a result, security prices find themselves adjusting before an investor has time to trade on and profit from a new piece of information (Clarke, Jandik & Mandelker, 2000:2).

The evidence that the stock market is fairly efficient is not hard to find, and this is what makes its predictability particularly difficult. In spite of these obstacles, market timing is still important because it can help traders to efficiently allocate investment funds among managers and academics with superior forecasting skills that can violate the Efficient Market Hypothesis (Henriksson & Merton, 1981:514).

Bearing in mind that any forecasting of performance is model specific, a possible concern is that results obtained are prone to model risk or misspecification (Woodward & Brooks, 2010:59). This article will shed some light into the basics of Market Timing Models.

1. The basics
On looking at the early proponents of market timing, Treynor and Mazuy (1966) and Henriksson and Merton (1981) support that successful market timers increase their market exposures when the market excess return is positive and can keep this exposure lower otherwise.

Burmeister, Roll and Ross (1994) (cited in Brown & Riley, 2009:248) analysed the predictive ability of a model based on a different set of macroeconomic factors and they defined five risk exposures:

  1. Confidence risk- this is based on unexpected changes in the willingness of investors to take on investment risk;
  2. Time horizon risk- which is the unpredicted changes in investors’ desired time to receive earnings;
  3. Inflation risk- this is based on a combination of the unexpected components of short-term and long-term inflation rates;
  4. Business cycle risk- which represents unanticipated changes in the level of overall business activity; and
  5. Market-timing risk defined as part of the Standard & Poor’s 500 total return that is not explained by the other four macroeconomic factors.

The market timing risk is computed as that part of the S&P 500 total return that is not explained by the first four macroeconomic risks and an intercept term (Burmeister, Roll & Ross, 2003:8). We will now consider the typical regression model.

According to Detemple and Rindisbacher (2013:2493) the typical market timing regression model is:


Each stock and portfolio has exposures (or betas) relating to the different types of systematic risks. Hence the pattern of economic betas for a particular stock or portfolio is known as its risk exposure profile. Markets with additional expected return reward risk exposures so that the risk exposure profile determines the volatility and performance of a well-diversified portfolio. In this way the profile serves to show how a stock or portfolio will perform under different economic conditions (Burmeister, Roll & Ross, 2003:3).

The beta of a portfolio is increased when the stock market is expected to be bullish, and decreased when the market is expected to change from bullish to bearish (Firer, Ward & Teeuwisse, 1987:19). As a result successful market timing would involve moving from 100% ordinary shareholding during bull markets to the holding of 100% of cash or cash equivalents during bear markets.

  • A bull market occurs when the market is following a long-term climb especially when the economic environment is strong, the unemployment rate is low and the inflation rate is relatively under control (Dickson & Knudsen 2011:2).
  • A bear market is the exact opposite and occurs when the market is following a long-term decline. This usually occurs during economic recessions and periods of high unemployment rate and rising inflation.

In a bear strategy, the investor initially holds a well-diversified portfolio of shares. If a market upturn is expected, the exposed portfolio of shares is held passively. In anticipation of a market downturn, options are purchased so as to hedge the overall position (Waksman et al., 1997:82).

Waksman et al. (1997:81) professes that a prerequisite for the successful exploitation of such a timing programme is the presence of a suitably liquid and frictionless market place. In the same study, it was found that South Africa’s economic environment was characterised by stock market illiquidity, high transaction costs and chronic scrip shortages. It was also found that the transaction costs and the opportunity costs of not being able to re-enter the spot market and thereby participate in positive market periods made a market timing strategy difficult to implement (Waksman et al., 1997:81).

The subsequent articles will shed more light into the current economic environment of South Africa. Of interesting importance are the three types of market timing abilities: strong form; mild-form and weak form.

2. Market Timing Ability:

2.1.1 Strong-form market timing ability

This requires that the value of beta satisfies β(x + ζ) > β(x) for all x and all ζ > 0. In other words, beta is a monotonic increasing function of the excess market return. Strong-form market timing ability is concluded when the estimates of the coefficients governing the positive relationship between the excess market return and risk are significant (Woodward & Brooks, 2010:63).

2.1.2 Mild-form market timing ability

This test requires that the value of the beta satisfies β(x + ζ) ≥ β(x) for all x and all ζ > 0 and β(x + ζ) > β(x) for some x and all ζ > 0. Mild-form market ability is concluded when the threshold model apples and δ , the estimated differential value of the up market slope, is significantly positive. It is important to note that this test does not give special attention to the behaviour of beta for (Rm – Rƒ)  near zero. If a fund beta is an increasing function of the excess market return in a small neighbourhood of zero but a decreasing function of the excess market returns everywhere else, then for most values of the excess market return, the manager acts in a perverse way (Woodward & Brooks, 2010:63).

2.1.3 Weak-form market timing ability

Weak form market timing

3. Conclusion
Advocates for market timing believe that it is indeed possible to track stock on the market so as to predict future upward or downward trends, while the ‘buy and hold’ proponents strongly believe that successful market timing in the long run is impossible given an efficient stock market. The next article will look at empirical evidence on successful market timing models, and lessons to build on to a working market timing model using a momentum strategy.

4. References

Brown, K. C. & Riley, F. K. 2009. Analysis of Investments and Management of Portfolios. 9th ed. USA:South-Western Cencage Learning.

Burmeister, E., Roll, R & Ross, S. A. 2003. Using Macroeconomic Factors to Control Portfolio Risk. [Online] Available: Accessed: 17 June 2015.

Clarke, J., Jandik, T & Mandelker, G. 2000. The efficient Market Hypothesis. [Online] Available: Accessed: 17 June 2015.

Detemple, J & Rindisbacher, M. 2013. A Structural Model of Dynamic Market Timing. The Review of Financial Studies, 26(10):2492-2547.

Dickson, R. A & Knudsen, T. L. 2012. Mastering Market Timing: Using the works of L. M Lowry and R. D Wyckoff to identify key market turning points. 1st ed. New Jersey, USA: Pearson Education.

Firer, C., Ward, M & Teeuwisse, F. 1987. Market timing and the JSE. The Investment Analysts Journal, 1987:19-31.

Henriksson, R. D & Merton, R. C. 1981. On Market Timing and Investment Performance. II. Statistical Procedures for evaluating Forecasting Skills. The Journal of Business, 54(4):513-533.

Waksman, G., Sandler, M., Ward, M & Firer, C. 1997. Market Timing on the Johannesburg Stock Exchange Using Derivative Instruments. Omega International Journal of Management, 25(1):81-91.

Woodward, G & Brooks, R. 2010. The market timing ability of Australian superannutation funds: Nonlinearities and smooth transition models. (In Gregoriou, G. N., Hoppe, C. & Wehn, C. S., ed The risk modelling evaluation handbook: Rethinking financial risk management methodologies in the global capital markets. New York: McGraw-Hill. p.59-73).

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