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The trend is not your friend! Why empirical timing success is determined by the underlying's price characteristics and market efficiency is irrelevant

Author

Listed:
  • Scholz, Peter
  • Walther, Ursula
Abstract
The often reported empirical success of trend-following technical timing strategies remains to be puzzling. In previous academic research, many authors admit some prediction power but struggle to substantiate their findings by referring vaguely to insufficient market effciency or unknown hidden patterns in asset price processes. We claim that empirical timing success is possible even in perfectly efficient markets but does not indicate prediction power. We prove this by systematically tracing back timing success to the statistical characteristics of the underlying asset price time series, which is modeled by standard stochastic processes. Five major impact factors are studied: return autocorrelation, trend, volatility and its clustering as well as the degree of market efficiency. We use trading rules based on different intervals of the simple moving average (SMA) as an example. These strategies are applied to simulated asset price data to allow for systematic parameter variations. Subsequently, we test the same strategies on real market data using non-parametric historical simulations and compare the results. Evaluation is done by an extensive selection of statistical-, return-, risk-, and performance figures calculated from the simulated return distributions.

Suggested Citation

  • Scholz, Peter & Walther, Ursula, 2011. "The trend is not your friend! Why empirical timing success is determined by the underlying's price characteristics and market efficiency is irrelevant," CPQF Working Paper Series 29, Frankfurt School of Finance and Management, Centre for Practical Quantitative Finance (CPQF).
    • Handle: RePEc:zbw:cpqfwp:29
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    References listed on IDEAS

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    Cited by:

    1. Dietmar Harhoff & Elisabeth Mueller & John Van Reenen, 2014. "What are the Channels for Technology Sourcing? Panel Data Evidence from German Companies," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 23(1), pages 204-224, March.
    2. Scholz, Peter, 2012. "Size matters! How position sizing determines risk and return of technical timing strategies," CPQF Working Paper Series 31, Frankfurt School of Finance and Management, Centre for Practical Quantitative Finance (CPQF).
    3. Böing, Philipp & Müller, Elisabeth, 2012. "Technological Capabilities of Chinese Enterprises: Who is Going to Compete Abroad?," VfS Annual Conference 2012 (Goettingen): New Approaches and Challenges for the Labor Market of the 21st Century 62081, Verein für Socialpolitik / German Economic Association.
    4. Inklaar, Robert & Koetter, Michael & Noth, Felix, 2012. "Who's afraid of big bad banks? Bank competition, SME, and industry growth," Frankfurt School - Working Paper Series 197, Frankfurt School of Finance and Management.
    5. Alexander Libman & Vladimir Kozlov & André Schultz, 2012. "Roving Bandits in Action: Outside Option and Governmental Predation in Autocracies," Kyklos, Wiley Blackwell, vol. 65(4), pages 526-562, November.
    6. Boeing, Philipp & Mueller, Elisabeth & Sandner, Philipp, 2012. "What makes Chinese firms productive? Learning from indigenous and foreign sources of knowledge," Frankfurt School - Working Paper Series 196, Frankfurt School of Finance and Management.
    7. Kostka, Genia & Moslener, Ulf & Andreas, Jan G., 2011. "Barriers to energy efficiency improvement: Empirical evidence from small-and-medium sized enterprises in China," Frankfurt School - Working Paper Series 178, Frankfurt School of Finance and Management.
    8. Yu, Xiaofan, 2011. "A spatial interpretation of the persistency of China's provincial inequality," Frankfurt School - Working Paper Series 171, Frankfurt School of Finance and Management.

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    More about this item

    Keywords

    bootstrapping; market efficiency; market timing; parameterized simulation; performance analysis; return distribution; technical analysis; technical trading;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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