Skip to main content
SpringerLink
Log in

Data, Portfolios, and Performance: How We Test the Strategies

  • Chapter
  • First Online:
Book cover Price-Based Investment Strategies

  • 876 Accesses

Abstract

In this chapter, the authors reviewed the methods, then tested and implemented particular strategies. They presented the data sources and explained how they had prepared the samples. Having demonstrated how they had formed the portfolios and implemented the strategies, the authors specified both the methods and indicators used to evaluate the strategies.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 139.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    This approach was used in numerous studies of the cross-section of stock returns. Examples include Liu et al. (2011), Bekaert et al. (2007), Brown et al. (2008), Rouwenhorst (1999), Barry et al. (2002), Griffin (2002), Bali and Cakici (2010), Chui et al. (2010), Hou et al. (2011), de Groot et al. (2012b), de Moor and Sercu (2013a, b), and Cakici et al. (2013).

  2. 2.

    Waszczuk (2014a, b) indicates that the discrete-time asset pricing theory provides no information on the relevant interval of expected returns (Fama 1998). Thus, we choose monthly intervals, which are also the most widely used in similar studies. The reasons are twofold. On the one hand, it offers a sufficient number of observations to ensure power of the conducted tests. On the other hand, monthly intervals avoid excessive exposure to the micro-structure issues (de Moor and Sercu 2013a). Lower frequency could be adequate for the estimation of capital cost but not for asset pricing tests, for which shorter time intervals markedly improve their quality. In practice, it is used rather rarely, mainly when the research additionally encompasses macroeconomic data. The paper by Avramov and Chordia (2006), who investigated the Consumption CAPM , may serve as an example. Some of the methods and their description in this book are analogous and sourced from Zaremba and Shemer (2017).

  3. 3.

    The filters applied in this book are similar to plenty of asset pricing studies on international equities. For instance, de Moor and Sercu (2013a, b) set the minimum market value at $100 million on the international sample and additionally limit the examinations to stocks with monthly trading volume larger than $100,000, identically as in this book. Brown et al. (2008) include only equities belonging to the intersection of top 50% market liquidity and top 50% market capitalization. van der Hart et al. (2005) set the lower boundary for the firm capitalization at $100 million for the last month of the study sample and Burghof and Prothmann (2011) use the limit of GBP20 million. Considering the price of the stock , most of the studies rely on the SEC definition, implying that penny stocks priced below $5 (Jegadeesh and Titman 2001; Gutierrez and Kelley 2008; Bhootra 2011).

  4. 4.

    The type of quantile portfolios highly depends on the number of available constituents, and it is a trade-off between the number of assets available and the grid resolution (Waszczuk 2014b). The most widely considered alternatives are quintiles, for example, Banz (1981) and Chan et al. (1998), and deciles, for example, Jegadeesh and Titman (1993, 2001) and Lakonishok et al. (1994). We decided that 78 diversified index portfolios are sufficient for the 20th and 80th breakpoints but insufficient for the 10th and 90th breakpoints. Among alternative approaches, Bauman et al. (1998) considered quartile grouping, Achour et al. (1998) worked with tertile portfolios, and Brav et al. (2000) used the 50% cut-off. In our case, due to a relatively small number of assets in the portfolios, we mostly rely on tertile portfolios.

  5. 5.

    For stocks, see, Arnott et al. (2005), Tamura and Shimizu (2005), Hsu and Campolo (2006), Walkshausl and Lobe (2010), and Zaremba and Miziołek (2017a). For comprehensive literature surveys, see Chow et al. (2011), Amenc et al. (2012), and Bolognesi and Pividori (2016); for country equity indices, see Estrada (2008), Yan and Zhao (2013), and Zaremba and Miziołek (2017b).

  6. 6.

    In the literature, by default the term volatility means a yearly standard deviation of returns. Both terms are used in this book in the same meaning.

  7. 7.

    In financial studies, we have two main methods of converting prices to returns: the arithmetic (simple) and logarithmic return approach. The latter is usually preferred for three basic reasons: (1) better arithmetical properties (including compounding over time), (2) return distributions that represent a larger degree of normality than arithmetic returns, and (3) reduced heteroscedasticity in logarithmic returns series (Waszczuk 2014b). This type of returns are not fully additive over assets, but the bias is rather small, especially for the short time intervals; so they are also used in the cross-sectional studies (e.g., Liew and Vassalou [2000], Diacogiannis and Kyriazis [2007]). In the calculations used in this book, for the sake of simplicity, we use arithmetic returns. For further discussion on the return calculation for financial studies, see Roll (1984) or Vaihekoski (2004).

  8. 8.

    The Sharpe ratio was later frequently revised and modified by many authors, including its inventor; across this book, however, we rely on the simplest and most intuitive definition described by Sharpe (1966). For more examples of the modifications and revisions of the Sharpe ratio, see Sharpe (1994), Vinod and Morey (1999), Dowd (2000), Israelsen (2005), or Le Sourd (2007).

  9. 9.

    The detailed characteristics of the Sharpe model were extensively presented in a number of financial textbooks, for example, Francis (1990), Elton and Gruber (1995), Campbell et al. (1997), Cochrane (2005), or Wilmott (2008).

  10. 10.

    Treynor (1961, 1962), Lintner (1965a, b) and Mossin (1966) developed a similar model at the same time, so all four—including Sharpe (1964)—are now considered to be the fathers of the CAPM model. See also French (2003).

  11. 11.

    For simplicity, in the book we use the Jensen’s alpha in its most basic form. Nonetheless, this performance measure has been frequently updated and modified over time (Zaremba 2015). For example, Black (1972) suggested using a portfolio with a beta coefficient equal to zero instead of a risk-free return. Brennan (1970), on the other hand, constructed a model taking into account taxes. Elton and Gruber (1995) suggested using a total risk instead of a systematic one. Many papers also suggested putting additional attention to the way the profit was earned and how the alpha coefficient was decomposed in respect of its origin (e.g., Treynor and Mazuy 1966, McDonald 1973, Pogue et al. 1974, Merton 1981, Henriksson and Merton 1981, Henriksson 1984, Grinblatt and Titman 1989). Furthermore, a substantial body of research attempts to improve the measure of systematic risk . There are several basic strands in this line of studies. The first uses conditional betas taking different values for growing and declining markets (Ferson and Schadt 1996; Christopherson et al. 1999). The second approach incorporates other risk factors and macroeconomic variables (e.g., Ross 1976; Fama and French 1996; Carhart 1997; Amenc and Le Sourd 2003). Example of different types of systematic risk could be found in the models of Connor and Korajczyk (1986), based on the arbitrage pricing theory, the index model by Elton et al. (1993), or the management style analysis according to Sharpe (1992).

  12. 12.

    In particular, we source the market factor returns from Kenneth R. French’s website: http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html.

  13. 13.

    All the regression parameters in this book were estimated using the OLS method. This approach has been employed, among many others, by Fama and French (2012). Furthermore, all the t-statistics were estimated using the bootstrap standard errors to avoid any distributional assumptions. Under our null hypothesis, all of the intercepts equal zero whereas the alternative hypothesis assumes the contrary. The bootstrap simulations are performed with the use of 10,000 random draws. All the statistical analyses are performed in R.

  14. 14.

    Further details could be found in basically any statistical textbook, for example, Aczel (2012).

References

  • Achour, D., Harvey, C., Hopkins, G., & Lang, C. (1998). Stock selection in emerging markets: Portfolio strategies in Malaysia, Mexico, and South Africa. Emerging Markets Quarterly, 2, 38–91.

    Google Scholar 

  • Aczel, A. D. (2012). Complete business statistics (8th ed.). Morristown: Wohl Publishing.

    Google Scholar 

  • Amenc, N., Goltz, F., & Lodh, A. (2012). Choose your betas: Benchmarking alternative equity strategies. Journal of Portfolio Management, 39(1), 88–111.

    Article  Google Scholar 

  • Amenc, N., & Le Sourd, V. (2003). Portfolio theory and performance analysis. Hoboken: John Wiley & Sons.

    Google Scholar 

  • Arnott, R. D., Hsu, J., & Moore, P. (2005). Fundamental indexation. Financial Analyst Journal, 61(2), 83–99.

    Article  Google Scholar 

  • Asness, C. S., Frazzini, A., & Pedersen, L. H. (2017). Quality minus junk. Available at SSRN: https://ssrn.com/abstract=2312432 or https://doi.org/10.2139/ssrn.2312432. Accessed 23 Oct 2017.

  • Avramov, D., & Chordia, T. (2006). Asset pricing models and financial market anomalies. Review of Financial Studies, 19(3), 1001–1040.

    Article  Google Scholar 

  • Bali, C., & Cakici, N. (2010). World market risk, country-specific risk and expected returns in international stock markets. Journal of Banking and Finance, 34, 1152–1165.

    Article  Google Scholar 

  • Bali, T. G., Cakici, N., & Fabozzi, F. J. (2013). Book-to-market and the cross-section of expected returns in international stock markets. Journal of Portfolio Management, 39(2), 101–115.

    Article  Google Scholar 

  • Banz, R. W. (1981). The relationship between return and market value of common stocks. Journal of Financial Economics, 9, 3–18.

    Article  Google Scholar 

  • Barry, C., Goldreyer, E., Lockwood, L., & Rodriguez, M. (2002). Robustness of size and value effects in emerging equity markets, 1985–2000. Emerging Markets Review, 3, 1–30.

    Article  Google Scholar 

  • Bauman, W. S., Conover, C. M., & Miller, R. E. (1998). Growth versus value and large-cap versus small-cap stocks in international markets. Financial Analyst Journal, 54(2), 75–89.

    Article  Google Scholar 

  • Bekaert, G., Harvey, C., & Lundblad, C. (2007). Liquidity and expected returns: Lessons from emerging markets. Review of Financial Studies, 20, 1783–1831.

    Article  Google Scholar 

  • Bhootra, A. (2011). Are momentum profits driven by the cross-sectional dispersion in expected stock returns? Journal of Financial Markets, 14, 494–513.

    Article  Google Scholar 

  • Black, F. (1972). Capital market equilibrium with restricted borrowing. Journal of Business, 45, 44–455.

    Google Scholar 

  • Bolognesi, E., & Pividori, M. (2016). Fundamental indexation in Europe: New evidence. Journal of Financial Management, Markets and Institutions, 4(2), 103–128.

    Google Scholar 

  • Brav, A., Geczy, C., & Gompers, P. (2000). Is the abnormal return following equity issuance anomalous. Journal of Financial Economics, 56, 209–249.

    Article  Google Scholar 

  • Brennan, M. J. (1970). Taxes, market valuation and corporate financial policy. National Tax Journal, 25, 417–427.

    Google Scholar 

  • Brown, A., Du, D. Y., Rhee, S. G., & Zhang, L. (2008). The returns to value and momentum in Asian markets. Emerging Markets Review, 9, 79–88.

    Article  Google Scholar 

  • Burghof, H. P., & Prothmann, F. (2011). The 52-week high strategy and information uncertainty. Financial Markets and Portfolio Management, 25(4), 345–378.

    Article  Google Scholar 

  • Cakici, N., Fabozzi, F. J., & Tan, S. (2013). Size, value, and momentum in emerging market stock returns. Emerging Markets Review, 16, 46–65.

    Article  Google Scholar 

  • Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (1997). The econometrics of financial markets. Princeton: Princeton University Press.

    Google Scholar 

  • Carhart, M. M. (1997). On persistence in mutual fund performance. Journal of Finance, 52(1), 57–82.

    Article  Google Scholar 

  • Chan, L., Karceski, J., & Lakonishok, J. (1998). The risk and return from factors. Journal of Financial and Quantitative Analysis, 33, 159–188.

    Article  Google Scholar 

  • Chow, T., Hsu, J. C., Kalesnik, V., & Little, B. (2011). A survey of alternative equity index strategies. Financial Analysts Journal, 67(5), 37–57.

    Article  Google Scholar 

  • Christopherson, J. A., Ferson, W. E., & Turner, A. L. (1999). Performance evaluation using conditional alphas and betas. Journal of Portfolio Management, 26(1), 59–72.

    Article  Google Scholar 

  • Chui, A. C. W., Titman, S., & Wei, J. K. C. (2010). Individualism and momentum around the world. Journal of Finance, 65(1), 361–392.

    Article  Google Scholar 

  • Cochrane, J. H. (2005). Asset pricing. Princeton: Princeton University Press.

    Google Scholar 

  • Connor, G., & Korajczyk, R. (1986). Performance measurement with the arbitrage pricing theory: A new framework for analysis. Journal of Financial Economics, 15(3), 373–394.

    Article  Google Scholar 

  • de Groot, W., Pang, J., & Swinkels, L. A. P. (2012b). The cross-section of stock returns in frontier emerging markets. Journal of Empirical Finance, 19(5), 796–818.

    Article  Google Scholar 

  • De Moor, L., & Sercu, P. (2013a). The smallest stocks are not just smaller: Global evidence. European Journal of Finance, 21(2), 51–70.

    Google Scholar 

  • De Moor, L., & Sercu, P. (2013b). The smallest firm effect: An international study. Journal of International Money and Finance, 32, 129–155.

    Article  Google Scholar 

  • Dowd, K. (2000). Adjusting for risk: An improved Sharpe ratio. International Review of Economics and Finance, 9(3), 209–222.

    Article  Google Scholar 

  • Elton, E. J., & Gruber, M. J. (1995). Modern portfolio theory and investment analysis. Hoboken: John Wiley & Sons.

    Google Scholar 

  • Elton, E. J., Gruber, M. J., Das, S., & Hlavka, M. (1993). Efficiency with costly information: A reinterpretation of evidence from managed portfolios. Review of Financial Studies, 6(1), 1–22.

    Article  Google Scholar 

  • Estrada, J. (2008). Fundamental indexation and international diversification. Journal of Portfolio Management, 34(3), 93–109.

    Article  Google Scholar 

  • Fama, E. F. (1998). Market efficiency, long-term returns, and behavioral finance. Journal of Financial Economics, 49(3), 283–306.

    Article  Google Scholar 

  • Fama, E. F., & French, K. R. (1996). Multifactor explanations of asset pricing anomalies. Journal of Finance, 51(1), 55–84.

    Article  Google Scholar 

  • Fama, E. F., & French, K. R. (2012). Size, value, and momentum in international stock returns. Journal of Financial Economics, 105(3), 457–472.

    Article  Google Scholar 

  • Ferson, W. E., & Schadt, R. W. (1996). Measuring fund strategy and performance in changing economic conditions. Journal of Finance, 51(2), 425–461.

    Article  Google Scholar 

  • Francis, J. C. (1990). Investments: Analysis and management. New York: McGraw Hill Higher Education.

    Google Scholar 

  • French, C. W. (2003). The treynor capital asset pricing model. Journal of Investment Management, 1(2), 60–72.

    Google Scholar 

  • Griffin, J. M. (2002). Are the Fama and French factors global or country specific? Review of Financial Studies, 15, 783–803.

    Article  Google Scholar 

  • Grinblatt, M., & Titman, S. (1989). Portfolio performance evaluation: Old issues and new insights. Review of Financial Studies, 2, 393–421.

    Article  Google Scholar 

  • Gutierrez, R. C., Jr., & Kelly, E. K. (2008). The long-lasting momentum in weekly returns. Journal of Finance, 63(1), 415–447.

    Article  Google Scholar 

  • Henriksson, R. D. (1984). Market timing and mutual fund performance: An empirical investigation. Journal of Business, 57(1), 73–96.

    Article  Google Scholar 

  • Henriksson, R. D., & Merton, R. C. (1981). On market timing and investment performance II: Statistical procedures for evaluating forecasting skills. Journal of Business, 54(4), 513–533.

    Article  Google Scholar 

  • Hou, K., Karolyi, G. A., & Kho, B. C. (2011). What factors drive global stock returns? Review of Financial Studies, 24(8), 2527–2574. https://doi.org/10.1093/rfs/hhr013.

    Article  Google Scholar 

  • Hsu, J. C., & Campolo, C. (2006). New frontiers in index investing: An examination of fundamental indexation. Journal of Indexes, 58, 32–37.

    Google Scholar 

  • Israelsen, C. L. (2005). A refinement to the Sharpe ratio and information ratio. Journal of Asset Management, 5(6), 423–427.

    Article  Google Scholar 

  • Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. Journal of Finance, 48, 65–91.

    Article  Google Scholar 

  • Jegadeesh, N., & Titman, S. (2001). Profitability of momentum strategies: An evaluation of alternative explanations. Journal of Finance, 56(2), 599–720.

    Article  Google Scholar 

  • Kyriazis, D., & Diacogiannis, G. (2007). Testing the performance of value strategies in the Athens Stock Exchange. Applied Financial Economics, 17(18), 1511–1528.

    Article  Google Scholar 

  • Lakonishok, J., Schleifer, A., & Vishny, R. W. (1994). Contrarian investment, extrapolation, and risk. Journal of Finance, 49(5), 1541–1578.

    Article  Google Scholar 

  • Le Sourd, V. (2007). Performance measurement for traditional investments. Literature survey (Research paper). DHEC Risk and Asset Management Research Centre. Available online: http://www.edhec-risk.com/performance_and_style_analysis/perf_measurement/index_html/attachments/EDHEC%20Publi%20performance%20measurement%20for%20traditional%20investment.pdf. Accessed 16 Oct 2017.

  • Liew, J., & Vassalou, M. (2000). Can book-to-market, size and momentum be risk factors that predict economic growth? Journal of Financial Economics, 57, 221–245.

    Article  Google Scholar 

  • Lintner, J. (1965a). The valuation of risk assets and the selection of risky investments in stock portfolios and capital budgets. Review of Economics and Statistics, 47(1), 13–37.

    Article  Google Scholar 

  • Lintner, J. (1965b). Security prices, risk and maximal gains from diversification. Journal of Finance, 20(4), 587–615.

    Google Scholar 

  • Liu, M., Liu, Q., & Ma, T. (2011). The 52-week high momentum strategy in international stock markets. Journal of International Money and Finance, 30, 180–204.

    Article  Google Scholar 

  • McDonald, J. (1973). French mutual fund performance: Evaluation of internationally diversified portfolios. Journal of Finance, 28(5), 1161–1180.

    Article  Google Scholar 

  • Merton, R. C. (1981). On market timing and investment performance: An equilibrium theory of value for market forecasts. Journal of Business, 54(3), 363–406.

    Article  Google Scholar 

  • Mossin, J. (1966). Equilibrium in a capital asset market. Econometrica, 35(4), 768–783.

    Article  Google Scholar 

  • Narang, R. K. (2013). Inside the black box: A simple guide to quantitative and high frequency trading. Hoboken: Wiley.

    Book  Google Scholar 

  • Novy-Marx, R., & Velikov, M. (2016). A taxonomy of anomalies and their trading costs. Review of Financial Studies, 29(1), 104–147. https://doi.org/10.1093/rfs/hhv063.

    Article  Google Scholar 

  • Pogue, G., Solnik, B., & Rousselin, A. (1974). International diversification: A study of the French mutual funds (Working paper). Sloan School of Management. Available at http://dspace.mit.edu/handle/1721.1/48147. Accessed 17 Oct 2015.

  • Roll, R. (1984). A simple implicit measure of the effective bid-ask spread in an efficient market. Journal of Finance, 39, 1127–1139.

    Article  Google Scholar 

  • Ross, S. (1976). The arbitrage theory of capital asset pricing. Journal of Economic Theory, 13(3), 341–360.

    Article  Google Scholar 

  • Rouwenhorst, G. K. (1999). Local return factors and turnover in emerging stock markets. Journal of Finance, 54, 1439–1464.

    Article  Google Scholar 

  • Sharpe, W. F. (1964). Capital asset prices: A theory of market equilibrium under conditions of risk. Journal of Finance, 19(3), 425–442.

    Google Scholar 

  • Sharpe, W. F. (1966). Mutual fund performance. Journal of Business, 39 (January), 119–138.

    Article  Google Scholar 

  • Sharpe, W. F. (1992). Asset allocation: Management style and performance measurement. Journal of Portfolio Management, 18, 7–19.

    Article  Google Scholar 

  • Sharpe, W. F. (1994). The Sharpe ratio. Journal of Portfolio Management, 21(1), 49–58.

    Article  Google Scholar 

  • Tamura, H., & Shimizu, Y. (2005). Fundamental indices. Do they outperform market-cap weighted indices on a global basis? Tokyo: Global Quantitative Research, Nomura Securities.

    Google Scholar 

  • Treynor, J. L. (1961). Market value, time, and risk. Available at SSRN: https://ssrn.com/abstract=2600356 or https://doi.org/10.2139/ssrn.2600356.

  • Treynor, J., & Mazuy, K. (1966). Can mutual funds outguess the market? Harvard Business Review, 44, 131–136.

    Google Scholar 

  • Treynor, J. L (1962). Toward a theory of market value of risky assets (Unpublished manuscript). Final version in Asset Pricing and Portfolio Performance (pp. 15–22), 1999, Robert A. Korajczyk (ed.). London: Risk Books. Available also at SSRN: http://ssrn.com/abstract=628187 or https://doi.org/10.2139/ssrn.628187. Accessed 17 Oct 2015.

  • Vaihekoski, M. (2004). Portfolio construction for tests of asset pricing models. Financial Markets, Institutions, and Instruments, 13(1), 1–39.

    Article  Google Scholar 

  • van der Hart, J., de Zwart, G., & van Dijk, D. (2005). The success of stock selection strategies in emerging markets: Is it risk or behavioural bias? Emerging Markets Review, 6, 238–262.

    Article  Google Scholar 

  • Vinod, H. D., & Morey, M. R. (1999). A double Sharpe ratio (Working paper). Available at SSRN: http://papers.ssrn.com/sol3/papers.cfm?abstract_ id=168748. Accessed 16 Oct 2017.

  • Walkshausl, C., & Lobe, S. (2010). Fundamental indexing around the world. Review of Financial Economics, 19(3), 117–127.

    Article  Google Scholar 

  • Waszczuk, A. (2014a). Assembling international equity datasets – Review of studies on the cross-section of returns. Procedia Economics and Finance: Emerging Markets Queries in Finance and Business(EMQ 2013), 15, 1603–1612.

    Article  Google Scholar 

  • Waszczuk, A. (2014b). Diversity of empirical design – Review of studies on the cross-section of common stocks (Working paper). Available at SSRN: http://ssrn.com/abstract=2428054 or https://doi.org/10.2139/ssrn.2428054. Accessed 11 Oct 2015.

  • Wilmott, P. (2008). Paul Wilmott on quantitative finance. Hoboken: John Wiley & Sons.

    Google Scholar 

  • Yan, Z., & Zhao, Y. (2013). International diversification: Simple or optimization strategies? International Journal of Finance, 25(1), 1–33.

    Google Scholar 

  • Zaremba, A. (2015). The financialization of commodity markets: Investing during times of transition. New York: Palgrave Macmillan.

    Book  Google Scholar 

  • Zaremba, A., & Andreu Sánchez, L. (2017). Paper profits or real money? Trading costs and stock market anomalies in country equity indices. Available at https://doi.org/10.2139/ssrn.3038514

  • Zaremba, A., & Miziołek, T. (2017a). Fundamental indexation in European emerging markets. Romanian Journal of Economic Forecasting, 20(1), 23–37.

    Google Scholar 

  • Zaremba, A., & Miziołek, T. (2017b, in press). Nothing lasts forever (and everywhere): Fundamental indexation at the global level. Journal of Index Investing, 8(3), 6–20.

    Google Scholar 

  • Zaremba, A., & Nikorowski, J. (2017). Trading costs, short sale constraints, and the performance of stock market anomalies in Emerging Europe. Available at SSRN: https://ssrn.com/abstract=2778063. Accessed 23 Oct 2017.

  • Zaremba, A., & Shemer, K. (2017, in press). Is there momentum in factor premia? Evidence from international equity markets. Research in International Business and Finance. https://doi.org/10.1016/j.ribaf.2017.12.002.

  • Zaremba, A., & Umutlu, M. (2018, in press). Less pain, more gain: Volatility-adjusted residual momentum in international equity markets. Investment Analysts Journal. https://doi.org/10.1080/10293523.2018.1469290.

Download references

Author information

Authors and Affiliations

  1. Poznan University of Economics and Business, Poznan, Poland

    Adam Zaremba

  2. AlphaBeta, Tel Aviv, Israel

    Jacob “Koby” Shemer

Authors
  1. Adam Zaremba
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jacob “Koby” Shemer
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

Copyright information

© 2018 The Author(s)

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Zaremba, A., Shemer, J.“. (2018). Data, Portfolios, and Performance: How We Test the Strategies. In: Price-Based Investment Strategies. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-91530-2_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-91530-2_1

  • Published:

  • Publisher Name: Palgrave Macmillan, Cham

  • Print ISBN: 978-3-319-91529-6

  • Online ISBN: 978-3-319-91530-2

  • eBook Packages: Economics and FinanceEconomics and Finance (R0)

Publish with us

Policies and ethics

Search

Navigation