Factor Investing in the A-share Market

Transcription

1 Factor Investing in the A-share Market Olivier d Assier Managing Director Axioma Inc. The 7 th Index and Indexing Investment Forum Shanghai 2013

2 Agenda Part I - Definition What is Factor Investing? What are Factors? Which ones, how many and for whom? Part II Implementation Identify candidate factors from the literature Validate each factor for your market Short-list based on own risk tolerance profile Monitor markets for mispricing of factor risk premium Part III Replication Use factor portfolios/etfs to replicate Active strategies Conclusions

3 What is Factor Investing? Definition A well-documented, differentiated approach to market-capitalization investing Active and dynamic management of exposures to systematic sources of risk Involves taking time-varying positions in broader factor portfolios based on own views of their future returns Fundamentally a contrarian strategy Quotes It's not about making super-stellar returns, it's about getting your outcome more in line with expectations you've expressed beforehand Suarez Menendez (Advisors to Dutch Pension Funds) Factor Premiums are reward for investors enduring losses during bad times Andrew Ang

4 What Are Factors? Four criteria determine a factor 1) Be justified by academic research 2) Have exhibited significant premiums that are expected to persist in the future 3) Have return history available for bad times 4) Be implementable in liquid, traded instruments. Examples from the literature (see White Paper list) Beta via different asset classes (asset allocation) Value, Growth, Size, Leverage Momentum, Liquidity/illiquidity, Volatility Credit, Duration, Yield, Dividend Earnings Quality, Earnings Revision, Analyst Coverage

5 Developed VS Emerging Markets (EQTY) November 2010 vs. February 2011

6 Developed VS Emerging Markets (EQTY) January 2013 vs. July 2013

7 A-share Market Becoming Multi-Factor

8 Which Ones, How Many and For Whom? Which Ones? Back-test a library of known factors on your target market Record risk-reward measures, drawdowns, size and duration of losses and full cycle lengths Short-list available premiums based on persistence Match against own risk profile and investment goals How Many? Research may show up to ten available in your market Pick 3-5 with best characteristics and diversification potential For Whom? Factor investing is not for everyone Below-average level of risk aversion, Above-average level of loss tolerance Counter cyclical rather than pro-cyclical investor

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10 Factor Investing A Case Study Start with a list of candidate Factors from the literature Value, Growth, Earnings Quality, Profitability, Capital Momentum, Liquidity, Analyst (coverage & Revisions) Build long-only portfolios with the following constraints: Each portfolio is a factor tilt to the target Factor Non-target factor exposures constrained to St. Dev. Relative to the CSI300 Individual Stock Holdings capped at max 2% Sectors constrained at +-5% of CSI 300 weight Rebalance monthly No ADV or Turnover Constraints

11 Candidate Factor List Value: A combination of top line and bottom line valuation metrics such as Sales/EV, EBITDA/EV, Dividend Yield and Earnings Yield, using both historic and consensus data. Technical: A composite of short term mean reverting signals such as 1 month price momentum, RSI and Williams R. Quality: Company earnings quality metrics such as Operating Accruals Profitability: Balance sheet profitability ratios such as ROE, ROA and ROIC. Momentum: A composite of medium term price momentum measures such as trailing 12 and 6 month price return

12 Candidate Factor List - Continued Liquidity: A composite for size and trading related metrics such as ADV and market capitalisation Growth: A composite of forecast and historic growth metrics covering earnings, sales and dividend growth. Capital: A composite of metrics related to capital usage including changes in external financing, buybacks and asset growth. Analyst: A composite of consensus analyst related signals such as revisions in EPS and DPS, number of analysts revising and recommendation changes.

13 Sample Back-Test Cumm. Returns $7.00 Yield Value Quality Momentum Growth Analyst CSI300 $6.00 $5.00 $4.00 $3.00 $2.00 $

14 Back Test Summary Factors Worst 12m active return Best 12m active return Hit Rate Yield 0% 100% 62% Value 0% 111% 67% Technical -87% 85% 51% Quality -64% 34% 55% Profit -38% 42% 52% Momentum -27% 30% 43% Liquidity -22% 60% 49% Growth -15% 71% 52% Capital -35% 36% 50% Analyst -12% 30% 62%

15 Risk-Reward for a 12m Holding period

16 Risk-Reward for a 12m Holding period

17 Active Return Correlation Yield Value Technical Quality Profit Momentum Liquidity Growth Capital Analyst Yield Value Technical Quality Profit Momentum Liquidity Growth Capital Analyst

18 Strategy Replication with Factor Indices Took top five performing funds from Wind database 华夏复兴 交银成长股票 景顺长城内需增长 上投摩根内需动力 申万菱信沪深 300 Use six CSI-Axioma Factor Indices plus Cash (3-month SHIBOR) H 中证 Axioma 300 优化高成长指数 H 中证 Axioma 300 优化高价值指数 H 中证 Axioma 300 优化高预测 Beta 指数 H 中证 Axioma 300 优化低预测 Beta 指数 H 中证 Axioma 300 优化高波动指数 H 中证 Axioma 300 优化低波动指数 Try to replicate return history of these Active Strategies

19 Strategy Replication R-Squared 86.2% 60.0% Buy & Hold Allocation for Fund % 50.0% 40.0% 30.0% 20.0% 24.2% 18.9% 10.0% 0.0% 0.0% 0.0% 0.0% 0.0% HiGrowth HiValue HiBeta LoBeta HiVol LoVol Cash

20 Periodic Rebalancing R-Squared 91.2%

21 Strategy Replication R-Squared 80.4%

22 Periodic Rebalancing R-Squared 94.1%

23 Strategy Replication - Summary MF Ticker Buy & Hold R-Squared High Growth High Value High Beta Low Beta High Volatility Low Volatility Cash Active St.Dev. Rebalance R-Squared % 36.17% 0.00% 0.00% 43.54% 0.00% 0.00% 20.29% 11.22% 92.70% % 25.16% 0.00% 0.00% 51.59% 2.74% 0.00% 20.51% 9.96% 91.80% % 4.62% 0.00% 0.00% 92.22% 0.00% 0.00% 3.17% 14.92% 95.70% % 24.21% 0.00% 0.00% 56.87% 0.00% 0.00% 18.92% 12.18% 94.10% % 0.00% 0.00% 0.00% 2.63% 0.00% 17.32% 80.04% 5.47% 60.30% CSI % 0.00% 0.00% 12.90% 1.89% 27.40% 51.01% 6.79% 8.12% 93.60%

24 Summary & Conclusions We live in a multi-factor world and those factors can be efficiently harvested to meet both absolute and relative investment goals There exist a number of well documented and researched factor premiums in the academic literature which can serve as the basis of market research Factor investing is not passive investing, it requires a forecast, an aboveaverage level of risk appetite, and holding power It is particularly well suited for an environment where systematic risk sources such as macro and regulatory news are the dominant determinant of asset return Factor investing is a disciplined, transparent approach, centered on an alternatively-weighted portfolio construction methodology The A-share market has matured to a point where factor investing should be considered as part of an investment plan Axioma and CSI have worked together to develop a suite of factor indices designed with the same sophistication as those available in developed markets

25 Appendix A Ulcer Index Ulcer Index measures the depth and duration of percentage drawdowns in price from earlier highs. The greater a drawdown in value, and the longer it takes to recover to earlier highs, the higher the UI. Technically, it is the square root of the mean of the squared percentage drawdowns in value. The squaring effect penalizes large drawdowns proportionately more than small drawdowns. In effect, UI measures the "severity" of drawdowns. For more information please visit the author s page:

26 Appendix B CSI-Axioma Factor Indices

27 Glossary of Factor Premium Research Valuation measures Key finding: After controlling for firm size, industry effects, and infrequent trading, low PE stocks provide clearly superior risk-adjusted returns. Paper: Peavy, J., and Goodman, D., The Significance of P/Es for Portfolio Returns, The Journal of Portfolio Management, Winter Low Volatility Key Finding: Agency effects, leverage and the dominance of cap weighted benchmarking all contribute to the low volatility effect, resulting in outperformance of low vol stocks in most markets around the world. Paper: R. Haugen, and Nardin Baker (1991), The Efficient Market Inefficiency of Capitalization-Weighted Stock Portfolios, Journal of Portfolio Management, vol. 17, No.1, pp Paper: Blitz, David C., and Pim van Vliet. (2007), The Volatility Effect: Lower Risk without Lower Return. Journal of Portfolio Management, vol. 34, No. 1, Fall 2007, pp Momentum Key Finding: Reluctance of investors to sell losing stocks creates a spread between fair value and equilibrium price, creating the momentum effect. Paper: Grinblatt, Mark, and Bing Han, 2005, Prospect theory, mental accounting and momentum. Journal of Financial Economics 78:2, Key Finding: Momentum trading generates significantly positive returns over a 3 to 12 month holding period, but the abnormal returns dissipate in the following two years. Paper: Jegadeesh, N. and Titman, S., :Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency, The Journal of Finance, Vol 48, No 1 March Quality Key finding: Stock prices are found to act as if investors "fixate" on earnings, failing to reflect fully information contained in the accrual and cash flow components of current earnings until that information impacts future earnings. Paper: Sloan, R., Do stock prices fully reflect information in accruals and cash flows about future earnings?. The Accounting Review 71, Earnings revisions Key finding: Abnormal returns exist after earnings revisions for as long as six months in the US equity market. Earnings revisions are predictive due to the herding behaviour of analysts one revision is likely to be followed by further revisions in the same direction. Paper: Stickel, S., Common Stock Returns Surrounding Earnings Forecast Revisions: More Puzzling Evidence, Accounting Review, Vol. 66, Issue2, April 1991.

28 Key finding: Abnormal returns last for a minimum of two months after the revisions take place. Paper: Givoly, D., and Lakonishok, J., The Information Content of Financial Analysts Forecasts of Earnings, Journal of Accounting and Economics,Volume 1, Consensus recommendations Key finding: Over the short term there is a positive response to buy recommendations and a negative response to sell recommendations. Paper: Bjerring, J., Lakonishok, J., and Vermaelen, T., Stock Prices and Financial Analysts Recommendations, The Journal of Finance, March Key finding: Recommendations are correlated with long run performance andconvey valuation information. Paper: Bauman, S., Datta, S., and Iskandar-Datta, M., Investment Analyst Recommendations: A Test of The Announcement Effect and the Valuable Information Effect, Journal of Business Finance and Accounting, July Recommendation revisions Key finding: Price reaction to analysts recommendations is a function of the strength of recommendation, the magnitude of the change in recommendation, the reputation of the analyst, the size of the brokerage house, the size of the recommended firm, and contemporaneous earnings forecast revisions. Paper: Stickel, S., The Anatomy of the Performance of Buy and Sell Recommendations, Financial Analysts Journal, September-October Forecast earnings certainty Key finding: Analyst uncertainty proxies beta as a risk measure and generates a positive return payoff. Paper: Carvell, S. and Strebel, P., A new beta incorporating analysts forecasts, Journal of Portfolio Management 11(1). Small Cap & Value Key Finding: Widely reference paper finding that size and book to market are explanatory variables for stock returns Fama, Eugene, Kenneth French (1992), The Cross-Section of Expected Stock Returns, Journal of Finance, Vol. 47, No. 2, June 1992, pp