Quantitative Investing in China A Shares

How China’s retail investors create a rich opportunity set for quantitative strategies.

Two decades of reform and the recent inclusion of A shares in benchmark MSCI indices have made China’s onshore equity market more accessible and more visible to non-Chinese investors. We can now all appreciate that this market is too big to ignore and diversifying enough to consider a distinct asset class in its own right. The potential excess returns available to quantitative investment strategies are less obvious, but very real. For example, the historical outperformance of non-momentum factors such as size, value and reversal has been strong in A shares, but close to non-existent in the U.S. over the same period. By contrast, momentum was not a useful factor in A shares, but performed well in the U.S. except for 2009. The uniquely strong performance of a “turnover” factor in A shares indicates the scale of the profits being left on the table by overactive, short-term, trend-following investors. The analysis shows that the China A shares opportunity set is arguably as rich as that of the developed markets 20 years ago, in the heyday of quant investing—but that success is not a matter of simply transporting U.S. equity factor models to this new market.

Executive Summary

  • China’s A-share market is too big to ignore: with some 3,500 listed companies across all 11 Global Industry Classification Standards sectors and an end-2018 market capitalization of over $8 trillion, it is the second-biggest equity market in the world, representing the second-biggest economy.
  • Two decades of reform and the recent inclusion of A shares in benchmark MSCI indices have made China’s onshore equity market more accessible and more visible to non-Chinese investors.
  • As well as its size, A shares’ low correlation with other equity markets, including other Asian and emerging markets, makes a strong case for considering it as an asset class and a portfolio allocation in its own right.
  • We believe that part of that allocation could be managed with quantitative strategies, as certain characteristics of the A-shares market make it well suited to this approach.
    • The A-shares market has excellent infrastructure to support quantitative portfolio management.
    • A-shares trading and investment is dominated by small retail investors, revealed in regular survey evidence to be poorly informed about company fundamentals and significantly biased toward short-term herding; these investors contribute to over 80% of the total trading volume, but receive just 10% of the profits.
    • Analysis of factor performance in A shares and the U.S. markets since 2006 reveals that factor performance has varied drastically between the two markets.
    • For example, simple factors like size, value and reversal performed strongly in A shares, despite not working at all in U.S. markets over the same period.
    • By contrast, momentum performed poorly in A shares and better in U.S. equities.
    • The uniquely strong performance of a “turnover” factor in the A-shares market indicates the excess returns potentially available to those systematically taking the other side of retail over-trading.
    • A simple composite strategy that equally invests in size, value, reversal and turnover factors delivered very strong results.
    • The analysis shows that the China A-shares opportunity set is arguably as rich as that of the developed markets 20 years ago, in the heyday of quant investing—but that success is not a matter of simply transporting U.S. equity factor models to this new market.

Three Simple Factors That Continue to Perform Well in China, Despite Fading in the U.S. Market

Cumulative and annualized returns and risk for the size, value and reversal factors in the China and U.S. equity markets, 2006 – 2018

Source: Juyuan, Kenneth R. French (http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/index.html), Neuberger Berman. Data as of December 31, 2018.
The size factor is created by going long companies with low market capitalization and short companies with higher market capitalization; the value factor is created by going long stocks with low price-to-book ratios and short stocks with high ratios; and the reversal factor is created by going long stocks with the worst one-month returns and short those with the best. Annualized return and volatility data are calculated based on historical returns of respective portfolios from 2006 to 2018, using monthly returns. The China market includes substantially all A shares, excluding only those with the lowest liquidity. The U.S. market includes all of the stocks in the Center for Research in Security Prices (CRSP) database. All portfolios are hypothetical long-short portfolios gross of transaction costs. For illustrative and discussion purposes only. While these data series are not reflective of actual investment returns, they are factors constructed using a disciplined methodology and, in our view, can be used as proxies for Alternative Risk Premia. The performance shown does not represent the performance of any Neuberger Berman product or strategy and does not reflect the fees and expenses associated with managing a portfolio. Investing entails risks, including possible loss of principal. Past performance is no guarantee of future results. See Hypothetical Backtested Performance Disclosures for more information on Fama/French Factors.

This material is provided for informational purposes only and nothing herein constitutes investment, legal, accounting or tax advice, or a recommendation to buy, sell or hold a security. Information is obtained from sources deemed reliable, but there is no representation or warranty as to its accuracy, completeness or reliability. All information is current as of the date of this material and is subject to change without notice. Any views or opinions expressed may not reflect those of the firm as a whole. Neuberger Berman products and services may not be available in all jurisdictions or to all client types.

This material may include estimates, outlooks, projections and other “forward-looking statements.” Due to a variety of factors, actual events or market behavior may differ significantly from any views expressed. Investing entails risks, including possible loss of principal. Investments in hedge funds and private equity are speculative and involve a higher degree of risk than more traditional investments. Investments in hedge funds and private equity are intended for sophisticated investors only. Indexes are unmanaged and are not available for direct investment. Past performance is no guarantee of future results.

China is considered an emerging market. Emerging markets are more likely than more developed markets to experience periods of extreme volatility. It impossible to predict with certainty how rebalancing the MSCI China Index to include China A shares will ultimately impact the performance of securities reflected on the Index or the China equity market as a whole. Moreover, investors in emerging markets often face heightened risks (some of which could be significant) and special considerations not typically associated with investing in other more established economies or securities markets. Such risks may include, but are not limited to: (a) greater social, economic and political uncertainty including war; (b) higher dependence on exports and the corresponding importance of international trade; (c) greater risk of inflation; (d) increased likelihood of governmental involvement in and control over the economies; (e) governmental decisions to cease support of economic reform programs or to impose centrally planned economies; and (f) certain considerations regarding the maintenance of foreign investors’ invested securities and cash with brokers and securities depositories outside their country of domicile. Separately, bid and offer spreads of the price of securities may be significant and accordingly, such investors may incur significant trading costs.

HYPOTHETICAL BACKTESTED PERFORMANCE DISCLOSURES

The hypothetical performance results included in this material are for backtested model portfolios and are shown for illustrative purposes only. Neuberger Berman calculated the hypothetical results by running a model portfolio on a backtested basis using the methodology described herein. The results do not represent the performance of any Neuberger Berman managed account or product and do not reflect the fees and expenses associated with managing a portfolio. If such fees and expense were reflected, returns referenced would be lower.

Model Portfolios

Models Presented: Individual size, value and momentum factor portfolios in both U.S. and China equities, based on the Fama-French factors; individual reversal and turnover factor portfolios in both U.S. and China equities, constructed using the methodology described herein; a blended portfolio of the size, value, reversal and turnover factors in China equities, constructed using the methodology described herein.

Period: January 2006 to December 2018.

Data Sources: Juyuan, Kenneth R. French, Neuberger Berman.
*Eugene Fama and Kenneth French posited their “three-factor” model of returns to stocks by adding the value and size factors to the single market factor used in the Capital Asset Pricing Model (CAPM). See Fama, E.F. and French, K.R., “Common Risk Factors in the Returns on Stocks and Bonds”, Journal of Financial Economics 33.1 (February 1993). In 1997 Mark Carhart described a fourth factor, monthly momentum, in his paper, “On Persistence in Mutual Fund Performance”, The Journal of Finance 52.1 (March 1997). This factor was later adopted by Fama and French. While these data series are not reflective of actual investment returns, they are simply factors constructed using a disciplined methodology and, in our view, can be used as proxies for Alternative Risk Premia. The performance shown does not represent the performance of any Neuberger Berman product or strategy and does not reflect the fees and expenses associated with managing a portfolio.

Hypothetical Backtest Methodology for Model Portfolios:

For individual factors in the portfolios constructed and backtested, positions were weighted equally and recalibrated and rebalanced monthly. For the blended portfolio of the size, value, reversal and turnover factors, the factors were weighted equally and the portfolio was rebalanced monthly. All portfolios are hypothetical long-short portfolios gross of transaction costs. The U.S. market includes all of the stocks in the Center for Research in Security Prices (CRSP) database. The China market includes substantially all A shares, excluding only those with the lowest liquidity, which includes all of those introduced via initial public offerings (IPOs) in the previous 12 months and all of those classified as ST or ST* companies (listed companies with Special Treatment because their profitability is so poor that they may be de-listed).

The model portfolio may not be appropriate for any investor. There may be material differences between the hypothetical backtested performance results and actual results achieved by actual accounts. Backtested model performance is hypothetical and does not represent the performance of actual accounts. Hypothetical performance has certain inherent limitations. Unlike actual investment performance, hypothetical results do not represent actual trading and accordingly the performance results may have under- or over-compensated for the impact, if any, that certain economic or other market factors, such as lack of liquidity or price fluctuations, might have had on the investment decision-making process or results if assets were actually being managed. Hypothetical performance may also not accurately reflect the impact, if any, of other material economic and market factors, or the impact of financial risk and the ability to withstand losses. Hypothetical performance results are also subject to the fact that they are generally designed with the benefit of hindsight. As a result, the backtested models theoretically may be changed from time to time to obtain more favorable performance results. In addition, the results are based, in part, on hypothetical assumptions. Certain of the assumptions have been made for modeling purposes and may not have been realized in the actual management of accounts. No representation or warranty is made as to the reasonableness of the assumptions made or that all assumptions used in achieving the hypothetical results have been stated or fully considered. Changes in the model assumptions may have a material impact on the hypothetical returns presented. There are frequently material differences between hypothetical performance results and actual results achieved by any investment strategy. Neuberger Berman did not manage any accounts in this manner reflected in the models during the backtested time periods shown.

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