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Why I’m Active in China (And Why Even Bogleheads Shouldn’t Hate Me For It)
Jason Hsu, Ph.D.
Chairman & CIO
This article was first published to Jason Hsu’s LinkedIn Newsletter—The Bridge. Please click the banner below to subscribe.
Before I turned my focus to Greater China and EM about 15 years ago, I was known primarily for my contributions to index-based investing. Despite the fact that I’m now an active investor, I like to feel I’m still appreciated by this large and passionate investor community, including by followers of my idol, Jack Bogle.
As an aside, I had the pleasure of appearing on a recent episode of the excellent Bogleheads on Investing Podcast with Rick Ferri. I can’t say for certain, but I suspect I’m among the few active managers featured on this well-known program, or at least among the few warmly received. I hope Jack Bogle would have approved!
Given my history with index-based strategies, I’m often asked why I believe China and EM investors should be active instead of passive. I’m also asked why I feel a quantamental approach—as opposed to a fundamental or pure quantitative approach—is right for these markets.
Why fundamental works in China
The fact is that—unlike in the United States and most developed markets—active investing has persistently delivered in Onshore China. Active fund managers have outperformed the CSI 300 by 6.1% per annum since January 2008. Most active managers in China are fundamental and they do exceedingly well despite steep fees of about 1.5% per annum.
My colleagues and I have a strong intuition for why fundamental works in China. The Chinese market has numerous unique characteristics from its large state-ownership, strong but often predictable regulatory crackdowns, unique disclosures, and a large retail investor base. A market with so many unique features is a gold mine for those with specialized knowledge, but can quant outperform in a market like China’s?
Why quant works in China
One might expect quant not to work well in China. The market is too different. The signals that work in the US cannot possibly work in a country like China, right? But as it turns out, a broad range of factors originally discovered in the US not only perform well in China, they perform better in China than they do in the US.
To understand why, remember that China’s volume is driven largely by retail trading—as is Taiwan and India for that matter. On the other hand, Hong Kong, France, and the United States are more institutionally traded; moreover, in Hong Kong, even the retail traders work at investment banks or other financial institutions.
Markets with sophisticated investors incorporate much of the publicly available information, making it difficult for standard quantitative investing to maintain an edge. Markets with a large unsophisticated retail base fail to incorporate this information, so that information can be used to earn excess returns.
But this should feel like it is leaving a lot on the table. Standard quant signals capture none of the nuance of China markets—the unique disclosures, the dual listings, the much wider set of analysts.
Why quantamental is right for China
Below we compare the performance of standard factors in China with China-specific factors like the A-H premium.
It is true that standard factors in China A have outperformed standard factors in any other large country. However, China-specific factors do even better. The reason is they capture the unique information that exists in the China market.
Historically, both fundamental and quantitative investing have delivered excess returns in China, but the evidence suggests the integration of the two can give an even greater edge.
Despite promoting an active approach in China and emerging markets, I haven’t strayed far from the principles that led me to a more passive (and certainly lower fee) approach in developed markets. In all cases, I have followed the data. It just so happens that in China and emerging markets, the data shows that an active approach has historically delivered persistent alpha. As an investor, I naturally want to access that alpha for as long as it’s available.
For anyone interested in exploring this topic further, Rayliant has published extensively over the past five years on the value of a quantamental approach in China and other emerging markets. For those who prefer an academic analysis, I recommend Rayliant’s paper “Anomalies in Chinese A-Shares,” published in the Summer 2018 issue of Journal of Portfolio Management. For those who favor a lighter read, I recommend any of the following Rayliant articles:
This article was first published to Jason Hsu’s LinkedIn Newsletter—The Bridge:
Issued by Rayliant Investment Research d/b/a Rayliant Asset Management (“Rayliant”). Unless stated otherwise, all names, trademarks and logos used in this material are the intellectual property of Rayliant.
This document is for information purposes only. It is not a recommendation to buy or sell any financial instrument and should not be construed as an investment advice. Any securities, sectors or countries mentioned herein are for illustration purposes only. Investments involves risk. The value of your investments may fall as well as rise and you may not get back your initial investment. Performance data quoted represents past performance and is not indicative of future results. While reasonable care has been taken to ensure the accuracy of the information, Rayliant does not give any warranty or representation, expressed or implied, and expressly disclaims liability for any errors and omissions. Information and opinions may be subject to change without notice. Rayliant accepts no liability for any loss, indirect or consequential damages, arising from the use of or reliance on this document.
Hypothetical, back-tested performance results have many inherent limitations. Unlike the results shown in an actual performance record, hypothetical results do not represent actual trading. Also, because these trades have not actually been executed, these results may have under- or over- compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated or hypothetical results in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown. In fact, there are frequently sharp differences between hypothetical performance results and the actual results subsequently achieved by any investment manager.