Jason Hsu: China Is 'the Last Great Remaining Alpha Reservoir'
The founder and chairman of Rayliant Global Advisors discusses the promise and challenges of investing in China, machine learning, and the investor timing gap.
The founder and chairman of Rayliant Global Advisors discusses the promise and challenges of investing in China, machine learning, and the investor timing gap.
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Our guest this week is Jason Hsu. Jason is founder and chairman of Rayliant Global Advisors, a quantitative asset manager based in Hong Kong. Jason also cofounded Research Affiliates with Robert Arnott and has been at the forefront of the fundamental indexing movement. Jason is a member of the board of directors at the Anderson School of Management at the University of California at Los Angeles, as well as an adjunct professor in finance there. He has authored more than 40 peer-reviewed articles, is an associate editor of the Journal of Investment Management, and serves on the editorial board of numerous other financial journals, including the Financial Analysts Journal. Jason earned his bachelor's in physics from the California Institute of Technology, his master's in finance from Stanford, and his doctorate in finance from UCLA.
Anderson School of Management at UCLA
Journal of Investment Management
The Fundamental Index: A Better Way to Invest, by Robert D. Arnott, Jason C. Hsu, and John M. West
Investing in China
“Timing Poorly: A Guide to Generating Poor Returns While Investing in Successful Strategies,” by Jason Hsu, Brett W. Myers, and Ryan Whitby, jpm.com, January 2016.
“Buy the Best, Perform the Worst,” by John Rekenthaler, Morningstar.com, April 15, 2016.
“In Defense of Alpha?!” by Jason Hsu, researchaffiliates.com, October 2017.
“The Biggest Failure in Investment Management: How Smart Data Can Make It Better or Worse,” by John West and Jason Hsu, researchaffiliates.com, October 2018.
“Where Retail Rules: Buying Into China’s Alpha Opportunity,” Rayliant.com, August 2019.
“How Do Investor Returns Stack Up Against Total Returns?” by Amy C. Arnott, Morningstar.com, Aug. 18, 2020.
“Should You Have More China in Your Portfolio? Putting Common Arguments for Increased Chinese Exposure to the Test,” by Jason Hsu, Xiang Liu, and Phillip Wool, The Journal of Index Investing, Winter 2020.
“China’s Got Talent: Fund Manager Skill and Alpha in Chinese Stocks,” by Phillip Wool, rayliant.com, March 2021.
“The China Syndrome: Lessons From the A-Shares Bubble,” by Jason Hsu, researchaffiliates.com, September 2015.
“Value, Growth and Bubbles: A Comparison Between China and US Markets,” by Jason Hsu, linkedin.com, Jan. 11, 2021.
“Fewer Loans in China: Impactful, but Perhaps Not in the Way You’d Expect,” by Jason Hsu, rayliant.com, April 9, 2021.
“Why Few Foreign Funds Are Entering China’s $3tr Mutual Fund Market,” by Twinkle Zhou, Asianinvestor.net, April 19, 2021.
“’Tiger Mom’ Vs. Montessori: A Simple Analogy for Comparing Chinese and U.S. Financial Regulation,” by Jason Hsu, linkedin.com, March 4, 2021.
“The Surprising Alpha From Malkiel’s Monkey and Upside-Down Strategies,” by Robert D. Arnott, Jason Hsu, Vitali Kalesnik, and Phil Tindall, The Journal of Portfolio Management, Summer 2013.
“A Framework for Assessing Factors and Implementing Smart Beta Strategies,” by Jason Hsu, Vitali Kalesnik, and Vivek Viswanathan, valuewalk.com, Summer 2015.
“Rob Arnott: Don’t Sleep on Value Investing (Especially Emerging-Markets Value),” The Long View Podcast, Morningstar.com, Aug. 21, 2019.
“Going Local: Developing a Quant Approach Specific to Emerging Markets,” by Phillip Wool, Rayliant.com, April 10, 2020.
“The Harm in Selecting Funds That Have Recently Outperformed,” by Bradford Cornell, Jason Hsu, and David Nanigian, papers.ssrn.com, Feb. 25, 2016.
“Coronavirus Crisis, Supertrends and Disruptive Innovations in Asset Management,” Financial Investigator Conference, rayliant.com, July 2, 2020.
“When Dollar-Cost Averaging Can Help (or Hurt),” by Amy Arnott, Morningstar.com, Sept. 4, 2020.
Jeff Ptak: Hi, and welcome to The Long View. I'm Jeff Ptak, chief ratings officer at Morningstar Research Services.
Christine Benz: And I'm Christine Benz, director of personal finance for Morningstar.
Ptak: Our guest this week is Jason Hsu. Jason is founder and chairman of Rayliant Global Advisors, a quantitative asset manager based in Hong Kong. Jason also cofounded Research Affiliates with Robert Arnott and has been at the forefront of the fundamental indexing movement. Jason is a member of the board of directors at the Anderson School of Management at the University of California at Los Angeles, as well as an adjunct professor in finance there. He has authored more than 40 peer-reviewed articles, is an associate editor of the Journal of Investment Management and serves on the editorial board of numerous other financial journals, including the Financial Analysts Journal. Jason earned his bachelor's in physics from The California Institute of Technology, his master's in finance from Stanford, and his Ph.D. in finance from UCLA.
Jason, welcome to The Long View.
Jason Hsu: Glad to be here.
Ptak: So, let's start by talking about your firm Rayliant. Why did you found Rayliant and what was the opportunity you were seeking to capitalize on when you founded it?
Hsu: I founded Rayliant with the single focus to take advantage of the emergence of China and the opportunity that it represents. I'm going to use a really old cliché, so I apologize for that. It's about skating to where the puck will be rather than where the puck is. A big part of my career was focused on designing quantitative strategies for developed large cap. But frankly, as the market has become so efficient, especially for the U.S., it is hard to consistently outperform. So, when I looked around, I was really exploring markets that would have a lot more, I would say, unsophisticated market participants, who can be on the other side of an alpha trade, and also a market whose beta itself is interesting. And I think China probably is that last remaining great alpha reservoir and is an underinvested beta. And so, the creation of Rayliant is really meant to capitalize on that opportunity.
Benz: As you reflect on the journey, since you started the firm, what has come as the biggest surprise?
Hsu: Everything takes twice as long and is three times as hard. I think anyone who becomes an entrepreneur, there's a part of us that is dreamy and optimistic. And so, I guess I signed up with a surprise--I thought building a firm and very quickly getting to significant AUM would have been faster and easier. But I think the reality is anything that's worthwhile doing will take time, anything that's worthwhile doing will necessarily be hard and challenging and the path will be filled with frustration. And in many ways, I'm glad and better for it.
Ptak: Maybe you can give a quick thumbnail of the firm through your client base? So, maybe you can describe your client base and talk about how that reflects some of the choices you've made in building the business and managing the firm. What does that picture look like?
Hsu: We really seek to service all constituencies. We have large institutions, sovereign wealth funds, who are our clients. We have retail individuals who buy our ETFs, who are very much our clients. And then, we produce a lot of materials to support them in that decision-making process. Financial advisors, financial intermediaries are very much our clients as well, because through them we can actually more effectively broadcast our message and product. So, we really cover the gamut there.
Benz: We're taught that markets are essentially zero-sum, that before fees losses must offset gains. Yet, it does appear that professionally managed funds in China have done very well as you've alluded to. Let's start by talking about how successful they've been. What does that picture look like?
Hsu: I'm really glad you brought up the alpha is a zero-sum concept. I think if I was talking to investors about allocating to, say, U.S. large cap, I would very much be in the Jack Bogle camp where low-cost, cap-weighted ETFs are the best thing to invest in. But the minute you talk about a market like China, where 85% of the trades are retail, and we're talking about retail whose probably less sophisticated than the average retail we think about in the U.S.--the retails who trade on Robinhood and who buy GameStop. The Chinese retail investors, they make a lot of mistakes in terms of overtrading, confusing public information for private information. And because 85% of all trades are conducted by those alpha suppliers, active managers have been very successful as a result of that. The average mutual fund in China on a net-of-fee basis have delivered anywhere from 2% to 4% in terms of net-of-cost alpha over the last 10 years. And that number doesn't seem to go away because the fraction of the market that's retail doesn't seem to change very much from its current level.
Ptak: It's fascinating to me that it's been as durable as you describe it. Why has it persisted to the extent that it has? I think that we're also trained that the market is efficient and arbitraging away opportunities. This seems like a golden opportunity given how difficult it is to capture alpha in other markets. And so, it seems like people would be flocking to China to try and take advantage, but it persists. Why is that?
Hsu: There are a few reasons. First of all, until more recently, accessing China was very, very hard. You had to go and apply for what's called a QFII quota, which are really only awarded to the largest financial institutions, and because of that restricted access, most hedge funds would not be able to come into China and try to arb out that alpha opportunity. When you look at domestic investors, China is not a very institutional market for two reasons. One is, pension funds in China are centralized into one big national scheme, and that scheme is more like the French and the German scheme, which is pay as you go. What that means is it's not fully funded, and it's largely funded by current tax receipt by the government. So, you don't have a lot of institutional assets in the stock market. Households, on the other hand, continue to become wealthier and wealthier as per capita GDP in China grow at neck-breaking pace. And those households simply save way too much in China, and that money has to go somewhere. And as a result, they go into the stock market. So, it's these confluences of factors that causes institutionalization of the market to be slow, almost nonexistent.
Benz: How long do you think it will take for so-called professional money management to overtake individuals in China? And what will hasten that process? Do you think the market is just one bad bear market away from seeking out help?
Hsu: I would say, again, two things. One is, of course, having more disciplined, long-term capital come into that market. I think as China opens up its capital market, and the Hong Kong Connect is very much a program in that direction, we'll see more pension funds globally go into China, and this more disciplined capital will certainly improve market efficiency. But we're early days when it comes to foreign capital going into China. And domestically, it's a matter of, can households trust mutual funds and advisors to manage their money? I think the track record so far is that after a bear market, households simply disengaged completely. They don't find professional help. They simply get so depressed that they don't want to think about the stock market until of course the bull market comes and then they jump in and the excitement of picking your own stocks and it's very much social gambling--draws people in and they forget the painful experience and forget the need for professional help. I think it's a long educational process if we want to see this change. Certainly, the financial advisory, the wealth management industry is in its very nascent stage. It will have an impact gradually over time, but I think it's going to take a long time.
Ptak: Does the evidence suggest Chinese fund investors have participated in this success that the managers have had? Or is there a reason to believe they've missed out on some of it by chasing performance?
Hsu: Well, funny, you should ask. I have a research paper out in China talking exactly about that. According to my calculation, the fund investors are 9% behind the fund return. So, I think this is a topic that Morningstar talks about quite a bit, which is called the return gap: the difference between what the fund generates and what investors actually earn, because investors go in and out of funds. In the U.S., the return gap is about 2%. In China, it's about 9%. And it's exactly what you alluded to--investors simply chase performance, and given that there's strong mean reversal, particularly in China with regard to manager performance, the outcome has been particularly bad.
Benz: Jeff notes the striking thing is that it's not strictly a retail phenomenon in that Chinese fund managers trade a lot and engage in market-timing too. Can you talk about that as well as the phenomenon of managers not sticking around very long?
Hsu: So, first of all, let me speak to managers not sticking around very much. All the star managers do quickly start their own hedge fund, because that is obviously the more lucrative business to be in. So, there is a lot of bleeding out of talent. In addition to that, this is just a very young industry. I think a few years back, I saw a statistic that the average mutual fund manager has been at his job for two years and actually had relatively little analyst experience before that. So, there's quite a bit of turnover as each fund house is trying to poach someone else's manager as they're launching a new fund or a new product into the marketplace. So, that dearth of talent has also increased turnover as well.
Now, when you look at what they actually do and what are their demonstrable skill being shown in the fund performance, the evidence is mixed. On average, they do outperform, so you know there is skill somewhere, but they also seem to do many things that are not very helpful. So, excessive turnover is something that my research documents quite a bit and also aggressive market-timing as well, both of which, I think, from the evidence don't seem to suggest that's how they're perhaps creating alpha, but yet they insist on conducting both. I think part of that has to do with a perception. And I think it's an inaccurate perception by the marketplace that the more the manager trades, the more alpha he is generating, the harder he is working. So, investors expect you to be in the stocks during bull markets and be out of stocks during bear markets. So, if managers aren't actively making a market-timing view, they also feel like they’re not working hard enough. So, this is related to this lack of benchmarking concept in China at this moment, which is forcing a lot of managers to time markets, which they aren't particularly, I think, well suited to do.
Ptak: I think you used the term “social gambling” earlier. And I'm curious the role that incentives and frictions play in creating the dynamic where investors, particularly individual investors, are prone to trade and speculate. Can you talk about what some of those factors are? I think that we found in some more developed markets that there can be constructive frictions that keep people from hurting themselves by overtrading. Is that not the case in China?
Hsu: So I think this is where perhaps the regulators in China should think more about putting into place constructive friction. I think in China, because the population is generally young, and it's really the young population who's come into wealth as sort of white collar, high-income professionals, who dominate the market in terms of day trading. So, they're very technology-savvy. So, access to market for them is a lot easier. Mobile phone trading apps, obviously, brokers are heavily incentivized to ensure that they're constantly being reminded by their cell phones, almost like addictive gaming, to place a trade. And I think it is precisely the incentive of the ecosystem that reinforcing self-harming behaviors that we observe with the Chinese retail traders.
Benz: What is building the team taught you about the talent pool in Asia and the best ways to tap into that potential?
Hsu: We have two teams. So, we have a U.S. team and a China team. We started off with just the U.S. team, but then we very quickly realized that there are just many, many things that we can't accomplish by researching and trading from California. You just don't know the market well enough. We may be quantitative in our methodology. But it doesn't mean all you need is some volume and price data and you can successfully extract alpha from Chinese A shares. You actually need to be in the market, understand the data, understand the great availability of data, talk to smart investors, smart managers, smart quantitative and qualitative managers and learn from them, and build better models and make better sense of the data.
So, as we begun that path of seeking talent in China, what we found is, first of all, it's a market with a lot of hungry highly trained professionals, many of them have received education in the U.S., working experience in the U.S. and have bolstered that with the work experience in China. So, we found there to be a great talent pool and that talent pool isn't cheap, either. They do nearly international prices as well. But of course, it just speaks to the value one can create with local talent, which is why they're fetching global prices. That market just is large and valuable. And the talent pool right now isn't quite as deep. So, it's quite competitive. Everyone is trying to hire someone who's well credentialed and have great work ethics. But so far, we have not been disappointed by the individuals we're able to recruit and retain.
Ptak: Speaking of deep, I wanted to go deeper on the Chinese market if we could and start by asking about the state of the public-private partnership in Chinese markets and the economy as a whole. What is the state of that partnership? The relationship seems to be at a bit of an inflection point given steps the Communist Party has taken to rein in some firms and their leaders. So, to start off, how would you characterize markets and commerce in China right now?
Hsu: To understand regulators in China, you really need to understand the way they see the world. Otherwise, it would seem arbitrary and confusing. I think the West has this imagery of Chinese regulators, either as very incompetent, because they're just a communist bureaucrat, or perhaps even outright evil, they intervene for reasons to disadvantage businesses or foreigners. And I think neither of those imageries are at all accurate. In fact, I recently posted a blog comparing Chinese regulators really to tiger moms and tiger dads. So, their worldview is very much the market mechanism. Left to its own devices will create very bad outcomes where big businesses would completely take advantage of unsuspecting individuals. Unsuspecting individuals need to be protected. So, the regulators actually work doubly hard, not just to make sure that rules are transparent and there's enforcement, but they're constantly modifying rules to protect the weaker participants.
Now, the result of that is, rules can change quite rapidly when the regulator judges that small investors might be harmed, might be taken advantage of and is quite iterative--they keep on changing the rules, trying to get the better rules. So, to give an example, stock exchanges actually do almost a second underwriting process because they so distrust companies and their investment bankers that they completely redo the underwriting process, have their own due-diligence process before approving and because there's personal liability for the regulator who approves the IPO listing, there's just great fear and reluctance to let anything through. And after a firm gets listed, there's ongoing due diligence. The stock exchange almost act like a sell-side analyst conducting research on the business, on the management, and writing reports to warn investors about issues. And so, these would be completely impossible and bewildering if they were to happen in the U.S. But in China, if you understand why the regulator does it, you sort of are sympathetic to that effort, but also recognize that that kind of very interventionist, almost a helicopter-parenting approach may not, in the long run, be as effective as a very hands-off approach where the market sorts things out.
Benz: What are the implications for investors like you? What are you doing now that you wouldn't have done prior to these recent interventions? And conversely, what have you stopped doing?
Hsu: I think the one thing I've learned is that you shouldn't try to figure out everything by just reading the rules that have been published. And you certainly shouldn't get frustrated by either complaining about the lack of clarity or the obvious conflicting policy in place. Because the best way is to ring up a regulator and have a conversation. Usually, there's someone who's assigned to you. He is the guy who provides window guidance to you and help you understand how the rule is supposed to work and how that applies to you. So, that's something I learned. This is not about hiring a big expensive law firm to read the new policy and to tell you how it's supposed to work. You actually want to talk directly to the regulator, and the regulator is not there to trick you--whatever he says actually becomes quite binding. And so, in some ways, once you realize that, the process becomes a lot cheaper, because big expensive law firm bills are not being incurred. And it's actually a lot safer, because you actually do understand how the rule actually applies to you. So, I would say, with that understanding now, I would have worked more directly with the regulators and perhaps less trying to intuit with lawyers what exactly compliance looks like.
Ptak: We're going to talk about quantitative investing in a moment. Before we do so, I wanted to ask your perspective on asset managers, foreign asset managers trying to enter China. We've seen a number of asset managers go to great lengths to enter the Chinese market. Some have succeeded. But others like Vanguard, which recently said it was abandoning its effort to stand up a Chinese operation, haven’t. What will it take, do you think, for foreign asset managers to really break through in China?
Hsu: Well, I think, this is a problem that's plagued many, many firms entering not just China but almost any foreign, non-English-speaking market, for American multinationals. You've got to respect the fact that the culture and the language being so different, there's a natural barrier to doing business that a foreign company simply has to overcome. And that's not something the regulator can help you out with. That's just part of the cost of doing business in a market where the culture, the language, the practices are so different. So, you just got to set your expectation correctly, first of all, and recognizing that that barrier exists. You have to find a way where you can hire someone who has got local experience, knows how to hire well locally, knows how to motivate employees locally, and knows how to deal with regulators locally. You can't micromanage that person and want to apply the U.S. way. Because if the U.S. way worked, you don't need to hire the local person to start with. And so, you've got to just trust enough and give enough autonomy for that to work.
I know a lot of U.S. firms, they go to China, and the first thing they do is they pretend Hong Kong is China because China is not as comfortable. So, they all just want to be in Hong Kong and manage from Hong Kong. That's slightly better, but it's probably no different than wanting to manage your Chinese portfolio from San Francisco. And the other part is, American firms tend to want to hire a Chinese person who speaks perfect English and is educated at a top U.S. university, whether the person actually speaks in Chinese or really knows China is almost secondary. And again, you shouldn't be surprised why that kind of hire, while very comfortable, while it fits all of our biases on what success might look like, isn't really what's going to drive success in China. So, I think, for a lot of American firms, you got to get over the set of preconceived notions about how things work in the U.S. and also what makes you comfortable if you want to get a better outcome.
Benz: We wanted to switch over and discuss quantitative investing. As a successful quantitative investor, you spend a lot of time thinking about what's best handled programmatically and where human involvement is welcome. We have listeners, who no doubt, are grappling with where to leverage technology versus where to use their own judgment to make decisions and advise clients. What advice would you give them on what to automate versus what to leave to judgment?
Hsu: I'm a big, big believer that you always want to combine the two and get the best of both worlds. Now, combining the two is actually quite difficult. And I'll get into that later. But I would say, there are many things that you want to automate, which are things that a human does, so you understand the intuition behind it and there's not a lot more unknown around it. So, it is repetitive. Applying a model, a calculation, a process to a large amount of data rapidly. These are things you want to automate. It's really replacing the human to do something that the human can do, but just can't do as fast and can't do it as reliably.
The things that you don't want to automate are things that require genuine insight because machines aren't particularly good at developing insights. And so, I would say, model building-- you want the humans to be building quantitative models, because we understand how the economy works. So, we have to have a lot of information, knowledge that can't quite be quantified. And we understand how other humans make mistakes. If you're building behavioral models, we understand why company insiders may have a conflict of interest against the broader shareholders. And so, understanding those allow you to build good models that will take machines too long to figure out.
But once you have the models built, saying, if you apply that to historical data, how large is the alpha? How reliable is the alpha? And when it doesn't work, how long might it not work for? If there's decay, how quickly does the signal stop working? These are things that humans aren't very good at, because they require a fairly precise calibration over large set of data. You let the machine do that. So, I would say, this partnership is likely to be significantly more successful versus just the humans trying to build signals and figure out how well a signal might work, or just having the machine develop a signal.
Ptak: Wanted to switch and talk about quant investing in China. If we were to use a baseball metaphor, what inning would you say quantitative investing in China is in right now?
Hsu: I would say it's probably inning number two. I would say, a few years back, China was probably more like in inning one, where many Chinese quants returned from the U.S. having gotten their MBA or MFEs and they learned about the traditional U.S. factors like value and momentum and low volatility. And then they took that back to China and applied it. And they by and large did well enough, just very simple stuff actually already worked very well, and that simply speaks to the inefficiency of the Chinese stock market.
I think we entered inning two, I'd say, sometime last year or the year before that, where some of the high-frequency practices that are leveraging technologies like machine learning to look at price and volume data and trying to exploit those patterns over, say, intraday horizons. That's starting to be attempted on, projects being built around that with some good success. But in terms of really much more sophisticated quantitative models in the multifactor sense, a lot more intuition goes into those model buildings. I think the U.S. is still significantly ahead of where China is today. And certainly, you think of the U.S., Renaissance Technologies, Citadel, Jane Street-type high-frequency shops, again, their technology, their infrastructure is still many generations ahead of what's in China today.
Benz: Why isn't it for further along, especially considering China's reputation for strength in areas like science and math?
Hsu: Well, finance is one thing that is, like engineering enough, but yet different enough that there's probably still a greater component that is art and experience. I would say if investing was a pure math and a statistical exercise, China may be significantly further along and may catch up a lot faster. But I think it's the art aspect of it, it's the fact that markets are dynamic, and it change, and as participants come in, it will change in response to competition, that it's that art of figuring out when has it changed, when has there been a regime shift that you have to change models or when is it just noise and you should stay on course--that art just takes time to develop. And given that this is a very, very young industry still in China, it's going to take decades before that kind of experience and insight and almost wisdom catches up with what you observe in the U.S.
Ptak: You recently told the story about how biographical information on executives at Chinese-state-owned enterprises can be a source of analytical edge. Can you explain how and why that information would potentially be valuable?
Hsu: Absolutely. So, this is really how the research related to the topic on state-owned enterprises in China. China and many other emerging-markets economies have a disproportionately large number of stocks, by capitalization or by number, which are state-owned enterprises. Now, the historical bias is state-owned enterprises are just bad because they aren't really for-profit entities and you should just exclude them out of the portfolio. Now, if you do that with the emerging markets, you would exclude a lot of companies and certainly, in China, excluding state-owned enterprises would eliminate 50% of the market cap. That's eliminating a lot of companies. So, you don't want to do that without having deeper insight into what you're eliminating.
So, when we look deeper into state-owned enterprises, we realize that's not a homogeneous group of companies. There are things that are centrally connected and there are things that are regionally connected. And to figure that out precisely, you actually need to read the biographies of the board and senior management team. What we discover is, if you have a state-owned enterprise that's primarily city-level, town-level party officials, you're not surprised. Oftentimes, these firms are run quite poorly, and statistically, they're about 6% behind the market in return on average. This is where you tend to find a lot more corruption and this is where you tend to find these businesses are much more engaged in or focused on ensuring employment rather than profitability, and often they survive because of large government subsidies.
And when you look at centrally connected enterprises, they tend to be incredibly well run. In fact, they outperform the broad market by 2% per annum. And, in fact, the biggest telltale sign is, if there's an upgrade in the leadership, meaning someone who is very senior has been appointed from Beijing to run the show, you can expect there's often going to be government policies given to the particular industry or the specific firm and oftentimes, the assigned official is often a turnaround expert who is basically the A Team and they really instantly upgrade the operational efficiencies and capabilities of the firm as well. So, having that biographical information tells you a lot about both how the shop will be run and also some insight into forthcoming government policy and policy support.
Benz: You've described your portfolio construction approach as a core and explore. You offer diversified exposure to Chinese stocks, but then there's an overlap where you'll seek alpha. Given the plentiful opportunity in the Chinese market, which you've described, why not run money in a more unconstrained sort of way?
Hsu: I think the China beta is on its own right interesting enough that you don't want to create such a high tracking-error solution that you're going to miss out in participating in the overall beta. So, this is very much a belief that accessing China beta, even in a passive sense, would deliver enough return as you participate in the broad growth of that economy and the fact that that's an economy that is not very correlated with the U.S., that's a stock market that oftentimes actually have lower correlation with broader global markets in distressed downtimes than during uptimes. So, it's got this asymmetric low correlation that's quite nice. So, you do want to access that, and you don't want to mess with it so much that you lose those benefits. And so, it's a careful combination of ensuring you're participating in the beta, ensuring you're not destroying the low correlation characteristic, while also seeking alpha. And a lot of our alpha-seeking approach could be described as eliminating the undesirable stuff from the portfolio, whether it's companies that have really bad accounting practices who you suspect might be fraudulent, whether it's eliminating firms that are regionally connected state-owned enterprises, which are likely not profit-maximizing for the shareholders. So, it's eliminating really problematic stocks that actually further improve on the quality of the beta. So, it's participating in the beta, but also participating in the more virtuous part of the beta. That I think is a better way to think about our process.
Ptak: Maybe you can give a few examples of aspects of stock investing in China that are significant to outcomes but might seem strange or anachronistic to investors who are more accustomed to developed markets. I think that maybe you've referenced some examples you've gone through, but does anything jump to mind as an example of something that you have to be watching for as a Chinese stock investor that really you probably wouldn't keep in mind if you were anywhere else in the developed world certainly?
Hsu: So, this example, I think, it, summarizes in one example all the interesting and bewildering features of that market. So, accounting quality. I think a lot of investors suspect that Chinese companies’ accounting quality is likely not very good. So, that's absolutely true. So, let me tell you the first surprising piece of information. The quality of accounting for Chinese firms that are listed in the U.S., so the NYSE or Nasdaq-listed Chinese firms, their accounting practices are generally significantly worse than the firms who are listed onshore in China. And I think investors are already going to be very surprised, because they would expect the opposite. Shouldn't it be the better firms that list in the U.S. because the U.S. market is competitive, it's more institutional, probably have higher listing requirements. No, U.S. listing requirements are actually one of the lowest globally. If you pay the listing fee and meet minimum compliance, you can list. And as a result, you have this adverse selection problem where many Chinese firms who cannot comply with China's listing requirement end up listing in the U.S. So, they leverage off that information asymmetry to take advantage of the market in the U.S.
Now, of course, this doesn't mean all the companies who list in China are perfect citizens. In fact, our research shows that most companies in China aggressively manipulate their earnings. So, an investor would say, “Well, that's not surprising. That's what we suspect what's happening.” Well, the surprising part is that the substantial majority actually manipulate their earnings downward. So, that's bewildering. If you're going to manipulate earnings, you want to manipulate them higher, so you get a higher share price. So, why do Chinese firms manipulate earnings downward? This is where I'm going to bring you back to my previous point.
The regulator is very paternalistic. So, the stock exchanges in China believe that it is their responsibility to list good companies. And by that, they define good companies as companies who produce a profit and grow their earnings. So, in China, if you have negative earnings, the stock exchange will literally come and slap you on the wrist. If you do it again next year, there will be major sanctions against your stock. So, your stock becomes not marginable. It will have very tight daily caps, and so you will lose liquidity in your stock. If you do it again, they are going to basically put you down the path of being delisted. And so, it's quite Draconian. And so, companies are terrified of that. So, what they do is, they have earnings, a big positive surprise earnings, they will underreport it to build a reserve, so that when they have a bad year next year, they can claw that back from their reserve and print a positive earnings. So, a lot of it is for earnings smoothing rather than for earnings manipulation.
I think that that's a big surprise to most people when they look at the data. So, instead of the story of evil companies trying to defraud investors, it's really companies trying to comply with naive regulation with unintended consequence. And if you think about it, the Tesla or Amazon would have been delisted three times over in China if they didn't also do what Chinese companies are doing, which is smooth earnings.
Benz: Hoping to switch over to discuss academic research. And to start, we thought we could ask you to update us on the state of the academic finance literature. If you were to look back at the past decade or so, what have been the biggest breakthrough pieces of research or realizations that have influenced the way that you run money?
Hsu: Well, the unfortunate thing is, China is a really large market with a lot of data. It's not viewed mainstream enough by the top journals. So, if you study China and try to publish interesting research, it's actually really, really hard to get audiences from the top journal. So, the amount of research out there that could guide investors and managers is actually very, very skinny. Now, having said that, the literature that's been, I would say, influential has been the research that talks about what are the traditional factors as we have built them in the U.S., whether they work well in China or not. And what we saw in the early days was depending on your sample length you could get completely different outcome. And that's really taught us early part of Chinese data is very messy, very noisy, and also, they contain almost exclusively the gigantic state-owned enterprises. So, if you include them, they really pollute the sample so much so that you can't really say anything intelligent from that sample.
So, first of all, you just got to figure out at what point does the China stock market behave like the stock market as we know it today. So, I think that's quite critical. And then, I think once you select the appropriate time range, you start to realize that it's a much shorter set of data for you to work with. So, you're not going to get a lot of strong statistical confidence. So, even if the effect is there, it might even be strong economically, you're going have to live with the fact that the T stats, statistical significance are small. And again, you can't hold the same sort of quality statistical reliability that you might hold U.S. research to when you look at Chinese research.
Ptak: What about outside of China? Maybe academic research that maybe you've incorporated at Research Affiliates or you've just found interesting?
Hsu: Oh, absolutely. I would say the research that's been done on machine learning, especially the part that's not about building sexy, exotic new models, but that's about how do you get a more honest back-test. That's been incredibly powerful and influential for myself and other quants, especially as they are trying to apply that to China where there isn't as much data and the risk of data mining is even higher. I think the tool kit from machine learning that allows you to aggressively shrink your result, to take out data-snooping and data-mining biases, I think that literature has been probably one of the most important and certainly the most influential for myself and my shop that came out of the academia the last few years.
Benz: What are you researching right now that might turn into a paper and what's on your wish list of papers you'd love to do but you just haven't been able to get off the ground or haven't had time to work on them?
Hsu: I have lots of China data. And the one paper that I think I'm most interested in completing and making that available to really Chinese investors is the harm in chasing performance. Now, we've already seen an inkling of that in the U.S. with the Morningstar study that looks at dollar-average return versus equally weighted manager return. In China, this problem is significantly worse that I mentioned. Simple calculation shows about 9% worse outcome for individual investors. So, I'd like to get my publication now that tells investors, look, when you look at the cross-sectional managers with so many managers who have 100% return, 40% alpha, you are just looking at an extreme positive outlier, and that's all luck, very little of that is skill. That skill, you would get a much better result performance-chasing than what you're seeing. So, I'd like to get that out there and really walk retail individuals and financial advisors in China through that exercise, and hopefully convince them, as now many U.S. financial advisors are convinced, that short-term performance chasing is incredibly harmful and that really most of the managers that have extreme performance are going to in the long run significantly underperform the media managers.
Ptak: A 9% timing gap is pretty insane. So, we'll look forward to seeing that paper from you some day. Maybe to move to another question. If you're a portfolio manager trying to stay current with the literature but wanting to be brutally efficient about which papers to read and which to ignore, what have you found is the best rule of thumb to separate the wheat from the chaff? You're very practiced at this, but not everyone is. So, if you could impart some lessons, what would those be?
Hsu: Well, first of all, you can't just Google and read whatever is on the Internet. I hope by now everyone is well aware of the fact that most things on the Internet don't come from credible sources or thoughtful people. So, really, you need to find people who are great curators of information. I would say, journals like the Financial Analysts Journal published by the CFA, the Journal of Portfolio Management, which is one of the longest-running professional journal that's created for people in our industry--those are definitely the starting places. And look at the people who are on their editorial boards, who regularly publish, because that goes through a very rigorous refereeing process. Then start to develop this intuition about who you can follow and whose blog and opinions are likely to be more trustworthy, unbiased. So, I would start with the two resources, the FAJ and the Journal of Portfolio Management.
Benz: What research do you think the investment management community is underrating right now, and what's most overrated in your opinion?
Hsu: I would say the most overrated are using very fancy technology like machine learning, like artificial intelligence to build yet another strategy that could potentially deliver unbelievable information ratios or Sharpe ratios. I think people who put time into it, mostly themselves are trying to use publication as a way to advertise a product or a strategy that they have. And so, with that kind of a conflict of interest, the research quality, I think, is a bit more suspect and the research insight that's really being produced is I'd judge to be significantly less valuable. So, I think there's just too many research pieces there that jump on a bandwagon, a fancy technology as a potential cure-all for the competitiveness in generating alpha.
I think what's underappreciated are ones that really look at the entire ecosystem and really identify and speak to this giant paradox of why we're in an industry where oftentimes the manager doesn't deliver value for the end client, whether it's because he doesn't generate alpha, or whether the way in which the fund is sold and advertised leads to performance chasing, which leads to the investor not participating in any of the alpha or return generally by the fund. I think there needs to be more research that looks into that and understand what's wrong with the way our ecosystem incentivizes itself, the way it operates and leads to essentially poor outcome from the end client, and while there's been poor outcome for the end clients, how is it that our industry continues to be so well-compensated?
Ptak: Well, Jason, this has been a very enlightening conversation. Thanks so much for taking the time to chat with us. We really enjoyed learning more about the Chinese market and what your new firm is working on. Thanks again.
Hsu: Thank you for taking the time to talk to me.
Benz: Thank you.
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Benz: And @Christine_Benz.
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