Jay:  Hey, Tao. How are you doing? Thank you for joining us. We’re very happy to have you, and we appreciate your time. For the audience that’s tuning in, maybe you could give us a quick introduction of who you are and what you do for a living.

Tao:  Thank you for having me, Jay. My name is Tao, and I’m currently a managing manager of Alpha Architect. We are an SEC-registered investment advisor based in a suburb in Philadelphia. We currently manage approximately $700 million across SMA and ETFs.

SMA stands for separately managed accounts, and ETFs are just exchange-traded funds. We’re an ETF provider as well.

Our main focus is we’re trying to deliver a focused-factor exposure to our target clients and especially value on momentum. For those people that are not familiar with these two terms, they’re essentially just factors that, out of hundreds of different factors as being discovered by academia, they tend to work in the past. They tend to offer what we believe the highest premium. We form a portfolio. We do it in a concentrated way. That’s pretty much what we do.

Jay:  Tao, thank you for the into. We’ll get into a little bit more about factor-based investing in a bit. Your background, are you from the Philadelphia area yourself, or are you from this part of the world?

Tao:  I came to the United States seven years ago. I was born and raised in China. I spent the first 22 years in China. The reason why I came to the United States is because I wanted to learn finance and investment in a more systematic way, and this is, apparently, I thought, and I still think, the center of the world and the best place to learn finance. So that’s why I came here.

Jay:  Were you exposed to… I’m just drawing off of my experience and a lot of experience from people maybe younger kids or students coming up through school. There are many different ways. The market is huge. There are many ways to make money in the market, and there are many specializations. You told me in a previous conversation about how you met Wes, the founder of Alpha Architect. Maybe you can share with the audience about that and what led you down this more quantitative path as opposed to maybe going to be an investment banker or to be a stockbroker.

Tao:  Exactly. Initially, an investment banker would probably be one of my dream jobs in the first place, but let me just give you some background information about getting to this systematic investment world.

My experience with investment started with being an observer or a watcher. Back in 2006 and ’07, you probably know China was in the middle of one of the biggest bull markets in history by its climbing speed. The index, the Shangai Exchange Composite Index went from 1000 to 6000 within less than two and a half years. It was definitely the craziest thing ever.

I was surrounded by all the people in college, classmates, either buying stock, actively involved in this, or talking things about investments, all that kind of stuff. So I was really interested, but I was also… I think I see myself as a very conservative guy. I was a little skeptical about what I was observing because I am also deeply influenced by my dad. He runs a family business for over 30 years in doing one thing for 30 years. Lately, the business is getting to see a little success and making money. So I know that you cannot get rich overnight.

That craziness, I was all skeptical about it. But I was definitely interested in risk. So I bought some books. I tried to learn that stuff in a more systematic way.

Barely before I finished any of the books, the market turned around and started to crash like there is no tomorrow, and everybody panicked. So I got to see a lot of human reactions towards that.

That’s what I made my decisions that, okay, I can be a stock picker. I can’t trade this thing out of my mind. I have to learn it systematically. So I came to the United States. I finished my master’s degree in finance from Drexel University, learned all those theories and concepts. But I still don’t feel comfortable about doing this with my own money by trading stocks.

During these two years, that’s also where and when I met Wesley Gray who is the founder of Alpha Architect. He was teaching one of the classes that I took, and he was also managing assets for his friends and families. So I thought, hey, this guy must know what he’s talking about.

So I approached him and said, “Hey, Wes, I learned a lot of stuff from school, textbooks, and I passed three levels of CFA within two years. But still, how do you connect what you’ve learned from the book, those theories, to real-world trading? For example, I know the benefits of diversification, but how do you generate real asset allocation and model and trade it?” I wanted to make the connection between these two.

I said, “Hey, Wes, I want to work for you for free. What do you think? I can do research projects, all that kind of stuff.”

Wes is a cheap ISO. He didn’t even blink his eyes. He basically said, “Hey, did I just hear Chinese cheap labor? Why not? I’m in.”

So I started working for him doing research, and what I did is basically collect ideas from different academic papers, summarizing those, back-testing various trading strategies and putting them into a real trading execution model and implementing them.

I got to see the whole process of how you can turn a research idea into a real trading strategy and then finally execute those. So that’s when I think, okay, I started feeling more comfortable and confident about investing my own money. I still this is probably the way of doing investments.

Jay:  Thanks for sharing that backstory. Wes is an interesting guy, to the audience listening in. He was a Marine in the US Navy. He’s got an interesting story.

What you mentioned about what you saw in Shanghai and the price action of the index there, I think this is pretty classic early, initial investor type sentiments that you experienced. Luckily for you, you didn’t have a lot of your net worth in the market, so you didn’t have to learn it necessarily the hard way. So kudos to that. You were able to spot what was happening and without jumping in with the herd mentality.

I know many of us, myself included, have definitely learned lessons the hard way that are very costly.

Just for the audience’s overview and background, Alpha Architect is a quant shop, and when it comes to investing, I think relying on factor-based investing, which we’ll get into a little bit later, takes some of the emotion out of investing, which is what I find appealing about it.

Maybe this is a good time to talk about, first, who are Alpha Architect’s clients? Are they institutions mostly? Can an individual participate in this high-level data-driven investing as well?

Tao:  Yes, most of our clients are actually retail clients, and lately we were getting… Potentially we were going to get a big allocation from an institution side. But I would say 90% of our money is still retail clients.

What’s interesting about our business is our business model is not about outsourced or outbound marketing shop. We don’t make any advertisements. We don’t post any ads on any websites. We do inbound marketing.

Wes basically started the company back in 2010 by writing blogs and summarizing ideas from academic papers and being transparent about investment. We’re not trying to make something look fancy. We make investment ideas simple to understand and basically makes the information symmetry and let the people know, okay, investment can be done a little simpler. We’re not trying to sell this thing in a complex way to justify the fees.

Our main goal is trying to raise a sustainable AUM towards sustainable clients. What “sustainable clients” is, they need to understand. Value momentum is basically factor-based investing. That’s also active investment relative to indexing, what’s so-called passive.

As soon as you deviate from passive, you’re going to have tracking error. Tracking error is basically how your portfolio deviates from your benchmark. It will be painful to see on your portfolio your benchmark for three to five years or even longer, but that’s the cost you’re going to have to pay. And we believe that it’s finally going to be compensated for taking that risk.

Jay:  That’s great. One of the things that is appealing to me about Alpha Architect is exactly what you said. Your history started off catering towards the individual investor, the small guy. When you think about quant and quantitative trading and factor-based, it’s hugely, massively data-driven. So usually that requires, like you say, a higher fee structure because there is so much initial investment that goes into analyzing the data and coming up with these models. But the fact that now it’s accessible to anyone, I think it’s exciting.

Let’s talk quickly about the different strategies or products that Alpha Architect offers.

Tao:  First, I just mentioned our main focus is to deliver focused, factor exposure like we have momentum. What that is, is basically a long-only equity investment strategy trying to do a little bit better than the index over the long term. That’s our main focus. Then we have our tactical asset allocation model. What that is, basically we offer a globally diversified asset allocation solution to our clients with tilts into value and momentum on a security selection process and also with downside protection by doing trend following.

Besides these two, we also offer tax-efficient alternatives like market-neutral, long-short, equity hedge fund type of products. We also have a commodity carry program or trend-following managed futures program. That’s pretty much the three main categories of our product.

Jay:  Let’s quickly talk about now factor-based investing. It’s funny. Again, retail investors, they tend to shy away from… I think it’s for a lack of education. When you say quant and you say data-driven and all this stuff, most people don’t even both trying to understand the science behind it. Why don’t you give us a factor-based investing 101. What is factor-based investing? What does that even mean?

Tao:  I would say factor, in plain language, it’s all the stocks… Let’s say you’re facing a universal stocks of 2000 stocks. It’s basically how you can differentiate one stock from another stock. And you can categorize one stock based on some characteristics of all that stock.

Let’s say some of the well-known factors, let’s just use value because everybody is familiar with value and it’s well documented for over hundreds of years. That factor, what that means is basically you can rank the stocks, universal stocks based on some cheapness measurement. And some classical measurements like price-to-earnings as opposed to price-to-sell multiples or EBITDA multiples. And you basically rank stocks based on that measure and put them into, let’s say, 10 buckets. And the one with the highest EBITDA or highest earnings-to-price multiples, they are so-called value stocks. And on the opposite, those are the growth stocks.

What value strategy does is you go along the value stocks and go short the growth stocks. And over time, they tend to provide a positive premium by doing so.

Jay:  Got it. I think it’s a interesting way to base your investment decisions on. Again, factors, because it’s data-driven, I feel like it gives the investor a little more confidence. This is datasets that are back-tested for decades. That certainly will help with your conviction and managing your emotion, which is, I would say, one of the largest components of investing, is how you manage your personal emotions when it comes to the market.

When you’re looking at investments and putting together these factors as you bucket them into your different strategies, in addition to back-testing and this sort of thing, you mentioned Wes actually started by looking at academic papers and journals and pouring through that sort of research and then filtering and using that to base the models on. What are some other processes that you guys go through when you’re kind of screening for investments or coming up with your process?

Tao:  Like you said, a lot of our investment ideas are initially sourced from academic papers. We would constantly read and review different academic papers to see if there was any new idea coming now. We start by testing various different theories and hypotheses. And we collect the data because we’re evidence-based investing. So we collect the data and see if there is any evidence to support, either support or against certain hypotheses.

And after that, we would so some robustness tests, out of sample tests, to see if the results are robust under different circumstances. Typically, we would test one idea and see if they work for different asset classes, see if they work in different counts and different sub-period to basically see if it’s robust enough.

And then we would put it into an implementation model. That’s pretty much how we generate investment ideas.

And then we constantly review those. We talk to our clients, collect feedback from interactions with the clients, and see if there are any improvements we can do to the models.

Jay:  That’s pretty interesting. I want to touch on what we just spoke about. I just mentioned it now talking about the emotions of trading and investors and how that leads investors to make wrong decisions during times of market dislocation or volatility. We just had Jason Hsu from Rayliant, another one of our mutual friends. We were talking about this book, Thinking Fast and Slow by Daniel Kahneman. He’s a Nobel Prize Winner. He talks about psychology and how human beings are very good at rationalizing their decisions after the fact. So when you make an investment and it’s not going your way, somehow the human brain is wired to justify it and rationalize it and say, “Maybe the next time will be different,” and this sort of thing.

Because using a quant and factor-based model for investing tends to stripe out a lot of that emotion, what are your thoughts on investing? What are some of the pitfalls you saw during that Shanghai market crash or just in general when you encounter clients who come to you and say, “I want to use Alpha Architect solutions to help me manage my emotions during trading.” What are your views on that in general?

Tao:  Yeah, basically, like you said, human beings tend to make irrational decisions, and they tend to be inconsistent with themselves depending on what kind of pressure they’re facing. One day you’re going to be doing this, and the other day, because outside conditions have changed, you probably will make a completely different decision, and that’s what we’ve been seeing.

Some of our clients have been changing their models because we do offer custom solutions to our clients. We will talk to our clients and say, “Hey, what are you thinking?” And we would recommend what we think would be the right thing to do. And so that’s why we see a lot of irrational human behaviors from that.

From the Shanghai exchange comps and index crash, I definitely see a lot of interesting human reactions but because I’m not actively involved into it. But I can give you an example.

Myself, I sometimes will do some prop trading just for fun outside of what we are doing for our clients. Sometimes I couldn’t even follow my own model. For example, I have like a VIX trading strategy where I’m supposed to rebalance every week on Thursday or Friday. But on Thursday, I’m losing big on that day, and because VIX is acting, reverting a lot recently, I’m supposed to balance. But if I rebalance, I basically realize the loss. And next day movement is not going to affect my model anymore.

So I would hope, “Okay, I think this is going to revert.” It happens to me a lot of times I didn’t rebalance where I was supposed to rebalance.

Even if I’ve been doing research for five, seven years, I still couldn’t follow a simple model. And it’s dangerous. I did some research afterwards to basically see if I rebalanced that model, basically if I follow that model strictly, what would happen?

Sometimes it’s the same, and most of the time it’s better off. Just follow the model.

Another example I can give you is I think people trying too hard, like me, we’re always trying to add some juice to the model that we’ve built. A good is example is, Joe Greenblatt, you must have heard his name. He’s known for the book, The Little Book That Beats the Market and also The Magic Formula.

Formula investing, his firm, they manage separate accounts for some of his clients. And Magic Formula is a pretty simple and, I would say, similar algorithm but not the same. He basically ranked the stocks based on cheapness and quality and combined them and by the top stocks, the highest the score.

What he did is he did some research. He basically wanted to see if I offer some discretion to our clients, what would happen. So he did a test. What he did, he offered two options. One is we do this automatically for you. Whatever the output is, whatever the final 30, 15 names generated from the model, whatever that is, we’re going to invest automatically for you in your account. Or you get to pick. Another option is we give you 30, 15 names, and you get to decide which name you want to exclude, what name you wanted to add into the portfolio.

And the result is fascinating. I think he that test from May 2009 to November 2011. I can’t remember the exact dates, but it was during that two or three years, and he collected all that data and summarized it. Basically it’s fascinating.

So the automatic accounts, I think they generated their return somewhere around like 89%, which is partially driven by the bull market of S&P during that time. So S&P, I think, earned somewhere around 69% or something. So basically the automatic accounts outperformed the passive index by about 20% of something.

The discretionary accounts where the customers get to pick what stock to be included or not, they’re not only underperforming the automatic accounts, they also underperformed the passive index.

So this is a perfect example. You think you’re adding value by collecting more information, but you’re not. You’re better off just following the model. So that’s a pretty interesting example.

Jay:  Thanks for that case study. That’s really interesting and so black and white on how human emotion can really fog things.

Another cognitive bias that investors have is something called home country bias where they invest the majority of their assets in the country they know best. As a lot of Americans… I’m American. And a lot of Americans only like to invest in the US stock markets, and that’s a global phenomenon. It’s a human behavior. I’m sure you’re well aware that people in Asia, I’m living in Hong Kong, and people just love the Hong Kong market, and they don’t look elsewhere. They think that it’s the only market that they can trade. Maybe they’re afraid, or maybe they just are lazy. They don’t want to do the work.

I wanted to shift gears now and talk about Asia and China and your views overall. You saw the big sell-off in Shanghai and then the subsequent rise. What are your thoughts on the market and China? What are the opportunities there that you see coming forward?

Tao:  Generally speaking, I’m native Chinese, so that’s my hometown. I love my country. And, especially like you said, we’re all subject to the home bias to some extent. I’ve seen a lot of good things that are happening to China right now. China is being more open to the world than before. FCI is adding 222 names into their index, and we have this China-Hong Kong connect. We’ve seen a lot of renovation and reform of the stock market specifically.

I definitely think China has a lot of opportunities. When it comes down to specific investment strategies or how you would invest in China… Because I’m not a macroeconomist. I’m a quant. So I tend to make decisions based on data that I looked at.

From a valuation standpoint, I think China right now is relatively cheap compared to the United States. I think the United States, at this stage, is probably the most expensive around the world. The ratio is probably 28 times or something, which is insane, probably over 90 percentile over the entire history.

So I think from a diversification standpoint, it’s definitely worthwhile checking out China, especially for US-based investors to diversify a little bit by having some exposure in China or Asia.

Specifically in Asia, it is kind of mixed. Some of the countries are not really cheap, like the Philippines and Malaysia. But some countries do have some opportunities, like Hong Kong, South Korea, China. They are trading multiples relatively lower than the rest of the world. So I definitely see some opportunities. China is still considered part of the emerging markets. It’s heavily retail-driven. Probably over 80% is driven by individuals. And that opens the gate to a lot of the systematic factor investing because I think Chinese, they tend to make irrational decisions. They tend to make more biased decisions relative to… I don’t want to say “rest of the world,” but than the people in the developed markets. On average, they’re still relatively less educated. I don’t want to offend any people here but less educated, I think, in the investment world.

Also, the Chinese market has a relatively smaller history. It started in the 1990s. I think that definitely has a lot of opportunities. I think systematic factor investing definitely has a chance there. We’ve done some research, and some typical factors, they tend to work in China as well.

Jay:  Absolutely. It’s exactly in line with what you were talking about with the Joe Greenblatt story and how human beings don’t know how to manage their emotions, and they end up just reducing the performance if they get involved.

If you take that to an emerging market — and I think over time, over the long term, investors are starting to get more sophisticated and trying to educate themselves more, but like you said, Tao, this is still an emerging market, so their characteristics are very much emerging market characteristics. 80-plus percent retail-driven in China.

Again, there is this irrational market behavior. And so therein lies the opportunity for people like quant shops and Alpha Architects or alpha-driven funds that can actually take advantage of this environment and make a lot of money. Because if 80-plus percent of the market are behaving irrationally… It’s a zero-sum game, so someone is going to be making the money on the other side.

Do you guys offer anything that has any sort of Chinese exposure or Asian market exposure?

Tao:  We have an international product that focused on the developed markets for now. We basically launched five ETFs. A few of them are international focused. One is called IVAL, one is called IMOM. IVAL is international quantitative value, and IMOM is international quantitative momentum.

We basically apply the value of momentum methodology into the developed markets. We’re excluding Canada and the United States. We currently don’t have any products that specifically tap into the emerging markets, but you do get some exposure because of having Hong Kong and… I don’t think we exclude ADRs, so we indirectly have some China exposure by having Hong Kong stock or ADR stocks in our universe.

But, yes, we don’t have any specific China exposure, especially the A-shares. But we’re open to that, and we’re doing some research on that side. I don’t see why we wouldn’t have that in the future.

Jay:  Yeah. For the audience listening, the offering that you have now, because it includes some of the US-based listed ADRs, is quite unique because basically, a lot of those are not included in any of the large ETFs and indices because they’re listed on NASDAQ. We’re talking Chinese internet names and this sort of thing. But, yeah, I think there is absolutely an opportunity for you there. It’s the reason why Jason Hsu is over at Rayliant. He spun off of Research Affiliates for pretty much that exact reason.

I’m excited to track you guys and see if you guys can come up with something because it could be very high demand, especially for international investors that want to get involved in that market that don’t have either the technical prowess or know-how or time to do as much research to the point where they would be comfortable investing. So I think there is definitely some demand there for your product.

Tao, thanks so much for your time and for sharing your insights and sharing about yourself. Is there anything that you’re working on these days, either personally or other than this part that we mentioned? At Alpha Architects, what are your goals for the near term? Anything you’re super excited about?

Tao:  We are actually thinking of potentially expanding our footprint into China. Me and another partner, Yang Xu, are Chinese nationals, and we started writing blogs or writing articles for some of the websites like Chechou, WallSteetCN.com. We’re writing some articles to basically explain what we’ve done in the past at Alpha Architect and try to educate Chinese investors with what we’ve done and all these systematic, evidence-based investment processes, value, momentum, what does value mean, what does momentum mean… Very basic 101 articles.

Interestingly, not that many people write that kind of stuff in China. Even if they write some of that stuff, I think they don’t explain it in a very clean way, so I think we’re filling in some gaps there.

Also, firm-wise, our goal is to still raise sustainable AUMs to sustainable clients. We’re doing great at the current stage, and our goal is to raise a billion dollars on all of our ETFs, and that’s our main focus right now.

Jay:  That’s exciting. Very exciting. I find it fascinating. I’m impressed at the way you guys built up Alpha Architect. It started from just a couple of guys writing blogs. Within finance, there is usually quite a divide between institutional investors and individual investors and the research and the writing is very catered towards the two different sides. But I kind of see this crossover now happening. And that’s also due to the internet and accessibility now. Individuals can jump online and get a lot of actually very good data-backed, peer-reviewed research that usually was only available to paying, institutional clients. That’s an exciting thing for me.

I definitely think that China is… You guys are definitely on the right track. It’s your home country, so that’s exciting.

Tao, again, thanks so much for your time. What’s the best place that people could find you, follow you, learn more about you and/or Alpha Architect?

Tao:  Sure. Wes basically started this business from writing blogs and generating content. We have a section and specifically we are constantly updating our content. There is a section called blog in our website. It’s straight up just AlphaArchitect.com. There is a second called blog where you can find a lot of white papers, a lot of articles that we’ve been writing. And we have some outside contributors as well —Laris Rogers also — writing some stuff for us. That could be a good source where you could learn what we’re doing.

Also you can reach out to me just by email. It’s Tao@AlphaArchitect.com. If you find what we’ve talked about interesting, you can send me an email, and we can talk about that in more details. Thank you very much, Jay, for having me.

Jay:  Yeah, thanks. We appreciate it. And thanks for offering your help. And we look forward to seeing what great things you guys come up with in the future. Thanks again.

Tao:  Thank you. Thanks, Jay.

Jay:  Alright. Take care.