A little over a month ago, Scott Vincent took aim at much of academic finance by publishing a paper entitled Is Portfolio Theory Harming Your Portfolio? In it, he makes a strong argument for active investment management.
Vincent, founder and managing partner at Green River Asset Management, LLC, a hedge fund based in Baltimore, agreed to answer Five Good Questions.
1. In your recent paper, you argue that modern statistical finance isn’t all that it’s cracked up to be, and that active management can and does work. On what do you base those conclusions?
The fundamental underpinnings of quantitative finance have been shown to be flawed and impractical as applied in practice. Most of quantitative finance depends on the basic concepts and statistical math introduced in CAPM and Portfolio Selection (two of the key theories behind Modern Portfolio Theory or (MPT). We tend to assume that because these theories appear sound, and the math behind them is flawless, they will generate accurate results when applied.
The problem is that mathematics and statistics are rigid disciplines, and they need certain rules and relationships to hold true if they are to generate reliable results. For those rules to be upheld when we apply these theories in financial markets, a set of assumptions is required. Those assumptions are simply unrealistic with respect to financial markets, where relationships are highly fluid. This means that quantitative finance generates unreliable results.
The most important example of this is shown in MPT’s treatment of risk.
When Harry Markowitz wrote "Portfolio Selection" in 1952, he was the first to formally recognize and try to quantify the tradeoff between risk and return. It was incredibly important work — this tension between risk and reward became the standard to describe how just about all securities are priced.
But to make his model work, to fit it to financial markets, he needed a quantitative measure of risk, and he chose variance of returns. Why?
There was no compelling empirical evidence that variance and returns were strongly correlated. It seems instead that variance was chosen because we needed a quantitative measure for risk, and it made some sense that riskier assets would be more volatile. To be fair to Markowitz, he left room for "the judgment of practical men" to alter variance as needed. But in practice, when large computations are done very rapidly, there's little room for judgment.
Just because an asset varies little in price, should it be thought of as safe? What about a highly volatile stock that trades below the level of net cash on the company's books and that generates cash?
I see that as an almost guaranteed return, while MPT would deem it risky. The theories rely on a host of other unrealistic and unfounded assumptions including that returns fit stable, normal distributions and that all investors are rational and have the same views on expected risk and return.
Another important problem with quantitative finance is that it relies on historical measures for model inputs. Practitioners look at the volatility or correlations of the past to predict the risks of the future.
In a dynamic environment, however, circumstances change and so do volatilities and correlations, so historic measures give inaccurate predictions of future volatilities. There's also the practical question of which time period to use in measuring historical volatility. Is it one year, one month, one day, or one hour? You'll often get dramatically different answers for each.
MPT's assumptions don’t square with reality, so we shouldn’t be surprised that its key concepts don’t hold up when put to the test in financial markets. Numerous empirical studies have shown that taking on more risk (as represented by volatility) doesn’t reliably deliver additional reward (see paper for references).
Studies also demonstrate that returns are neither stable nor normal, and that investor behavior is far from rational. If you're looking for further proof, note that some of the founding fathers of MPT and its key early proponents (Harry Markowitz, Eugene Fama, and Paul Samuelson, to name a few) have admitted to the theory’s serious shortcomings.
Some people would argue, “So what? These quantitative techniques give us an answer that’s close enough most of the time, so there’s no real harm in continuing to employ them.” However, these folks probably don’t fully understand where this line of thinking leads us.
When an equity portfolio manager adds another position to his 150-stock portfolio in order to increase his beta exposure, he’s usually not analyzing the fundamentals of the company to detect whether the stock is priced inefficiently. He’s buying it based primarily on one number, and this can create inefficiencies.
When a fixed income manager buys a triple-A rated CDO based primarily on a default correlation number rather than an understanding of the fundamental risks inherent in the underlying credits, we get inefficiencies (which can lead to calamity, as we’ve recently witnessed).
The misapplication of financial theories gives us a precise measure of risk, which imbues us with a false sense of security and allows us to build very large portfolios. Yet when the predictably unpredictable happens, and correlations break down, we realize — too late — the mistakes we’ve made.
With regard to active managers, I argue that, on average, they aren’t really that active at all. The average actively managed fund holds approximately 140 positions and turns over around 100% per year, meaning that the average fund probably holds much more than 140 positions during the course of a year.
Holding so many positions means that these funds tend to behave like very expensive index funds. The human judgment component of management is reduced by the desire on the part of these managers to closely track their benchmark index. So, when you see studies that compare average “active” managers to index funds, you’re not really getting a fair representation of “active” management results.
Stripping away the influence of portfolio theory (which encourages broad diversification) involves isolating and evaluating the relatively small group of equity managers who rely heavily on judgment to build concentrated equity portfolios. Empirical data from multiple studies (see paper) show that, in fact, these concentrated managers persistently outperform indexes.
I generally take empirical work with a grain of salt, as we all know that data can be tortured to advance an agenda. It's worth noting, however, that if we compare the studies that focus on teasing apart the influence of more active, concentrated management, to the broad, all-inclusive active management studies, there’s a large change in the signal received.
It's understandable that investors would abandon active managers for the better returns of index funds. What's less understandable is that we would abandon the idea of active management and the use of judgment to make investment decisions.
The quantitative alternative that promises an efficient frontier doesn't make sense, nor does it work when applied in practice. Human judgment, on the other hand, has never been proven ineffective at uncovering inefficiencies. The real issue is that we need more products that employ truly active, concentrated strategies.
We don't have the space to address the issue adequately right here, but it's interesting to ask, Why do our capital markets continue to embrace quantitative finance so enthusiastically, despite its widely acknowledged shortcomings? And what are the ramifications?
I think the short answer to the first question is that we have a lot vested in our financial system that depends on quantitative finance.
With respect to the second question one can argue that the result is massive inefficiencies and misallocation of capital. I think that an overreliance on quantitative finance played a big role in causing the recent financial crisis. Anyone wishing to learn more should read Amar Bhide's book, A Call For Judgment.
2. There are a number of books of late making the same general point from people like Howard Marks, Joel Greenblatt and James Montier – Nassim Taleb even. How do you fit within this circle and how have people like them informed your work?
The authors whom I have found very helpful include Nassim Taleb, Amar Bhide, and Peter Bernstein, as well as authors of classic works such as Benjamin Graham. Taleb and Bhide were the most influential in forming opinions for this paper — their perspectives were novel and thought provoking. I think that over time we’ll see more authors supporting the “pro-judgment” argument, because the harmful effects of quantitative finance are becoming more pronounced as time passes.
Is Portfolio Theory Harming Your Portfolio?fits together a lot of different puzzle pieces. Some of these pieces come from academic studies, some from the theoretical work of others, and some from my practical experiences.
The paper doesn’t introduce any new empirical data. It focuses on the active equity management industry, since that's where I have spent my career – on both the buy-side and the sell-side.
I wrote the piece because I had not seen any books or papers that connect the influence of MPT to the inability of the average active manager to add value consistently. Nor had I read anywhere about the cover that MPT’s call for diversification provides fund complexes.
Diversification allows funds to achieve massive scale and profitability, even if it may prevent them from offering real active management (where managers take large positions in select names) and superior returns.
3. How do you get along or make peace with quants, who get some serious criticism from you?
There will always be a place for quantitative finance. We’re not trying to argue that the models don’t work in theory. We’re saying that they are misapplied in practice.
If all the assumptions that the models require hold, then they generate a fairly accurate picture. So, in some circumstances, the models can give a helpful reference point when analyzing a security. It’s when they provide the sole or primary reference point that we get in trouble.
Even though the facts are stacked against them, the quants aren’t in any real danger of losing their jobs. As mentioned earlier, we've built a financial services system around the idea that quantitative finance works. That system depends on quantitative finance for its life blood of profits.
Quantitative finance also has the benefit of defining the debate over its validity using terms that presuppose the validity of the very theories over which we argue.
How can we deliberate about risk-adjusted returns, Sharpe ratios, or alpha fade when those terms rely on bogus assumptions? The measuring stick is broken but we keep using it.
Some investors mistakenly believe that I am arguing against the use of index funds. This isn’t the case at all. Index investing is a fantastic, low-cost way to gain market exposure. Investing using active managers requires more research and monitoring, and can be frustrating because of the lack of appropriate options. However, empirical evidence shows that an investor who makes the effort to find the right funds can expect to outperform over time.
4. You say that persistence has been demonstrated among “concentrated, fundamentally-driven, relatively small funds with talented managers” based upon “past performance among other considerations.”
Yet Vanguard claims, for example, that over a 20 year period, the probability that a portfolio of actively managed fund will outperform a comparable portfolio of index funds is less than 3%, and then it's not by much. Where is that demonstration of persistence, who are those out-performing managers, and where should one go to find them?
First, I agree with studies such as Vanguard’s that show that active managers on average underperform index funds. As they rightly state, the underperformance is “largely owing to the cumulative effect of costs” and really comes down to simple math. I would expand the Vanguard argument by adding that active managers aren’t all that active and are managing expensive, enhanced index funds. Why should we expect them to outperform on average?
But broad studies such as Vanguard’s do little to evaluate the ability of “truly” active managers to add value. Truly active managers are those who run concentrated portfolios, who rely on their judgment to pick stocks rather than manage a diverse portfolio that hugs an index to reduce tracking error. They are less influenced by MPT’s push for diversification.
To measure whether active management adds value, we look to see whether we can find evidence of persistence within the group of managers who run concentrated funds. In fact, several studies demonstrate evidence that relatively concentrated managers not only outperform but do so with persistence (six papers are cited in my paper and more exist).
In their 2007 study, Martijn Cremers and Antti Petajisto noted that “the best performers are concentrated stock pickers” and “we also find strong evidence for performance persistence for the funds with the highest active share.”
Persistence is what really matters. When we see persistence, it means that judgment is having an impact — returns are not being generated randomly around the market mean. A poor manager may persistently underperform, just as a talented manager persistently outperforms.
Evidence of persistence confirms that track records matter. You have a better chance at outperforming by choosing managers who have outperformed over time (assuming that the manager closes the fund to new assets before reaching a point at which asset levels influence strategy).
5. Who are your mentors and what money managers you admire?
My stepfather has been an important mentor to me. He isn’t an expert in finance, but he can think critically, and he helps me do the same. I also rely a lot on friends with whom I’ve worked over the years.
I enjoy reading the work of people who have a somewhat contrarian approach, and who focus on achieving high returns over running a business. Warren Buffett is a big favorite — not only for his investment prowess and process but also for his approach to life. As mentioned earlier, Taleb and Graham have been very influential. I respect Bill Miller for his process, even if his results have been lackluster of late.
But given that I’m a stock picker, the people who help me most are analysts who have a deep understanding of the companies they follow, who don’t take management at their word, and who understand not only what makes a great company but what makes a great investment. I’ve gotten to know a lot of outstanding analysts over the years and I’m privileged to count many of them as friends.