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Alpha Theory Blog - News and Insights

17 posts categorized "Alpha Theory Press"

October 16, 2020

Best Ideas Update

 

The Cohen, Polk, Silli “Best Ideas” paper was first released in 2005 and Alpha Theory incorporated the 2010 draft in the Concentration Manifesto as an empirical proof (#3 to be exact) of why managers should concentrate. An updated version of the “Best Ideas” paper was released in June, it expands the data set from 24 to 37 years and reconfirms the earlier findings that active managers are 1) good at selecting and sizing a few “Best Ideas” and 2) then dilute the “Best Ideas” with a bunch of positions that are basically random noise.

 

The “Best Ideas” portfolio outperforms the rest of the portfolio and benchmarks by 2.8% to 4.5% per year with high statistical significance, across a thousand-plus mutual and hedge fund managers, and with consistency amongst managers and from year-to-year.

 

This abnormal performance appears permanent, showing no evidence of subsequent reversal, even several years later. Interestingly, cross-sectional tests indicate that active managers’ best ideas are most effective in illiquid, growth, momentum stocks, or for funds that have outperformed in the past.

 

Given the strong empirical evidence for concentration, why don’t managers concentrate more on their best ideas? The “Concentration Manifesto” highlights myriad reasons managers should concentrate but does not investigate why they do not. The “Best Ideas” paper does:

 

We identify four reasons managers may overdiversify.

 

1. Regulatory/legal. A number of regulations make it impossible or at least risky for many investment funds to be highly concentrated. Specific regulations bar overconcentration; additionally, vague standards such as the “Prudent man” rule make it more attractive for funds to be better diversified from a regulatory perspective. Managers may well feel that a concentrated portfolio that performs poorly is likely to lead to investor litigation against the manager. Anecdotally, discussions with institutional fund-pickers make their preference for individual funds with low idiosyncratic risk clear. Some attribute the effect to a lack of understanding of portfolio theory by the selectors. Others argue that the selector’s superior (whether inside or outside the organization) will tend to zero in on the worst-performing funds, regardless of portfolio performance. Whatever the cause, we have little doubt that most managers feel pressure to be diversified.

2. Price impact, liquidity, and asset-gathering. Berk and Green (2004) outline a model in which managers attempt to maximize profits by maximizing assets under management. In their model, as in ours, managers mix their positive-alpha ideas with a weighting in the market portfolio. The motivation in their model for the market weight is that investing in an individual stock will affect the stock’s price, each purchase pushing it toward fair value. Thus, there is a maximum number of dollars of alpha that the manager can extract from a given idea. In the Berk and Green model managers collect fees as a fixed percentage of assets under management, and investors react to performance so that in equilibrium each manager will raise assets until the fees are equal to the alpha that can be extracted from their 26 good ideas. This choice leaves the investors with zero after-fee alpha. Clearly in the world of Berk and Green, (and in the real world of mutual funds), managers with one great idea would be foolish to invest their entire fund in that idea, for this would make it impossible for them to capture a very high fraction of the idea’s alpha in their fees. In other words, while investors benefit from concentration as noted above, managers under the most commonly used fee structures are better off with a more diversified portfolio. The distribution of bargaining power between managers and investors may therefore be a key determinant of diversification levels in funds.

3. Manager risk aversion. While the investor is diversified beyond the manager’s portfolio, the manager himself is not. The portfolio’s performance is likely the central determinant of the manager’s wealth, and as such we should expect them to be risk-averse over fund performance. A heavy bet on one or a small number of positions can, in the presence of bad luck, cause the manager to lose their business or their job (and perhaps much of their savings as well, if they are heavily invested in their own fund, as is common practice). If manager talent were fully observable this would not be the case – for a skilled manager, the poor performance would be correctly attributed to luck, and no penalty would be exacted. But when ability is being estimated by investors based on performance, risk-averse managers will have an incentive to overdiversify.

4. Investor irrationality. There is ample reason to believe that many investors – even sophisticated institutional investors – do not fully appreciate portfolio theory and therefore tend to judge individual investments on their expected Sharpe ratio rather than on what those investments are expected to contribute to the Sharpe ratio of their portfolio. For example, Morningstar’s well-known star rating system is based on a risk-return trade-off that is highly correlated with Sharpe ratio. It is very difficult for a highly concentrated fund to get. This behavior is consistent with the general notion of “narrow framing” proposed by Kahneman and Lovallo (1993), Rabin and Thaler (2001), and Barberis, Huang, and Thaler (2006). A top rating even if average returns are very high, as the star methodology heavily penalizes idiosyncratic risk. Since a large majority of all flows to mutual funds are to four- and five-star funds, concentrated funds would appear to be at a significant disadvantage in fundraising. Other evidence of this bias includes the prominence of fund-level Sharpe ratios in the marketing materials of funds, as well as maximum drawdown and other idiosyncratic measures. Both theory and evidence suggest that investors would benefit from managers holding more concentrated portfolios.

Our view is that we fail to see managers focusing on their best ideas for a number of reasons. Most of these relate to benefits to the manager of holding a diversified portfolio. But if those were the only causes, we would be hearing an outcry from investors about overdiversification by managers, while in fact, such complaints are rare. Thus, we speculate that investor irrationality (or at least bounded rationality) in the form of manager-level analytics and heuristics that are not truly appropriate in a portfolio context, play a major role in causing overdiversification.

 

The reasons for diversification (not concentration) are real and will require systematic change and mutual agreement from both funds and LPs. Given the state of flows from active to passive, there may be a strong enough catalyst for that change.

 

May 15, 2020

Alpha Theory Announces Partnership with New Constructs

 

Alpha Theory has partnered with New Constructs, the leading provider of insights into the fundamentals and valuation of private and public businesses, to provide a score based on a firms’ likelihood of beating or missing earnings.

 

This feature works by pulling New Constructs’ Earnings Distortion Scores directly into Alpha Theory. These scores indicate the likelihood of a firm to beat or miss consensus expectations for EPS, revenue, or guidance in the next quarter:

 

    1 – Strong Beat
    2 – Beat
    3 – Inline
    4 – Miss
    5 – Strong Miss

 

“We are excited that Alpha Theory’s clients will now have access to our proprietary consensus earnings prediction tool, which will help them make smarter investment decisions,” said David Trainer, founder and CEO of New Constructs.

 

Earnings Distortion measures the level of non-core income/expense contained within reported earnings. It is a proprietary measure featured by professors from Harvard Business School and MIT Sloan in a recent paper: Core Earnings: New Data & Evidence. The paper empirically demonstrates the superiority of New Constructs’ measure of Core Earnings based on its proprietary adjustments for unusual gains/losses.

 

Earningsdist

 

“Alpha Theory’s goal is to constantly provide new sources of value for our clients and we believe the Earnings Distortion Score from New Constructs is a great addition”, said Cameron Hight, CEO of Alpha Theory.

 

Full press release can be found here

 

January 5, 2019

Valuing Momentum: Part 2

 

I’ll highlight one major article written by Cliff Asness and his team at AQR, published in May 2014 (it’s also worth checking out “What Works on Wall Street” by O’Shaunassy and their fund strategies which combine value and momentum and have solid long-term track records). The AQR piece titled Fact, Fiction and Momentum Investing evaluates some of the most prominent myths regarding Momentum and uses empirical research to refute those myths. In doing so, it gives a compelling account showing why the marriage of value and momentum are potent partners. Here are a few excerpts to give a sense of their conclusions:

 

As we’ll show in this essay, value and momentum work better when used as complements, and it is the combination of the two we stress and most-strongly recommend. We are fans of both momentum and value but bigger fans of their combination (and not fans of myths at all).

 

Evidence for Momentum

The (momentum) return premium is evident in 212 years (yes, this is not a typo, two hundred and twelve years of data from 1801 to 2012) of U.S. equity data,3 dating back to the Victorian age in U.K equity data,4 in over 20 years of out-of-sample evidence from its original discovery, in 40 other countries, and in more than a dozen other asset classes.

 

1

 

88% of returns positive for momentum and 89% for value.

 

2

 

Israel and Moskowitz (2013) show that the long and short side of momentum is equally profitable using 86 years of U.S. data as well as 40 years of international equity data, and another 40 years of data from five other asset classes outside of equities. Everywhere they looked and in every way, they could not find any evidence that the short side profits were systematically larger or more important than the long side.

 

Benefits of Momentum and Value Combined

Sharpe ratio and percent of years with positive returns increase with a 60% value / 40% momentum strategy.

 

Group 2

 

Suppose, despite all of the evidence to the contrary and our strong belief it’s positive, momentum had a zero expected return going forward. Would it still be a valuable investment tool? The answer is clearly, though perhaps surprisingly, yes. The reason is because of momentum’s tremendous diversification benefits when combined with value.

 

The diversification benefits are so great that even a zero expected return would be valuable to your portfolio! The logic is simple. Since value is a good strategy and momentum is -0.4 correlated with it, one should expect momentum to lose money based only on that information. Yet, the fact that it does not lose but in this assumed case breaks even makes it a valuable hedge. (We note that using the definition of value in Asness and Frazzini (2013) dramatically increases the magnitude of this negative correlation (to -0.7) and the power of combining value and momentum. Following their methodology, the results of this section would be far stronger.)

 

But, there’s an even simpler and equally effective way to mitigate these crashes, as we mention repeatedly: combining momentum with value. This combination has effectively eliminated these crashes in our long-term sample evidence — and not just those for momentum but also the crashes that can occur for value investing. In other words, the diversification benefits of combining momentum with value don’t just appear during normal times, but also during these extreme times, which makes their combination even more valuable. For example, Asness and Frazzini (2013) show that the combination of value and momentum did not suffer as badly in 2009. Going the other way, in 1999 momentum helped ameliorate value’s pain. Both factors have worked well over the long-term, but neither has a Sharpe ratio of 10, meaning that both will have hard times occasionally, but when combined together they will have fewer hard times. Using Kenneth French’s data, we can show similarly that these very poor episodes for momentum and value are ameliorated. The diversification benefits between momentum and value are evident, even during these extreme times. For example, the worst drawdown over the full sample is -43% for value, -77% for momentum, but only -30% for a 60/40 combination of value and momentum.

 

By the way, we fully recognize and acknowledge that the past ten years have not been great for momentum, with the 10-year return for UMD (Momentum) falling in the 7th percentile of rolling 10-year returns (going back to 1927). At the same time, the past ten years have not been great for value, either, with the 10-year return for HML (Value) falling in the 5th percentile of rolling 10-year returns. That, of course, makes the prior 10-year return of the 60/40 combination of the two low (2nd percentile), but still positive (12%). You know a strategy has a pretty great history when the 2nd percentile return is still positive.

 

Summing up the points from the AQR paper:

 - Momentum works better with value (negatively correlated with each other)

 - The better the value mechanism the better the whole portfolio performs (see the bolded section in the excerpt above)

 

This is where our clients shine. They are great value estimators and their research is not easily systematized. What should be systematized is the translation of that research into a portfolio and a new push for Alpha Theory will be to give our clients tools to incorporate momentum. 

 

Active manager's search for alpha is more difficult today than it has ever been. There is an existential requirement for active managers to leverage the tools and evidence around them and maximize the return they get from their research. To that end, over the coming months, you will see Alpha Theory develop new functionality to better account for momentum in position sizing. We welcome your input as we embark upon this journey.

 

June 4, 2018

Don’t Double Discount your Discounted Cash Flow

 

I was working with a client recently and we were discussing their use of discounted cash flow analysis (DCF). Most of our clients are value investors, so DCF is a key tool for many of our clients, especially when valuing businesses where the major value to be unlocked is more than a year in the future.

 

Here is the problem. The client was double discounting the risk-premium in their discount rate. What exactly does it mean?

 

Below is a simple DCF, where there is a single stream of cashflows. The investor picks a terminal date and terminal multiple and then discounts the Terminal Value back to today. The discount rate is usually a combination of the risk-free rate and a risk premium (cost of capital) that accounts for the “riskiness” of the stream of cashflows. One of the biggest challenges is the sensitivity of the discount rate. Small changes of large impacts on the total value (there is a 15% difference in valuation if I use 2% above or 2% below the current discount rate).

 

Screen Shot 2018-06-04 at 11.09.25 AM

 

The most subjective assumption in the analysis above is the risk-premium in the discount rate. It is required when looking at a single stream of cash flows. But, for investors that use scenario analysis, a risk-premium isn’t required. That’s because the risk premium (the “riskiness” of the cash flow streams) is accounted for in the forecast of risk scenarios with probabilities:

 

Screen Shot 2018-06-04 at 11.10.12 AM

 

In this case, only the risk-free rate is needed in the discount rate. The probabilities and multiple scenarios account for the “riskiness” of the cash flow streams.

 

This benefits scenario-based investors in three ways:

1. NO RISK PREMIUM: The Risk Premium assumption is subjective and creates extreme sensitivity in DCF analysis. Removing this step reduces the noise in the analysis.

2. NO DOUBLE COUNTING: Using this approach means that there is no double counting of risk (risk premium + Risk scenario).

3. EFFECTIVELY ACCOUNT FOR RISK SCENARIOS: What’s the right risk premium to add into the discount rate for a Risk scenario that is bankruptcy. 12%? 18%? 26%? It’s a question that’s not required to be answered when there is an actual probability weighted scenario that includes bankruptcy as part of the entire analysis (now how you size a position by scenario is a topic for another blog).

 

I think there is general confusion about using DCFs and scenario analysis. For most, DCFs came first. We learned to build them with a single stream of cash flows that were discounted back to present value. We learned scenario analysis at a different time and merged them together on our own. There is overlap in those two methods and hopefully this article will prompt a discussion for those funds using both DCF and scenario analysis.

 

March 12, 2018

Capital Allocators Podcast with Ted Seides: Moneyball for Managers

 

Learn how to enhance your investment results in this great podcast from Ted Seides and his guests, Clare Flynn Levy from Essentia Analytics and Cameron Hight from Alpha Theory.

This conversation covers the founding of these two respective businesses, the mistakes portfolio managers commonly make, the tools they employ to help managers improve, and the challenges they face in broader adoption of these modern tools. The good news is the clients of Essentia Analytics and Alpha Theory have demonstrated improvement in their results after employing these techniques. If you ask Clare and Cameron, you may develop a whole new appreciation about the potential for active management going forward.

 

LevyHight-FINAL

 

By creating a disciplined, real-time process based on a decision algorithm with roots in actuarial science, physics, and poker, Alpha Theory takes the guessing out of position sizing and allows managers to focus on what they do best – picking stocks.

In this podcast, you will learn how Alpha Theory allows Portfolio Managers convert their implicit assumptions into an explicit decision-making process. 

 

To learn how this method could be applicable to your decision-making process:

 

LISTEN NOW

 


 

 

May 15, 2017

Changing The Course Of Active Management — The Concentration Manifesto

Is this the end of active portfolio management? You would think so if you listen to pundits. But I see it differently. I believe we have reached a critical juncture that will ultimately redefine the space for the better — where the winners will search for ways to constantly refine their process to maximize their edge.

At Alpha Theory, we are also searching for ways for our clients to maximize edge. To that end, about a year ago, while doing some research on the impact of “crowdedness” in portfolio sizing, my team and I discovered that crowded names consistently outperformed less crowded names. That made us wonder; in general, do holdings with bigger position sizes outperform those with a smaller position size? After digging through the numbers from a cross section of 60 funds totaling over $70 billion in assets under management, we found empirical evidence that they did.

We knew we were on to something. We then isolated our clients’ highest expected return positions to see if they were the best returns. They were. With all of this demonstrated skill and ability, the question remained: why do active managers underperform? The simple answer: low conviction positions negated most of the performance they generated with the high conviction names.

The Concentration Manifesto is my attempt to get a critical dialogue started between managers and allocators to ultimately improve the active management process. As you will see, the solution is simple, but not easy. It will require that both sides cast aside outdated thinking and embrace the notion that concentration is in their best interest. But by encouraging these important discussions, I believe we will be solidifying the long term survival of the active management industry.

I hope you find the analysis insightful and valuable and I look forward to being part of the conversation.

 

DOWNLOAD FULL VERSION

 

 

March 13, 2017

Ted Seides - Alpha Theory Book Club

 

On March 7th, Alpha Theory hosted a book club with over 30 portfolio managers, analysts, and allocators coming together to discuss Ted Seides’ book, “So You Want to Start a Hedge Fund?”. We were lucky enough to have Ted present and answer questions about the capital raise environment, investment process best practices, hiring, keeping investors happy, etc.

 

Here are a few takeaways:

 

1. CAPITAL RAISE ENVIRONMENT: It’s hard out there and isn’t getting any easier. Allocators are getting pressure from their investors about their hedge fund investments.

2. INVESTING ENVIRONMENT: Once again, it’s hard out there and isn’t getting any easier. There are more smart managers than ever looking at the same ideas.

3. FEES: Fee pressure will continue and managers will be asked for fee strategies which better align the interests of the investor and the manager.

4. DURATION DISCONNECT: There has been, and probably always will be, a disconnect between the duration that a manager is judged and the duration in which a manager manages their portfolio. The best thing a manager can do is be open and honest about their challenges so that investors get comfortable with volatility of performance numbers.

5. TURNOVER: Managers should be quick to remove “bad fit” analysts, even if they’re going to get push-back from investors over changes with the team.

6. STASIS: Many hedge funds have a “set it and forget it” mentality towards culture, personnel, and investment process. Many great corporations have advanced human capital strategies and hedge funds can leverage that knowledge to build superior organizations (i.e. Bridgewater or Point72).

7. COACHES: To prevent stasis, it is important to read and sometimes bring in outside help. There are experts in team building, time management, bias mitigation, decision science, investment process, etc.

8. RUNNING A BUSINESS IS HARD: Most hedge fund managers don’t have the luxury of just picking stocks. They’re charged with hiring/firing, raising capital, investor relations, human resources, picking accountants, selecting offices, etc. All the things that a CEO of a company deals with plus managing a fund. The reason portfolio managers are so busy is because they have two full time jobs.

9. THE BET: As most know, Ted was the other side of the famous 10-year bet with Warren Buffett pitting the S&P 500 against a basket of hedge fund allocators. Ted still fully believes that hedge funds can outperform in the right environments (i.e. market is overbought).

 

Thanks to all those that attended and contact Alpha Theory if you would like to learn more about attending future book clubs.

 

February 22, 2016

How Do Hedge Funds Become Better Forecasters? - A collaborative study between Novus and Alpha Theory.

We believe that one of the few untapped frontiers in Alpha Generation is measuring and putting process around forecasting.  Alpha Theory co-authored “How Do Hedge Funds Become Better Forecasters?” with our friends at Novus to explore a few ways investors can improve their process and forecasting acumen.

 

CLICK HERE TO DOWNLOAD THE ARTICLE

 

Selected Quotes from the Article:

“Many investors chafe at price targets because they smack of “false precision". Those investors are missing the point because the key to price targets is not their absolute validity but their explicit nature which allows for objective conversation about the assumptions that went into them.”

“Unlike real life, investors can track every investment choice they have ever made. Being able to analyze statistically significant trends on a complex and numerate datasets is a huge advantage and is a crucial tool in avoiding the confirmation biases that anecdotal thinkers lean on when rationalizing decisions.”

“Developing a process orientation isn’t about stifling fluidity or gut feel. It is about recognizing that intuition is actually an informal process. By being able to document and empirically study past behaviors, all investors can understand flaws in their internal process.”

March 21, 2014

Dynamic factor modeling reveals hidden risks

GUEST POST FROM BENN DUNN, President of Alpha Theory Advisors:

Damian Handzy, CEO of Investor Analytics, and I developed the concept of dynamic factor modeling in this latest article on Risk.net.  We argue that traditional 3rd party vendor models do not accurately reflect many firm’s investment processes and leave measurable risk hidden.  Using beta as a common language between risk and portfolio managers, we recommend leveraging the literally thousands of listed instruments and funds to ease the process of risk measurement and hedging.

Click Here to full the article on Risk.net.

November 5, 2013

Less Correlation Gives Stock Pickers Opportunity

We’d like to welcome our first blog from Benn Dunn who runs our Risk Consulting practice. I’m a little biased, but I believe that Benn is one the smartest risk minds in investing today. Check out this article on Risk.net where he is quoted on the topic of correlation in portfolio management.

While lower correlations across asset classes and within markets are generally thought of as positive for security selection, the path to lower correlations can often be confusing.  Traditional risk models deliver confusing and difficult to interpret results during these regime shifts.  Fortunately, Alpha Theory is not dependent on trailing correlations when making portfolio construction recommendations. 

Click here to read the full article on Risk.net