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Alpha Theory Blog - News and Insights

4 posts categorized "Clare Flynn Levy"

July 1, 2019

Brief Buys…Slow Sells

 

Sean Stannard-Stockton, who runs Ensemble Capital, sent us a link to a recent paper titled “Selling Fast and Buying Slow on return contribution of buy and sell decisions on over 4 million trades across 700+ portfolios. The result is that the portfolio managers in this study were great buyers and lousy sellers. On top of that, they compounded the problem by slowly buying, when they would have made more money by quickly buying, and quickly selling when they would have lost less money if they would have slowly sold.

 

Alpha Theory does this by design. It starts (buys) positions quickly and sells them slowly. We’ve measured a 4% difference between our clients’ ROIC of 6% and the 10% ROIC if they’d have traded according to Alpha Theory’s recommendations. We further break that down into initial position sizing and trading, where we find that about half, or 2%, comes from better trading. The “Selling Fast and Buying Slow” paper finds 170bps from better buying and selling decisions, which is close to the trading difference we’ve measured for our clients*.

 

Excerpt from “Selling Fast and Buying Slow” - Is there skill in buying and selling?

 

We examine this question using a unique data set containing the daily holdings and trades of sophisticated market experts—experienced institutional portfolio managers (PMs). Our data is comprised of 783 portfolios, with an average portfolio valued at approximately $573 million. More than 89 million fund-security-trading dates and 4.4 million high-stakes trades (2.0 and 2.4 million sells and buys, respectively) are observed between 2000 and 2016.

 

While the investors display clear skill in buying, their selling decisions underperform substantially. Positions added to the portfolio outperform both the benchmark and a strategy which randomly buys more shares of assets already held in the portfolio by over 100 basis points per year. In contrast, selling decisions not only fail to beat a no-skill random selling strategy, they consistently underperform it by substantial amounts. In our preferred specification, PMs forgo 70 basis points per year in raw returns.

 

Why would a majority of portfolio managers appear to exhibit skill in buying while at the same time underperforming substantially in selling? At face value, the fundamentals of buying and selling to optimize portfolio performance are similar: Both require incorporating information to forecast the distribution of future returns of an asset. Skill in both decisions requires the investor to look for relevant information and integrate it into the forecast. However, there is a reason to suspect that selling and buying decisions involve different psychological processes (Barber and Odean 2013). Recent work from the lab is consistent with this discrepancy: Buying decisions appear to be more forward-looking and belief-driven than selling decisions in an experimental asset market (Grosshans, Langnickel, and Zeisberger 2018). And indeed, anecdotal evidence from our sample points to PMs thinking differently about the two decisions; extensive interviews suggest that they appear to focus primarily on finding the next great idea to add to their portfolio and view selling largely as a way to raise cash for purchases.

 

We utilize a unique dataset and find evidence that financial market experts—institutional investors managing portfolios averaging $573 million—display costly, systematic biases. A striking finding emerges: While investors display skill in buying, their selling decisions underperform substantially—even relative to random sell strategies. We provide evidence that investors use heuristics when selling but not when buying, and that these heuristic strategies are empirically linked to the documented difference in performance.

 

As shown in Section 4, the comparison of trades on earnings announcement versus nonannouncement days suggests that PMs do not lack fundamental skills in selling; rather, results are consistent with PMs devoting more cognitive resources to buying than selling. When decision-relevant information is salient and readily available—as it is on announcement days—PMs’ selling performance improves substantially. We propose a mechanism through which overall underperformance in selling can be explained by a heuristic two-stage selling process, where PMs limit their consideration set to assets with salient characteristics (extreme prior returns) and sell those they are least attached to (low active share assets). A proxy for this heuristic strategy is associated with substantial losses relative to a no-skill random selling strategy.

 

The question remains of why professional PMs have not learned that their selling decisions are underperforming simple no-skill strategies. While we can only speculate, the environment in which fund managers make decisions offers several clues. As Hogarth (2001) notes, the development of expertise requires frequent and consistent feedback. While it is feasible to generate this type of feedback for both buy and sell decisions, anecdotal evidence from our interviews with PMs suggests that decisions are overwhelmingly focused on one domain over the other. In terms of time allocations, our understanding is that the vast majority of the investors’ research resources are devoted to finding the next winner to add to the portfolio. Moreover, standard reporting practices are well-suited for evaluating the performance of buying decisions: Purchased assets are tracked, providing salient and frequent feedback on the outcomes of buying decisions. This process appears successful in producing expertise—purchased assets consistently outperform the benchmark. In comparison, paltry resources are devoted to decisions of what to sell, and the relevant feedback is largely lacking: Assets sold are rarely if ever, tracked to quantify returns relative to potential alternatives such as our random sell counterfactual.

 

A recent paper by our friends at Essentia Analytics titled “The Alpha Lifecycle” confirms this conclusion with a different data set and a different approach.

 

Essentia is wrapping up a 5-month analysis of this phenomenon (Alpha Lifecycle), involving data from 42 portfolios over more than 10 years. The conclusions are clear: alpha has a beginning, a middle and an end. It tends to decay over time, reducing — or even reversing — the benefits it offered early on. Active managers who wish to deliver sustained alpha in their portfolios need to understand their own alpha lifecycles and adjust their investment decision-making processes accordingly.

 

Dominant Lifecycle from Essentia Analytics

Picture1

 

Alpha has a lifecycle and tends to decay over time — frequently causing managers who fall in love with their stocks to suffer. On average, managers we analyzed experienced a 400 basis point peak-to-trough decay in return on each position. 

 

These papers are great examples of the value of feedback for firms that want to improve. Capturing data, analyzing that data, and changing behavior based on empirical evidence is akin to Tiger Woods hitting golf balls while hooked up to a TrackMan and adjusting his swing to maximize the attributes that give him the greatest chance of success. The managers of the future are already adopting regimens that treat their process like that of an elite athlete. Those that don’t will get left behind.

 

*** We recognize this is not a perfect apples-to-apples comparison as our analysis measures the trading value as the difference between the Alpha Theory return and the return of keeping a consistent position size from beginning to end of the holding period.

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

 


 

 

November 10, 2017

Predictably Insightful: Recap of the Behavioral Alpha Conference

 

This is a picture of me and Dan Ariely, author of “Predictably Irrational” and five other great books on decision pitfalls we all fall into. Dan was the keynote speaker at Behavioral Alpha 2017 an event put on by our friends at Essentia Analytics and we were proud to help sponsor.

 

Behavioral Alpha

 

The day was packed with great speakers including:

- Dan Ariely: “Behavioral Finance in Practice” 

- Denise Shull talking about “Your Senses, Feelings & Emotions are the Ultimate Dataset”

- Clare Flynn Levy: "Applying Behavioral Finance to Your Own Investment Process" 

- Fireside Chat with Mark Baumgartner: “Why Asset Allocators Care About Behavioral Analysis” 

- Cameron Hight: “Mistakes Managers Make & How to Fix Them”

- Peer Idea Exchange: Paul Sonkin and Paul Johnson: “Pitching the Perfect Investment:

- Managing the Tensions Between Analysts and Managers” 

- Dave Winsborough: “How the Collective Personality of Your Team Affects Performance”

 

Here’s a quick recap of some of the takeaways:

Dave Winsborough discussed ways that we can build better teams by understanding the goal we’re trying to accomplish, the needed components to accomplish that goal, and measuring the team participants to make sure that the team has all of the necessary components. It’s a relatively straightforward idea that should be applicable to almost any team.

Denise Shull discussed ways we can become better in tune with our feelings and emotions with the idea of learning when and how to leverage those feelings. Learning how to identify our own emotions is a powerful first step towards being able to mute the negative emotions and take advantage of the positive (signals).

Much of the conference was on emotion and bias and how they cause us to make poor decisions. I completely agree, but that’s not my expertise. I spent much of my time talking the processes that help mitigate bias. This primarily involved making our assumptions and decision process explicit so that they can be judged and analyzed.

Dan Ariely gave several fascinating anecdotes like how casinos are the best at applying behavioral tools, how company internal satisfaction surveys have predictive power for stock performance, how Intuit is giving teams time and money to try bold new initiatives to help them get over the risk of projects that fail, a weight scale that doesn’t show your weight (but tracks it over time) is a much better way to lose weight than one that gives immediate feedback that is subject to good-habit-breaking volatility, and how people in the next to the lowest tax bracket are the ones most opposed to minimum wage hikes because it could push them into the lowest rung of society. His major takeaway was the bias and personality are tough to eliminate so you have to create habits, rules, and routinized behaviors that help us do the things we say we want to do (very Alpha Theory😉).

Clare Flynn-Levy showed how investors can make better decisions by capturing some basic information about themselves and their decisions. Taking the time to tie those data points together can help us better understand when we make good decisions and when we make poor decisions. By understanding these cues when they’re happening we can take advantage of the positive and avoid the negative.

Mark Baumgartner discussed his time at the Ford Foundation and Institute of Advanced Studies and some of the things he’s seen in the managers he evaluates. He said that about 10% of the managers he meets have some form of structured process around behavioral science, decision making, portfolio management, position sizing, etc. He believes that the primary value of a manager isn’t based on these processes, but he believes there is a lot of easy to pick up alpha form implementing process. He would like to see his managers embrace it more actively but says the industry moves glacially while the products that help improve the process are evolving very fast.

The room was full of managers and allocators. There was a self-selection bias, but the crowd truly embraced the concepts for how to be better using the behavioral science discussed during the day. In fact, the crowd asked amazing questions and one of my favorite parts of the day was from a member of the audience that was expanding on his thoughts about the difficulties of capturing alpha. He said the number of investors has increased from 5,000 to 1 million over 50 years. How do you reverse that trend when it is one of the highest paid professions, where you get to work with amazing people, research a broad range of interest, get to meet leaders in industry, academics, and government, and be exposed to an array of amazing ideas? If I’m ambitious and at the top of my class, why would I not pursue that profession.

Hmmmmm, maybe we can ask Dan Ariely if he has some creative way to change that behavior.

 

April 4, 2016

Active Managers: The Time is Now

Clare Flynn Levy, the CEO of Essentia Analytics and a friend of Alpha Theory, wrote an article that I wish I could claim. It sums up many of the reasons why the “time is now” to optimize process to stay competitive.

Selected Quotes:

At the end of the day, whether the strategy is hedge or long-only, active management involves a portfolio manager who reviews the information presented by analysts, risk systems and external sources, and then makes what is ultimately a qualitative judgement call.

Now, more than ever, is the time to stop and consider how you could be learning from past success and mistakes in a more efficient way, refocusing your team’s energy on doing more of what you’re good at, and less of what you’re not.

For even though investment management is an industry whose true value proposition is the way decisions are made, very few managers are doing anything to make the decision-making process a provable competitive advantage for themselves.

Click here for a link to the article.