O’Shaughnessy Quarterly Investor Letter Q3 2018 - OSAM

Past performance is no guarantee of future results. Please see important information titled “General Legal Disclosures & Hypothetical and/or Backtested Results Disclaimer” at the end of this presentation. 1

O’Shaughnessy Quarterly Investor Letter Q3 2018

September 30, 2018

Dear Investor,

Basic factor investing is settled territory. Most investors have been bludgeoned with countless strategies that use factors like value, momentum, quality, or low volatility. As William Gibson observed in Pattern Recognition, “commodification will soon follow identification.” The primary factors were identified long ago and have been packaged and repackaged in just about every way imaginable.

I’d like to use this letter to describe the more interesting, next stage of factor investing: alpha within factors. This simple idea describes what we’ve pursued at OSAM over the years, and what we continue to pursue through our research agenda today. We will soon be sharing a broader and more formal paper on alpha within factors, but as a precursor I’ll use this letter to illustrate what we mean through an abbreviated example: an exploration of buybacks, capital allocation, and the buyback factor. My goal is not to showcase our entire research process (which has a lot more nuance), but instead to highlight the spirit of how we search for useful signals.

In accordance with our mantra of “learn, build, share, repeat” I will also use statistical learning methods1 as part of this analysis to show how useful they can be. Methods like the clustering technique described below help detect complex correlation structures in data sets. The identification of patterns can lead to insight, understanding, new ideas, and model improvements.

Why We Care About Buybacks As a broad category, the stocks of companies which have repurchased large percentages of shares have outperformed the market. But within the sample of high buyback firms, there has been a wide dispersion of outcomes. The question I explore is whether we can model this dispersion to find alpha within the buyback factor.

First, it is helpful to review how important buybacks have become. Consider a new metric we call “Peak Yield,” which is the total reduction in shares outstanding from a company’s peak historical shares. Peak yield tells us how large a total buyback program a company has completed through a given date in history (e.g. Apple has repurchased 25% of its shares since 2013).

1 I’m trying to avoid the phrase “machine learning” whenever possible!

https://osam.com/Philosophy-and-Process

http://investorfieldguide.com/machinelearning/

https://osam.com/pdfs/research/_28_Commentary_HighConvictionBuybacks.pdf


Here is Northrup Grumman as a visual example, including two periods of share buybacks. Its shares are shown in red, “peak shares” (the maximum amount shares outstanding in a given company’s history) are tracked in green, and peak yield (cumulative total buyback percentage since the share peak) is shown in blue

Since 2004 Northrup has steadily and aggressively repurchased 52% of its shares.

Here is the average peak yield of all stocks in the U.S., shown for both large and small stocks. The average large cap stock has repurchased 20% of its shares from the peak. This average includes all the companies which remain at their share peak (i.e. their peak yield = 0), which is roughly 20% of the large cap sample.

The average time since peak shares is more than 12 years, and the overall market’s buyback activity has been steady between 2% and 3% per year. Barring legislative action around buybacks, we expect companies to continue to use considerable amounts of cash to buy back shares.

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Northrop Grumman (NOC) - Peak Yield

Total Shares Peak Shares Peak Yield (%)Source: OSAM Research.

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US Large Stocks US Small StocksSource: OSAM Research.Source: OSAM Research.


Excess Returns We are so interested in this factor because during (and after) these periods of significant share buybacks, these stocks have outperformed. Here is the average excess return of these stocks as they are repurchasing shares (where time zero is set at the peak share date for each company). We group companies by their buyback intensity. As you can see below where we group stocks into those that have repurchased more than 5% of share, more than 10% and more than 20%, the higher the cumulative buyback yield, the higher the excess return.

These are returns that happen alongside buybacks, but investors should only care about signals which are predictive of forward returns. Here are the results for a variety of simple buyback factors. The factors sort companies by looking back between 6 months and 10 years of trailing buyback activity.

Across the board, buying companies which have repurchased a large percent of shares in the past continue to outperform in the future. Companies in the lowest decile, which are issuing the most shares, perform poorly.

Even looking back ten years, or all the way to share peak, buyback factors have still delivered strong forward return spreads.

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Buyback Programs Excess Returns (> 1 Yr) -Large Stocks Universe

Yield >= 5 Yield >= 10 Yield >= 20Source: OSAM Research.

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Buyback Program Excess Returns (> 1 Yr) -Small Stocks Universe

Yield >= 5 Yield >= 10 Yield >= 20

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Trailing Buyback Yield Returns - Large Stocks (1982 - 8.2018)

Peak Yield 6 Mon. 1 YR 3 YR 5 YR 10 YRSource: OSAM Research.


Capital Pies Buybacks on their own seem to provide an interesting signal, but buybacks are just one of several potential uses of corporate cash. OSAM’s investing model places significant emphasis on capital allocation factors because we believe that with so much focus on the balance sheet and operating metrics, these factors are an underused and underappreciated source of differentiation.

Capital allocation factors also lend themselves to quantitative analysis because they can be summarized and measured in just a few major categories. We call these capital pies.

Spending Pie: cash can be spent on buybacks, dividends, debt paydown, capital expenditures, research & development, working capital, and acquisitionsi.

Sourcing Pie: cash can be sourced from operating cash flow, debt issuance, equity issuance, sales of assets, and sale of investments.

Here are the sources and uses of cash for all large cap companies on average, based on data from the statement of cash flows. One important note: you’ll notice that while mergers and acquisitions are generally the largest use of capital, acquisition cash flow is a small slice here. That is because the capital for acquisitions comes from debt and equity issuance, and from existing cash. Only the use of existing cash (netted against any cash acquired) shows up here as a separate item.

Source: OSAM Research

What we are most interested in is whether different styles of capital allocation beyond buybacks lead to unique outcomes that we as investors can use in our process. One idea would be to use buyback intensity as a distinguishing factor for bucketing capital allocation styles. Doing so, we can create simple style groups:

1) Issuers (negative buyback yield)

2) Buybacks >=0

3) Buybacks >5% (high conviction)

4) Buybacks >10% (highest conviction)

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Overall Cash Flow Uses Average Since 1990

Buybacks CapExAcquisitions InvestmentsDividends Debt PaydownWorking Cap. Chg. R&DOther

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Overall Cash Flow Sources Average Since 1990

Op. Cash Flow Investment SalesSale of PPE Equity IssuanceDebt Issuance Working Cap. Chg.Other

https://osam.com/Philosophy-and-Process


This grouping does one thing well: it reflects the relative maturity of the companies within each group. Here is the average trailing five-year sales growth for each, showing that firms issuing shares tend to be growing much faster, and thus consuming more capital. Those with the highest buybacks are growing much slower.


By building the capital pies for each group, we begin to see how companies behave at different stages, starting with issuers on the left, and steadily higher buyback levels as we move right:

Cash Flow Uses – Average Since 1990

Cash Flow Sources – Average Since 1990

Source: OSAM Research While there are some noticeable differences (issuers spend more on CAPEX and R&D, higher and higher buyback firms are more reliant on debt financing), the pies are very roughly similar. So perhaps our group isn’t ideal for producing further insight.


The Right Kind of Buyback Each company is different, and no two capital allocation strategies will be exactly alike. But the entire quantitative research process is about finding common categories which perform in similar ways, so that we can then buy or avoid/sell short the categories. Rather than classify different styles of capital allocation manually (as we did above with levels of buyback activity), we can also use methods like clustering (k-means) to identify patterns for us. These patterns may point towards sources of alpha within factors.

For this exercise, we start with all companies with a positive buyback yield, and set the number of clusters to three, meaning the algorithm will create three capital allocation/sourcing “archetypes” and then assign every stock to one of three2. To build the archetypes, the clustering algorithm needs data, so we feed it every slice of the capital pies for every company, on every date since 1990.

What I love about this method is that it classifies companies objectively, based on the most similar traits, and not based on our opinion of what the groupings should be. The resulting clusters are not delineated based on their buyback level as we tried above. Instead they are grouped based on the financing source and level of investment.

We will call these groups:

1) Internal financing, high investment

2) Mixed financing, mixed investment

3) Debt financing, low investment

Cash Flow Uses – Average Since 1990

Cash Flow Sources – Average Since 1990


2 For this part of the exercise, we exclude financial firms.


These relationships are much more distinct than we saw when we grouped companies by their buyback activity. Here is a time series of the percent of cash coming from operations vs. debt for the three clusters:

The internal financing companies spend the most (as a percent of total spending) on both CAPEX and R&D:

Here is the average relative valuation for each group (where the 50th percentile is the median valuation across all large stocks, and 1st percentile is cheapest stock). Companies buying back shares tend to be slightly cheaper than the market on average, and you can see that reflected here. But for the most part, the relative valuations of these groups are similar, despite very different capital sourcing and spending styles.

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Debt financing, low investmentSource: OSAM Research.

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Debt financing, low investmentSource: OSAM Research.

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Debt financing, low investment


Now, here are the returns of each cluster since 1990, shown as excess returns vs. the overall group of positive buyback companies. The internally financed, high investment group outperformed the debt financing, low investment group by 3% per year, annually. That is a large number in a large cap universe, keeping in mind that most common factors usually applied in this space (value, momentum, etc.) are entirely absent here.

This tells us that financing source is likely a robust way to generate alpha within the buyback factorii.

We return to our clustering algorithm, but add the valuation score shown above as a variable when building the clusters, so now we are grouping stocks based on their capital pies and their current valuation. We do so because intuitively, the price at which buybacks are happening should be critical. If a management team repurchases shares below intrinsic value, that is good decision for shareholders (and if they do so at a premium, it’s a bad decision). With valuation added, different clusters emerge.

1) High debt financing

2) Cheap buybacks

3) Expensive buybacks

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Value Composite (Ex. Sh. Yld)

Internal financing, high investment Mixed financing, mixed investment Debt financing, low investmentSource: OSAM Research.

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Excess Return - All Buyback Companies

Internal financing, high investment Mixed financing, mixed investment Debt financing, low investmentSource: OSAM Research.


The debt financing cluster remains distinct as with our first iteration. But the two other groups stand in stark contrast measured by their current valuation:

Again, we can measure the performance of these clusters and find an interesting trend. The debt financing group confirms our earlier finding, with bad results. But the cheap buyback group outperforms the expensive buyback group by close to 2% per year, despite otherwise similar capital allocation and sourcing levels across the two groups.

Alpha Within Buybacks When you roll this all together, you realize quickly that raw buyback yield, while powerful, can be improved with additional information (and keep in mind that for simplicity, we’ve only explored a few extra dimensions here).

To confirm, we run three traditional factor tests. We start with a universe of high buyback firms (top quintile) and then bucket those companies in quintiles based on the percent of their financing derived from operations (panel 1), the percent derived from debt issuance (panel 2), and their valuation score (panel 3). These show excess returns versus the large stocks universe. Notice the negative excess returns in the fifth quintile of the first two

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High debt financing Cheap buybacks Expensive buybacksSource: OSAM Research.

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Excess Return - All Buyback Companies

High debt financing Cheap buybacks Expensive buybacksSource: OSAM Research.


panels. This means that in this period, the positive effect of buybacks is undone if those companies repurchase at expensive prices or repurchase alongside the highest level of debt financing.

In each case, the factor returns suggest that we can improve upon a simple buyback factor.

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Highest Quintile Buybacks

Source: OSAM Research.

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Conclusion – The Future of Factors One of my favorite things to do is talk to discretionary, fundamental analysts and portfolio managers. They often know their stocks and industries to a depth that is hard for a quant to fathom. When you ask them their opinion on buybacks, or valuation, or capital allocation, they inevitably respond: “it depends.” Pursuing alpha within factors is answering the question “depends on what?”

In the case of buybacks, the financing source (debt issuance vs. operating cash flows) and valuation are two of many answers. A model which adjusts for these findings represents an empirical and intuitive improvement over a simple buyback factor, which is why we use several factors measuring leverage, capital sourcing, and cash flows in our live model.

Passive and smart beta are on the rise, and fees continue to fall. Style box investing is now 25 years old. Perhaps, in the future, investors will abandon style boxes and instead focus on three simpler categories: 1) passive, 2) smart beta (commodity factors) and 3) alpha.

Nothing will work all of the time, and idiosyncratic explanations will often trump the broader observations in this letter, but our goal is always to generate alpha by tilting the odds in our clients’ favor. I believe that a process that improves upon commodity factors by finding alpha within factors gives us the best odds of doing so in the future.

We will be back with much more on this topic soon, so be sure to follow along here. Thanks to Danny Nitiutomo, CFA, a member of OSAM’s research team, for his work on this letter.

________________________

i. Companies can also accumulate cash, which often show up on the statement of investing cash flows in the form of marketable securities

ii. This is not meant to be an academic paper, so I am only sharing the highlights, but for anything in production, we consider much more than these high level numbers.

https://osam.com/Commentary


GENERAL LEGAL DISCLOSURES & HYPOTHETICAL AND/OR BACKTESTED RESULTS DISCLAIMER

The material contained herein is intended as a general market commentary. Opinions expressed herein are solely those of O’Shaughnessy Asset Management, LLC and may differ from those of your broker or investment firm.

Please remember that past performance may not be indicative of future results. Different types of investments involve varying degrees of risk, and there can be no assurance that the future performance of any specific investment, investment strategy, or product (including the investments and/or investment strategies recommended or undertaken by O’Shaughnessy Asset Management, LLC), or any non-investment related content, made reference to directly or indirectly in this piece will be profitable, equal any corresponding indicated historical performance level(s), be suitable for your portfolio or individual situation, or prove successful. Due to various factors, including changing market conditions and/or applicable laws, the content may no longer be reflective of current opinions or positions. Moreover, you should not assume that any discussion or information contained in this piece serves as the receipt of, or as a substitute for, personalized investment advice from O’Shaughnessy Asset Management, LLC. Any individual account performance information reflects the reinvestment of dividends (to the extent applicable), and is net of applicable transaction fees, O’Shaughnessy Asset Management, LLC’s investment management fee (if debited directly from the account), and any other related account expenses. Account information has been compiled solely by O’Shaughnessy Asset Management, LLC, has not been independently verified, and does not reflect the impact of taxes on non-qualified accounts. In preparing this report, O’Shaughnessy Asset Management, LLC has relied upon information provided by the account custodian. Please defer to formal tax documents received from the account custodian for cost basis and tax reporting purposes. Please remember to contact O’Shaughnessy Asset Management, LLC, in writing, if there are any changes in your personal/financial situation or investment objectives for the purpose of reviewing/evaluating/revising our previous recommendations and/or services, or if you want to impose, add, or modify any reasonable restrictions to our investment advisory services. Please Note: Unless you advise, in writing, to the contrary, we will assume that there are no restrictions on our services, other than to manage the account in accordance with your designated investment objective. Please Also Note: Please compare this statement with account statements received from the account custodian. The account custodian does not verify the accuracy of the advisory fee calculation. Please advise us if you have not been receiving monthly statements from the account custodian. Historical performance results for investment indices and/or categories have been provided for general comparison purposes only, and generally do not reflect the deduction of transaction and/or custodial charges, the deduction of an investment management fee, nor the impact of taxes, the incurrence of which would have the effect of decreasing historical performance results. It should not be assumed that your account holdings correspond directly to any comparative indices. To the extent that a reader has any questions regarding the applicability of any specific issue discussed above to his/her individual situation, he/she is encouraged to consult with the professional advisor of his/her choosing. O’Shaughnessy Asset Management, LLC is neither a law firm nor a certified public accounting firm and no portion of the newsletter content should be construed as legal or accounting advice. A copy of the O’Shaughnessy Asset Management, LLC’s current written disclosure statement discussing our advisory services and fees is available upon request.

Hypothetical performance results shown on the preceding pages are backtested and do not represent the performance of any account managed by OSAM, but were achieved by means of the retroactive application of each of the previously referenced models, certain aspects of which may have been designed with the benefit of hindsight.

The hypothetical backtested performance does not represent the results of actual trading using client assets nor decision-making during the period and does not and is not intended to indicate the past performance or future performance of any account or investment strategy managed by OSAM. If actual accounts had been managed throughout the period, ongoing research might have resulted in changes to the strategy which might have altered returns. The performance of any account or investment strategy managed by OSAM will differ from the hypothetical backtested performance results for each factor shown herein for a number of reasons, including without limitation the following:

▪ Although OSAM may consider from time to time one or more of the factors noted herein in managing any account, it may not consider all or any of such factors. OSAM may (and will) from time to time consider factors in addition to those noted herein in managing any account.

▪ OSAM may rebalance an account more frequently or less frequently than annually and at times other than presented herein.

▪ OSAM may from time to time manage an account by using non-quantitative, subjective investment management methodologies in conjunction with the application of factors.

▪ The hypothetical backtested performance results assume full investment, whereas an account managed by OSAM may have a positive cash position upon rebalance. Had the hypothetical backtested performance results included a positive cash position, the results would have been different and generally would have been lower.

▪ The hypothetical backtested performance results for each factor do not reflect any transaction costs of buying and selling securities, investment management fees (including without limitation management fees and performance fees), custody and other costs, or taxes – all of which would be incurred by an investor in any account managed by OSAM. If such costs and fees were reflected, the hypothetical backtested performance results would be lower.

▪ The hypothetical performance does not reflect the reinvestment of dividends and distributions therefrom, interest, capital gains and withholding taxes.

▪ Accounts managed by OSAM are subject to additions and redemptions of assets under management, which may positively or negatively affect performance depending generally upon the timing of such events in relation to the market’s direction.

▪ Simulated returns may be dependent on the market and economic conditions that existed during the period. Future market or economic conditions can adversely affect the returns.

Composite Performance Summary

For full composite performance summaries. please follow this link: http://www.osam.com

OSAM CONTACT INFORMATION:

O’Shaughnessy Asset Management, LLC ■ Six Suburban Avenue ■ Stamford, CT 06901 ■ 203.975.3333 Tel ■ 203.975.3310 Fax

http://www.osam.com/

Documents

O’Shaughnessy Quarterly Investor Letter Q3 2018 - OSAM