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May 02, 2005 01:00 AM

Using share buybacks as investment indicator

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    By Easton Ragsdale

    Companies typically use available cash in five ways.

    First, they can return cash to shareholders in the form of cash dividends. Second, companies can use cash to purchase their own shares in the open market, thereby shrinking the capital base; this activity is referred to as a share buyback or repurchase. Third, they can use cash to repay debt. Fourth, they can use cash for capital expenditures, such as new plant and equipment. Finally, a company can use cash to acquire another company.

    Some of these uses for cash are riskier than others and might lead to poor stock performance. For example, academic studies have shown that acquisitions tend to be risky and lead to poor stock returns for the acquirers. Likewise, academic studies have found that companies with aggressive capital expenditures tend to perform poorly. In many cases, companies which are aggressive in terms of capital expenditures and acquisitions choose to fund these activities by selling additional shares through a seasoned equity offering, thereby increasing their shares outstanding.

    Both academic and investment practitioner research have suggested that companies with a conservative approach to their use of cash perform better in the stock market over the long term. Specifically, companies that use cash to reduce their shares outstanding by buying back shares tend to outperform companies that increase their shares outstanding.

    Share buybacks have one other interesting feature that appeals to management: It is the only use of cash that encourages shareholder loyalty. For all other uses, every shareholder is affected equally by the company's activity. In the case of share buybacks, however, investors who do not wish to remain shareholders are selling their shares back to the company. The result of this self-selection process is a more loyal shareholder base.

    Long history

    There is a long history of investors making use of information about share buybacks in one form or another. For example, in the late 1970s, some institutional investors with a quantitative bent were already selecting stocks based on announcements (not actual implementation) of share buyback programs.

    We decided to test what we call the Share Buyback, or SBB, factor, to see whether it could add value to a quantitative stock selection model. The conclusions were positive:

    • In a stand-alone or single-factor historical back test, the SBB factor provided an annualized return difference of 8.29% between the most attractive decile of stocks (top) and the least attractive decile (bottom).

    • When examined in a historical back test as part of a multifactor stock selection model, the SBB factor contributed an annualized return relative to the benchmark of 1.21%, holding all the other factors constant.

    In our investigation of share buybacks, we employed at first a simple measure. We calculated the SBB factor as the percentage change in shares outstanding from 12 months ago (time t-12) to today (time t). We then calculated the SBB factor for an extended universe of large-capitalization stocks, using only data that were available at each point in time. The next step was to sort the stocks into deciles, and we measured how well the stocks in each decile performed over the next month, beginning in January 1990 and ending in May 2004. Clearly, on a stand-alone basis the SBB factor does a good job of discriminating between good-performing stocks and poor-performing ones. The decile spread for the full test period was a strong 8.29%.

    Did a good job

    While this was good news, we needed to see if the SBB factor could discriminate not just between the top and bottom decile, but also between neighboring deciles such as the ninth and eighth deciles. We found the SBB factor did a good job of sorting stocks according to future returns. But what if implementing the SBB factor as a signal led to so much portfolio turnover that the actual trading costs consumed most of the theoretical returns? We found that during the back-test period, the average monthly turnover was 15.5% for the top decile of stocks sorted under the SBB factor and 12.4% for the bottom decile, for a total of 27.9%. These statistics compare quite favorably with those for the other factors in Weiss, Peck & Greer's stock selection model.

    Next we had to check to see if the SBB factor could continue to add value for more than a single month. (See chart 3). We found the SBB factor's ability to predict the average annual return difference between top and bottom deciles actually grew and widened with longer holding periods. Good news, again.

    At this point it was time to see how the SBB factor functioned as part of a multifactor stock selection model. How would the SBB factor behave when its signals had to compete with other factors in a model? After all, that is how we actually use such a factor in our investment process. Ideally, the SBB factor would have a low correlation with other factors in the model, meaning it was able to measure some characteristic of stocks not captured by the other variables. We performed a regression for each month of the back-test period; the results were quite strong, with the SBB factor making an average annual contribution to returns relative to the benchmark of 1.21%.

    Our conclusion is that the SBB factor is a very promising addition to our stock selection model. However, there is still much to learn about this factor. For example, we need to better understand the relationship between the SBB factor and other factors such as dividend yield. Does the SBB factor work better in some economic sectors than in others? Do companies that repeatedly buy back shares exhibit stronger or weaker performance than companies that buy back shares intermittently or for the first time?

    As with any stock selection factor, there is always room for more research.

    Easton Ragsdale is managing director of Weiss, Peck & Greer Investments/Robeco USA, New York.

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