Alex Edmans, Itay Goldstein, and Wei Jiang
The real effects of financial markets: The impact of prices on takeovers
Journal of Finance | Volume 67, Issue 3 (Jun 2012), 933–971

Does a low market valuation make a firm a takeover target? Answering this question is important to gauge how effective the takeover market is in disciplining firm management. In theory, if a manager underperforms, his firm's stock price will decline, in turn increasing the risk of a hostile takeover. The fear of such a takeover will induce the manager to maximize value in the first place. In practice, however, there seems to be no systematic relationship between a firm's stock price and its takeover vulnerability. While some studies find a negative (but economically insignificant) link between takeover likelihood and firm valuations, others find a zero or even a positive link. These results suggest that the market for corporate control is an ineffective governance mechanism.

We argue that it is difficult to detect this trigger effect—the impact of a fall in stock prices on takeover vulnerability—in the data, due to at least two reasons. First, existing studies typically predict a firm's takeover likelihood with its raw valuation (such as price-to-earnings or market-to-book ratios). However, a low raw valuation may not indicate underperformance and thus the need for a disciplinary takeover, it may be outside the manager's control and irremediable—for example, because the firm is in a low-growth, competitive industry. Instead, we hypothesize that the true driver of takeovers is the “discount” between the firm's raw valuation and its maximum potential value. This discount measures the value that an acquirer can create by taking over the firm and restoring it to its potential.

Benchmark firm valuation to peers

We estimate this discount by using the actual values of peer firms with similar fundamentals. Let X be a vector of firm fundamentals that determine a firm's potential value. Then, by observing the values of peers with similar X's, we can infer the maximum potential value of the firm in question. Specifically, if V* represents a firm's potential, we have V* = f( X ). Since V* represents the potential value after the acquirer has corrected managerial inefficiencies, the X variables should consist of firm characteristics that bidders are unlikely to change upon takeover. We thus use two approaches to choose our X variables and thus define a firm's peer group. The first is to let X be a firm's industry affiliation. Acquirers are unlikely to change the target's sector and instead typically aim to restore its value to that commanded by successful peers in the same sector. However, a firm's industry may not be the only relevant determinant of its valuation. The second approach is thus to let X be a set of firm characteristics: firm size, firm age, asset intensity, R&D intensity, market share, growth opportunities, and business cyclicality. Since these characteristics are not completely outside the bidder's control, we use the tercile rank of these characteristics within a sector. This specification allows for bidders to change the values of these fundamentals within a given tercile, but not to alter them sufficiently to move it into a different tercile. Excluding targets close to the edges of the tercile cutoffs does not change the results.

Having defined the peer group, we now infer a firm's potential given the valuations of its peers. If the set of firm characteristics X is exhaustive, and there is no mispricing, then the firm's potential would be the maximum valuation across all of its peers. However, idiosyncratic factors like misvaluation or unique core competencies could mean that this maximum is unattainable by the firm in question, even with efficient management. For example, a typical search engine is unlikely to command the valuation of Google. Instead, we assume that a firm's potential equals the valuation commanded by the 80th percentile of its peer group. We come up with 80% by taking the median takeover premium of 37–39% from Andrade-Mitchell-Stafford (JEP 2001), and adding this to the actual values of firms that later became the target of a takeover. This calculation places the median takeover target at the 77th percentile of its respective industry, which gives 80% when rounding to the nearest decile. Our results are little changed when we use 70% or 90%.

Market valuation may not be low if a takeover is anticipated

The second empirical challenge is that, while the trigger effect leads to low prices attracting takeovers, the anticipation effect runs in the opposite direction: the expectation of a takeover will increase the stock price. Thus, there is a two-way feedback loop between prices and takeovers: prices both reflect and affect a firm's takeover probability. This reverse causality will weaken the relationship between these variables in the data.

Addressing the endogeneity of firm valuations requires an instrument—a variable that affects the market price (the relevance criterion), but does not affect takeover probability other than through the market prices (the exclusion restriction). Our chosen instrument is MFFlow, the price pressure created by mutual fund trading. Since a mutual fund's actual trades could be driven by private information on a firm's likely takeover potential, we instead study mutual funds' hypothetical trades mechanically induced by flows by their own investors. Fund investors' decisions to accumulate or divest mutual fund shares are unlikely to be influenced with the takeover prospects of individual firms held by the fund. An investor, who wishes to speculate on the takeover likelihood of an individual firm, will trade the stock of that firm, rather than a mutual fund share. Hence, investor flows lead to price pressure that may affect the probability of a takeover, but are not directly motivated by this probability. We find that our measure causes significant price changes, followed by slow reversal that ends with full correction only after about two years.

Our general model can be written as Discount = γ 0 · X + γ 1 · Z1 + γ 2 · Z2 + δ · ξ + η, Takeover* = μ 1 · Discount + μ 2 · X + μ 3 · Z1 + ξ  ,   text{Takeover} = left { 
    1  RAWAMP;  text{ if }  text{Takeover}^{ ast} 0,  RAWBACKBACK;
    0  RAWAMP;  text{  text{otherwise}  ;,}
;/var/tmp/iawltxhtml/mathcache//udisplaymath9e22f9540d549fc32e8e4310b158fad5.svg  corr( eta ^{ prime}, xi ) = 0  ;,   label{Corr} ;/var/tmp/iawltxhtml/mathcache//udisplaymath728fe386ada8364963fcef4fa386404d.svg δ < 0 , where Takeover* is the unobserved variable for takeover likelihood, and Takeover is the corresponding observed binary outcome. Z1 measures firm characteristics or policies that affect both discount and takeover probability, either by proxying for managerial entrenchment (thus deterring takeovers) or by affecting the ease of takeover execution. These variables include leverage, payout, institutional ownership, and illiquidity. Z2 is the MFFlow instrument.

The construction of the Discount variable relies on the choice of a valuation metric to determine V. We use both Q and  text{Enterprise Value (EV)};/var/tmp/iawltxhtml/mathcache//mathd5941d7c525f3f7907976a232fe280e6.svg divided by Ebitda (EV/Ebitda). Combined with the two specifications for X, these two specifications for Discount yield four specifications in total.

We first ignore the anticipation effect (Discount) and estimate (Takeover) equations separately (essentially treating Discount as being unaffected by takeover probability). As is intuitive, Discount is decreasing in leverage (a potential discipline on management) and industry concentration (which affects market power), and increasing in firm concentration (consistent with the literature on the diversification discount) and illiquidity (consistent with Amihud (JFM 2002)). Most importantly, our instrument, MFFlow, is significantly associated with lower discounts across all four specifications.

Undervalued firms are more likely takeover targets

A one percentage point increase in Discount is associated with a one to three basis point increase in takeover probability, and an interquartile change in Discount is associated with a 0.4 to 1.6 percentage point increase, out of an unconditional probability of 6.2%. While a number of prior papers find no relationship between takeovers and raw valuation, this coefficient is highly statistically significant. The result is consistent with the hypothesis that the discount to potential value, rather than raw valuation, motivates acquisitions. Nevertheless, the economic magnitude is modest, especially when using EV/Ebitda. This weak relationship may result from the endogeneity of Discount, which is shrunk by the prospect of a takeover.

...but anticipation impedes takeovers

We next take into account the anticipation effect and estimate the full model using non-linear two-stage least squares, employing our MFFlow instrument. We find that a one percentage point increase in Discount would lead to a statistically significant 12 to 16 basis point increase in Takeover probability, if Discount did not shrink in anticipation of a takeover. An interquartile change in Discount is associated with a 5.7 to 7.6 percentage point increase in Takeover probability, which is economically large. Accounting for the anticipation effect and measuring a firm's valuation using the discount to its potential shows that prices are a far more important driver of takeover activities than implied by existing literature.

These results have a number of implications for takeover markets. First, the trigger effect implies that financial markets are not just a side show. They have a real effect on corporate events such as takeovers, and thus on firm value. To our knowledge, our paper is the first to use an instrumental variable to capture the effect of exogenous price changes on corporate events. Interestingly, the active role of financial markets implies that any factor that influences prices can also influence takeover activity (and other real actions). Therefore, mispricing (e.g. due to market frictions or investor errors) can have real consequences by impacting takeovers. Hence, our paper is related to the behavioral corporate finance literature. In this literature, temporary overvaluation often improves a firm's fundamental value as it allows managers to raise capital or undertake acquisitions at favorable prices. Here, it can reduce fundamental value by deterring value-creating takeovers.

Second, regarding the anticipation effect, our results demonstrate the illusory content of stock prices. While researchers typically use valuation measures to proxy for management performance, a firm's stock price may not reveal the full extent of its agency problems, as it may also incorporate the expected correction of these problems via a takeover. Our results thus challenge the common practice of using Tobin's Q or stock price performance to measure management quality. By breaking the correlation between market valuations and takeover activity into trigger and anticipation effects, our analysis enables us to ascertain the extent to which future expected takeovers are priced in.

Third, considering the full feedback loop—the combination of the trigger and anticipation effects—our results suggest that the anticipation effect could become an impediment to takeovers—the anticipation of a takeover boosts prices, deterring the acquisition of underperforming firms. Indeed, many practitioners believe that the anticipation effect has significant effects on real-life takeover activity. A December 22, 2005 Wall Street Journal article claims that this has been a major problem in the U.S. banking industry: “takeover potential raises [the] value of small financial institutions, making them harder to acquire.” This may have led to severe consequences, as small banks remained stand-alone and were less able to withstand the recent financial crisis. The belief of an upcoming takeover becomes self-defeating, which in turn sheds new light on other important real-world phenomena. First, it suggests why merger waves endogenously die out. If a recent spate of mergers leads the market to predict future acquisitions, this causes valuations to rise (anticipation effect), dissuading further acquisition attempts. Second, it provides a rationale for the practice of CEOs publicly expressing concerns about an upcoming takeover. Such statements act as a takeover defense, as they inflate the price, which in turn deters the takeover from occurring.

Forward-looking prices complicate inference and remedial action

Our paper also has a number of wider implications outside the takeover market. The feedback loop may apply to other corrective actions, such as CEO replacement, shareholder activism, and regulatory intervention. Low valuations trigger intervention, but market anticipation causes prices to rise, which in turn may deter the correction from occurring. In addition, while many existing papers use raw valuation or profitability to measure management quality or agency problems (e.g. to correlate it with CEO pay or corporate governance), this paper's approach of measuring these variables using a discount to potential value can be applied to these other settings. Furthermore, trigger effects are often estimated in non-M&A settings, such as the link between firm valuation and CEO turnover. Our approach of purging valuations of the anticipation effect is applicable to the estimation of these trigger effects also.

More broadly, our results contribute to the growing literature that analyzes the link between financial markets and corporate events (see Bond-Edmans-Goldstein (AnnRvw 2012) for a recent survey). While the corporate finance literature typically studies the effect of prices on firm actions and the asset pricing literature examines the reverse relation, our paper analyzes the full feedback loop—the simultaneous, two-way interaction between prices and corporate actions that combines the trigger and anticipation effects. We show that prices both affect and reflect real decisions. One important strand of this literature concerns the link between financial market efficiency and real efficiency. While most existing research suggests that the former is beneficial for the latter, our results point to an intriguing disadvantage of forward-looking prices—they may deter the very actions that they anticipate.

Zhao Zhiqian (1829–1884): Hemerocallis. China, 1859.. This radiant flower painting is an example of the Shanghai School of painting. Shanghai had an influx of foreigners and grew wealthy through trade (thanks to the Opium War, though this one is not a poppy). This created a lucrative market for art and a place for artists to break away from the traditional “literati” style into an innovative amalgamation of traditional subjects and modern techniques. Zhao Zhiqian, who created a dazzling array of flower paintings, inspired later masters, such as Qi Baichi (on our FAMe cover). This painting now hangs in the Shanghai Museum.