Chris Yung

Entrepreneurial Financing and Costly Due Diligence

In the traditional solution to the adverse selection problem, entrepreneurs indirectly signal quality via security choice, typically debt. This paper models an alternative solution. The costly due diligence of venture capitalists directly reveals the quality of projects, thereby reducing information asymmetry. It is shown that this mechanism necessitates profit-sharing, a contractual feature usually associated in the literature with managerial agency costs rather than adverse selection.

The Misuse of Expected Returns

Much textbook emphasis is placed on the mathematical notion of expected return and its historical estimate via an arithmetic average of past returns. But those wanting to forecast a typical future cumulative return should be more interested in estimating the median future cumulative return than in estimating the mathematical expected cumulative return. For that purpose, continuous compounding of the mathematical expected log gross return is more relevant than ordinary compounding of the mathematical expected gross return. Self-test Pensions, endowments, and other long-term investors often want to forecast the future cumulative returns associated with various asset-class indices or investment strategies. Because no one can foretell the future, the future cumulative return is always a random variable that has a probability distribution. As a point forecast of the future cumulative return, some analysts have chosen to estimate the mathematical expectation of the future cumulative return’s distribution. We argue that this choice is misguided because the distribution of the future cumulative return is often heavily (positively) skewed. As a result, the mathematical expectation of its distribution is not as good a measure of its central tendency (i.e., what is more likely to happen) as is the median future cumulative return. The median future cumulative return has a 50 percent chance of being met or exceeded, but we show that the probability of meeting or exceeding the mathematical expectation approaches zero as the forecast horizon grows to infinity. As a result, even an accurate forecast of the mathematical expected future cumulative return is a badly overoptimistic forecast of what is likely to occur over long horizons. For example, our simulations indicate that there is only about a 30 percent probability of meeting or exceeding the mathematical expected future cumulative return of a large-capitalization stock index at the 30-year horizon that typifies retirement planning forecasts. We use a relatively recent result in the theory of statistics to argue that analysts who want to estimate the median future cumulative return should focus their attention on the mathematical expected logarithm of a single period’s gross return distribution. Continuously compounding the expected log gross return through T periods approximates the median future cumulative return at the T-period horizon. A simple point forecast of the median future cumulative return is made by (1) computing the average of the historical log gross returns (e.g., historical daily or monthly return data) in all past measurement periods and then (2) continuously compounding Step 1’s result up to the T-period forecast horizon. Substituting the average historical ordinary net return for the average historical log gross return in Step 1 is not recommended. Unfortunately, use of any historical average return is somewhat problematic, even in ideal statistical circumstances that may not characterize the real world. Even if the distribution of period log gross returns has been (and will remain) stable over time, the volatility of these log gross returns can make historical averages significantly different from future long-term averages. We show that typical stock index return volatility (15 percent) is enough to cause substantial fluctuation in historical averages. For example, even with 54 years of historical log gross return data, the fluctuation in future historical log gross return averages will be ±400 bps.

CEOs in Family Firms: Does Junior Know What He's Doing?

We model the evolution of CEO quality in family firms. When heirs work toward a common goal alongside an older generation, Bayesian updating attributes success mostly to the older (proven) agent. Thus, heirs learn little about their own skill. This effect is strongest after the founder, implying that family firms tend to either die immediately or be relatively long-lived. More generally, we obtain an even/odd fluctuation in generational quality. Because uncertainty breeds caution, our analysis points to a conservative managerial style in family firms and emphasizes the importance of external screening mechanisms, especially for heirs following a very successful generation.

The Long-Run Supply and Demand for Venture Capital Funds: Information and Endogenous Entry

The characteristics of both entrepreneurs and venture capitalists are jointly determined by the set of real investment opportunities. An improvement in these opportunities has two effects: 1) it encourages marginal, low-quality entrepreneurs to pool with high-quality entrepreneurs, and 2) it induces the entry of venture capitalists that are less efficient at screening new investments. The market for venture capital financing is therefore plagued by a double-sided asymmetric information problem. The severity of both frictions severities is increasing but concave in market heat, and this is shown to imply that supply and demand are more elastic in cold markets. The paradigm makes predictions regarding the evolution of venture capital partnership quality.

Why Do We Miss Early Warning Signs of Economic Crises

This paper shows that agents underreact to rare and extreme signals. Agents observing these signals choose delay, hoping to condition their behavior on future actors (who may themselves also delay). This stalemate prevents society from recognizing the presence of rare states, even when the relevant signals are widely distributed across agents. Instead, rare signals accumulate privately (and redundantly) until they become overwhelming, after which they are all simultaneously revealed in a burst.

Manipulation and Fraud with Staged Financing

It has been argued that short-term financing has a drawback: managers must manipulate interim performance signals in order to keep funds flowing. In contrast, this paper finds that total (expected) manipulation across two rounds of short-term financing may be either greater than or lower than manipulation with long-term financing. Manipulation in the two rounds may either act as complements or substitutes, depending on whether one is looking forward or backward in time. Regulatory fraud prevention remedies have more power when directed at the first round behavior. Manipulation is nonmonotonic in both firm quality and leverage.

IPO Quantity Revisions

During IPO bookbuilding, issuers revise both the offer price and the number of shares (or equivalently, insider retention). These two percentage revisions are of comparable magnitude and are nearly uncorrelated. We show theoretically that revision to offer price and to retention capture information differently: offer prices increase with good news of any kind, whereas retention rises with good news about assets-in-place but declines with good news about growth options. Consistent with the model, retention is positively associated with the return of the Fama-French value portfolio and negatively with that of the growth portfolio during the bookbuilding period. Post-IPO abnormal capital expenditures are positively associated with price revision when retention revision is downward, but not when it is upward. These findings indicate that price and retention revisions can disentangle the nature of information received during the IPO process.