Knowledge that Transforms

We develop a tractable dynamic model of an index option market maker with limited capital. We solve for the variance risk premium and option prices as a function of the asset dynamics and market maker option holdings and wealth. The market maker absorbs end users’ positive demand and requires a more negative variance risk premium when she incurs losses. We estimate the model using returns, options, and inventory and find that it performs well, especially during the financial crisis. The restrictions imposed by nested existing reduced-form stochastic-volatility models are strongly rejected in favor of the model with a market maker.

How does informed trading affect liquidity in limit order markets, where traders can choose between market orders (demanding liquidity) and limit orders (providing liquidity)? In a dynamic model, informed trading overall helps liquidity: A higher share of informed traders i) improves liquidity as proxied by the bid–ask spread and market resiliency, and ii) has no effect on the price impact of orders. The model generates other testable implications, and suggests new measures of informed trading.

The well-known weak empirical relationship between beta risk and the cost of equity (the beta anomaly) generates a simple tradeoff theory: As firms lever up, the overall cost of capital falls as leverage increases equity beta, but as debt becomes riskier the marginal benefit of increasing equity beta declines. As a simple theoretical framework predicts, we find that leverage is inversely related to asset beta, including upside asset beta, which is hard to explain by the traditional leverage tradeoff with financial distress that emphasizes downside risk. The results are robust to a variety of specification choices and control variables.

Intermediation in private equity involves illiquid investments, professional investors, and high information asymmetry. We use this unique setting to empirically evaluate theoretical predictions regarding intermediation. Using placement agents has become nearly ubiquitous, but agents are associated with significantly lower abnormal returns in venture and real estate funds, consistent with investor capture and influence peddling. However, returns are higher for buyout funds employing a top-tier agent and for first-time real estate and venture funds employing an agent, and are less volatile for agent-affiliated funds, consistent with a certification role. Our results suggest heterogeneous motives for intermediation in the private equity industry.

We study the implications of predictability on the optimal asset allocation of ambiguity-averse long-term investors and analyze the term structure of the multivariate risk–return trade-off considering parameter uncertainty. We calibrate the model to real returns of U.S. stocks, long-term bonds, cash, real estate, and gold using the term spread and the dividend–price ratio as additional predictive variables, and we show that over long horizons, the optimal asset allocation is significantly influenced by the covariance structure induced by estimation errors. The ambiguity-averse long-term investor optimally tilts his or her portfolio toward a seemingly inefficient portfolio, which shows maximum robustness against estimation errors.

We investigate the implications of providing loan officers with a nonlinear compensation structure that rewards loan volume and penalizes poor performance. Using a unique data set provided by a large international commercial bank, we examine the main activities that loan officers perform: loan prospecting, screening, and monitoring. We find that when loan officers are at risk of losing their bonuses, they increase prospecting and monitoring. We further show that loan officers adjust their behavior more toward the end of the month when bonus payments are approaching. These effects are more pronounced for loan officers with longer tenures at the bank.

In portfolio risk minimization, the inverse covariance matrix of returns is often unknown and has to be estimated in practice. Yet the eigenvalues of the sample covariance matrix are often overdispersed, leading to severe estimation errors in the inverse covariance matrix. To deal with this problem, we propose a general framework by shrinking the sample eigenvalues based on the Schatten norm. The proposed framework has the advantage of being computationally efficient as well as structure-free. The comparative studies show that our approach behaves reasonably well in terms of reducing out-of-sample portfolio risk and turnover.

We provide a theoretical rationale for dealer objections to ex post transparency in over-the-counter markets. Disclosure of the terms of a transaction conveys information possessed by the dealer about the asset quality and reduces the dealer’s rents when she disposes of the inventory in a second transaction. We show that costly signaling in a transparent market benefits investors through lower spreads and higher volume. Dealers may also gain from transparency despite lower spreads when potential gains from trade are small or adverse selection is high, because in those circumstances higher volume offsets smaller spreads for dealer profits.

Numerous papers have shown that developing economies are more volatile. We show that, despite greater aggregate and industry stability, performance and size of individual firms in developed countries are more volatile. In developing countries, market imperfections insulate incumbent firms from competition. Consistent with this, firms in developing countries have higher profit, higher market concentration, and less capital raising. Cross-country differences in operating risk and competition intensity are greater in industries that are dependent on external finance, where we expect higher impacts of capital-market imperfections. We show the inverse relation between aggregate and firm-level volatilities has important implications for international studies of cash holding.

In the capital structure literature, speed of adjustment (SOA) estimates are similar whether book or market leverage is used. This robustness is suspect, given the survey evidence that firms target their book leverage and the empirical evidence that they don’t issue securities to offset market leverage changes caused by stock price changes. We show that existing market SOA estimates are substantially upward biased due to the passive influence of stock price fluctuations. Controlling for this bias, the SOA estimate is 16% for book leverage and 10% for market leverage, implying that the trade-off theory is less important than previously thought.