Liquidity risk,price impacts and the replication problem

We extend a linear version of the liquidity risk model of Çetin et al. (Finance Stoch. 8:311–341, 2004) to allow for price impacts. We show that the impact of a market order on prices depends on the size of the transaction and the level of liquidity. We obtain a simple characterization of self-financing trading strategies and a sufficient condition for no arbitrage. We consider a stochastic volatility model in which the volatility is partly correlated with the liquidity process and show that, with the use of variance swaps, contingent claims whose payoffs depend on the value of the asset can be approximately replicated in this setting. The replicating costs of such payoffs are obtained from the solutions of BSDEs with quadratic growth, and analytical properties of these solutions are investigated.     

Pricing exotic options using MSL-MC

Today, better numerical approximations are required for multi-dimensional SDEs to improve on the poor performance of the standard Monte Carlo pricing method. With this aim in mind, this paper presents a method (MSL-MC) to price exotic options using multi-dimensional SDEs (e.g. stochastic volatility models). Usually, it is the weak convergence property of numerical discretizations that is most important, because, in financial applications, one is mostly concerned with the accurate estimation of expected payoffs. However, in the recently developed Multilevel Monte Carlo path simulation method (ML-MC), the strong convergence property plays a crucial role. We present a modification to the ML-MC algorithm that can be used to achieve better savings. To illustrate these, various examples of exotic options are given using a wide variety of payoffs, stochastic volatility models and the new Multischeme Multilevel Monte Carlo method (MSL-MC). For standard payoffs, both European and Digital options are presented. Examples are also given for complex payoffs, such as combinations of European options (Butterfly Spread, Strip and Strap options). Finally, for path-dependent payoffs, both Asian and Variance Swap options are demonstrated. This research shows how the use of stochastic volatility models and the θ scheme can improve the convergence of the MSL-MC so that the computational cost to achieve an accuracy of O(ε) is reduced from O(ε⁻³) to O(ε⁻²) for a payoff under global and non-global Lipschitz conditions.     

Communication networks,externalities, and the price of information

Information goods (or information for short) play an essential role in modern economies. We consider a setup where information has some idiosyncratic value for each consumer, exerts externalities, and can be freely replicated and transmitted in a communication network. Prices paid for information are determined via the (asymmetric) Nash Bargaining Solution with endogenous disagreement points. This decentralized approach leads to unique prices and payoffs in any exogenous network. We use these payoffs to find connection structures that emerge under different externality regimes in pre‐trade network formation stage. An application to citation graphs results in eigenvector‐like measures of intellectual influence.     

Higher Order Expectations in Asset Pricing

We examine formally Keynes' idea that higher order beliefs can drive a wedge between an asset price and its fundamental value based on expected future payoffs. We call this the higher order wedge, which depends on the difference between higher and first order expectations of future payoffs. We analyze the determinants of this wedge and its impact on the equilibrium price in the context of a dynamic noisy rational expectations model. We show that the wedge reduces asset price volatility and disconnects the price from the present value of future payoffs. The impact of the higher order wedge on the equilibrium price can be quantitatively large.     

Disagreement,tastes, and asset prices

Standard asset pricing models assume that: (i) there is complete agreement among investors about probability distributions of future payoffs on assets; and (ii) investors choose asset holdings based solely on anticipated payoffs; that is, investment assets are not also consumption goods. Both assumptions are unrealistic. We provide a simple framework for studying how disagreement and tastes for assets as consumption goods can affect asset prices.     

The Conditional Performance of REIT Stock Repurchases

This paper uses a conditional performance measure to test whether real estate investment trust (REIT) managers announcing stock repurchases have private information about their firms' prospects. We use stock price to condition for public information and measure the managers' implied private information by the covariance between repurchase size and subsequent stock payoffs (or operating performance). Results show that managers have private information but mostly with respect to long-term as opposed to near-term payoffs. We also find that repurchase size is positively related to a stock's idiosyncratic return volatility, perhaps because noisy stocks deviate farther from fundamental value, offering informed managers larger profit potential. JEL Classification G12 G14 G35     

Why Do Firms Issue Equity?

We develop and test a new theory of security issuance that is consistent with the puzzling stylized fact that firms issue equity when their stock prices are high. The theory also generates new predictions. Our theory predicts that managers use equity to finance projects when they believe that investors' views about project payoffs are likely to be aligned with theirs, thus maximizing the likelihood of agreement with investors. Otherwise, they use debt. We find strong empirical support for our theory and document its incremental explanatory power over other security‐issuance theories such as market timing and time‐varying adverse selection.     

Market Cycles and the Performance of Relative Strength Strategies

We study the effect of market cycles on both medium‐run and long‐run relative strength trading strategies. We find that payoffs for both strategies tend to be relatively higher within a market state (rising or falling markets), but substantially lower over transitions between states. Since shorter duration strategies are relatively less likely to include market transitions, our results help reconcile the puzzling fact that medium‐run strategies are profitable, but long‐run strategies are not. We find that the market's cross‐sectional return dispersion: 1) tends to be higher around market transitions, and 2) is negatively related to the subsequent payoffs for both medium‐run and long‐run strategies.     

An Evaluation of the Corporate Takeover Model Using Neural Networks

Neural networks have been found to be promising in financial prediction tasks like bankruptcy and loan defaults. Their use in the capital markets is relatively new, although they have been used with some success in picking undervalued stocks. Accurate prediction of corporate takeover targets results in high financial payoffs. Researchers have used statistical procedures like logistic regression with little success in predicting corporate takeover targets. We use neural networks that are capable of producing complex mapping functions to predict mergers. We develop several neural network models carefully controlling for overfitting. Our results indicate that although neural networks map the data very well, they do not predict merger targets significantly better than logistic regression. This strongly suggests that the financial models used to predict mergers are inadequate. Firms should approach the development of merger prediction models cautiously and identify other factors that are more likely to predict mergers. Attempts to apply better analysis techniques to existing models will most likely produce similar results.     

Persistence and Reversal in Herd Behavior: Theory and Application to the Decision to Go Public

We model rational herd behavior when the underlying value changesover time, with payoffs that are either dependent or independentof the underlying value. We show that herding does not lastforever and is not monotone in signal quality. High correlationamong agents' actions does not necessarily imply herding. Thissuggests alternative empirical methods are needed to detectherding. The model has many applications, including the IPOdecision in which payoffs are state dependent. The model impliesthat the decision to go public is more likely associated withherding than the decision to delay an IPO.     

Market Created Risk

We develop a multiperiod rational expectations model of securities market equilibrium in which equilibrium prices may move between periods even though it is common knowledge that no new information has arrived about ultimate security payoffs. This happens because investors know they have imperfect information about the endowments of other investors and this knowledge affects their probability beliefs about the prices that will prevail at the intermediate trading date. These beliefs are reflected in the equilibrium at the initial trading date when investors focus on the probabilities of intermediate capital gains and losses, rather than ultimate payoffs.     

The joint impact of accountability and transparency on managers’ reporting choices and owners’ reaction to those choices

We report the results of an experiment designed to investigate the fundamental conflict of interest between managers and owners in a financial reporting setting. In our setting, owners seek accurate reports of financial performance whereas managers have incentives to distort performance reports in a self-serving fashion. Regulatory responses to such conflicts often call for improved disclosure, including more accountability and transparency (e.g., Sarbanes-Oxley Act and Dodd-Frank Act). We use the term accountability to imply answerability—wherein managers are required to reconcile the difference between reported and actual performance. We predict and find that when managers’ incentives are transparently disclosed, accountability does not rein in managers’ opportunistic reporting. By comparison, when managers’ incentives are less transparently disclosed (opaque), accountability dampens managers’ propensity to misreport. However, this reduction in opportunistic reporting due to accountability comes about because managers offset higher reporting bias in compensation periods with lower reporting bias in other periods. Therefore, not only are the benefits of accountability restricted to the setting where managers’ incentives are opaque, but the reduced reporting bias might arise due to window-dressing. Although managers seem to care enough about accountability to engage in window-dressing, financial incentives seem to dominate accountability, at least in our setting. We also find that managers’ payoffs are higher when their incentives are opaque, but owners’ payoffs are invariant regardless of whether incentives are transparent or opaque. Our analyses suggest that owners may be relying on accountability to curb opportunistic reporting by managers—a reliance that may be misplaced. Our findings have implications for regulatory responses aimed at addressing conflicts of interest.     

Financial Forecasting,Risk and Valuation: Accounting for the Future

Valuation involves forecasting payoffs and discounting expected payoffs for risk. Forecasting is often seen as the province of the statistician, risk determination the province of asset pricing. This paper elaborates on the idea that financial forecasting, risk determination and valuation are a matter of accounting. Accounting not only provides information to forecast payoffs but also specifies the payoffs to be forecasted. Further, accounting determines the transition from the present to the future and thus implicitly the evolutionary parameters that a statistician might estimate for forecasting. Accounting also bears on risk determination in the way it handles uncertainty. Accordingly, accounting is involved in both the numerator and the denominator of a valuation model. Indeed, a valuation model is a model of accounting for the future, and the effectiveness of a valuation model rides on the accounting principles employed.     

A model of biased intermediation

We study situations in which consumers rely on a biased intermediary's advice when choosing among sellers. We introduce the notion that sellers' and consumers' payoffs can be congruent or conflicting, and show that this has important implications for the effects of bias. Under congruence, the firm benefiting from bias has an incentive to offer a better deal than its rival and consumers can be better‐off than under no bias. Under conflict, the favored firm offers lower utility, and bias harms consumers. We study various policies for dealing with bias and show that their efficacy also depends on whether the payoffs exhibit congruence or conflict.     

Moral Hazard and Information Sharing: A Model of Financial Information Gathering Agencies

We propose a theory of information gathering agencies in a world of informational asymmetries and moral hazard. In a setting in which true firm values are certified by screening agents whose payoffs depend on noisy ex post monitors of information quality, the formation of information gathering agencies (groups of screening agents) is justified on two grounds. First, it enables screening agents to diversify their risky payoffs. Second, it allows information sharing. The first effect itself is insufficient despite the risk aversion of screening agents and the stochastic independence of the monitors used to compensate them.     

Information control in the hold‐up problem

We study the use of information control to mitigate hold‐up risks. We identify a distinction between asymmetric information that creates an ex ante investment incentive and asymmetric information that causes ex post inefficiency, which then allows ex post inefficiency to be eliminated without compromising the ex ante investment incentive. We characterize the properties of the optimal information structure and the payoffs and welfare achievable with information control in the presence of hold‐up risks.     

Social learning and health plan choice

I use data from the University of California to empirically examine the role of social learning in employees' choices of health plans. The basic empirical strategy starts with the observation that if social learning is important, health plan selections should appear to be correlated across employees within the same department. Estimates of discrete choice models in which individuals' perceived payoffs are influenced by coworkers' decisions reveal a significant (but not dominant) social effect. The strength of the effect depends on factors such as the department's size or the employee's demographic distance from her coworkers. The estimated effects are present even when the model allows for unobserved, department-specific heterogeneity in employee preferences, so the results cannot be explained away by unobservable characteristics that are common to employees of the same department.     

HOW FIRMS MANAGE RISK: THE OPTIMAL MIX OF LINEAR AND NON-LINEAR DERIVATIVES

This paper provides guidance on how corporations should choose the optimal mix of "linear" and "non-linear" derivatives. Linear derivatives are products such as futures, forwards, and swaps, whose payoffs vary in linear fashion with changes in the un-derlying asset price or reference rate. Non-linear derivatives are contracts with option-like payoffs, including caps, floors, and swaptions.
A company's optimal hedging position should generally consist of linear contracts because of their effective-ness in smoothing corporate cash flows. But as the firm's business (quantity) risk increases, its use of linear contracts will decline due to costs associated with overhedging. At the same time, there will be a shift towards the use of non-linear contracts. The degree of substitution of non-linear for linear in-struments will depend on the relation-ship between the quantities to be hedged and market prices. A negative relationship will tend to exacerbate the substitution effect while a positive re-lationship will dampen the effect. An empirical examination of corporate derivative holdings provides support for all of the major hypotheses.     

Equity home bias and corporate disclosure

I show that more comprehensive corporate disclosure reduces investors’ uncertainty about domestic companies’ payoffs at no cost, thereby decreasing investors’ equity home bias toward a country. Since investors should base their investment decisions on valid and easily interpretable company information only, more comprehensive disclosure will reduce the home bias only if domestic securities law is sufficiently stratified and domestic companies use international accounting standards. Using panel data for 38 countries from 2003 to 2008 I find that more comprehensive disclosure reduces investors’ home bias, though significantly only for countries that sufficiently enforce their securities law and implement international accounting standards.     

Sensitivity estimates for portfolio credit derivatives using Monte Carlo

Portfolio credit derivatives are contracts that are tied to an underlying portfolio of defaultable reference assets and have payoffs that depend on the default times of these assets. The hedging of credit derivatives involves the calculation of the sensitivity of the contract value with respect to changes in the credit spreads of the underlying assets, or, more generally, with respect to parameters of the default-time distributions. We derive and analyze Monte Carlo estimators of these sensitivities. The payoff of a credit derivative is often discontinuous in the underlying default times, and this complicates the accurate estimation of sensitivities. Discontinuities introduced by changes in one default time can be smoothed by taking conditional expectations given all other default times. We use this to derive estimators and to give conditions under which they are unbiased. We also give conditions under which an alternative likelihood ratio method estimator is unbiased. We illustrate the application and verification of these conditions and estimators in the particular case of the multifactor Gaussian copula model, but the methods are more generally applicable.