When Does a Merger Create Value? Using Option Prices to Elicit Market Beliefs

I introduce and test a method to identify market expectations about value creation in mergers. Post‐announcement market prices reflect beliefs about both merged and standalone firm values, and the likelihood of either outcome. Stock prices alone do not contain sufficient information to identify these latent beliefs. By adding exchange‐traded stock option data, I deliver a clear decomposition of observed value change into two parts: 1) value creation and 2) new information about standalone value. Previous research has struggled to disentangle the two. This decomposition provides a strong and practical measure of the market's expectations about value creation in a merger.     

金融期货合约规模设计研究

金融期货合约规模的大小会对市场交易造成影响。过小的合约规模将增加交易者的交易成本，而过大的合约规模却会阻止一些小额交易者进入市场，使得成交量减小，买卖价差价值扩大，市场交易效率降低。合约规模是否合理可通过比例法和合约风险价值法来判断。我国开展金融期货，可采用先大合约规模、后小合约规模方式进行。     

Directors skill and financial reporting quality

Motivated by theoretical models in economics which show that there is matching between CEO skill and firm size, we introduce a new measure of director skill which is based on the aggregate size of firms on which the director serves as an independent director. We validate our measure by showing that it is positively associated with director experience, financial expertise, industry expertise and managerial experience. We then examine whether our average measure of skill across board members is positively associated with monitoring quality. Controlling for the endogenous relationships between board composition and financial reporting quality, we find a positive association between our board measure for skill and monitoring quality, and we show that directors have a causal impact on monitoring effort and outcomes. Furthermore, consistent with the enhanced monitoring provided by skilled directors, we document a positive association between the level of and changes in our measure and firm value.     

Towards a general theory of bond markets

The main purpose of the paper is to provide a mathematical background for the theory of bond markets similar to that available for stock markets. We suggest two constructions of stochastic integrals with respect to processes taking values in a space of continuous functions. Such integrals are used to define the evolution of the value of a portfolio of bonds corresponding to a trading strategy which is a measure-valued predictable process. The existence of an equivalent martingale measure is discussed and HJM-type conditions are derived for a jump-diffusion model. The question of market completeness is considered as a problem of the range of a certain integral operator. We introduce a concept of approximate market completeness and show that a market is approximately complete iff an equivalent martingale measure is unique.     

Active fund management: Global asset allocation funds

We examine the value of active fund management of global asset allocation funds. We use unique daily data and a modified Sharpe's [Sharpe, W., 1992. Asset allocation: management style and performance measurement. Journal of Portfolio Management 18, 7–19] Return-Based Style Analysis method to create a three-index model. We introduce an alternative method derived from Sharpe to calculate attribution returns that measure active fund management performance. Our results suggest that a sample of global asset allocation funds add value for investors. To determine the estimation ability of our model and the implications for estimated asset allocation decisions, we report historical and cross-sectional root mean square errors, which give positive indications of reliability.     

Value-at-risk vs. building block regulation in banking

Existing regulatory capital requirements are often criticized for only being loosely linked to the economic risk of the banks' assets. In view of the attempts of international regulators to introduce more risk sensitive capital requirements, we theoretically examine the effect of specific regulatory capital requirements on the risk-taking behavior of banks. More precisely, we develop a continuous time framework where the banks' choice of asset risk is endogenously determined. We compare regulation based on the Basel I building block approach to value-at-risk or ‘internal model’-based capital requirements with respect to risk taking behavior, deposit insurance liability, and shareholder value. The main findings are: (i) value-at-risk-based capital regulation creates a stronger incentive to reduce asset risk when banks are solvent, (ii) solvent banks that reduce their asset risk reduce the current value of the deposit insurance liability significantly, (iii) under value-at-risk regulation the risk reduction behavior of banks is less sensitive to changes in their investment opportunity set, and (iv) banks' equityholders can benefit from risk-based capital requirements.     

Productivity-based asset pricing: Theory and evidence

In a general real business cycle model, we derive a pricing kernel that involves only production function arguments. The productivity shock is the single factor and the capital stock relative to a productivity measure is the conditioning variable. The model compares favorably with the complementary consumption-based and market-based approaches and with the Fama-French three-factor model. A size premium arises from differences in unconditional sensitivities—small firms are more sensitive to productivity shocks—and a value premium from differences in conditional sensitivities to productivity shocks—growth firms are more sensitive to productivity shocks when the productivity risk premium is low.     

The Investment Performance of U.S. Equity Pension Fund Managers: An Empirical Investigation

This paper presents an empirical examination of the selectivity and market timing performance of a sample of U.S. equity pension fund managers. Regardless of the choice of benchmark portfolio or estimation model, the average selectivity measure is positive and the average timing measure is negative. However both selectivity and timing appear to be somewhat sensitive to the choice of a benchmark when managers are classified by investment style. Meta-analysis revealed some real variation around the mean values for each measure. The 80 percent probability intervals for selectivity revealed that the best managers produced substantial risk-adjusted excess returns. We also found a negative correlation between selectivity and timing, but we argue that the observed negative correlation in our data is largely an artifact of negatively correlated sampling errors for the two estimates.     

The impact of costly regulation on R&D investment levels and productivity

Prior research finds that risk-taking has declined after the Sarbanes-Oxley Act of 2002, consistent with the notion that SOX's corporate governance and internal control mandates diverted resources away from corporate risk-taking. We introduce to the accounting literature a new measure of R&D productivity, Research Quotient, to examine whether SOX affects R&D risk-taking and R&D productivity differently and whether the quality of the firm's governance and internal controls, pre-SOX, moderate these relations. While we find the relation between SOX and R&D risk-taking is sensitive to research design choices, we find a consistent positive relation between SOX and Research Quotient. Our evidence indicates that while firms may allocate fewer resources to R&D post-SOX, they concurrently manage their R&D investments more productively. Further, our results are robust to a difference-in-difference design and are stronger for firms with weaker governance pre-SOX.     

A NEOCLASSICAL MEASURE OF PROFIT: AN EXTENSION FOR UNCERTAINTY

This note extends the economic model used by Scapens (1978 and 1979) to develop a neoclassical measure of profit. A certainty equivalent formula in a multiperiod framework is used to introduce uncertainty into the analysis. It is demonstrated that the measure of economic profit developed in earlier papers is not crucially dependent upon the assumption of certainty.     

A model for interest rates with clustering effects

We propose a model for short-term rates driven by a self-exciting jump process to reproduce the clustering of shocks on the Euro overnight index average (EONIA). The key element of the model is the feedback effect between the absolute value of jumps and the intensity of their arrival process. In this setting, we obtain a closed-form solution for the characteristic function for interest rates and their integral. We introduce a class of equivalent measures under which the features of the process are preserved. We infer the prices of bonds and their dynamics under a risk-neutral measure. The question of derivatives pricing is developed under a forward measure, and a numerical algorithm is proposed to evaluate caplets and floorlets. The model is fitted to EONIA rates from 2004 to 2014 using a peaks-over-threshold procedure. From observation of swap curves over the same period, we filter the evolution of risk premiums for Brownian and jump components. Finally, we analyse the sensitivity of implied caplet volatility to parameters defining the level of self-excitation.     

Neighborhood Street Layout and Property Value: The Interaction of Accessibility and Land Use Mix

This paper evaluates how consumers value differences in neighborhood composition and street layout, factors not previously included in empirical studies of house value. Highly connected street patterns are important to New Urbanism. We use measures of neighborhood street connectivity and their interaction with other neighborhood attributes to evaluate how street layout affects property values. We employ two different methods of indexing street layout. Both methods show layout has a significant impact on price, but conclusions are sensitive to the method used. In pedestrian oriented neighborhoods, a more gridiron-like street pattern increases house value using one measure, but greater connectivity decreases house value using the other. In auto-oriented developments, a more gridiron-like street pattern reduces house value using either measure.

VaRSOM: A Tool to Monitor Markets' Stability Based on Value at Risk and Self-Organizing Maps

We introduce a variant of self-organizing maps (SOMs) termed VaRSOM that evaluates the similarity among inputs and nodes of the map employing value at risk (VaR). In this way we embed risk measurement within a machine-learning architecture, thus becoming particularly well-suited to analysing financial data. We tested the visualization capabilities and the explicative power of VaRSOM on data from the German Stock Exchange; we then evaluated the results in a comparative perspective, opposing the VaRSOM outcomes to those of SOM trained with more conventional similarity measures. The results lead to the conclusion that VaRSOM is a tool particularly well suited to visualize and exploit critical patterns in financial markets. This, in turn, opens perspectives for a general machine-learning framework sensitive to financial distress and contagion effects. Copyright © 2015 John Wiley & Sons, Ltd.     

No value in par: a history of the no par value debate in the United Kingdom

Proposals for shares of no par value have been considered several times this century, and there have been recommendations by government committees and unfulfilled government commitments to introduce them. This paper traces the history of the debate in the United Kingdom, from attempts by guarantee companies last century to issue shares without any value attached, up to a 1973 White Paper. It shows that failure to introduce no par value shares can be explained variously by ignorance, misunderstanding and political cowardice and highlights the way in which the issue became a significant factor in industrial relations during the 1950s.     

Modeling and measuring intraday overreaction of stock prices

We introduce a model for stock prices consisting of a fundamental price process and a news impact curve, which allows for either overreaction, underreaction, or correct response to changes of the fundamental value. We further develop statistics based on OHLC data, which separately measure upside and downside overreaction. The distribution of these statistics under the hypothesis of correct response and fundamental prices following Brownian motions is used to derive tests for upside and downside overreaction. We show that more realistic and frequently used fundamental price processes with correct response leave the distribution of the test statistics widely unaffected or lead to conservative tests. Empirical application to different stock markets provides strong evidence for intraday overreaction, particularly to bad news. The economic significance of the discrimination induced by the proposed statistics is further illustrated by analyzing the performance of a simple buy on bad news strategy.     

Exit as Governance: An Empirical Analysis

Recent theory posits a new governance channel available to blockholders: threat of exit. Threat of exit, as opposed to actual exit, is difficult to measure directly. However, a crucial property is that it is weaker when stock liquidity is lower and vice versa. We use natural experiments of financial crises and decimalization as exogenous shocks to stock liquidity. Firms with larger blockholdings experience greater declines (increases) in firm value during the crises (decimalization), particularly if the manager's wealth is sensitive to the stock price and thus to exit threats. Additional tests suggest exit threats are distinct from blockholder intervention.     

The market value of decomposed carbon emissions

We introduce the decomposition of carbon emissions into an expected and an unexpected component and analyze the association between these components and firm value. The expected component captures a firm's average carbon emissions inherent to its business model and operating environment. The unexpected component, meaning the firm-specific deviation from expected carbon emissions, reflects the management's effort and ability to implement carbon management and actively influence carbon emissions. For a sample of US firms operating in carbon-intensive industries, we estimate the expected component using a regression of carbon emissions on firm characteristics and industry. The residual of this regression represents the unexpected component. The results reveal that, on average, investors attach value to both components. While investors consider the expected component to be relevant regardless of assurance, they consider the unexpected component to be more relevant in the presence of assurance. The assurance alleviates credibility concerns about the information content of the unexpected component. Additionally, we confirm the nomological validity of our measure of the unexpected component, as it is negatively related to indicators of better carbon management systems.     

CEO Horizon,Optimal Pay Duration,and the Escalation of Short‐Termism

This paper studies optimal contracts when managers manipulate their performance measure at the expense of firm value. Optimal contracts defer compensation. The manager's incentives vest over time at an increasing rate, and compensation becomes very sensitive to short‐term performance. This generates an endogenous horizon problem whereby managers intensify performance manipulation in their final years in office. Contracts are designed to encourage effort while minimizing the adverse effects of manipulation. We characterize the optimal mix of short‐ and long‐term compensation along the manager's tenure, the optimal vesting period of incentive pay, and the dynamics of short‐termism over the CEO's tenure.     

Noise sensitivity of portfolio selection under various risk measures

We study the sensitivity to estimation error of portfolios optimized under various risk measures, including variance, absolute deviation, expected shortfall and maximal loss. We introduce a measure of portfolio sensitivity and test the various risk measures by considering simulated portfolios of varying sizes N and for different lengths T of the time series. We find that the effect of noise is very strong in all the investigated cases, asymptotically it only depends on the ratio N/T, and diverges (goes to infinity) at a critical value of N/T, that depends on the risk measure in question. This divergence is the manifestation of a phase transition, analogous to the algorithmic phase transitions recently discovered in a number of hard computational problems. The transition is accompanied by a number of critical phenomena, including the divergent sample to sample fluctuations of portfolio weights. While the optimization under variance and mean absolute deviation is always feasible below the critical value of N/T, expected shortfall and maximal loss display a probabilistic feasibility problem, in that they can become unbounded from below already for small values of the ratio N/T, and then no solution exists to the optimization problem under these risk measures. Although powerful filtering techniques exist for the mitigation of the above instability in the case of variance, our findings point to the necessity of developing similar filtering procedures adapted to the other risk measures where they are much less developed or non-existent. Another important message of this study is that the requirement of robustness (noise-tolerance) should be given special attention when considering the theoretical and practical criteria to be imposed on a risk measure.