Managerial responses to incentives: Control of firm risk, derivative pricing implications, and outside wealth management

We model a firm’s value process controlled by a manager maximizing expected utility from restricted shares and employee stock options. The manager also controls allocation of his outside wealth, which allows partially hedging of his exposure to firm risk. Managerial control increases the expected time to exercise for his employee stock options. It also reduces the gap between his certainty equivalent and the firm’s Fair Value for his compensation, but that gap remains substantial. Managerial control also causes traded options to exhibit an implied volatility smile. With costly control the same basic patterns remain, but the manager’s risk-taking is dampened.     

Estimating the degree of operating efficiency gains from a potential bank merger and acquisition: A DEA bootstrapped approach

We propose a bootstrapped Data Envelopment Analysis (DEA)-based procedure to pre-calculate and pre-evaluate the short-run operating efficiency gains of a potential bank merger or acquisition (M&A). As an illustrative example, we apply our proposed procedure to investigate the degree of operating efficiency gains of 45 possible bank M&As in the Greek banking industry over the period from 2007 to 2011. The results reveal that a year before and a year after the initiation of the Greek fiscal crisis, the majority of the potential bank M&As under examination were unable to generate short-run operating efficiency gains. In addition, our results for 2011 indicate that the majority of bank M&As can lead to short-run operating efficiency gains. Finally, the empirical findings support the view that a merger or acquisition between efficient banks does not ensure an efficient bank M&A.     

Asymmetric information and liquidity constraints: A new test

Using a novel measure of the degree of information asymmetry across firms, this study shows that information-related financial market imperfections do matter for a firm’s access to external finance. Prior studies of the importance of liquidity constraints faced by nonfinancial firms have suffered from a glaring weakness. They have been based on a sample of publicly traded firms, omitting precisely those firms most likely to be liquidity constrained. Furthermore, they have tended to rely on indirect measures of the degree of information asymmetry, such as firm size. We overcome these limitations by focusing on the banking sector. Unlike the nonfinancial sector, the banking sector has balance sheet and income data available for all firms, whether or not they are publicly traded. This allows the use of a superior measure of the degree of information asymmetry across firms by distinguishing between publicly traded and non-publicly traded banks.     

Trading networks and liquidity provision

We study the profitability of traders in two fully electronic and highly liquid markets: the Dow and Standard & Poor?s 500 e-mini futures markets. Using unique information that identify counterparties to a transaction, we show and seek to explain the fact that the network pattern of trades captures the relations between behavior in the market and returns. Our approach includes a simple representation of how much a shock is amplified by the network and how widely it is transmitted. This representation provides a possible shorthand for understanding the consequences of a fat-finger trade, a withdrawing of liquidity, or other market shock.     

Credit lines as monitored liquidity insurance: Theory and evidence

We propose a theory of credit lines provided by banks to firms as a form of monitored liquidity insurance. Bank monitoring and resulting revocations help control illiquidity-seeking behavior of firms insured by credit lines. The cost of credit lines is thus greater for firms with high liquidity risk, which in turn are likely to use cash instead of credit lines. We test this implication for corporate liquidity management by identifying exogenous shocks to liquidity risk of firms in corporate bond and equity markets. Firms experiencing increases in liquidity risk move out of credit lines and into cash holdings.     

Asymmetric effect of basis on dynamic futures hedging: Empirical evidence from commodity markets

The dynamic minimum variance hedge ratios (MVHRs) have been commonly estimated using the Bivariate GARCH model that overlooks the basis effect on the time-varying variance–covariance of spot and futures returns. This paper proposes an alternative specification of the BGARCH model in which the effect is incorporated for estimating MVHRs. Empirical investigation in commodity markets suggests that the basis effect is asymmetric, i.e., the positive basis has greater impact than the negative basis on the variance and covariance structure. Both in-sample and out-of-sample comparisons of the MVHR performance reveal that the model with the asymmetric effect provides greater risk reduction than the conventional models, illustrating importance of the asymmetric effect when modeling the joint dynamics of spot and futures returns and hence estimating hedging strategies.     

Nonlinear portfolio selection using approximate parametric Value-at-Risk

As the skewed return distribution is a prominent feature in nonlinear portfolio selection problems which involve derivative assets with nonlinear payoff structures, Value-at-Risk (VaR) is particularly suitable to serve as a risk measure in nonlinear portfolio selection. Unfortunately, the nonlinear portfolio selection formulation using VaR risk measure is in general a computationally intractable optimization problem. We investigate in this paper nonlinear portfolio selection models using approximate parametric Value-at-Risk. More specifically, we use first-order and second-order approximations of VaR for constructing portfolio selection models, and show that the portfolio selection models based on Delta-only, Delta–Gamma-normal and worst-case Delta–Gamma VaR approximations can be reformulated as second-order cone programs, which are polynomially solvable using interior-point methods. Our simulation and empirical results suggest that the model using Delta–Gamma-normal VaR approximation performs the best in terms of a balance between approximation accuracy and computational efficiency.     

Using Tucker’s theorem of the alternative to simplify,review and expand discrete arbitrage theory

For valuing derivatives and other assets in securities and commodities markets, arbitrage pricing theory has been a major approach for decades. This paper derives fundamental arbitrage pricing results in finite dimensions in a simple unified framework using Tucker’s theorem of the alternative. Frictionless results, that is perfect market results, plus imperfect market results such as those with dividends, periodic interest payments, transaction costs, different interest rates for lending and borrowing, shorting costs and constrained short selling are presented. While the results are mostly known and appear in various places, our contribution is to present them in a coherent and comprehensive fashion with very simple proofs. The analysis yields a simple procedure to prove new results and some are presented for cases with imperfect market frictions.     

Explaining share price disparity with parameter uncertainty: Evidence from Chinese A- and H-shares

The price disparity between the A- and H-share markets for dual-listed firms in China is one of the most intriguing puzzles in the Mainland and Hong Kong financial markets. In this paper, we revisit this price disparity puzzle using the channel of parameter uncertainty. In the presence of information asymmetry and market segmentation, investors have different views on a firm’s asset volatility, and hence different valuations of the same reference firm. We estimate a structural model for equity pricing using a Bayesian approach, in which the uncertainty of investor model parameters is represented by the posterior standard deviation of the firm’s asset volatility. Our regression analysis shows that in addition to other market-based and macro factors, parameter uncertainty explains variations in price disparity.     

Pitfalls in backtesting Historical Simulation VaR models

Historical Simulation (HS) and its variant, the Filtered Historical Simulation (FHS), are the most popular Value-at-Risk forecast methods at commercial banks. These forecast methods are traditionally evaluated by means of the unconditional backtest. This paper formally shows that the unconditional backtest is always inconsistent for backtesting HS and FHS models, with a power function that can be even smaller than the nominal level in large samples. Our findings have fundamental implications in the determination of market risk capital requirements, and also explain Monte Carlo and empirical findings in previous studies. We also propose a data-driven weighted backtest with good power properties to evaluate HS and FHS forecasts. A Monte Carlo study and an empirical application with three US stocks confirm our theoretical findings. The empirical application shows that multiplication factors computed under the current regulatory framework are downward biased, as they inherit the inconsistency of the unconditional backtest.     

Price discovery and trade fragmentation in a multi-market environment: Evidence from the MTS system

This paper proposes new metrics for the process of price discovery on the main electronic trading platform for euro-denominated government securities. Analysing price data on daily transactions for 107 bonds over a period of 27 months, we find a greater degree of price leadership of the dominant market when our measures (as opposed to the traditional price discovery metrics) are used. We also present unambiguous evidence that a market’s contribution to price discovery is crucially affected by the level of trading activity. The implications of these empirical findings are discussed in the light of the debate about the possible restructuring of the regulatory framework for the Treasury bond market in Europe.     

Asset market linkages: Evidence from financial, commodity and real estate assets

We use a general Markov switching model to examine the relationships between returns over three different asset classes: financial assets (US stocks and Treasury bonds), commodities (oil and gold) and real estate assets (US Case-Shiller index). We confirm the existence of two distinct regimes: a “tranquil” regime with periods of economic expansion and a “crisis” regime with periods of economic decline. The tranquil regime is characterized by lower volatility and significantly positive stock returns. During these periods, there is also evidence of a flight from quality - from gold to stocks. By contrast, the crisis regime is characterized by higher volatility and sharply negative stock returns, along with evidence of contagion between stocks, oil and real estate. Furthermore, during these periods, there is strong evidence of a flight to quality - from stocks to Treasury bonds.     

An improved estimation method and empirical properties of the probability of informed trading

We report evidence that boundary solutions can cause a bias in the estimate of the probability of informed trading (PIN). We develop an algorithm to overcome this bias and use it to estimate PIN for nearly 80,000 stock-quarters between 1993 and 2004. We obtain two sets of PIN estimates by using the factorized likelihood functions in both [Easley et al., 2010] and [Lin and Ke, 2011], respectively. We find that the estimate based on the EHO factorization is systematically smaller than the estimate based on the LK factorization, meaning that there is a downward bias associated with the EHO factorization. In addition, we find that boundary solutions appear with a very high frequency when the LK factorization is used. Thus it is necessary to use the LK factorization together with the algorithm in this paper. At last, we document several interesting empirical properties of PIN.     

Regime switching correlation hedging

This paper investigates the hedging effectiveness of commodity futures when the correlations of spot and futures returns are subject to multi-state regime shifts. An independent switching dynamic conditional correlation GARCH (IS-DCC) which is free from the problems of path-dependency and recombining is applied to model multi-regime switching correlations. The results of hedging exercises indicate that state-dependent IS-DCC outperforms state-independent DCC GARCH and three-state IS-DCC exhibits superior hedging effectiveness, illustrating importance of modeling higher-state switching correlations for dynamic futures hedging.     

An analysis of the true notional bond system applied to the CBOT T-bond futures

The conversion factor system (CFS) is used in the determination of the invoice price of the Chicago Board of Trade Treasury-bond futures. As an alternative to the CFS, Oviedo [Oviedo, R.A., 2006. Improving the design of Treasury-Bond futures contracts. The Journal of Business 79, 1293–1315] proposed the True Notional Bond System (TNBS), and showed that it outperforms the CFS when interest rates are deterministic. The main purpose of this paper is to compare the effectiveness of the two systems in a stochastic environment. In order to do so, we price the CBOT T-bond futures as well as all its embedded delivery options under both the CFS and the TNBS. Our pricing procedure is an adaptation of the Dynamic Programming algorithm described in Ben-Abdallah et al. [Ben-Abdallah, R., Ben-Ameur, H., Breton, M., 2007. Pricing CBOT Treasury Bond futures. Les Cahiers du GERAD G-2006-77]. Numerical illustrations show that, in a stochastic framework, TNBS does not always outperform the CFS. However, as the long-term mean moves away from the level of the notional rate, the TNBS performs increasingly better than the CFS.     

Reforms in Thai bank governance: The aftermath of the Asian financial crisis

This paper provides an empirical analysis of Thailand's bank governance reforms after the 1997 Asian financial crisis and then examines the stock market's response. Unlike the pre-crisis period, we find that the bank sector returns (or return volatilities) have become more Granger causal to the overall stock market in the post-crisis period. Announcements of bank governance reforms are also generally associated with significant change in bank sector returns. This adds to the proposition that improved bank governance is related to improved bank performance as measured by their bank stock returns.     

The liquidity of bank assets and banking stability

This paper shows that an increased liquidity of bank assets, paradoxically, increases banking instability and the externalities associated with banking failures. This is because even though higher asset liquidity directly benefits stability by encouraging banks to reduce the risks on their balance sheets and by facilitating the liquidation of assets in a crisis, it also makes crises less costly for banks. As a result, banks have an incentive to take on an amount of new risk that more than offsets the positive direct impact on stability.     

Actual share repurchases,timing and liquidity

Research on the impact of open market share repurchases has been hindered by the lack of data available on actual share repurchases in many countries, including the US. Using a previously unused database containing detailed information on 36,848 repurchases made by 352 French firms, we show that corporate share repurchases have a significant adverse effect on liquidity as measured by bid–ask spread or depth. Our results also indicate that share repurchases largely reflect contrarian trading rather than managerial timing ability.     

Option-implied volatility factors and the cross-section of market risk premia

The main goal of this paper is to study the cross-sectional pricing of market volatility. The paper proposes that the market return, diffusion volatility, and jump volatility are fundamental factors that change the investors’ investment opportunity set. Based on estimates of diffusion and jump volatility factors using an enriched dataset including S&P 500 index returns, index options, and VIX, the paper finds negative market prices for volatility factors in the cross-section of stock returns. The findings are consistent with risk-based interpretations of value and size premia and indicate that the value effect is mainly related to the persistent diffusion volatility factor, whereas the size effect is associated with both the diffusion volatility factor and the jump volatility factor. The paper also finds that the use of market index data alone may yield counter-intuitive results.     

DETERMINANTS OF CAPITAL STRUCTURE IN BUSINESS START‐UPS: THE ROLE OF NONFINANCIAL STAKEHOLDER RELATIONSHIP COSTS

According to the finance literature, nonfinancial stakeholders (NFS), such as customers, suppliers, and employees, take into account their expected liquidation costs when dealing with a firm. In this framework, firms can influence their probability of liquidation by choosing an appropriate capital structure. Also, the literature suggests NFS bargaining power may affect firm financing decisions. In the current article we investigate these ideas for initial financing decisions by business start‐ups, where ex ante failure risk is high and NFS must decide whether to make relationship‐specific investments. We find that start‐ups imposing larger costs on their NFS following liquidation significantly reduce leverage. This effect is strengthened when suppliers have greater bargaining power. We also document a marginally negative effect of NFS liquidation costs on the proportion of bank loans. Finally, business start‐ups rely less on bank loans when customers and suppliers are in a powerful bargaining position.