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This paper finds positive evidence of return predictability and investment gains for individual corporate bonds for an extended period from 1973 to 2017. Our sample consists of both public and private company bond observations. We have implemented multiple machine learning methods and designed a Fama-Macbeth-type predictive performance evaluation. In addition to robust predictability evidence, there are four main findings. First of all, we find the lagged corporate bond market return as the most important predictor, suggesting a short-term market reversal story. Second, this paper concludes that equity information is conditionally redundant for similar public and private company bond performance. Third, a model-forecast-implied long-short strategy delivers 1.48% monthly returns and 1.4% alpha during the last two decades, which substantially drops if we do not consider private company bonds. Finally, the return predictability is mainly due to the cash flow component instead of the discount rate component.

Large-scale shocks directly affect some firms and households and indirectly affect others through general equilibrium spillovers. In this paper, I describe how researchers can directly estimate spillovers using quasi-experimental or experimental variation. I then argue that spillover estimates suffer from distinct sources of mechanical bias that standard empirical tools cannot resolve. These biases are particularly relevant in finance and macroeconomics, where multiple spillover channels and nonlinear effects are common. I offer guidance on how to detect and overcome mechanical biases. An application and several examples highlight that the suggested methods are broadly relevant and can inform policy and multiplier calculations. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Purpose The purpose of this paper is to investigate how the timing behavior and the adjustment toward the target of capital structure interact with each other in the capital structure decisions. Past literature finds that both timing and targeting are significant in determining the leverage ratio which is inconsistent with any standalone framework. This study argues that the preference of the firm for timing behavior or targeting behavior depends on the cost of deviation from the target. Since the cost of deviation from the target is likely to be asymmetric between overleveraged and underleveraged firms, the direction of the deviation from the target leverage is expected to alter the preference toward timing or targeting in the capital structure decision. Design/methodology/approach This study used the GMM system estimators with the Malaysian data for the period of 1992-2009 to fit a standard partial adjustment model and to estimate the speed of adjustment (SOA) of capital structure. Findings This study finds that Malaysian firms, on average, adjust their leverage at a slow speed of 12.7 percent annually and this rate increased to 14.2 percent when the timing variable is accounted for. Moreover, the SOA is found to be significantly higher and the timing role is lower for overleveraged firms compared with underleveraged firms. Overleveraged firms seem to find less flexibility to time the market as more pressure is exerted on them to return to the target regardless the timing opportunities because of the higher costs of deviation from the target leverage. Underleveraged firms place lower priority to rebalance toward the target compared with overleveraged firms as the costs of being underleveraged are lower and hence, these firms have more flexibility to time the market. Research limitations/implications The findings of this study support that firms consider both targeting and timing in their financing decisions. No standalone theory can interpret the full spectrum of empirical results. The empirical work is based on partial adjustment model of leverage; however, this model has been criticized by inability to distinguish between active adjustment behavior and mechanical mean reversion. This is an avenue for future research. Originality/value This study investigates if targeting and timing behaviors are mutually exclusive as theoretically expected or they can coexist. A theoretical explanation and an empirical investigation support the conclusion that firms consider both targeting and timing in their financing decisions. This study provides evidence from Malaysian firms that are characterized by concentrated ownership structure and separation of cash flow rights and control rights of the firm due to pyramid ownership structure. Therefore, it provides evidence on how environmental characteristics may affect the capital structure determinants of the firm.

This paper specifies a simulated convertible bond arbitrage portfolio to characterise the risks in convertible bond arbitrage. For comparison the risk profile of convertible bond arbitrage hedge fund indices at both monthly and daily frequencies is also examined. Results indicate that convertible bond arbitrage is positively related to default and term structure risk factors. These risk factors are augmented with the simulated convertible bond arbitrage portfolio, mimicking a passive investment in convertible bond arbitrage, to assess the risk and return of individual hedge funds. We provide estimates of the performance of two hedge fund indices (an equally weighted and value weighted index) and a sample of convertible bond arbitrage hedge funds using a factor model methodology. Lagged and contemporaneous observations of the risk factors are specified, controlling for illiquidity in the securities held by funds. Our results cover two time periods. Initially we find evidence of abnormal risk adjusted returns in the individual hedge fund data and the equally weighted hedge fund index and no evidence of abnormal risk adjusted returns in the value weighted hedge fund index. When we examine performance during the credit crisis of 2007 and 2008 we find evidence of negative abnormal returns amongst individual hedge funds and the hedge fund indices.

This paper investigates whether the use of broader Divisia monetary aggregates improves money’s performance in forecasting economic activity within a time-varying parameter vector autoregressive (TVP-VAR) framework. We evaluate entire predictive densities from several alternative models of US output growth and inflation, each using eight different Divisia monetary aggregates. Using the broadest, M4 aggregate produces out-of-sample forecasts which consistently outperform those based on narrower measures of money, pooling of forecasts from several models, and a large-scale, 143-variable model. Our results show that TVP-VARs with Divisia M4 forecast economic activity more accurately than constant-parameter models with alternative or no measures of money.

This paper takes a revealed preference approach for set identifying the discount factor in the exponential discounting model. My methodology allows for measurement error in prices and full heterogeneity in preferences. Using longitudinal data from checkout scanners, I obtain bounds on the discount factor of every household in the panel. Furthermore, I find that bounds are correlated with demographic variables such as education and age.

Processes of polarization have been documented in several applications. Yet most existing theories focus on how herding behavior and convergence of opinions tend to occur in different contexts. In this paper we develop a model where agents correct their heterogeneous initial opinion by averaging the opinions of their neighbors. Our key contribution is to let the network arise endogenously. To do so, we micro–found how individuals optimally choose reference groups and we characterize a dynamic process where the network evolves along with individual opinions. Results show that there are always conditions on the strength of social influence preventing the network from being connected. This causes polarization in the long run. However, polarization can also arise during the transition to a consensus. We show how each of these cases is tied to a key network statistic, the initial diameter.

This paper explores firms’ bunching responses to training expenses deduction policy using microdata on Chinese manufacturing firms from 2004 to 2007. By exploiting a bunching method, we estimate elasticities of training intensity with respect to (one plus) the marginal tax rate at the kink points. We provide robust evidence that firms bunch at the kink points and gradually respond to threshold change. Taking the policy compliance into account, the estimated elasticity of fiscal incentive is −0.713 and −0.499 for DOEs and FOEs, respectively. Based on these estimates, we find that if all the training expenses are deductible, the training intensity will increase by 23.5% (DOEs) and 7.5% (FOEs). Heterogeneous analyses indicate that the wage-ratio-based policy may spur more bunching incentives among firms with higher wage bills. Finally, we rule out alternative explanations of tax evasion and relabeling.