Business cycles,financial cycles and capital structure

We perform peridogram based cycle analysis of firm capital structure and find evidence that firms’ leverage is both persistent and cyclical. The cyclicality of leverage is supported by the trade-off, pecking order and market timing capital structure theories (Korajczyk and Levy in J Financ Econ 68:75–109, 2003; Bhamra et al. in Rev Financ Stud 23:645–703, 2010). Although market timing theory research supports persistence, previous literature dictates that the trade-off and pecking order theories may predict either persistent or mean reverting leverage. Our tests reject mean reversion in favor of persistent and cyclical leverage. We corroborate pecking order theory literature that predicts leverage is persistent. In these models, when firms’ investment spending is below earnings, leverage decreases. In addition, we examine whether firms change their capital structure as a result of business and financial cycles. Since financial cycles last longer than business cycles, financial cycles should have a long term effect on leverage. Our findings confirm the persistent leverage business cycle models that suggest firms change their capital structure due to financial and credit cycles (Jermann and Quadrini in Am Econ Rev 102:238–271, 2012; Azariadis et al. in Rev Econ Stud 83:1364–1405, 2016). We conclude that leverage is persistent due to the cyclicality of the financing decision.     

Short-term spot rate models with nonparametric deterministic drift

Most studies assume stationarity when testing continuous-time interest-rate models. However, consistent with Bierens [Bierens, H. (1997). Testing the unit root with drift hypothesis against nonlinear trend stationary, with an application to the US price level and interest rate. Journal of Econometrics, 81, 29–64; Bierens, H. (2000). Nonparametric nonlinear co-trending analysis, with an application to interest and inflation in the United States. Journal of Business and Economics Statistics, 18, 323–337], our nonparametric test results support nonlinear trend stationarity. To accommodate nonstationarity, we detrend the interest-rate series and re-examine a variety of continuous-time models. The goodness-of-fit improves significantly for those models with drift-induced mean reversion and worsens for those with high volatility elasticity. The inclusion of a nonparametric trend component in the drift significantly reduces the level effect on the interest-rate volatility. These results suggest that the misspecification of the constant elasticity model should be attributed to the nonlinear trend component of the short-term interest-rate process.     

Value of information analysis in healthcare: a review of principles and applications

Background:

Economic evaluations are increasingly utilized to inform decisions in healthcare; however, decisions remain uncertain when they are not based on adequate evidence. Value of information (VOI) analysis has been proposed as a systematic approach to measure decision uncertainty and assess whether there is sufficient evidence to support new technologies.

Scope:

The objective of this paper is to review the principles and applications of VOI analysis in healthcare. Relevant databases were systematically searched to identify VOI articles. The findings from the selected articles were summarized and narratively presented.

Findings:

Various VOI methods have been developed and applied to inform decision-making, optimally designing research studies and setting research priorities. However, the application of this approach in healthcare remains limited due to technical and policy challenges.

Conclusion:

There is a need to create more awareness about VOI analysis, simplify its current methods, and align them with the needs of decision-making organizations.     

A new look at the forward premium “puzzle”

We decompose the spot and forward rates into (permanent) nonlinear trend components and (transitory) stationary components. We examine the unbiasedness of the permanent (transitory) component of the forward rate in predicting the permanent (transitory) component of its corresponding future spot rate. The transitory component of the future spot rate under reacts to the transitory component of the forward rate. However, the permanent component of the forward rate is an unbiased predictor of the permanent component of the future spot rate. A robust nonlinear cotrending relation is also found between the forward and future spot rates and the hypothesis of the forward‐rate unbiasedness is sustained in the long run. These results suggest that the forward rate better explains the long‐term behavior of the future spot rate. Simulation analysis shows that if the transitory component of the forward rate fully predicts the transitory component of the future spot rate, the forward premium puzzle disappears. © 2010 Wiley Periodicals, Inc. Jrl Fut Mark 31:599–628, 2011     

An Extreme Value Approach to Test the Effect of Price Limits on Volatility

Many stock exchanges around the world enforcing daily price limits on the amount asset prices can change to prevent the market from overreacting and to reduce volatility. Price limits are artificial boundaries set by market regulators who restrict price changes of a stock to a pre-specified range during a trading day or a single trading session. The primary aim of price limit rules is to stabilize the markets during panic trading, to moderate vitality by repressing excessive speculation, and to allow stocks to be traded at prices close to their fair value. However, their impact on the market is a somewhat unresolved issue （Harris, 1998）. Using a methodology of comparing volatility based on the extreme value technique, the authors empirically investigate the impact of price limits on the volatility of the Stock Exchange of Thailand. The empirical results support price limits advocates, suggesting that price limits rules moderate stock price volatility.     

Disentangling Sentiment from Cyclicality in Firm Capital Structure

This study examines the relationship between capital structure choices and investor and managerial sentiment, finding that periods of positive sentiment are associated with reduced leverage within firms. We focus on the cyclicality of leverage using non-orthogonalized sentiment indices and find a strong negative relationship. Leverage, therefore, appears countercyclical, implying that the decision to take on debt is a consequence of either Admati et al.'s (2018) ratchet effect or a managerial attempt to time the market. Our findings lead us to question some fundamental capital structure theories, namely, trade-off (Kraus and Litzenberger, 1973), and Hackbarth's (2008) managerial traits theory. Instead, we favour the idea that leverage is a consequence of countercyclical market timing behaviour.