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On 29 January 2001, Euronext LIFFE introduced single security futures contracts on a range of global companies. The purpose of this paper is to examine the impact that the introduction of these futures contracts had on the behaviour of opening and closing UK equity returns.

The paper models the price discovery process using the Amihud and Mendelson partial adjustment model which can be estimated using a Kalman filter.

Empirical results show that during the pre‐futures period both opening and closing returns under‐react to new information. After the introduction of futures contracts opening returns over‐react. A rise in the partial adjustment coefficient also takes place for closing returns but this is not large enough to cause over‐reaction.

This is the first study to examine the impact of a single security futures contract on the speed of spot market price discovery.

The purpose of this paper is to examine the optimal leverage ratio, speed of adjustment, and which factors contribute to achieving the target of selected telecom companies in a partial adjustment framework from 2008 to 2017. Further is to analyze the likelihood of bankruptcy of sample companies by Altman Z-Score model and to suggest which theory of capitals structure is better in explaining leverage strategies and judicious mix of debt and equity structure of the selected telecom companies.

This paper chooses a partial adjustment model and uses the generalized method of moments technique to identify the variables that influence the target leverage ratio and the factors that influence the speed at which the target leverage is adjusted. Second, the Altman Z-score model is used in this paper to research the financial status of telecom companies using financial instruments and techniques.

For Indian telecom firms, firm-specific variables such as profitability, NDTS and Z-score lead to greater debt adjustment towards optimal level target leverage. The paper also highlights new paradigms in the Indian telecom sector, stating that top market leaders such as Bharti Airtel, BSNL, Idea, Vodafone and R.com, among others, should focus on debt reduction and interest payments, as well as implement new strategies to solve the crisis and change financial policies.

It mainly focuses on firm-specific variables because the firm-specific variables affect the leverage framework. The country-specific variables are not taken into the study. These results may be unique to telecom companies due to some peculiarities existing in the telecom sector in India. Although other sectors, both national and international level, can be taken into consideration.

This paper has ramifications for corporate executives, investors and policymakers in India, for example, in terms of considering different transition costs while changing a telecom company’s financing decisions.

To the best of the authors’ knowledge, this is the first paper of its kind to look at both financial and econometric tools to assess financial performance using the Altman Z-Score model, as well as decide leverage strategies and the pace with which they can be adjusted to target leverage in the context of Indian telecom companies.

This paper aims to test the empirical validity of the dynamic trade-off theory in its symmetric and asymmetric versions in explaining the capital structure of a panel of publicly listed US industrial firms over the period from 2013 to 2019. It analyzes the existence of an adjustment of leverage toward its target level and whether the speed of this adjustment is influenced by the debt measure, the model specification or/and the fact that the actual debt ratio is higher or lower than its long-term target level.

This paper uses a quantitative research methodology using panel data analysis under the partial adjustment model and the error correction model using the generalized moment method in first differences and in systems to explore the dynamic nature of firms’ capital structure behavior.

The results show that the effects of the conventional determinants of leverage are globally consistent with the trade-off theory predictions. The dynamic versions confirm that firms exhibit leverage-targeting behavior. Although this speed of adjustment (SOA) depends on the debt and model specifications, it is around 60% on average. The estimated SOA is higher for the market leverage measure compared to the book leverage. The asymmetric adjustment model reveals that firms are more sensitive to reducing leverage than increasing it when they are away from their target; overleveraged firms exhibit approximately 5% faster adjustment than underleveraged firms when book leverage is used.

The originality of this research paper lies in its development and test of an asymmetric model to allow the leverage adjustment speed to vary depending on whether the firm’s debt ratio is above or below its target level and the methodological approach as well as the different model specifications used and the insights generated through the application of rigorous econometric techniques.

This paper aims to theorize that if risk affects costs and benefits of capital structure adjustments, then it should affect the speed at which firms adjust their leverage toward the target. To investigate this hypothesis, the author empirically examines the role of firm-specific and macroeconomic risk on firms’ capital structure adjustments.

The author augments the standard reduced-form partial adjustment model of capital structure by incorporating firm-specific and macroeconomic risk. The two-step robust system-generalized method of moments (GMM) estimator is used to estimate the proposed model for a large panel of UK manufacturing firms. An unbalanced annual panel data set covering the period from 1981 to 2009 is utilized for empirical analysis.

The estimated adjustment speeds indicate that both firm-specific risk and macroeconomic risk significantly affect the speed at which firms adjust their capital structure toward the target. In particular, the author shows that firms adjust their leverage faster toward the target when firm-specific risk is relatively low. This is perhaps because firms face lower costs of adjustment when both firm-specific and macroeconomic risks are low. Overall, the paper provides evidence that different levels and different types of risk exert asymmetric effects on capital structure adjustments.

The results presented in this paper suggest that managers have to carefully consider both the overall state of the economy and the solvency of their own business activities when making their financing decisions. The results also help in explaining why firms time equity and debt markets.

The paper significantly adds to our understanding of asymmetries in adjustment speed across firms and over times. The paper can also be useful to understand why firms would not aggressively act to offset the effects of changes in the market value of equity or gains and losses in earnings.

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.

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.

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.

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.

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.

Develops a habit‐persistence model which is based on the assumption that experience conditions present behaviour and expectations. Notes that the model combines the adaptive expectations hypothesis with the partial adjustment process. Concludes that accurate forecasts for declining regions are produced but the results for growing regions are not significant.

The purpose of this paper is to test the validity of dynamic tradeoff theory and argue that the speed of adjustment toward the target capital structure may vary depending primarily on some inherent firm characteristics.

The objective of this article is to study the impact of the corporate governance arrangements on the capital structure behavior taken by listed French firms. The author measures the corporate governance arrangements in three different ways to capture its influences on the capital structure and analyze how it affects a firm's rebalancing behavior in the presence of relevant control variables. Assuming that costs related to deviations from the target leverage are positively correlated with the duration of the deviation, the author finds that firms with a strong governance system adjust at a faster rate because the longer the deviation lasts, the greater the loss in firm value. In addition, firms with more efficient governance structures face lower adjustment costs.

The author measures corporate governance quality in different ways by using several proxies. The results make a major contribution to the literature and show that the quality of the governance system is an important factor in helping the company achieve fatly its target leverage. The authors produces further support for the initial finding by showing that the two extreme leverage deviation groups are dominated by firms with weak governance. The author also shows that the rebalancing speed is faster for firms with strong governance systems.

The paper proposes that a firm characterized by a strong governance system will display a shorter-duration deviation from the target capital structure and a higher adjustment level than a firm with weak governance. In other words, the author argues that the deviation from the target capital structure and the adjustment level are related to the quality of corporate governance. The results indicate that firms with a stronger governance structure are characterized by shorter-term deviations from the target. The author also finds that firms belonging to the two subsamples where leverage deviation is at extremely high or low levels are characterized by a weak governance system. The results corroborate the hypothesis on the speed of adjustment toward the desired target leverage. Furthermore, the author empirically proves that the adjustment level of firms with stronger governance is higher in both extreme leverage situations. This paper extends the existing literature on capital structure adjustment by introducing the effect of corporate governance.

Building upon the framework of the tradeoff model of capital structure and motivated by the equity market timing theory, we examine whether equity misvaluation is a source of adjustment “costs” that will affect a firm’s leverage adjustment speed toward target. We also investigate whether the quality of a firm’s long-term growth options will influence the decisions of managers to exploit the mispriced equity to converge to the optimum. Using a sample of listed Taiwanese firms during 1992–2014 and employing the market-to-book decomposition as developed by Rhodes-Kropf, Robinson, and Viswanathan (2005), we find that overleveraged and overvalued firms demonstrate faster adjustment speed than overleveraged but undervalued firms. Furthermore, controlling for the misvaluation status, high-growth firms converge to target faster than their low-growth counterparts. The effect of growth options on the relation between equity mispricing and adjustment speed does not mirror the effect of financing deficits. With the detailed financial information of the local companies across a rather long time series, this study provides incremental inputs to the literature of capital structure from the determinants of target leverage, the estimation of leverage adjustment speeds, to the identification of the sources of adjustment costs in an emerging market where institutional environment is strikingly different from the US.

This paper aims to investigate the non-homogeneity in the speed of adjustment (SoA) of the capital structure of manufacturing companies. It also attempts to study the key determinants that accelerate the speed of adjustment towards the target leverage level.

Using the dynamic panel fraction (DPF) estimator on the partial adjustment model, the study captures the heterogeneous SoA of 2,866 firms across eight prominent sectors of the Indian manufacturing industry from 2009 to 2020. To ensure robustness, the empirical inferences of DPF are cross-verified with the estimates of panel-corrected standard errors (PCSE).

The authors find a combination of the capital structure's slow, moderate and rapid adjustment speed along with the relevance of trade-off theory. Interestingly, the lowest and fastest SoA is recorded by the dwindling textile sector and expanding food and agro sector, respectively. Profitability, firm size, asset tangibility and non-debt tax shields are the key firm-specific parameters that impact the SoA towards the target.

Availing the rarely employed estimator ‘DPF’ and the objective of documenting diverse and non-uniform adjustment speeds across the Indian manufacturing sectors marks a novel addition to capital structure literature.

This paper aims to provide evidence that market efficiency varies greatly across individual stock, and across market exchanges.

Three approaches, partial adjustment model, Dimson beta model and variance ratio test, are used on a large sample of US stocks.

This paper finds prices are closer to random walk benchmarks (i.e. more efficient) for stocks with better liquidity provision, frequent trading, greater return volatility, higher prices, larger market capitalizations and smaller trade sizes. These findings suggest that liquidity stimulates arbitrage activity, which, in turn, enhances market efficiency. Market efficiency also varies with information environment. The results show that stocks with greater information-based trading exhibit higher level of efficiency. Finally, market structure influences market efficiency. New York Stock Exchange stocks achieve higher level of efficiency than NASDAQ stocks do. The empirical results are robust and not driven by differences in stock attributes between the two markets.

Overall, these results indicate that liquidity provision, stock attributes and market structure exert a significant impact on the realization of market efficiency.

In addition, this paper is also relevant to both stock exchanges facing increased competition and to market regulators.

Prior studies offer little evidence on the speed at which new information is impounded into the price. There is also limited evidence regarding how liquidity provision and market structure affect market efficiency. Using a transformation of the speed of price adjustment and other measurements as proxies for individual stock efficiency, this study may shed further lights on our understanding of market efficiency.