The growth companies puzzle: can growth opportunities measures predict firm growth?

While numerous empirical studies include proxies for growth opportunities in their analyses, there is limited evidence as to the validity of the various growth proxies used. Based on a sample of 1942 firm-years for listed UK companies over the 1990-2004 period, we assess the performance of eight growth opportunities measures. Our results show that while all the growth measures show some ability to predict growth in company sales, total assets, or equity, there are substantial differences between the various models. In particular, Tobin's Q performs poorly while dividend-based measures generally perform best. However, none of the measures has any success in predicting earnings per share growth, even when controlling for mean reversion and other time-series patterns in earnings. We term this the 'growth companies puzzle'. Growth companies do grow, but they do not grow in the key dimension (earnings) theory predicts. Whether the failure of 'growth companies' to deliver superior earnings growth is attributable to increased competition, poor investments, or behavioural biases, it is still a puzzle why growth companies on average fail to deliver superior earnings growth

Single-inhaler fluticasone furoate/umeclidinium/vilanterol versus fluticasone furoate/vilanterol plus umeclidinium using two inhalers for chronic obstructive pulmonary disease: A randomized non-inferiority study

Background: Single-inhaler fluticasone furoate/umeclidinium/vilanterol (FF/UMEC/VI) 100/62.5/25 μg has been shown to improve lung function and health status, and reduce exacerbations, versus budesonide/formoterol in patients with chronic obstructive pulmonary disease (COPD). We evaluated the non-inferiority of single-inhaler FF/UMEC/VI versus FF/VI + UMEC using two inhalers. Methods: Eligible patients with COPD (aged ≥40 years; ≥1 moderate/severe exacerbation in the 12 months before screening) were randomized (1:1; stratified by the number of long-acting bronchodilators [0, 1 or 2] per day during run-in) to receive 24-week FF/UMEC/VI 100/62.5/25 μg and placebo or FF/VI 100/25 μg + UMEC 62.5 μg; all treatments/placebo were delivered using the ELLIPTA inhaler once-daily in the morning. Primary endpoint: change from baseline in trough forced expiratory volume in 1 s (FEV1) at Week 24. The non-inferiority margin for the lower 95% confidence limit was set at − 50 mL. Results: A total of 1055 patients (844 [80%] of whom were enrolled on combination maintenance therapy) were randomized to receive FF/UMEC/VI (n = 527) or FF/VI + UMEC (n = 528). Mean change from baseline in trough FEV1 at Week 24 was 113 mL (95% CI 91, 135) for FF/UMEC/VI and 95 mL (95% CI 72, 117) for FF/VI + UMEC; the between-treatment difference of 18 mL (95% CI -13, 50) confirmed FF/UMEC/VI’s was considered non-inferior to FF/ VI + UMEC. At Week 24, the proportion of responders based on St George’s Respiratory Questionnaire Total score was 50% (FF/UMEC/VI) and 51% (FF/VI + UMEC); the proportion of responders based on the Transitional Dyspnea Index focal score was similar (56% both groups). A similar proportion of patients experienced a moderate/severe exacerbation in the FF/UMEC/VI (24%) and FF/VI + UMEC (27%) groups; the hazard ratio for time to first moderate/ severe exacerbation with FF/UMEC/VI versus FF/VI + UMEC was 0.87 (95% CI 0.68, 1.12). The incidence of adverse events was comparable in both groups (48%); the incidence of serious adverse events was 10% (FF/UMEC/VI) and 11% (FF/VI + UMEC). Conclusions: Single-inhaler triple therapy (FF/UMEC/VI) is non-inferior to two inhalers (FF/VI + UMEC) on trough FEV1 change from baseline at 24 weeks. Results were similar on all other measures of efficacy, health-related quality of life, and safety. Trial registration: GSK study CTT200812; ClinicalTrials.gov NCT02729051 (submitted 31 March 2016)

Who violates expectations when? How firms’ growth and dividend reputations affect investors’ reactions to acquisitions

Research summary: We investigate the role of a firm’s dividend and growth reputations in shaping investors’ interpretations of acquisitions as a negative or positive expectation violation. While our findings reveal that both an acquiring firm’s dividend and growth reputations trigger positive investor reactions, they also show that investors react negatively to an acquisition of a target firm with a strong growth reputation when the acquiring firm has a strong dividend reputation. We also find that investors are inclined to give managers “the benefit of the doubt” to the extent that an acquiring firm strategically frames an acquisition announcement in such a way that it provides assurance to investors that the acquisition is meant to exceed investors’ expectations about shareholder value creation. Managerial summary: We study why investors respond to some acquisitions positively and others negatively. We find that the way acquiring and target firms have created shareholder value in the past, and the information conveyed in the acquisition announcements are important determinants of investors’ differential reactions to acquisitions. Our findings show that while investors generally react positively to acquisitions by firms known for creating value either through dividends or growth, their reactions become negative when a firm known for value creation through dividends acquires a target known for value creation through growth. We further find that managers can favorably influence investor reactions by making it salient in the acquisition announcement how the acquisition is intended to exceed investors’ value creation expectations from the acquiring firm

Capital structure and its determinants in the United Kingdom – a decompositional analysis

Prior research on capital structure by Rajan and Zingales (1995) suggests that the level of gearing in UK companies is positively related to size and tangibility, and negatively correlated with profitability and the level of growth opportunities. However, as argued by Harris and Raviv (1991), 'The interpretation of results must be tempered by an awareness of the difficulties involved in measuring both leverage and the explanatory variables of interest'. In this study the focus is on the difficulties of measuring gearing, and the sensitivity of Rajan and Zingales' results to variations in gearing measures are tested. Based on an analysis of the capital structure of 822 UK companies, Rajan and Zingales' results are found to be highly definitional-dependent. The determinants of gearing appear to vary significantly, depending upon which component of debt is being analysed. In particular, significant differences are found in the determinants of long- and short-term forms of debt. Given that trade credit and equivalent, on average, accounts for more than 62% of total debt, the results are particularly sensitive to whether such debt is included in the gearing measure. It is argued, therefore, that analysis of capital structure is incomplete without a detailed examination of all forms of corporate debt

Funding issues in a major strategic project: A case of investment appraisal

This paper describes and allows interaction with the issues involved in a major investment decision. In the summer of 1997, UKH faced major decisions concerning the purchase and funding of new plant and equipment. The authors were given excellent access to the company and were able to document key steps in the decision process. The issues are set out in a case study format that allows the reader to retrace the analyses carried out within UKH. A number of tasks are suggested that should test, develop and enhance a range of analytical, social and negotiation skills. The case can be handled in a variety of ways and most of the suggested tasks can be undertaken or omitted depending on the pedagogical objectives of the course/ instructor

The effect of mergers on US bank risk in the short run and in the long run

We examine changes in risk following US bank mergers in the period 1981-2014. Short-run (two-year) increases in acquirer risk following mergers occur only in the first few mergers undertaken by the same acquirer, not in the later ones. They occur only in the stocks’ sensitivity to banking industry risk and not in bank-specific risk. The equity volatility of acquirers does not increase, but diversification benefits are entirely dissipated. Using a new approach to measure the long-run effect we find that these results persist, consistent with banks maintaining a constant level of total equity risk in the long run. We measure the loss of diversification of the US bank industry associated with mergers and find it to be 40% of the risk level in 1981. Almost all of this occurred prior to 2004. In addition, there has been a large increase in correlations between the largest banks, much of which has come from sources other than mergers

Cost of capital and valuation in the public and private sectors: tax, risk, and debt capacity

Cost of capital and valuation differ in the private and public sectors, because taxes are a cost to the private sector but are only a transfer to the private sector. We show how to transform the after-tax private sector cost of capital into its pre-tax equivalent, for comparison with the public sector cost of capital. We establish the existence of a tax induced wedge between these two costs of capital. The wedge introduces a preference on the part of the private sector for assets with rapid tax depreciation, high debt capacity, and low risk. We show that, in circumstances where an asset has identical public and private sector valuation in the absence of taxes, the tax induced difference in valuation is identical to the change in government tax receipts that results from having the asset owned by the private rather than the public sector. We provide some examples of distortions that result from failure to adjust for changes in tax revenues, and show how to effect such adjustment

A system dynamics model of capital structure policy for firm value maximization

The complexity surrounding the maximization of firm value agenda demands a comprehensive causal model that effectively embeds the intertwining relationships of the variables and the policies involved. System dynamics provides an appropriate methodology to model and simulate such complex relationships to facilitate decision making in a complex business environment. The objective of the study is to analyze the impact of capital structure policy, being a key managerial decision, on the firm value. For this purpose, the study develops a system dynamics‐based corporate planning model for an oil firm, including the operational as well as financial processes. Various scenarios and capital structure policies have been designed and simulated to identify the policy that helps in increasing the firm value. The results demonstrate that increase in debt percentage in capital structure mix increase the firm value.publishedVersio

Natural language processing for mimicking clinical trial recruitment in critical care: a semi-automated simulation based on the LeoPARDS trial

Clinical trials often fail to recruit an adequate number of appropriate patients. Identifying eligible trial participants is resource-intensive when relying on manual review of clinical notes, particularly in critical care settings where the time window is short. Automated review of electronic health records (EHR) may help, but much of the information is in free text rather than a computable form. We applied natural language processing (NLP) to free text EHR data using the CogStack platform to simulate recruitment into the LeoPARDS study, a clinical trial aiming to reduce organ dysfunction in septic shock. We applied an algorithm to identify eligible patients using a moving 1-hour time window, and compared patients identified by our approach with those actually screened and recruited for the trial, for the time period that data were available. We manually reviewed records of a random sample of patients identified by the algorithm but not screened in the original trial. Our method identified 376 patients, including 34 patients with EHR data available who were actually recruited to LeoPARDS in our centre. The sensitivity of CogStack for identifying patients screened was 90% (95% CI 85%, 93%). Of the 203 patients identified by both manual screening and CogStack, the index date matched in 95 (47%) and CogStack was earlier in 94 (47%). In conclusion, analysis of EHR data using NLP could effectively replicate recruitment in a critical care trial, and identify some eligible patients at an earlier stage, potentially improving trial recruitment if implemented in real time