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There is still an ongoing debate on the value relevance of capital structure and its determinants. Recently the issue has been explored in family firms after being explored in mature firms. This paper investigates the role of institutional investors and the firm's innovation activity in influencing the firm's decision and ability to acquire debt capital.

A large sample of 700 privately-held family firms in Italy from 2010 to 2019. Two analysis techniques are used: panel analysis and path analysis. The value of debt and the debt ratio are used as leverage measures. The value of patent (as a proxy for innovation) and institutional investor are the explanatory variables.

The results show that institutional investors have no relationship with financial leverage measures except when controlling for an interaction variable (Institutional investors × Lombardy region). The patent value is positively correlated with debt; however, the ratio patent-to-asset is negatively related to financial leverage indicating higher risk exposure. The nonlinearity test demonstrates a turning point when the relationship between patent value and debt inverts.

Firms should monitor their innovation activity since excessive innovation increases risk exposure and affects financing opportunities and value. The involvement of institutional investors does not always enhance value.

Existing literature focuses separately on family firm innovations and financial leverage as outcome variables, emphasizing the role of institutional investors in both fields by adopting agency theory and socioemotional wealth framework. In this study, the authors go further by merging both relationships, investigating the dynamics of the institutional-family firm innovation relationship in influencing the firm's capital structure. The authors contribute to the ongoing debate by providing original findings on capital structure, governance and innovation, supported by rigorous methods to enhance family firms' decision-making.

This study aims to measure impact of several firm-specific factors on alternative measures of leverage. The authors also aim to study impact of the subprime crisis on such associations.

The authors utilized an unbalanced panel data of 973 firm-year observations on 47 UK listed non-financial firms for the years 1990–2019. Book-based and market-based long-term and total leverage measures have been used as explained variables. The explanatory variables are profitability, size, two measures of growth, asset tangibility, non-debt tax shields, firm age and product uniqueness. Fixed effect and random effect models with clustered robust standard errors have been utilized for data analysis. To find the effect of subprime crisis, original dataset was split to create pre-crisis and post-crisis datasets.

The authors find that profitability significantly reduces leverage while firms having more tangible assets use significantly more debt in capital structure. Firm size and non-debt tax shield have statistically insignificant positive impact on leverage. Having more unique products reduces use of external debt, albeit insignificantly. Growth, when measured as market-to-book ratio, has inconsistent impact, whereas capital expenditure insignificantly reduces leverage. Age is found to be an insignificant predictor of leverage. After the subprime crisis, firms started relying more on internal fund instead of external debt, more particularly short-term debt. Having more collateral is gradually becoming more important for availing external debt.

Data limitations restrict generalization of the findings.

This is one of the pioneering attempts to show how subprime crisis altered the theoretical domain of capital structure research in the UK.

In a first of its kind, this paper tries to explore the long-run relationship between investors' sentiment and selected industries' returns over the period January 2010 to December 2021.

The paper uses 23 market and macroeconomic proxies to measure investor sentiment. Principal component analysis has been used to create sentiment sub-indices that represent investor sentiment. The autoregressive distributed lag (ARDL) model and other sophisticated econometric techniques such as the unit root test, the cumulative sum (CUSUM) stability test, regression, etc. have been used to achieve the objectives of the study.

The authors find that there is a significant relationship between sentiment sub-indices and industries' returns over the period of study. Market and economic variables, market ratios, advance-decline ratio, high-low index, price-to-book value ratio and liquidity in the economy are some of the significant sub-indices explaining industries' returns.

The study has relevant implications for retail investors, policy-makers and other decision-makers in the Indian stock market. Results are helpful for the investor in improving their decision-making and identifying those sentiment sub-indices and the variables therein that are relevant in explaining the return of a particular industry.

The study contributes to the existing literature by exploring the relationship between sentiment and industries' returns in the Indian stock market and by identifying relevant sentiment sub-indices. Also, the study supports the investors' irrationality, which arises due to a plethora of behavioral biases as enshrined in classical finance.

The main aim of the paper is to examine the small and medium-sized enterprises’ (SMEs) capital structure determinants in Central and Eastern Europe (CEE) (Poland, Czechia, Slovakia, Hungary, Bulgaria and Romania).

The authors used panel models to analyze financial data of 15,253 companies operating in the years 2014–2017.

The authors confirmed the dominant role of firm-specific factors. Industry and country variables explain only 4% of debt variability of the surveyed companies. The direction of influence of the diagnosed firm-specific factors is consistent with the pecking order theory. About one-fourth of SMEs in CEE hold a stock of debt capacity. It negatively affects the share of debt in the capital. The authors did not confirm the influence of the systematic industry business risk.

The limitations of the study are (1) the inclusion of only six CEE countries in the sample; (2) the exclusion of microenterprises from the sample; (3) the capital structure relationships are observed following the applications of static panel; (4) the endogeneity issue has not been addressed in the model.

This study shows that business-friendly institutional environment is an important factor influencing the indebtedness of companies. It increases the leverage and, consequently, the return on equity, especially in CEE countries.

SME analyses in CEE countries are not as frequent as for other regions. Despite the classical determinants of the SMEs' capital structure, the authors have included debt capacity and systematic industry business risk in this study.

The objective of the paper is to investigate the relationship between financial risk and the value of the company. In this context, the study is to revisit the trade-off theory of capital structure in the Indian context.

After applying outlier, the study considered 389 nonfinancial companies from BSE500 from 2001 to 2018 collected from the Capitaline database. The statistical package E-views 10 has been utilized for analysis. To understand the nature of the data the descriptive analysis, correlation analysis, normality, unit root, multi-collinearity and Heteroskedasticity were conducted. The Panel Estimated Generalised Least Square with cross-section weight was found suitable for analysis due to the existence of cross-correlated residuals. Further, the study has classified the levels of financial risk to determine the relationship of different levels of financial risk with corporate value.

It was found that the financial risk and corporate value had a significant negative relation during the period of study. On class interval-wise financial risk analysis, it was found that the debt-equity (DE) of around 1:1 may be considered optimal. Below that threshold limit, the DE affects value positively above which the ratio affects the value negatively.

The paper makes an attempt to determine the optimal financial risk at the corporate level in the Indian context.

This paper aims to explore the relevant literature available regarding the use of repetitive transcranial magnetic stimulation (rTMS) as a mode of treatment for obsessive-compulsive disorder (OCD); to evaluate the evidence to support the use of rTMS as a treatment option for OCD.

The authors electronically conducted data search in five research databases (MEDLINE, CINAHL, Psych INFO, SCOPUS and EMBASE) using all identified keywords and index terms across all the databases to identify empirical studies and randomized controlled trials. The authors included articles published with randomized control designs, which aimed at the treatment of OCD with rTMS. Only full-text published articles written in English were reviewed. Review articles on treatment for conditions other than OCD were excluded. The Covidence software was used to manage and streamline the review.

Despite the inconsistencies in the published literature, the application of rTMS over the supplementary motor area and the orbitofrontal cortex has proven to be promising in efficacy and tolerability compared with other target regions such as the prefrontal cortex for the treatment of OCD. Despite the diversity in terms of the outcomes and clinical variability of the studies under review, rTMS appears to be a promising treatment intervention for OCD.

The authors of this scoping review acknowledge several limitations. First, the search strategy considered only studies published in English and the results are up to date as the last day of the electronic data search of December 10, 2020. Though every effort was made to identify all relevant studies for the purposes of this review per the eligibility criteria, the authors still may have missed some relevant studies, especially those published in other languages.

This review brought to bare the varying literature on the application of rTMS and what is considered gaps in the knowledge in this area in an attempt to evaluate and provide information on the potential therapeutic effects of rTMS for OCD.

Analysts expect reduced bank earnings as a result of the impact of the increase in bad loans. Banks have strategically created high provision coverage ratios allocating large funds for possible deterioration in asset quality. Given the expected faster growth and recovery in the bank lending sector, investors have always been interested in banking stocks, despite the waves of non-performing assets (NPAs) and recessionary influences. Historical references reiterate that the banking stocks have been better performers in their returns compared to the capital markets.

The study aims to examine the impact of key accounting variables on the stock prices of Indian banks in the panel data framework.

The current study explores the impact of accounting variables on the market prices of shares. After the study, it may be concluded that earning per share (EPS), return on equity (ROE), capital adequacy ratio (CAR) and net interest margin (NIM) have an incremental impact on the prices of banking stocks, and the current ratio (CR) and NPAs have a detrimental impact on them.

Studying their impact on stock prices is the most convenient fundamental analysis that could be conducted on the stock prices of the banks.

To provide insights into the association of the accounting and regulatory variables there is a severe limitation in the quantity of the literature available. This study has attempted to build a relationship between the accounting and regulatory variables and the stock prices of banking stocks, to help investors with some reliable methods to estimate the stock prices in the future.