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The purpose of this paper is to contribute to empirical evidence by recognizing the importance of stock markets in the financial system and consequently its causality to economic growth and vice versa.

The study used the autoregressive distribute lag model (ARDL) with bound testing procedures, the sample covered quarterly time-series data from 2001q1 to 2019q2 in Tanzania.

The results suggest that stock market development have both negative and positive causality for both short-run dynamics and long-run relationship with economic growth. Economic growth is found to only cause and relate negatively to liquidity both in the short-run and in the long-run. The results show predominantly a unidirectional causality flow from stock market development to economic growth and finds partial causality flow from economic growth to stock market development, as represented by stock market turnover which proxied liquidity.

The use of quarterly data to reflect more realistically the dynamics of the variables because yearly data may sometimes cover-up specific dynamics that may be useful for prediction and policy planning. The study uses indices to capture general aspects within the stock market against economic growth as an intuitive way to aggregate the stock market development effects.

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.

This paper examines the impact of political instability on the investors' behavior, measured by Google search queries, and on the dynamics of stock market returns.

First, by using the DCC-GARCH model, the authors examine the effect of investor sentiment on the Tunisian stock market return. Second, the authors employ the fully modified dynamic ordinary least square method (FMOL) to estimate the long-term relationship between investor sentiment and Tunisian stock market return. Finally, the authors use the wavelet coherence model to test the co-movement between investor sentiment measured by Google Trends and Tunisian stock market return.

Using the dynamic conditional correlation (DCC), the authors find that Google search queries index has the ability to reflect political events especially the Tunisian revolution. In addition, empirical results of fully modified ordinary least square (FMOLS) method reveal that Google search queries index has a slightly higher effect on Tunindex return after the Tunisian revolution than before this revolution. Furthermore, by employing wavelet coherence model, the authors find strong comovement between Google search queries index and return index during the period of the Tunisian revolution political instability. Moreover, in the frequency domain, strong coherence can be found in less than four months and in 16–32 months during the Tunisian revolution which show that the Google search queries measure was leading over Tunindex return. In fact, wavelet coherence analysis confirms the result of DCC that Google search queries index has the ability to detect the behavior of Tunisian investors especially during the period of political instability.

This study provides empirical evidence to portfolio managers that may use Google search queries index as a robust measure of investor's sentiment to select a suitable investment and to make an optimal investments decisions.

The important research question of how political instability affects stock market dynamics has been neglected by scholars. This paper attempts principally to fill this void by investigating the time-varying interactions between market returns, volatility and Google search based index, especially during Tunisian revolution.

The purpose of this study is to empirically weigh the evidence for financial depth, liquidity and efficiency role to economic growth, and test for the existence of cointegration between financial development variables and economic growth in Tanzania.

The study used the autoregressive distributed lag model with bound testing procedures. The sample covered yearly time-series data from 1980 to 2017, i.e. 38 years.

The results suggest that financial system depth is positively related to economic growth in the short run and that financial system liquidity and efficiency is strongly negatively associated with economic growth both in the short and long run. Further, it is found that financial development is cointegrated with economic growth. Thus, financial reforms and liberalisation have not fully brought the desired positive effects on economic growth yet.

The study uses principal component analysis to capture specific dimensions within the financial system as an intuitive way to aggregate financial development effects. Unlike studies that included several countries with heterogeneous characteristics, which are sometimes difficulty to homogenise, in recognition of countries’ unique experiences, this study uses data from Tanzania as a specific case. It documents pertinent pieces of evidence for a developing economy necessary for financial policy adjustments post the financial and economic liberalisation and reforms period. It nevertheless sheds light on financial policies for other comparable developing economies during and after both financial and economic liberalisation settings.

This paper aims to analyse trends and determinants of NPAs in India's banks. It has empirically examined the bank-specific determinants of NPAs.

An FE panel estimation of a sample of 44 banks was carried out for the post-crisis time period, from 2010 to 2020 to identify the bank-specific determinants of NPAs. The sample of 44 banks includes 20 PSBs, 19 private banks and 5 foreign banks. Separate FE estimation was also carried out to identify the drivers of NPAs in PSBs.

The determinant of NPAs during the post-crisis period suggests that faulty earning management and deterioration in loan quality have resulted in high NPAs in India's banks. The result is similar for PSBs as well.

The findings of the study suggest that the banks, especially the Public Sector Banks (PSBs) need to revisit their earning management strategies to maximise income and improve their loan quality in order to reduce the incidence of loan failure.

The paper contributes by empirically analysing the determinants of NPAs during the recent decade, between 2010 and 2020. Separate estimations have been carried out to understand whether the drivers of NPAs differ in the case of PSBs.

Young consumers are increasingly using online reviews and celebrity influence to make purchase decisions. The purpose of this study is to ascertain the influence of online customer reviews, celebrity influencer’s attractiveness, celebrity influencer’s credibility on female millennials’ purchase intention of beauty products.

To validate the research questions and hypotheses, data were obtained from young female consumers using an electronic self-administered survey questionnaire that was close ended. A total of 203 valid responses were obtained from which data were analysed by making use of structural equation modelling Mplus and the Statistical Package for the Social Sciences version 28.

The obtained results showed that the seven hypotheses of the study were positive. However, two hypotheses were negative, namely, celebrity influencer attractiveness did not have a significant influence on the attitude of consumers; and brand loyalty was not significantly correlating with young female consumers’ purchase intention of beauty products.

Given that millennials are known to be active users of social media and often consult online peer product reviews, marketers and practitioners of beauty industry should improve the effectiveness and usability of beauty influencers and online reviews to attract female millennial consumers.

This research contributes to understanding young female consumers’ attitudes towards purchasing beauty products, especially the combined influence of group influence (online reviews) and media influence (celebrity beauty influencers) on such attitudes.

The measure of companies' Innovation Performance is fundamental for enhancing the value and decision-making processes of firms. The purpose of this paper is to present a new measure of Innovation Performance, called Innovation Patent Index (IPI), which makes it possible to quantitatively summarize different aspects of firms' innovation.

In order to define the IPI, a secondary source, i.e. patent data, has been used. The five dimensions of IPI, i.e. efficiency, time, diversification, quality and internationalization have been defined both analyzing the literature and applying three different machine learning algorithms (regularized least squares, deep neural networks and decision trees), considering patent forward citations as a proxy of the innovation performance.

Results show that the IPI index is a very useful tool, simple to use and very promptly. In fact, it is possible to get important results without making time consuming analysis with primary sources. It is a tool that can be used by managers, businessmen, policymakers, organizations, patent experts and financiers to evaluate and plan future activities, to enhance the innovation capability, to find financing and to support and improve innovation.

Patent data are not widely used in all the sectors. Moreover, the pure number of forward citations is not the only forward looking indicator suggested by the literature.

The demand for a useable Innovation Performance tool, as well as the lack of tools able to grasp different aspects of the innovation, highlight the need to develop new instruments. In fact, although previous studies provide several measures of Innovation Performance, these are often difficult for managers to use, do not appreciate different aspects of the innovation and are not forward looking.

With the ongoing transformation of the microfinance sector, questions have been raised on the ability of microfinance institutions (MFIs) to perform financially well without compromising with their social objectives. The current study attempts to analyse the social and financial performance of Indian MFIs with an objective to find the kind of relationship between these two objectives.

The dynamic framework of simultaneous equations model is used to find the nature of the relationship which exists between social and financial performance of Indian MFIs.

The study finds that depth of outreach enables MFIs to achieve financial sustainability. On the other hand, financially strong MFI lend more as reflected by an increase in their average loan size.

Many MFIs still receive subsidies to support their operations. Ideally, adjustments should be made to remove the effect of such subsidies on their cost. However, due to non-availability of data, the study fails to make any adjustment for the subsidies.

The presence of a complementary relationship between social and financial performance in the Indian microfinance sector is quite encouraging for the policymakers during the current time when the sector is becoming less dependent on subsidies. However, the recent upsurge in the average loan size requires attention.

The findings suggest that MFIs can achieve financial sustainability while targeting poor clients. This indicates that MFIs can perform socially good along with their financial performance.

Such study is vital when the Indian microfinance sector is moving away from subsidies to become self-reliant and commercialised. Few studies have focused on this aspect of Indian microfinance sector.

This study aims to examine the impact of fiscal deficit, exchange rate and trade openness on current account deficit (CAD). The study tried to empirically investigate the ‘twin deficits hypothesis’ and ‘compensation hypothesis’ in the Indian context.

Autoregressive distributed lagARDL) bound test approach was used by taking annual time series data from 1978 to 2021. The estimates confirm a significant long-run and short-run relationship between dependent variables, i.e. CAD and independent variables such as the fiscal deficit, exchange rate and trade openness.

The results show that positive shocks of all explanatory variables significantly affect the CAD. CAD and fiscal deficit are significantly associated, as the coefficient of fiscal deficit is positive and significant. The study also found that exchange rate and trade openness significantly affect the CAD. The coefficients of exchange rate and trade openness are positive and significant. The findings show that an increase in CADs results from liberal trade policies that help domestic industries grow their trade and expansionary fiscal policy, leading to a higher fiscal deficit. The negative and significant error correction term suggests that short-run disequilibrium converges to long-run equilibrium at a speed of 19.2%. The findings validate the ‘twin deficits hypothesis’ and ‘compensation hypothesis’ in the Indian context.

It can be inferred from the study that liberal policy to promote economic growth and trade openness should be designed and promoted judiciously. An excessive liberalised approach may impact other macroeconomic variables such as current account balances. Integrating the domestic market with global markets poses a big challenge for countries like India that aspire to penetrate global markets. Furthermore, the Indian policy makers should rigorously work and promote the policies such as Fiscal Responsibility and Budget Management (FRBM) as reduction in fiscal deficits, trade imbalances will also be reduced.

This study contributes to the existing literature on ‘twin deficit’ and trade openness by giving new evidence on the trilemma between designing sustainable fiscal policy by spending wisely without imperilling the country's global presence and CAD.

Mucorales has been described to be widely distributed during the most recent COVID-19 pandemic, with a greater frequency of disease in India, particularly among those with immune deficiencies. This study aims to use computational tools to develop a vaccine.

The authors investigated at Mucorales proteins that had previously been associated to virulence factors. Recent research suggests that a vaccine based on high-level cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL) and B-cell lymphocyte (BCL) epitopes from diverse proteins might be developed. Furthermore, the vaccine assembly contains the targeted epitopes as well as PADRE peptides to induce an immune response. Computational approaches were used to analyze the immunological parameters used to build the suggested vaccine and validate its TLR-3 binding.

These studies show that the vaccination is capable of triggering a particular immune response. The authors offer a technique for developing and evaluating candidate vaccines using computational tools. To the best of their knowledge, this is the first immunoinformatic research of a prospective mucormycosis vaccine.

During this audit, a successful attempt was made to create a subunit MEV against black fungus. In the current study, MEV has been proposed as a suitable neutralizer candidate since it is immunogenic, secure, stable and interacts with human receptors. A stream study, on the other hand, is produced via a mixed vaccinosis approach. Following that, vaccinologists may perform more exploratory testing to evaluate whether the vaccine is effective.