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Explains the strengths and weaknesses of neural networks and uses them to analyse racial patterns in 1994 mortgage (conventional and FHA) data for the city of Atlanta (USA). Admits the difficulty of interpreting the results of neural network models but suggests that race does have an impact on lending patterns. Compares the results from a regression analysis and finds that as the percentage black increases in a neighbourhood FHA loans increase, conventional loans decreased and conventional loans denied increase; but these trends reverse when the black percentage rises further. Considers the practical reasons for the findings and concludes that race remains an important factor in the spatial distribution of lending.

Summarizes the main hypotheses used in previous research on dividend policy and reports a study of patterns in dividend payouts/growth using neural networks as a data mining technique. Discusses the properties of neural networks, recognizes that they are unsuitable for hypothesis testing and uses sensitivity analysis on 1992‐1997 data from 201 US firms. Presents the results, which do not outperform a previous model based on factor analysis, finds no significant nonlinear relationship in the data; but shows that dividend variability is sensitive to input variables, especially dividend growth.

The purpose of the current study is to examine audit committee reports of a sample of companies listed on the NYSE to determine the extent to which these reports contain voluntary disclosures that would indicate compliance with the relevant requirements of the Sarbanes‐Oxley Act (SOX) and the rules imposed by the SEC and NYSE.

Reviewed the contents of the audit committee reports from the 2004 proxy statements of a random sample of one hundred companies from those listed on the NYSE. These companies were drawn from a variety of industries and represented a wide cross‐section of the total market. The content of audit committee reports was examined to see if the committees voluntarily disclosed, within the body of the report, compliance with the requirements of SOX.

The results reveal that there is a significant diversity in the form and content of the audit committee reports published in the sample. It appears that while some audit committees treat their report as more than just a regulatory requirement and provide more voluntary disclosure, many others continue to provide only the minimum required information in their report.

The study focused on the actual body of the audit committee reports to examine disclosures about the compliance with SOX. It is likely that in many cases, the disclosures that did not appear within the audit committee reports may appear elsewhere in the proxy statement. Also, the study only examined audit committee reports of a sample of NYSE companies. Future research might include audit committee reports of those companies in the NASDAQ system.

Readers of audit committee reports might view more favorably the performance of those audit committees whose reports contain more extensive disclosures of the compliance with the SOX requirements.

This paper fulfills a need to know if audit committees are meeting the requirement of SOX and disclosing it. It warns readers that in order to obtain complete information as to the functioning of audit committees, they might need to conduct a complete search of the proxy statements and not only the section relating to the audit committee report.

Reviews the literature on economies of scale and scope in savings and loan institutions and uses 1980‐1987 US data to explore the cost effects of simultaneous production of outputs (mortgage loans, other loans and deposits), the impact of size and product‐specific economies of scale. Includes interest as a non‐operating cost and divides the sample into four groups based on asset values. Shows that total costs rose faster than assets, deposits or loans over the period; that there are product‐specific diseconomies of scale for deposits and loans‐ and that economies of scope were made by the larger firms following deregulation.

This study identifies the factors responsible for obtaining price premium on privately placed equity in a developing market.

We examine a unique data set of a special case of private placement of equity, Qualified Institutional Placement (QIP) in India purchased at a premium. The study analyzed 188 equity issues offered between September 2006 and December 2014. On average, we find that QIP issues received a price premium of 4.38%. The study employed binary probit and ordinary least square regression models to analyze the probability and magnitude of the premium.

The study attributes the price premium of QIP to certification effect through group affiliation, signaling through promoters' ownership and monitoring effect through existing institutional investors. These factors influence the probability of premium for QIP issues. However, group affiliation and institutional ownership do not significantly influence the magnitude of the premium.

The private placement of equity is usually offered at a discount. Our findings contribute to the existing literature by evaluating the premium obtained on private placement as a unique scenario in emerging market supported through certification hypothesis, monitoring hypothesis and signaling.

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.

With a sample of 22 banks, this study examines the significance of the news contents about the privatization of two public sector banks in India. New information does impact the stock markets. This study provides evidence on how the privatization of public sector banks impacted the returns of the Indian banking sector.

This study employs the standard event study methodology with the market model for estimating the normal returns.

The statistical results indicate that while the private sector banks experienced positive average abnormal returns on the event day, the cumulative effect of the announcement is negatively significant for both private and public sector banks. The statistical results also provide evidence of information leakage, with significant results before the announcement date. The shorter event windows analysis exhibits significant positive returns in the 5-days [−2, +2] window for the private sector banks and the entire sample, signifying a positive short-term impact on the private sector banks.

The event study literature captures the impacts of many events. However, to the best of our knowledge, the impacts of the privatization of the Indian public sector banks have never been examined using the event study methodology. Hence, this study anticipates being the first-ever study to fill this gap and extend the available literature in finance. In addition, although we provide Indian evidence, future studies may be oriented to capture cross-country impacts.

The purpose of this paper is to examine the performance parameters of WEDM to improve the productivity and material removal rate (MRR) with a high surface finish of high chromium-high carbon dies steel.

The experiments were performed on AGIE CUT 220 CNC WEDM. High chromium-high carbon dies steel (D3) was used in the form of a rectangular plate. The workpiece and the brass wire having diameter ɸ 0.25 mm had linked up with +ve and –ve polarity in the DC power source, respectively. De-ionized water having a conductivity level of 0.6 µs/cm was used as the dielectric medium. The dielectric fluid was flushed from the top and bottom nozzles and material was submerged in the dielectric.

The WEDM process parameters for D3 die steel had optimized by using Grey relational analysis method couples with Taguchi method. The optimum solution has been calculated for MRR, cutting speed (Cs), machining time and surface roughness (SR) (Ra value). A fuzzy logic model using Matlab was developed for the prediction of performance parameters, namely MRR, cutting speed (Cs), machining time (M/c time) and SR with respect to changes in input parameters.

The fuzzy model shows the 96.19 percent accuracy between the experimental values and the predicted values.

The optimized parameters by multi-parametric optimization method showed considerable improvement in the process and will facilitate the WEDM, tool and die industries, defense and aerospace industries to improve the productivity with the higher surface finish.

This manuscript represents valid work and the authors have no conflict of interests. The attained optimum outcomes had also been examined through a real experiment and established to be satisfactory.

This paper aims to investigate the productivity behavior of Indian banks in the presence of non-performing assets (NPAs) over the period 1999 to 2017. The study examines whether Indian banks withstand the shocks of the global financial crisis (GFC) of 2007–2009 and sustain their total factor productivity (TFP) levels in the post-crisis economic turbulent period or not.

The robust estimates of TFP and its components: efficiency change and technical change are obtained using the state-of-the-art and innovative sequential Malmquist-Luenberger productivity index (SMLPI) approach. The key advantages of this approach are that it explicitly allows the joint production of undesirable output (NPAs in our case) along with desirable inputs and outputs in the production process and precludes the possibility of spurious technical regress.

The empirical results of the study reveal that the Indian banking system has experienced a (−1) percent TFP regress, contributed solely by efficiency loss during the period under investigation. The GFC has slowed down the growth trajectory of TFP growth in the Indian banking industry. Among ownership groups, the effect of the GFC was pronounced on the public sector banks.

The practical implication drawn from the study is that the Indian banks have not been able to successfully transmit the use of installed technology in a way to generate early warning signals and mitigate the risk of defaults so as to maximize their productivity gains in the banking industry.

This study is perhaps the first one to understand the productivity dynamics of the Indian banks in response to both endogenous (i.e. NPA crisis) and exogenous (i.e. global financial and economic stress) crises. Moreover, the authors obtain the robust estimates of TFP growth of Indian banks by explicitly accounting for NPAs as an undesirable output and equity as a quasi-fixed input in the bank production process.