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This article aims to examine the pro-poor innovation diffusion models adopted by university intermediate organizations and their stakeholders at the bottom of the pyramid.

The study employed a qualitative case study approach. Between April 2021 and May 2022, 60 semi-structured interviews were conducted online and telephonically.

The study identified various models for promoting the diffusion of pro-poor innovations through university intermediary organizations (non-corporate organizations) and their stakeholders at the bottom of the pyramid. The study also identifies the priority stakeholders and classifies them based on the attributes they might possess.

Other developing economies can consider adopting the diffusion model outlined in our study as a potential working hypothesis to improve the productivity and quality of life for rural poor employed in the informal sector. Such studies advance our understanding of possible organizational methods and processes for diffusing innovation at the bottom of the pyramid.

The study brings a new perspective on how non-corporate organizations, such as university intermediaries, are involved in pro-poor innovation diffusion at the bottom of the pyramid. Additionally, the study brings valuable insights into how stakeholders’ theory can be utilized towards pro-poor innovation diffusion at the bottom of the pyramid.

This paper investigates if investors consider legal insider trading data while making investment decisions. If any investment decision is based on insider transactions, then it will result in abnormal stock characteristics. The purpose of this paper is to investigate if insider trading affects stock characteristics like price, return and volume. The paper further investigates the effect on stock characteristics after the trade of different types of insiders and the relationship between abnormal return and abnormal volume.

The study uses the event study method to measure the abnormal price, return and volume. Two-stage least square regression is used to investigate the relationship between abnormal return and abnormal volume.

The insider trades affect price, return and volume. The results are identical for both buy and sell transactions. The trades of different types of insiders have diverse effects on stock characteristics. The trades of substantial shareholders give rise to the highest abnormal price and return, whereas the promoters' trades result in the highest abnormal volume. No relationship is detected between abnormal return and volume.

A novel method to calculate the abnormal price is proposed. The effect of trading of all types of insiders on stock characteristics is analyzed. The relationship between abnormal return and abnormal volume, after an insider trade, is investigated.

The purpose of this paper is to empirically estimate industry beta in Indian stock market with three alternative models and compare the accuracy of forecasting error to find the most suitable model for time-varying beta estimation.

The paper applies the standard regression model, Kalman filter model, other statistical approaches and secondary material.

The paper finds that the existence of dynamic beta in Indian market. The results also indicate systematic risk or beta of Indian industries is susceptible to the global economic effect. Finally, the Kalman filter generates the lower forecasting error compared to the other method for almost all the industries.

The accurate estimation of beta which is a measure of systematic risk helps investors to make investment decision easier. The implication of this result is important for finance practitioners such as portfolio managers, investment advisors and security analysts. This study will help to determine the country risk with respect to the global index and analyze the global financial market integration effect on India.

This paper reliably estimate industry portfolio beta for India. The time-varying beta is estimated using Kalman filter method which is rarely applied in Indian literature. This paper contributes by extending the knowledge of existing literature by introducing a new data set with Indian data which is not affected by the “data snooping” bias. This study will also help to determine the country risk with respect to the global index and analyze the global financial market integration effect on India.