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In this paper, we explore the problem of establishing a network among the stocks of a market at high frequency level and give an application to program trading. Our work uses high frequency data from the National Stock Exchange, India, for the year 2014. To begin, we analyse the spectrum of the correlation matrix to establish the presence of linear relations amongst the stock returns. A comparison of correlations with pairwise mutual information shows the further existence of non-linear relations which are not captured by correlation. We also see that the non-linear relations are more pronounced at the high frequency level in comparison to the daily returns used in earlier work. We provide two applications of this approach. First, we construct minimal spanning trees for the stock network based on mutual information and study their topology. The year 2014 saw the conduct of general elections in India and the data allows us to explore their impact on aspects of the network, such as the scale-free property and sectorial clusters. Second, having established the presence of non-linear relations, we would like to be able to exploit them. Previous authors have suggested that peripheral stocks in the network would make good proxies for the Markowitz portfolio but with a much smaller number of stocks. We show that peripheral stocks selected using mutual information perform significantly better than ones selected using correlation. [ABSTRACT FROM AUTHOR]

In this paper, we model the bus networks of six major Indian cities as graphs in L-space, and evaluate their various statistical properties. While airline and railway networks have been extensively studied, a comprehensive study on the structure and growth of bus networks is lacking. In India, where bus transport plays an important role in day-to-day commutation, it is of significant interest to analyze its topological structure and answer basic questions on its evolution, growth, robustness and resiliency. Although the common feature of small-world property is observed, our analysis reveals a wide spectrum of network topologies arising due to significant variation in the degree-distribution patterns in the networks. We also observe that these networks although, robust and resilient to random attacks are particularly degree-sensitive. Unlike real-world networks, such as Internet, WWW and airline, that are virtual, bus networks are physically constrained. Our findings therefore, throw light on the evolution of such geographically and constrained networks that will help us in designing more efficient bus networks in the future. [ABSTRACT FROM AUTHOR]

Background: As population health and well-being are influenced by multiple factors that cut across sectoral boundaries, an intersectoral approach that acknowledges and leverages the multiple determinants, actors and sectors at play is increasingly seen as critical for achieving meaningful and lasting improvements. In this study, we utilize social network analysis (SNA) to characterize the intersectoral collaboration between the organizations working on maternal & child health (MCH) and water & sanitation (WASH) before and immediately after the implementation of HCL Foundation (HCLF)-funded HCL Samuday Project (2015–2017) in a rural block of Uttar Pradesh state, India. While SNA has been used to examine public health issues, few have used it monitor stakeholder relationships, intervene, improve and facilitate project implementation involving intersectoral partnerships, particularly in the context of a low-and middle-income countries. Method: An organization-level SNA was conducted with 31 key informants from 24 organizations working on MCH and/or WASH in Kachhauna, Uttar Pradesh, India. Data were collected using face-to-face, semi-structured interviews between June and September 2017. Density, centrality and homophily were calculated to describe the network and a qualitative analysis was also conducted to identify the strengths and weaknesses of collaboration between organizations working on MCH and WASH. Results: Overall, our findings showed that the network of organizations working on MCH and WASH in Kachhauna grew in number since the implementation of Samuday. HCLF rapidly achieved centrality, thus positioning the organization to serve as a gatekeeper of information and enabling it to play a coordinator role within the network. Direct collaboration between other organizations working on MCH and WASH was low at both time points. Interviews with key informants indicated widespread interest in increasing interorganizational interactions and engagement throughout the network. Conclusion: This study demonstrates the feasibility and practical application of SNA for projects like Samuday that involve intersectoral collaboration. It also provides lessons about the use of SNA with organizations as the unit of analysis and in the context of rural India, including challenges, practical considerations, and limitations. [ABSTRACT FROM AUTHOR]