Grading Initial Public Offerings (IPOs) in Indias Capital Markets A Globally Unique Concept

<div align=justify>IPO grading assesses the fundamentals of the Initial Public Offerings (IPOs) and is reflected on a five-point point scale (1-5) with a higher score indicating stronger fundamentals of the IPO issuing firm. SEBI (India capital market regulator) introduced the IPO grading as a mandatory requirement for all IPOs, and the requirement seems to have been borne by the fact that, in India, where institutions are less developed and retail participation in IPOs is significant, quality signal represented by an IPO grade yields discernible benefits to the market. We note that while SEBI and the rating agencies advocate the benefit of the IPO grade, not everyone in the industry and academia is convinced of the grades merits. To analyze the efficacy of IPO grading, we conducted regression analysis study of a total of 63 IPOs that have been graded. Through this study, we find that securities with higher IPO grades tend to exhibit under-pricing to a lesser extent. We also find that, with higher IPO grades, the subscription rate of the IPOs improves across all class of investors, including retail investors. We also find that IPO grades are inversely related to the short-term liquidity of the IPOs, i.e. at least in the short term, higher graded IPOs dont exhibit high turnover ratio. We further find that the IPO grade fails to explain with any significance the subsequent market performance of the issues in terms of capital gains.</div>

Distributed Machine Learning Approach to Fast Frequency Response-based Inertia Estimation in Low Inertia Grids

Recent updates to the IEEE 1547-2018 standard allow active participation of distributed energy resources (DERs) in power grid services with the goal of increased grid reliability and resiliency. With the rapid growth of DERs towards a low inertia converter-dominated grid, the DERs can provide fast frequency response (FFR) services that can quickly counteract the change in system frequency through inertial support. However, in low voltage grids, frequency and voltage face dynamics coupling due to a high resistance to reactance ratio and cannot be controlled separately as in the bulk electric grid. Due to the coupling effect, the control of one parameter also affects the dynamics of the other parameter. A part of this work highlights the role of DERs to provide grid ancillary services underscoring the challenges of combined voltage and frequency control in low voltage grids. Increasing penetration of renewable energy sources (RES) also decreases the power system inertia, there by affecting the stability of bulk grid. The stochastic nature of RES makes the power system inertia a time-varying quantity. Furthermore, converter-dominated grids have different dynamics compared to conventional grids and therefore estimates of the inertia constant using existing dynamic power system models are unsuitable. This work proposes a novel inertia estimation technique based on convolutional neural networks (CNN) that use local frequency measurements. The model uses a non-intrusive excitation signal to perturb the system and measure frequency using a phase-locked loop. The estimated inertia constants, have significant accuracy for the training, validation, and testing sets. Additionally, the proposed approach can be applied over traditional inertia estimation methods that do not incorporate the dynamic impact of renewable energy sources. The frequency response of power systems changes drastically when multi-area power systems with interconnected tie-lines are considered. Furthermore, higher penetration of RES increases the stochasticity in interconnected power systems. Hence, it is important to estimate the multi-area parameters ensuring communication and coordination between each of the areas. A robust and secure client-server-based distributed machine learning framework is used to estimate power system inertia in a two-area system. The proposed approach can be efficiently optimized to increase the training performance. It is important to analyze the performance of a trained machine learning model in a real-world scenario with unknown dynamics. A pre-trained CNN is tested on a system with model predictive controller (MPC)-based virtual inertia (VI) unit. Results show that the frequency and inertial response of conventional synchronous generators-based system differs drastically as compared to the system with non-synchronous generator-based VI support

Master of Science

thesisThis study evaluates the structural integrity of spent nuclear fuel (SNF) rods under impacts caused by accidents during transportation. SNF rods consist of uranium dioxide fuel pellets encapsulated in a zircaloy cladding tube. The linear and nonlinear buckling analysis of a typical 532 mm (21 in.) long fuel rod segment is performed in finite element software Abaqus, under static loading conditions. Initially, the analysis is carried out for a vertical end drop, including an initial imperfection of 0.1 mm in the model. Thereafter, impact drops are evaluated with the fuel rod at different orientations. The results indicate that pellets significantly stiffen the fuel rod when its orientation is nearly vertical. However, the pellet contribution decreases significantly as the orientation angle at impact increases. The effect of pellet-cladding interaction (PCI) on the buckling performance of the SNF rods is also studied. The results indicate that the PCI composite action is partially retained even for relatively large rod impact angles with respect to the vertical direction. The inelastic buckling controls the buckling behavior of the fuel rods with lower slenderness ratio. Therefore, the effect of degradation mechanisms of the irradiated clad after long-term storage are considered on the buckling behavior of 252 mm (10 in.) and 140 mm (5.5 in.) fuel rod segments. The study concludes that long-term degradation only affects the 140 mm simply supported fuel rod segment, length equivalent to the end cantilever segment. However, this segment is not expected to fail because its buckling capacity is one order of magnitude higher than that of a typical 532 mm segment

Renewable Energy and Other Strategies for Mitigating the Energy Crisis in Nepal

The overarching aim of this research is to carefully review Nepal’s energy scenario from the technical and socio-economic perspective in order to determine the optimal near-term as well as long-term strategies to overcome the energy crisis. Renewable energy sources are pivotal to this research due to the abundant availability of these resources in Nepal. The long-term energy supply and demand forecast for Nepal over the next 30 years was obtained in Long-Range Energy Planning (LEAP) software. Other quantitative results were obtained using software packages, including PVsyst, Meteo, and HOMER. In many other cases, energy data collected from open literature,government and regulator reports were analysed. There are also several case studies considered in the thesis. The PV rooftop energy systems for Nepalese town and rural households can minimise the energy trade deficit with neighbouring India, enhance energy security, and improve local employment opportunities as well as improve utilisation of the local resources. In particular, a 3kW PV rooftop system was designed and simulated in MATLAB/Simulink, and the corresponding PV and IV curves were obtained, including analysing the effects of environmental temperature and solar irradiation. The design was followed by techno-economic feasibility, assuming typical households inthe Kathmandu valley. The study outcome is that the PV system for a residential building in Kathmandu is economically feasible, and it can provide nearly 6,000 kWh/year of energy. The potential energy efficiency improvements in the cement industry were studied using data collected directly at one of the major cement plants in Nepal. The cement production processes are very energy-intensive, and they have not changed for years. Since the energy costs in Nepal are abnormally high, they represent over half of the cement production costs. It creates substantial pressure to conserve energy and materials while reducing the carbon footprint. Other important factors that must be considered apart from energy issues are production efficiency and sustainability, and how to exploit innovations and encourage investments. The chaotic energy situation in Nepal is exacerbated by rather significant electricity distribution losses and frequent cases of electricity theft. These two issues are significant contributors to a widening gap between energy supply and demand. iv. Other such issues include overpriced and delayed hydropower projects, insufficient and outdated infrastructure, lack of energy conservation, deficient energy management, inadequately low efficiency of equipment, unsustainable energy pricing strategies, indecisive energy market regulations, reliance on energy imports, and especially inadequate exploitation of vast amounts of renewable energy resources. All these factors are also adversely affecting the geopolitical, environmental, and socioeconomic situation in Nepal. The developments in the energy sector in Nepal are also discussed in light of the relevant energy policies which have been adopted by the government over the past two decades. The results presented in the thesis can be used by the government regulators and energy policy planners, and possibly also by the public and private energy companies. It should be noted that the findings and observations in the thesis are also applicable to other countries with a similar development status and geography as Nepal

Alternative Masculinities in South Asia

Summaries Masculinity and its impact on gender relations and the institutionalisation of power exercised by men have been critically commented upon on by activists and academics working on issues related to gender relations. The failure of the early ‘developmentalist’ approach to population control programmes, the increase in violence against women, and the HIV/AIDS pandemic has pushed to the fore, amongst others issue, the question of male sexuality and male culture. The Save the Children (UK) South and Central Asia Regional Office and UNICEF Regional Office for South Asia is proposing to make a series of films on masculinities, which deconstructs and reconstructs patriarchy within South Asia. The film?making project involves the production of films on masculinities by male film?makers from India, Nepal, Bangladesh and Pakistan, within their own countries. This film?making project, is intended to increase and extend the impact of SCF's and UNICEF's country programmes in tackling the problems of increasing violence against girls. The intent is to try and explore the broad patterns of masculinities without ignoring the particularities of each category of men (in terms of class, caste, sexual preference, etc.). The way men negotiate between duties and dreams, dominance and love, anxiety and pleasure, power and insecurity are the kernels around which the stories are to be constructed

Measurement Of The Cross Section Of Top Quark Pairs Produced In Association With A Photon In Lepton + Jets Events At √s = 13 Tev With Full Runii Cms Data

The inclusive production cross section of top quark pairs in association with a photon is measured in proton-proton collisions at the LHC with 13 TeV energy using the full RunII data collected by CMS in 2016, 2017, and 2018 with a total corresponding integrated luminosity of 137 fb −1 . The relative fraction of ttγ events normalized to inclusive tt production is measured. The cross section measurement provides important information about the electromagnetic coupling of the standard model top quark and is sensitive to physics beyond the standard model. The analysis is carried out in the in semileptonic decay channel with a well isolated high P T lepton (electron and muon), at least four jets out of which at least one must be b-tagged, and an isolated photon. Photons may be emitted from initial state radiation, top quarks, and decay products of top quarks. A simultaneous likelihood fit of control regions with the signal region is done to constraint the backgrounds and to extract the ttγ cross section. The measurement of the ratio of ttγ to tt is 0.02055 ± 0.00099 (syst.) ± 0.00099 (stat.) in the e + jets channel, 0.02156 ± 0.00068 (syst.) ± 0.00068 (stat.) in µ + jets channel, and 0.02203 ± 0.00064 (syst.) ± 0.00064 (stat.) in the l + jets channel. The measured inclusive cross section is 3.81 ± 0.15 (syst.) ± 0.10 (stat.) pb in e + jets channel, 3.87 ± 0.11 (syst.) ± 0.07 (stat.) pb in µ + jets channel, and 3.96 ± 0.10 (syst.) ± 0.06 (stat.) pb in l + jets channel for full RunII data. The results are in agreement with the standard model next to leading order prediction

Robust Estimation of Loss Models for Lognormal Insurance Payment Severity Data

The primary objective of this scholarly work is to develop two estimation procedures - maximum likelihood estimator (MLE) and method of trimmed moments (MTM) - for the mean and variance of lognormal insurance payment severity data sets affected by different loss control mechanism, for example, truncation (due to deductibles), censoring (due to policy limits), and scaling (due to coinsurance proportions), in insurance and financial industries. Maximum likelihood estimating equations for both payment-per-payment and payment-per-loss data sets are derived which can be solved readily by any existing iterative numerical methods. The asymptotic distributions of those estimators are established via Fisher information matrices. Further, with a goal of balancing efficiency and robustness and to remove point masses at certain data points, we develop a dynamic MTM estimation procedures for lognormal claim severity models for the above-mentioned transformed data scenarios. The asymptotic distributional properties and the comparison with the corresponding MLEs of those MTM estimators are established along with extensive simulation studies. Purely for illustrative purpose, numerical examples for 1500 US indemnity losses are provided which illustrate the practical performance of the established results in this paper.Comment: 32 page

Truncated, Censored, and Actuarial Payment-type Moments for Robust Fitting of a Single-parameter Pareto Distribution

With some regularity conditions maximum likelihood estimators (MLEs) always produce asymptotically optimal (in the sense of consistency, efficiency, sufficiency, and unbiasedness) estimators. But in general, the MLEs lead to non-robust statistical inference, for example, pricing models and risk measures. Actuarial claim severity is continuous, right-skewed, and frequently heavy-tailed. The data sets that such models are usually fitted to contain outliers that are difficult to identify and separate from genuine data. Moreover, due to commonly used actuarial "loss control strategies" in financial and insurance industries, the random variables we observe and wish to model are affected by truncation (due to deductibles), censoring (due to policy limits), scaling (due to coinsurance proportions) and other transformations. To alleviate the lack of robustness of MLE-based inference in risk modeling, here in this paper, we propose and develop a new method of estimation - method of truncated moments (MTuM) and generalize it for different scenarios of loss control mechanism. Various asymptotic properties of those estimates are established by using central limit theory. New connections between different estimators are found. A comparative study of newly-designed methods with the corresponding MLEs is performed. Detail investigation has been done for a single parameter Pareto loss model including a simulation study

Water-wise Landscape Ideas for Existing Landscapes

This fact sheet outlines five easy ways to convert an existing landscape to a water-wise landscape without substantial renovation for those who do not have the time, resources, or expertise to renovate the existing landscape completely

Multi-level analysis of Malware using Machine Learning

Multi-level analysis of Malware using Machine Learnin