scholarly journals Optimal Returns in Indian Stock Market during Global Pandemic: A Comparative Study

2021 ◽  
Vol 14 (12) ◽  
pp. 592
Author(s):  
Pradip Debnath ◽  
Hari Mohan Srivastava
Keyword(s):  
Stock Exchange ◽  
Real Life ◽  
Stock Selection ◽  
Data Set ◽  
Global Pandemic ◽  
Proposed Model ◽  
Real Life Situation ◽  
The Difference ◽  
And Performance ◽  
Selection Methodology

This research is an extension of our previous work [Debnath and Srivastava (2021)]. In that paper, we designed a portfolio based on data taken from National Stock Exchange (NSE), India, during 1 January 2020 to 31 December 2020 and performance of that portfolio in real-life situation was examined during 1 January 2021 to 21 May 2021 assuming investments were made according to the proposed model. We observed that our proposed portfolio was efficient enough in that period to beat the performance of most of the in-demand mutual funds. It was also conjectured that this portfolio would be sustainable post the second wave of COVID-19 in India. In the present paper, our aim is to validate this conjecture. Here, we examine the performance of this portfolio during the period 1 January 2021 to 18 October 2021 using the same previous data set. We also investigate the performance of this portfolio if it was blindly adopted without applying the stock selection methodology during 1 January 2019 to 31 December 2019. Using paired t-test between the difference of means of the performances in the year 2019 and the year 2021, we show that the performance in 2021 was significantly enhanced because of selecting the stocks applying our proposed model.

scholarly journals Optimizing Stock Market Returns during Global Pandemic Using Regression in the Context of Indian Stock Market

2021 ◽  
Vol 14 (8) ◽  
pp. 386
Author(s):  
Pradip Debnath ◽  
Hari Mohan Srivastava
Keyword(s):  
Stock Market ◽  
Portfolio Management ◽  
Stock Exchange ◽  
Real Life ◽  
Third Wave ◽  
Stock Market Returns ◽  
Global Pandemic ◽  
Proposed Model ◽  
Real Life Situation ◽  
Indian Stock Market

Stock markets around the world experienced a massive collapse during the first wave of COVID-19. Roughly in the month of January 2021, the second wave of COVID-19 struck in India, reaching its peak in May, and by the end of May, the active cases started to decline. A third wave is again predicted by the end of 2021, and as such, the COVID-19 pandemic seems to have become a periodic phenomenon over the last couple of years. Therefore, the study of the behavior of the stock market as well as that of the investors becomes very interesting and crucial in this highly volatile and vulnerable market trend. Motivated by these facts, in the present paper, the researcher develops a model for portfolio management, using curve-fitting techniques and shows that this model can encounter the market volatility efficiently in the context of the Indian stock market. The portfolio is designed based on data taken from the National Stock Exchange (NSE), India, during 1 January 2020 to 31 December 2020. The performance of the portfolio in real-life situation during 1 January 2021 to 21 May 2021 is examined, assuming investments are made according to the proposed model.

PROFIT ESTIMATION FOR A PRODUCT UNDER WARRANTY: AN EVALUATION BASED ON CUSTOMER'S EXPECTATION AND SATISFACTION

2014 ◽  
Vol 21 (06) ◽  
pp. 1450029 ◽  
Author(s):  
P. K. KAPUR ◽  
ADARSH ANAND ◽  
NITIN SACHDEVA
Keyword(s):  
Real Life ◽  
Fixed Cost ◽  
Inventory Cost ◽  
Data Set ◽  
Customer Complaints ◽  
Customer Expectation ◽  
Real Life Data ◽  
Proposed Model ◽  
The Difference ◽  
Warranty Claims

Performance of a product not as expected by the customer brings warranty expenditure into the picture. In other words, the deviation of the product performance (PP) from the customer expectation (CE) is the reason for customer complaints and warranty expenses. When this conflicting scenario occurs in market, warranty comes into existence and fulfilling warranty claims of customers adds to product's overall cost. In this paper, based on the difference between PP and CE about the product we estimate profit for the firm. Furthermore, factors like fixed cost, production cost and inventory cost have also been considered in framing the optimization problem. In the proposed model, a two-dimensional innovation diffusion model (TD-IDM) which combines the adoption time of technological diffusion and price of the product has been used. Classical Cobb–Douglas function that takes into account the technological adoptions and other dimensions explicitly has been used to structure the production function. The proposed model has been validated on real life data set.

scholarly journals Construction of Optimal Portfolio and Selection of Stock using Fuzzy Approach

2018 ◽  
Vol 7 (3.30) ◽  
pp. 118
Author(s):  
Ity Patni ◽  
Nishu Gupta
Keyword(s):  
Stock Exchange ◽  
Optimal Portfolio ◽  
Fuzzy Approach ◽  
Total Risk ◽  
Stock Selection ◽  
Data Set ◽  
Index Model ◽  
Single Index Model ◽  
Proposed Model ◽  
Selection Of

Stock selection methods and strategies have been the prominent area of research since long. Portfolio theory is a connotation how an intelligent bias free investor should make an optimal portfolio. The line of the work is first inclined towards construction of optimal portfolio using Sharpe-Single Index model, CAPM, Jenson’s Measure, Treynor & Sharpe Ratio. These measures consider total risk i.e. systematic and unsystematic risk and suggests a rational investor in what proportion an investment can be made to a particular stock. Further, the purpose of the work is to combine the fuzzy approach for closer representation with reference to stock selection problem in a non-linear and uncertain environment. For demonstration, data set is taken from National Stock Exchange (NSE) for a period of 6 years (1st April, 2011 to 31st March, 2017). The proposed model will serve both ranking and assigning weight procedures to the selected stocks.  

scholarly journals A Fuzzy-Based Decision-Making Model for Improving the Carrying Capacity of Ship Locks: A Three Gorges Dam Case

2019 ◽  
Vol 7 (8) ◽  
pp. 244
Author(s):  
Shaoyue Shi ◽  
Danhong Zhang ◽  
Yixin Su ◽  
Chengpeng Wan ◽  
Mingyang Zhang ◽  
...  
Keyword(s):  
Decision Making ◽  
Carrying Capacity ◽  
Real Life ◽  
Three Gorges Dam ◽  
Three Gorges ◽  
Analytic Hierarchy ◽  
Proposed Model ◽  
Order Preference ◽  
Real Life Situation ◽  
Decision Making Model

This paper develops a decision-making model to assist the improvement of the carrying capacity of ship locks by combing fuzzy logic, the analytic hierarchy process (AHP) method, and the technique for order preference by similarity to an ideal solution (TOPSIS). A three-level hierarchical structure is constructed to identify the key factors influencing the carrying capacity of ship locks from the aspects of ship locks, vessels, environment, and administration. On this basis, a series of targeted strategies have been put forward to improve the carrying capacity of ship locks, and the TOPSIS method is applied to rank these strategies in terms of their performance. A case study of the five-stage dual-track ship lock of the Three Gorges Dam in China has been conducted to demonstrate the feasibility and rationality of the proposed model, and correlation analysis is conducted to verify the identified influencing factors in order to eliminate potential bias which may be generated from using AHP. The results obtained from the proposed methods are consistent with the real-life situation to a certain extent, indicating that the proposed method can provide a useful reference for improving the carrying capacity of ship locks.

scholarly journals A New Generalized Transmuted Inverse Exponential Distribution: Properties and Application

2018 ◽  
pp. 1-13
Author(s):  
Uchenna U. Uwadi ◽  
Elebe E. Nwaezza
Keyword(s):  
Exponential Distribution ◽  
Real Life ◽  
Quantile Function ◽  
Moment Generating Function ◽  
Maximum Likelihood Estimates ◽  
Data Set ◽  
Real Life Data ◽  
Proposed Model ◽  
Inverse Exponential Distribution ◽  
The Moment

In this study, we proposed a new generalised transmuted inverse exponential distribution with three parameters and have transmuted inverse exponential and inverse exponential distributions as sub models. The hazard function of the distribution is nonmonotonic, unimodal and inverted bathtub shaped making it suitable for modelling lifetime data. We derived the moment, moment generating function, quantile function, maximum likelihood estimates of the parameters, Renyi entropy and order statistics of the distribution. A real life data set is used to illustrate the usefulness of the proposed model.     

Performance and development of a thin stock market: the Stockholm Stock Exchange 1912–2017

2020 ◽  
pp. 1-19
Author(s):  
Kristian Rydqvist ◽  
Rong Guo
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Prices ◽  
Stock Price ◽  
Stock Exchange ◽  
Stock Selection ◽  
Data Set ◽  
Transaction Prices ◽  
Limit Orders ◽  
A Value

We estimate historical stock returns for Swedish listed companies in a newly constructed data set of daily stock prices that spans more than 100 years. Stock returns exhibit all the familiar characteristics. The growth of the public sector depressed the stock market, and the process of globalization revitalized it. Banks played an important role in the early development of the stock market. There was little trading in the past, and we examine the effects on return measurement from missing data. Stock selection and the replacement of missing transaction prices through search back procedures or limit orders make little difference to a value-weighted stock price index, while ignoring the price effects of capital operations makes a big difference.

scholarly journals Cliques in high-dimensional random geometric graphs

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Konstantin E. Avrachenkov ◽  
Andrei V. Bobu
Keyword(s):  
Data Science ◽  
Real Life ◽  
Geometric Graph ◽  
Dimensional Euclidean Space ◽  
Geometric Graphs ◽  
Data Set ◽  
Random Geometric Graph ◽  
Random Geometric Graphs ◽  
Real Life Situation ◽  
Average Vertex

AbstractRandom geometric graphs have become now a popular object of research. Defined rather simply, these graphs describe real networks much better than classical Erdős–Rényi graphs due to their ability to produce tightly connected communities. The n vertices of a random geometric graph are points in d-dimensional Euclidean space, and two vertices are adjacent if they are close to each other. Many properties of these graphs have been revealed in the case when d is fixed. However, the case of growing dimension d is practically unexplored. This regime corresponds to a real-life situation when one has a data set of n observations with a significant number of features, a quite common case in data science today. In this paper, we study the clique structure of random geometric graphs when $$n\rightarrow \infty$$ n → ∞ , and $$d \rightarrow \infty$$ d → ∞ , and average vertex degree grows significantly slower than n. We show that under these conditions, random geometric graphs do not contain cliques of size 4 a. s. if only $$d \gg \log ^{1 + \epsilon } n$$ d ≫ log 1 + ϵ n . As for the cliques of size 3, we present new bounds on the expected number of triangles in the case $$\log ^2 n \ll d \ll \log ^3 n$$ log 2 n ≪ d ≪ log 3 n that improve previously known results. In addition, we provide new numerical results showing that the underlying geometry can be detected using the number of triangles even for small n.

scholarly journals A Machine Learning Approach to Fitting Prescription for Hearing Aids

Electronics ◽  
2019 ◽  
Vol 8 (7) ◽  
pp. 736
Author(s):  
Mondol ◽  
Lee
Keyword(s):  
Hearing Loss ◽  
Hearing Aids ◽  
Real Life ◽  
Training Data ◽  
Prescription Database ◽  
Data Set ◽  
Promising Tool ◽  
Proposed Model ◽  
Machine Learning Approach ◽  
Two Phases

A successful Hearing-Aid Fitting (HAF) is more than just selecting an appropriate HearingAid (HA) device for a patient with Hearing Loss (HL). The initial fitting is given by the prescriptionbased on user’s hearing loss; however, it is often necessary for the audiologist to readjust someparameters to satisfy the user demands. Therefore, in this paper, we concentrated on a new applicationof Neural Network (NN) combined with a Transfer Learning (TL) strategy to develop a fittingalgorithm with the prescription database for hearing loss and readjusted gain to minimize the gapbetween fitting satisfaction. As prior information, we generated the data set from two popularhearing-aid fitting software, then fed the training data to our proposed model, and verified theperformance of the architecture. Pondering real life circumstances, where numerous fitting recordsmay not always be accessible, we first investigated the number of minimum fitting records requiredfor possible sufficient training. After that, we evaluated the performance of the proposed algorithmin two phases: (a) NN with refined hyper parameter showed enhanced performance in compareto state-of-the-art DNN approach, and (b) the TL approach boosted the performance of the NNalgorithm in a broad way. Altogether, our model provides a pragmatic and promising tool for HAF.

scholarly journals The Effect of Corporate Governance and Ownership Structure on Financial Performance of Listed Companies in Nepal

2019 ◽  
Vol 12 (1) ◽  
pp. 1-18
Author(s):  
Surya Bahadur G. C. ◽  
Ravindra Prasad Baral
Keyword(s):  
Corporate Governance ◽  
Panel Data ◽  
Least Squares ◽  
Ownership Structure ◽  
Stock Exchange ◽  
Listed Companies ◽  
Ownership Concentration ◽  
Data Set ◽  
Listed Firms ◽  
And Performance

The paper attempts to analyze relationships among corporate governance, ownership structure and firm performance in Nepal. The study comprises of panel data set of 25 firms listed at Nepal Stock Exchange (NEPSE) covering a period of five years from 2012 to 2016. The econometric methodology for the study consists primarily of least squares dummy variable (LSDV) model, fixed and random effects panel data models and two-stage least squares (2SLS) model. The study finds bi-directional relationship between corporate governance and performance. Among corporate governance internal mechanisms; smaller board size, higher proportion of independent directors, reducing ownership concentration, improving standards of transparency and disclosure, and designing appropriate director compensation package are important dimensions that listed firms and regulators in Nepal should focus on. Ownership concentration is found to have positive effect on performance; however, it affects corporate governance negatively. This study raises understanding and provides empirical evidence for endogenous relationship between corporate governance and performance and offers support for principal-principal agency relationship. The results of this study lead to several practical implications for listed firms as well as policymakers of Nepal in promoting sound corporate governance practices and codes. For listed companies, the improvement in compliance with a code of corporate governance or voluntary adoption of best practices can provide a means of achieving improved performance.

scholarly journals Compensation is for real: Evidence from existing groups in the context of actual relations

2016 ◽  
Vol 20 (6) ◽  
pp. 745-756 ◽  
Author(s):  
Laurent Cambon ◽  
Vincent Y. Yzerbyt
Keyword(s):  
Real Life ◽  
Social Judgment ◽  
The Other ◽  
Ingroup Bias ◽  
Life Situation ◽  
The Status ◽  
Real Life Situation ◽  
Status Difference ◽  
The Difference

Compensation refers to the fact that a group perceived as higher than another on one of the fundamental dimensions of social judgment (competence and warmth) is also perceived as lower than the other group on the other dimension. Relying on a full-crossed design, the present work tested compensation in a real-life situation using existing groups involved in an ongoing relation. As predicted, compensation emerged when (a) the difference between the groups, and thus the perceived legitimacy of the status difference, was large as opposed to small, and (b) the relation between the groups was asymmetrical. In contrast, the smaller the difference (the lesser the legitimacy), the more ingroup bias emerged.

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