scholarly journals Comparative analysis of the stock quotes dynamics for IT-sector and the entertainment industry companies based on the characteristics of memory depth

2021 ◽  
Vol 107 ◽  
pp. 01003
Author(s):  
Nataliia Maksyshko ◽  
Oksana Vasylieva
Keyword(s):  
Time Series ◽  
Comparative Analysis ◽  
Rapid Development ◽  
Entertainment Industry ◽  
Long Term Memory ◽  
Range Analysis ◽  
Goods And Services ◽  
Rescaled Range Analysis ◽  
Persistence Property ◽  
The Impact

The article is devoted to the study and comparative analysis of the stock quotes dynamics for the world’s leading companies in the IT sector and the entertainment industry. Today, these areas are developing the fastest and most powerful, which attracts the attention of investors around the world. This is due to the rapid development of digital communication technologies, the growth of intellectualization and individualization of goods and services, and so on. These spheres have strong development potential, but the question to how their companies’ stock quotes respond to the impact of such a natural but crisis phenomenon as the COVID-19 pandemic remains open. Based on the nonlinear paradigm of the financial markets dynamics, the paper considers and conducts a comprehensive fractal analysis of the quotations dynamics for six leading companies (Apple Inc., Tesla Inc., Alphabet Inc., The Walt Disney Company, Sony Corporation, Netflix) in this area before and during the COVID-19 pandemic. As a result of the application of the rescaled range analysis (R/S analysis), the presence of the persistence property and long-term memory in the stock quotes dynamics for all companies and its absence in their time series of profitability was confirmed. The application of the method of sequential R/S analysis made it possible to construct fuzzy sets of memory depths for the considered time series and to deepen the analysis of the dynamics due to the quantitative characteristics calculated on their basis. Taking into account the characteristics of memory depth in the dynamics of quotations made it possible to conduct a comparative analysis of the dynamics, both under the influence of the natural crisis situation and in terms of investing in different terms. The peculiarities of the delayed profitability dynamics of quotations for each of the companies are also taken into consideration and compared. The developed recommendations can be used in investment activities in the stock market.

scholarly journals Impact and Challenges of GST in India with Reference to Media & Entertainment Sector – An Insight

2021 ◽  
Vol 23 (08) ◽  
pp. 366-382
Author(s):  
Sudipta Chakraborty ◽  
Keyword(s):  
Entertainment Industry ◽  
Online Delivery ◽  
Cascading Effects ◽  
Indian Economy ◽  
Goods And Services ◽  
Indirect Taxes ◽  
The Media ◽  
Brand Promotion ◽  
Almost All ◽  
The Impact

The biggest tax reform since independence i.e., Goods and Services Tax (GST) has now become a part of Indian economy from 1st July, 2017. It is a comprehensive indirect tax on manufactures, sales and consumption of goods and services; thereby subsuming almost all other indirect taxes that were in existence throughout India before its implementation and also eliminating the cascading effects thereby. GST was introduced just after demonetisation in November, 2016 and has changed the whole scenario of indirect tax system in India. It aims at boosting overall growth of Indian economy by integrating all indirect taxes into one. The media and entertainment (M&E) industry in India is one of the fastest growing sectors and has outperformed expectations in recent years. With the expansion of the economy, the sector has accelerated its growth. The sector spreads into big and small screens, media, events, exhibitions, amusement facilities and gaming zones, with various combinations of offline and online delivery systems. With the advent of GST, things have become relatively simpler for the entertainment industry as it is subjected to only one tax and permissible local body taxes. One of the major changes has been the subsuming of Entertainment Tax under GST. Earlier, prior to implementation of GST, the rate of Entertainment Tax for the film industry varied from state to state, ranging from 15% to 110%. Introduction of GST has stabilised the rate variance and provided a uniform market across the nation. In this study, we have also made an attempt to study the pre and post GST effects on different activities of the media and entertainment industry like exhibition of movies, food and beverages sold at movie halls, services rendered by artists and other technician, sponsorship and brand promotion and advertisement. Thus, this paper is an endeavour to understand the impact of GST on media and entertainment sector and aims at pointing out the challenges of the same under the present structure and provide some way outs to it.

scholarly journals Applied principles of niche narrowing as an innovative strategy for promotion in social networks in the conditions of business digitalization and formation of the digital environment

2020 ◽  
Keyword(s):  
Social Networks ◽  
Rapid Development ◽  
Innovative Strategy ◽  
Scientific Methods ◽  
Goods And Services ◽  
Doing Business ◽  
General Scientific ◽  
Marketing Tool ◽  
Almost All ◽  
The Impact

In today's world, people go online not only for entertainment, but also to study, shop, search for the necessary information and more. And social networks are approaching a giant like Google every year in terms of number of users and frequency of using.Therefore, almost all entrepreneurs have their own page on social networks, which are an ideal platform for promoting their products and services. Over the past 10 years, a new Internet marketing tool has appeared that specializes in promoting and doing business on social networks – SMM (Social Media Marketing). And here it is especially important to build a quality and effective strategy that will make social networks a quality image and sales channel of any goods and services. The subject of the article is a marketing strategy for development and promotion in social networks.The purpose of the article is to develop the applied principlesof an innovative strategy for narrowing the niche for promotion in social networks according to the features and means of its implementation for various business projects, brands and blogs. General scientific methods are used, such as systems analysis, synthesis and abstract-logical – to clarify the features of the blogs in each niche, which work on the strategy of narrowing the niche; analysis of Facebook for Business algorithms – to determine the impact of such a strategy on the further effectiveness of targeted advertising and the allocation of a unique trade offer due to the strategy of narrowing the niche.The following results were obtained: ways of implementing a niche narrowing strategy for various blogs, brands and business projects were developed and demonstrated, their effectiveness was proved. Conclusions: the practical principles of implementing an innovative strategy for narrowing the niche for social networks, which can be used for various business projects, brands and blogs, described the possibilities of implementing this strategy according to their features and tools, highlighted the main advantages of this strategy for rapid development of social networks.

scholarly journals The effects of China’s cross-border e-commerce on its exports: a comparative analysis of goods and services trade

2021 ◽  
Author(s):  
Zi Hui Yin ◽  
Chang Hwan Choi
Keyword(s):  
Sustainable Development ◽  
Comparative Analysis ◽  
Gravity Model ◽  
Positive Impact ◽  
Trade In Services ◽  
The Sustainable Development ◽  
Goods And Services ◽  
Cross Border ◽  
Belt And Road ◽  
The Impact

AbstractThis study examines the effects of China’s cross-border e-commerce (CBEC) on its goods and services exports to ‘Belt and Road’ (B&R) countries for the period 2000–2018 using a gravity model. We find that CBEC has a greater positive impact on trade in services than on trade in goods, especially after the implementation of the B&R initiative. Furthermore, as the level of CBEC rises, distance tends to have a lower (higher) impact on services (goods) trade, whereas the impact on services (goods) trade increased (decreased) annually. Hence, promoting the sustainable development of CBEC can lead to increased export volumes.

scholarly journals An attempt to unified approach to the evolution of products in the entertainment industry

E-methodology ◽  
2020 ◽  
Vol 6 (6) ◽  
pp. 80-93
Author(s):  
ANDRZEJ BUDA ◽  
ANDRZEJ JARYNOWSKI ◽  
KATARZYNA KUŹMICZ
Keyword(s):  
Time Series ◽  
Temporal Dynamics ◽  
Life Cycles ◽  
Creative Industries ◽  
Point Of View ◽  
Entertainment Industry ◽  
Accurate Data ◽  
Unified Approach ◽  
Statistical Point ◽  
The Impact

Aim. We analyze temporal dynamics of entertainment industry including literature,music, fi lms and video games, introducing possible analogies between them. We providea framework for further explanation based on the economic concepts as revenue, organizationstructure and marketing goals in these creative industries for different technologicaleras.Methods. Initially, accurate data collected for time series of weekly record sales areanalyzed from statistical point of view (e.g. networks of artists, record labels and producers).This method may be extended to other parts of entertainment industry in search ofanalogies, under the infl uence of technological revolutions.Results. We provide the statistical properties of the mass art entertainment industry(including value of the markets, seasonality, products life-cycles) and interactions betweenvarious kinds of entertainment (e.g. fi lms might be infl uenced by literature with a delay).We are able to distinguish predigital, digital and postdigital eras.Conclusions. There are many ways of describing and measuring the impact of selectedentertainment industries with the most important as literature, music, fi lms and videogames. However, universal analogies may explain objective properties of entertainmentindustry in general.

scholarly journals Comparative analysis of machine learning approaches to analyze and predict the COVID-19 outbreak

2021 ◽  
Vol 7 ◽  
pp. e746
Author(s):  
Muhammad Naeem ◽  
Jian Yu ◽  
Muhammad Aamir ◽  
Sajjad Ahmad Khan ◽  
Olayinka Adeleye ◽  
...  
Keyword(s):  
Machine Learning ◽  
Time Series ◽  
Comparative Analysis ◽  
Prediction Models ◽  
Mean Absolute Percentage Error ◽  
Percentage Error ◽  
Support Vector ◽  
Absolute Percentage Error ◽  
Statistical Measures ◽  
The Impact

Background Forecasting the time of forthcoming pandemic reduces the impact of diseases by taking precautionary steps such as public health messaging and raising the consciousness of doctors. With the continuous and rapid increase in the cumulative incidence of COVID-19, statistical and outbreak prediction models including various machine learning (ML) models are being used by the research community to track and predict the trend of the epidemic, and also in developing appropriate strategies to combat and manage its spread. Methods In this paper, we present a comparative analysis of various ML approaches including Support Vector Machine, Random Forest, K-Nearest Neighbor and Artificial Neural Network in predicting the COVID-19 outbreak in the epidemiological domain. We first apply the autoregressive distributed lag (ARDL) method to identify and model the short and long-run relationships of the time-series COVID-19 datasets. That is, we determine the lags between a response variable and its respective explanatory time series variables as independent variables. Then, the resulting significant variables concerning their lags are used in the regression model selected by the ARDL for predicting and forecasting the trend of the epidemic. Results Statistical measures—Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and Symmetric Mean Absolute Percentage Error (SMAPE)—are used for model accuracy. The values of MAPE for the best-selected models for confirmed, recovered and deaths cases are 0.003, 0.006 and 0.115, respectively, which falls under the category of highly accurate forecasts. In addition, we computed 15 days ahead forecast for the daily deaths, recovered, and confirm patients and the cases fluctuated across time in all aspects. Besides, the results reveal the advantages of ML algorithms for supporting the decision-making of evolving short-term policies.

SUNSPOTS DATA ANALYSIS USING TIME SERIES

Fractals ◽  
2008 ◽  
Vol 16 (03) ◽  
pp. 259-265 ◽  
Author(s):  
YUSUF H. SHAIKH ◽  
A. R. KHAN ◽  
M. I. IQBAL ◽  
S. H. BEHERE ◽  
S. P. BAGARE
Keyword(s):  
Time Series ◽  
Hurst Exponent ◽  
Sunspot Cycle ◽  
Fractal Dimensions ◽  
Data Sets ◽  
Range Analysis ◽  
Data Set ◽  
Rescaled Range ◽  
Rescaled Range Analysis ◽  
Sunspot Data

The record of the sunspot number visible on the sun is regularly collected over the centuries by various observatories for studying the different factors influencing the sunspot cycle and solar activity. Sunspots appear in cycles, and last several years. These cycles follow a certain pattern which is well known. We analyzed monthly and yearly averages of sunspot data observed from year 1818 to 2002 using rescaled range analysis. The Hurst exponent calculated for monthly data sets are 0.8899, 0.8800 and 0.8597 and for yearly data set is 0.7187. Fractal dimensions1 calculated are 1.1100, 1.1200, 1.1403 and 1.2813. From the study of Hurst exponent and fractal dimension, we conclude that time series of sunspots show persistent behavior. The fundamental tool of signal processing is the fast Fourier transform technique (FFT). The sunspot data is also analyzed using FFT. The power spectrum of monthly and yearly averages of sunspot shows distinct peaks at 11 years confirming the well known 11-year cycle. The monthly sunspot data is also analyzed using FFT to filter the noise in the data.

scholarly journals Diagnostics of a persistence property for quotations dynamics on high-tech stock markets

2019 ◽  
Vol 65 ◽  
pp. 06009
Author(s):  
Nataliia Maksyshko ◽  
Oksana Vasylieva
Keyword(s):  
Time Series ◽  
Deterministic Chaos ◽  
High Tech ◽  
Long Term Memory ◽  
Investment Horizon ◽  
Fractal Nature ◽  
Instrument Choice ◽  
Persistence Property ◽  
Microsoft Corporation

The research purpose is diagnosis of the persistence property for the stock quotes time series of leading companies belonging to the high-tech sector: Apple Inc., Microsoft Corporation and Samsung Electronics Co. The persistence property or the trend-stability of the time series is crucial meaning for the investor. As a result of the application of the R\S-analysis, it is proved that the stock quotations dynamics of these companies have the persistence property. Also, the method of sequential R\S analysis is applied: the leading characteristics of the long-term memory are discovered, which makes it possible to carry out a comparative analysis of their predictability. It is found that the time series of profitability do not have the properties of persistence. However, the tests for diagnostic of a deterministic chaos reveal the appearance of the persistence property in the time series of “delayed” profitability. The obtained results allows to state the fractal nature for the time series of quotations, while the characteristics of the persistence (depth of memory) determined by the research can be useful to the investor in terms of the investment instrument choice and the investment horizon as well as can be used in selecting the parameters for a forecasting model.

Dynamic interaction between higher education and economic progress: a comparative analysis of BRICS countries

2018 ◽  
Vol 46 (4) ◽  
pp. 225-238 ◽  
Author(s):  
Victor Chang ◽  
Yian Chen ◽  
Chang Xiong
Keyword(s):  
Higher Education ◽  
Time Series ◽  
Economic Development ◽  
Comparative Analysis ◽  
Dynamic Interaction ◽  
Content Type ◽  
Brics Countries ◽  
Economic Progress ◽  
The Government ◽  
The Impact

PurposeThe purpose of this paper is to gain a deeper insight on how education boosts economic progress in key emerging economies. This project is aimed at exploring the interactive dynamics between the tertiary education sector and economic development in BRICS countries. The author also aims to examine how the structure of higher education contributes to economic expansion.Design/methodology/approachThe author uses the time series data of BRICS countries across approximately two decades to determine the statistical causality between the size of tertiary enrollment and economic development. The linear regression model is then used to figure out the different impact levels of academic and vocational training programs at the tertiary level to economic development.FindingsData from all BRICS countries exhibited a unidirectional statistical causality relationship, except the Brazilian data. The national economic expansion Granger Caused increased tertiary enrollment in Russia and India, while in China and South Africa, higher education enrollment Granger Caused economic progress. The impact from tertiary academic training is found to be positive for all BRICS nations, while tertiary vocation training is shown to have impaired the Russian and South African economy.Research limitations/implicationsThis project is based on a rather small sample size, and the stationary feature of the time series could be different should a larger pool of data spanning a longer period of time is used. In addition, the author also neglects other control variables in the regression model. Therefore, the impact level could be distorted due to possible omitted variable bias.Practical implicationsTertiary academic study is found to have a larger impact level to all countries’ economic advancement, except for China, during the time frame studied. There is a statistical correlation between the education and economic progress. This is particularly true for BRICS countries, especially China. But the exception is Brazil.Social implicationsThe government should provide education up to the certain level, as there is a direct correlation to the job creation and economic progress. Furthermore, the government should also work closely with industry to ensure growth of industry and creation of new jobs.Originality/valueThe comparative analysis and evaluation of the dynamic interaction of tertiary enrollment and economic output across all five BRICS nations is unique, and it deepens the understanding of the socioeconomic development in these countries from a holistic management perspective.

MINIMIZING PERIODIC TRENDS BY APPLYING LAPLACE TRANSFORM

Fractals ◽  
2011 ◽  
Vol 19 (02) ◽  
pp. 203-211 ◽  
Author(s):  
AIJING LIN ◽  
PENGJIAN SHANG
Keyword(s):  
Time Series ◽  
Laplace Transform ◽  
Moving Average ◽  
Stationary Time Series ◽  
Fluctuation Analysis ◽  
Range Analysis ◽  
Long Range Correlations ◽  
Cross Correlation Analysis ◽  
Rescaled Range Analysis ◽  
Cross Correlations

Rescaled range analysis (R/S analysis), detrended fluctuation analysis (DFA) and detrended moving average (DMA) are widely-used methods for detection of long-range correlations in time series. Detrended cross-correlation analysis (DCCA) is a recently developed method to quantify the cross-correlations of two non-stationary time series. Another method for studying auto-correlations and cross-correlations was presented by Sergio Arianos and Anna Carbone in 2009. Recent studies have reported the susceptibility of this methods to periodic trends, which can result in spurious crossovers. In this paper, we propose the modified methods base on Laplace transform to minimizing the effect of periodic trends. The effectiveness of our techniques are demonstrated on stock data corrupted with periodic trends.

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