scholarly journals Forecasting Aggregate Retail Sales with Google Trends

2021 ◽  
Vol 80 (4) ◽  
pp. 50-73
Author(s):  
Elizaveta Golovanova ◽  
◽  
Andrey Zubarev ◽  
Keyword(s):  
Food Products ◽  
Google Trends ◽  
The Internet ◽  
Retail Sales ◽  
Online Tool ◽  
Macroeconomic Variables ◽  
Forecasting Models ◽  
Out Of Sample ◽  
Online Stores ◽  
Made In

As the internet grows in popularity, many purchases are being made in online stores. Google Trends is an online tool that collects data on user queries and forms categories from them. We forecast the dynamics of both aggregate retail sales and individual categories of food and non-food products using macroeconomic variables and Google Trends categories that correspond to various product groups. For each type of retail, we consider the best forecasting models from macroeconomic variables and try to improve them by adding trends. For these purposes, we use pseudo-out-of-sample nowcasting as well as recursive forecasting several months ahead. We conclude that forecasts for food and non-food products can improve significantly once trends are added to the models.

scholarly journals The Impact Of Macroeconomic Variables On Real Estate Price Forecasting Modelling In Abuja Nigeria

2019 ◽  
Vol 8 (5C) ◽  
pp. 67-72
Keyword(s):  
Real Estate ◽  
Negative Impact ◽  
Positive Impact ◽  
Consumer Price Index ◽  
Price Forecasting ◽  
Macroeconomic Variables ◽  
Real Estate Price ◽  
Forecasting Models ◽  
Out Of Sample ◽  
The Impact

This paper examined the impact of macroeconomic variables on real estate price forecasting modelling in Abuja, Nigeria using the family of Box-Jenkins ARIMA models. The ARIMA and ARIMAX models were used to forecast real estate residential price in Abuja, Nigeria using quarterly data from 2000Q1 to 2017Q in Naira (N). The outcome revealed that, macroeconomic variables such as consumer price index, price of crude oil, exchange rate of Naira against US dollar, GDP, interest rate, household income has significant positive impact on the real estate residential price forecasting models of 2 bedroom flat, 3 bedroom flat and 5 bedroom flat, while they have strong negative impact on the price forecasting model of 4 bedroom flat. Moreover, ARIMA and ARIMAX provides best out of sample forecasting models.

ASPECTS IN BUILDING A COMPANY WEB-SITE AND ITS ROLE FOR THE DEVELOPMENT OF BUSINESS

2018 ◽  
pp. 117-124
Author(s):  
Petar Halachev ◽  
Victoria Radeva ◽  
Albena Nikiforova ◽  
Miglena Veneva
Keyword(s):  
Life Cycle ◽  
Web Site ◽  
The Internet ◽  
A Company ◽  
The Web ◽  
Design Construction ◽  
Made In ◽  
Site Types

This report is dedicated to the role of the web site as an important tool for presenting business on the Internet. Classification of site types has been made in terms of their application in the business and the types of structures in their construction. The Models of the Life Cycle for designing business websites are analyzed and are outlined their strengths and weaknesses. The stages in the design, construction, commissioning, and maintenance of a business website are distinguished and the activities and requirements of each stage are specified.

Interest on the internet for systemic lupus erythematosus: Analysis of Google Trends in Latin American countries

Lupus ◽  
2021 ◽  
pp. 096120332110103
Author(s):  
Paul J Tejada-Llacsa ◽  
Pamela Villacorta-Landeo ◽  
Eder Aguilar-Buitrón ◽  
Graciela S Alarcón ◽  
Manuel F Ugarte-Gil
Keyword(s):  
Systemic Lupus Erythematosus ◽  
Latin American ◽  
Lupus Erythematosus ◽  
Google Trends ◽  
The Internet ◽  
Systemic Lupus ◽  
Web Based ◽  
Pan American ◽  
Health Institutions ◽  
Latin American Countries

Background/Objective Information available on the internet about Systemic Lupus Erythematosus (SLE) can influence the doctor-patient relationship. Therefore, the aim of this study was to identify the terms used for SLE on the internet. Methods We analyzed the data downloaded from Google Trends, considering the term “Lupus” in a six-year web-based research. The frequency of the terms for each Pan-American country was obtained automatically from Google Trends, which reports relative search volumes or RSV (on a scale from 0 to 100) across regions. Results We obtained a total of 67 registered terms in 18 countries. The terms were distributed into five categories. The categories with interest in all countries were “definition” and “symptoms”. Conclusions Google Trends allows us to find useful information about SLE on the internet; once the accuracy of this information is validated, it can be used by patients, health institutions, rheumatologists and other health professionals.

scholarly journals Forecasting the Volatility of Crude Oil: The Role of Uncertainty and Spillovers

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4173
Author(s):  
Rangan Gupta ◽  
Christian Pierdzioch
Keyword(s):  
Crude Oil ◽  
Predictive Value ◽  
Realized Variance ◽  
International Spillovers ◽  
Forecasting Models ◽  
West Texas ◽  
Out Of Sample ◽  
One Year ◽  
Lasso Estimator

We use a dataset for the group of G7 countries and China to study the out-of-sample predictive value of uncertainty and its international spillovers for the realized variance of crude oil (West Texas Intermediate and Brent) over the sample period from 1996Q1 to 2020Q4. Using the Lasso estimator, we found evidence that uncertainty and international spillovers had predictive value for the realized variance at intermediate (two quarters) and long (one year) forecasting horizons in several of the forecasting models that we studied. This result holds also for upside (good) and downside (bad) variance, and irrespective of whether we used a recursive or a rolling estimation window. Our results have important implications for investors and policymakers.

scholarly journals Mathematical Development and Evaluation of Forecasting Models for Accuracy of Inflation in Developing Countries: A Case of Vietnam

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Nhu-Ty Nguyen ◽  
Thanh-Tuyen Tran
Keyword(s):  
Raw Materials ◽  
Arima Model ◽  
Consumer Price Index ◽  
Forecast Accuracy ◽  
Complex Problem ◽  
Forecast Performance ◽  
Forecasting Models ◽  
Out Of Sample ◽  
Forecasting Inflation ◽  
Using Data

Inflation is a key element of a national economy, and it is also a prominent and important issue influencing the whole economy in terms of marketing. This is a complex problem requiring a large investment of time and wisdom to attain positive results. Thus, appropriate tools for forecasting inflation variables are crucial significant for policy making. In this study, both clarified value calculation and use of a genetic algorithm to find the optimal parameters are adopted simultaneously to construct improved models: ARIMA, GM(1,1), Verhulst, DGM(1,1), and DGM(2,1) by using data of Vietnamese inflation output from January 2005 to November 2013. The MAPE, MSE, RMSE, and MAD are four criteria with which the various forecasting models results are compared. Moreover, to see whether differences exist, Friedman and Wilcoxon tests are applied. Both in-sample and out-of-sample forecast performance results show that the ARIMA model has highly accurate forecasting in Raw Materials Price (RMP) and Gold Price (GP), whereas, the calculated results of GM(1,1) and DGM(1,1) are suitable to forecast Consumer Price Index (CPI). Therefore, the ARIMA, GM(1,1), and DGM(1,1) can handle the forecast accuracy of the issue, and they are suitable in modeling and forecasting of inflation in the case of Vietnam.

scholarly journals Relative High Interest in Acne on the Internet: A Web-Based Comparison Using Google Trends

2014 ◽  
Vol 26 (5) ◽  
pp. 641 ◽  
Author(s):  
Hyun-Tae Shin ◽  
Se-Won Park ◽  
Dong-Youn Lee
Keyword(s):  
Google Trends ◽  
The Internet ◽  
Web Based ◽  
High Interest

scholarly journals Online Gardening Search Activities and Purchases

2008 ◽  
Vol 26 (4) ◽  
pp. 210-216
Author(s):  
Bridget K. Behe ◽  
Brittany Harte ◽  
Chengyan Yue
Keyword(s):  
United States ◽  
The United States ◽  
Internet Technology ◽  
The Internet ◽  
Demographic Differences ◽  
Online Purchases ◽  
Online Purchase ◽  
Region Of Residence ◽  
Baseline Information ◽  
Made In

Abstract Consumers have readily adopted personal computers and Internet technology with many seeking information and/or make purchases online. However, the extent to which horticultural consumers seek information and make purchases online is not well documented. A survey of 1588 consumers, representative of the United States on average, was conducted in 2004 to provide baseline information about online gardening search and purchase activities. Nearly 28% searched for gardening information at least once; of those, more than 50% of the participants searched for information at least weekly. There were differences in gardening-related searches by age and marital status, but not by region of residence, income, or gender. Nearly 50% of the study respondents made an online purchase in the year prior to the survey but only 7.4% made a gardening related purchase online. Over 50% had made a gardening-related purchase in-person. The same respondents who made in-person purchases were the individuals who made the online gardening purchases, so the Internet provided a supplemental shopping venue. There were demographic differences between those who made online gardening purchases and solely in-person gardening purchases. More males, younger and slightly less affluent participants were more likely to make online purchases than solely in-person purchases for gardening products, supplies, and services while more females who were slightly older and more affluent were more likely to make in-person gardening-related purchases.

scholarly journals Impact of the COVID-19 Pandemic on Instagram and Influencer Marketing

2021 ◽  
Vol 13 (2) ◽  
pp. 20
Author(s):  
Evelina Francisco ◽  
Nadira Fardos ◽  
Aakash Bhatt ◽  
Gulhan Bizel
Keyword(s):  
Social Media ◽  
Marketing Strategy ◽  
Online Survey ◽  
Video Conferencing ◽  
Marketing Mix ◽  
The Internet ◽  
Exploratory Research ◽  
Social Media Platforms ◽  
The Impact ◽  
Made In

The COVID-19 pandemic and the resulting stay-at-home orders have disrupted all aspects of life globally, most notably our relationship with the internet and social media platforms. People are online more than ever before, working and attending school from home and socializing with friends and family via video conferencing. Marketers and brands have been forced to adapt to a new normal and, as a result, have shifted their brand communication and marketing mix to digital approaches. Hence, this study aims to examine the shift of influencer marketing on Instagram during this period and the possible future implications. By employing an online survey for exploratory research, individuals answered questions addressing their perceptions about the impact of the pandemic, brands and influencers’ relationship, and the overall changes made in marketing strategy.

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