Analysis and Forecast of COVID-19 in India, the US and Italy - An Application of Arima Model

2020 ◽  
Author(s):  
Elbin Siby ◽  
Maria Joseph ◽  
Noel George ◽  
Richu Rajesh ◽  
Aneena Thankachan
Keyword(s):  
Arima Model ◽  
The Us

Testing the weak form of efficient market hypothesis for socially responsible and Shariah indexes in the USA

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abbas Khan ◽  
Muhammad Yar Khan ◽  
Abdul Qayyum Khan ◽  
Majid Jamal Khan ◽  
Zia Ur Rahman
Keyword(s):  
Stock Prices ◽  
Arima Model ◽  
Weak Form ◽  
Efficient Market Hypothesis ◽  
Future Price ◽  
Short Term ◽  
Socially Responsible ◽  
Efficient Market ◽  
Content Type ◽  
The Us

Purpose By testing the weak form of efficient market hypothesis (EMH) this study aims to forecast the short-term stock prices of the US Dow and Jones environmental socially responsible index (SRI) and Shariah compliance index (SCI). Design/methodology/approach This study checks the validity of the weak form of EMH for both SCI and SRI prices by using different parametric and non-parametric tests, i.e. augmented Dickey-Fuller test, Philip-Perron test, runs test and variance ratio test. If the EMH is invalid, the research further forecasts short-term stock prices by applying autoregressive integrated moving average (ARIMA) model using daily price data from 2010 to 2018. Findings The research confirms that a weak form of EMH is not valid in the US SRI and SCI. The historical data can predict short-term future price movements by using technical ARIMA model. Research limitations/implications This study provides better guidance to risk-averse national and international investors to earn higher returns in the US SRI and SCI. This study can be extended to test the EMH of Islamic equity in the Middle East and North Africa region and other top Islamic indexes in the world. Originality/value This study is a new addition to the existing literature of equity investment and price forecasting by comparing and investigating the market efficiency of two interrelated US SRI and SCI.

scholarly journals Forecasting US Tourists’ inflow to Slovenia by modified Holt-Winters Damped model: A case in the Tourism industry logistics and supply chains

2019 ◽  
Vol 10 (1) ◽  
pp. 11-30
Author(s):  
Dejan Dragan ◽  
Abolfazl Keshavarzsaleh ◽  
Tomaž Kramberger ◽  
Borut Jereb ◽  
Maja Rosi
Keyword(s):  
Supply Chains ◽  
Predictive Models ◽  
Arima Model ◽  
Exponential Smoothing ◽  
Tourism Industry ◽  
Proposed Model ◽  
The Us ◽  
Forecasting System ◽  
Exponential Smoothing Method ◽  
Practical Implications

Abstract Forecasting is important in many branches of logistics, including the logistics related to Tourism supply chains. With an increasing inflow of American tourists, planning and forecasting the US tourists’ inflow to Slovenia have gained far more importance attention amongst scholars and practitioners. This study, therefore, was conducted to forecast the American tourists’ inflow to Slovenia using one of the predictive models based on the exponential smoothing approach, namely Holt-Winters damped additive (HWDA) exponential smoothing method. The model was modified by several improvements, while the obtained results were generalized to other supply chain components. The results show that the forecasting system can predict well the observed inflow, while the methodology used to derive the model might have enriched the plethora of existing practical forecasting approaches in the tourism domain. Benchmarking demonstrates that the proposed model outperforms a competitive ARIMA model and official forecasts. The practical implications are also discussed in this paper.

scholarly journals Evaluation of Long Memory on the Malaysia Exchange Rate Market

2018 ◽  
pp. 653-656
Author(s):  
Atikullah Ibrahim ◽  
Siti Aida Sheikh Hussin ◽  
Zalina Zahid ◽  
SitiShalizaMohd Khairi
Keyword(s):  
Exchange Rate ◽  
Long Memory ◽  
Arima Model ◽  
Likelihood Estimation ◽  
Model Forecast ◽  
Monthly Data ◽  
The Us ◽  
Us Dollar ◽  
Arfima Model

This research evaluates the presence of long memory or long-term dependence on the Malaysian exchange rate. Daily, weekly and monthly data are evaluated against the US dollar (USD) covering from January 2005 to March 2018. Evaluation of long memory is based on the Geweke and Porter-Hudak estimation and the Maximum Likelihood Estimation. The result suggests the presence of long memory on all the daily, weekly and monthly data. Results show that shock on the Malaysian exchange rate persist longer than expected. The forecast capability also concludes that addition of the long memory presence from ARIMA model to ARFIMA model could improve the model forecast.

scholarly journals Methodology of Multi-criteria Analysis of Changes in Unemployment Rates in Selected World Economies and Forecasting with the ARIMA Model of the US Unemployment Rate for the Future

2020 ◽  
Vol 15 (1) ◽  
pp. 71-85
Author(s):  
Bartosz Kozicki ◽  
Jan Žukovskis ◽  
Grzegorz Mizura
Keyword(s):  
Unemployment Rate ◽  
Arima Model ◽  
Unemployment Rates ◽  
The Us ◽  
The Future ◽  
Multi Criteria Analysis

W artykule przedstawiono metodykę wielokryterialnej analizy stóp procentowych bezrobocia w wybranych gospodarkach światowych oraz próby przeprowadzenia prognozowania stopy bezrobocia w USA na trzy przyszłe okresy. Badania rozpoczęto od analizy wielowymiarowej zmienności stóp procentowych bezrobocia w wybranych gospodarkach światowych w ujęciu sześciomiesięcznym w latach 2011-2018. Następnie przeprowadzono jej ocenę. Dalszym etapem badania była analiza i ocena szeregu czasowego danych dotyczących stóp procentowych bezrobocia w USA w ujęciu dynamicznym. Następnie zbudowano model prognostyczny ARIMA i wykonano prognozowanie na trzy przyszłe okresy.

scholarly journals Forecasting of Primary Energy Consumption Data in the United State: a comparison between ARIMA and Holter Winters Models

2017 ◽  
Author(s):  
Abdul Rahman ◽  
Ansari Saleh Ahmar
Keyword(s):  
Energy Consumption ◽  
Arima Model ◽  
Primary Energy ◽  
Primary Energy Consumption ◽  
Seasonal Model ◽  
Consumption Data ◽  
The Us ◽  
Total Data ◽  
Multiplicative Type ◽  
Design And Manufacture

This research has a purpose to compare ARIMA Model and Holt-Winters Model based on MAE, RSS, MSE, and RMS criteria in predicting Primary Energy Consumption Total data in the US. The data from this research ranges from January 1973 to December 2016. This data will be processed by using R Software. Based on the results of data analysis that has been done, it is found that the model of Holt-Winters Additive type (MSE: 258350.1) is the most appropriate model in predicting Primary Energy Consumption Total data in the US. This model is more appropriate when compared with Holt-Winters Multiplicative type (MSE: 262260,4) and ARIMA Seasonal model (MSE: 723502,2).Paper ini dipresentasikan pada The 3th International Conference on Green Design and Manufacture 2017 (Krabi, Thailand, 29-30 April 2017), diunggah oleh Ansari Saleh Ahmar

scholarly journals Multivariate Time Series in Macroeconomics

2020 ◽  
Vol 11 (2) ◽  
pp. 151
Author(s):  
Ahmadi Ahmadi ◽  
R Adisetiawan
Keyword(s):  
Inflation Rate ◽  
Stock Exchange ◽  
Multivariate Time Series ◽  
Arima Model ◽  
Gold Price ◽  
Price Inflation ◽  
Vector Error Correction ◽  
Jones Index ◽  
The Us ◽  
Us Dollar

Gold is one of the most popular commodities and investment alternatives. Gold prices are thought to be influenced by several other factors such as the US Dollar, oil price, inflation rate, and stock exchange so that gold price modeling is not only influenced by its own value. This research was conducted to determine the best forecasting model and to find out what factors influence the price of gold. This research modeled the price of gold in a multivariate and reviewed the univariate modeling that will be used as a comparison model of multivariate modeling. Univariate modeling is done using ARIMA model where the modeling results state that gold price fluctuations as white noise. Multivariate gold price modeling is done using Vector Error Correction Model with gold, oil, US Dollar and Dow Jones indices, and inflation rate as predictors. The results showed that the VECM model has been able to model the gold price well and all the factors studied influenced the gold price. The US dollar and oil prices are negatively correlated with gold prices, while the inflation rate is positively correlated with gold prices. The Dow Jones index was positively correlated with gold prices in just two periods.

The Eleventh Circuit Holds that Agreements in which Pharmaceutical Companies Pay Generic Companies Not to Compete May be Valid

2004 ◽  
Vol 32 (1) ◽  
pp. 181-184
Author(s):  
Amy Garrigues
Keyword(s):  
Pharmaceutical Companies ◽  
Court Decisions ◽  
Patent Holder ◽  
Trial Court ◽  
Court Of Appeals ◽  
The Us ◽  
Antitrust Laws ◽  
Per Se ◽  
Appeals Court ◽  
Two Sides

On September 15, 2003, the US. Court of Appeals for the Eleventh Circuit held that agreements between pharmaceutical and generic companies not to compete are not per se unlawful if these agreements do not expand the existing exclusionary right of a patent. The Valley DrugCo.v.Geneva Pharmaceuticals decision emphasizes that the nature of a patent gives the patent holder exclusive rights, and if an agreement merely confirms that exclusivity, then it is not per se unlawful. With this holding, the appeals court reversed the decision of the trial court, which held that agreements under which competitors are paid to stay out of the market are per se violations of the antitrust laws. An examination of the Valley Drugtrial and appeals court decisions sheds light on the two sides of an emerging legal debate concerning the validity of pay-not-to-compete agreements, and more broadly, on the appropriate balance between the seemingly competing interests of patent and antitrust laws.

The Effects of Significant International Sports Events on Hungarian Suicide Rates

Crisis ◽  
2016 ◽  
Vol 37 (2) ◽  
pp. 148-154 ◽  
Author(s):  
Karoly Bozsonyi ◽  
Peter Osvath ◽  
Sandor Fekete ◽  
Lajos Bálint
Keyword(s):  
Significant Relationship ◽  
Olympic Games ◽  
Arima Model ◽  
Age Groups ◽  
The Elderly ◽  
Intervention Analysis ◽  
Middle Aged ◽  
Sports Events ◽  
Sport Events ◽  
The Olympic Games

Abstract. Background: Several studies found a significant relationship between important sport events and suicidal behavior. Aims: We set out to investigate whether there is a significant relationship between the raw suicide rate and the most important international sports events (Olympic Games, FIFA World Cup, UEFA European Championship) in such an achievement-oriented society as the Hungarian one, where these sport events receive great attention. Method: We examined suicide cases occurring over 15,706 days between January 1, 1970, and December 31, 2012 (43 years), separately for each gender. Because of the age-specific characteristics of suicide, the effects of these sport events were analyzed for the middle-aged (30–59 years old) and the elderly (over 60 years old) generations as well as for gender-specific population groups. The role of international sport events was examined with the help of time-series intervention analysis after cyclical and seasonal components were removed. Intervention analysis was based on the ARIMA model. Results: Our results showed that only the Olympic Games had a significant effect in the middle-aged population. Neither in the older male nor in any of the female age groups was a relationship between suicide and Olympic Games detected. Conclusion: The Olympic Games seem to decrease the rate of suicide among middle-aged men, slightly but significantly.

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