Augmented Dickey-Fuller Test and the Lag Length Selection Problem

2011 ◽  
Vol 130-134 ◽  
pp. 3019-3022 ◽  
Author(s):  
Lu Deng
Keyword(s):  
Information Criteria ◽  
Selection Problem ◽  
Selection Methods ◽  
Leg Length ◽  
Selection Models ◽  
Proper Size ◽  
Augmented Dickey Fuller ◽  
Modified Information Criteria ◽  
Adf Test

Many studies indicated that ADF test is very sensitive to different leg length selection models. Based on Hall, and Ng, Perron’s works, this article simulates a more general ARIMA(0,1,q) process and compares the influence of different selection methods to the size and power of the ADF test. Finally, it is proved that the Modified Information Criteria always shows a more proper size and the General to Special Criteria has more robust ADF test properties.

scholarly journals Sarima Modeling of Monthly Temperature in the Northern part of Ghana

2021 ◽  
pp. 37-45
Author(s):  
Emmanuel Ayitey ◽  
Justice Kangah ◽  
Frank B. K. Twenefour
Keyword(s):  
Northern Region ◽  
Temperature Data ◽  
Information Criteria ◽  
Sarima Model ◽  
Monthly Temperature ◽  
Augmented Dickey Fuller ◽  
Best Fitting ◽  
Adf Test ◽  
Fitting Model ◽  
Sarima Models

The Sarima model is used in this study to forecast the monthly temperature in Ghana's northern region. The researchers used temperature data from January 1990 to December 2020. The temperature data was found to be stationary using the Augmented Dickey Fuller (ADF) test. The ACF and PACF plots proposed six SARIMA models: SARIMA (1,0,0) (1,0,0) (12), SARIMA (2,0,0) (1,0,0) (12), SARIMA (1,0,1) (1,0,0) (12), SARIMA (0,0,1) (1,0,0) (12), SARIMA (0,0,1) (0,0,1) (12), SARIMA (0,0,1) (0,0,1) (12). The best model was chosen based on the lowest Akaike Information Criteria (AICs) and Bayesian Information Criteria (BIC) values. The Ljung-Box data, among others, were used to determine the model's quality. All diagnostic tests are passed by the SARIMA (1,0,0) (1,0,0) (12) model. As a result, the SARIMA (1,0,0) (1,0,0) (12) is the best-fitting model for predicting monthly temperatures in Ghana's northern region.

scholarly journals Time Series Analysis of Road Traffic Accidents in Ghana

2021 ◽  
pp. 12-20
Author(s):  
Frank B. K. Twenefour ◽  
Emmanuel Ayitey ◽  
Justice Kangah ◽  
Lewis Brew
Keyword(s):  
Time Series ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Model Building ◽  
Road Traffic ◽  
Information Criteria ◽  
Augmented Dickey Fuller ◽  
Accident Data ◽  
Adf Test

This study uses Time Series models to predict the annual traffic accidents in Ghana. The traffic accidents data spanning from January 1990 to December 2019 was used. The Box-Jenkins model building strategy was used. The Augmented Dickey Fuller (ADF) test showed that the accident data was stationary. Three ARMA models were suggested based on the ACF and PACF plots of the differenced series, these were ARMA (0,0), ARIMA (1,0), and ARMA (2,0). The model with the smallest corrected Akaike Information Criteria (AICs) and Bayesian Information Criteria (BIC) was chosen as the best model. The Ljung-Box statistics among others were used in assessing the quality of the model. ARMA (1,0) was the best model for the Ghana annual Traffic Accident data. The results showed that, from January to July, it would be difficult to make accurate estimates of the number of road incidents for the years leading up to 2020. This was due to the fact that the white noise process values were statistically independent at various times.

scholarly journals PRICE INTERACTIONS AND CAUSAL RELATIONSHIPS AMONG CORN, EXCHANGE RATE AND ANIMAL PROTEIN SOURCES IN NIGERIA

2021 ◽  
Vol 59 (1) ◽  
Author(s):  
Unekwu Onuche
Keyword(s):  
Exchange Rate ◽  
Granger Causality ◽  
Poultry Meat ◽  
Causality Test ◽  
Vector Autoregressive ◽  
Meat Price ◽  
Augmented Dickey Fuller ◽  
Causality Tests ◽  
Short Run ◽  
Adf Test

Price transmissions between corn, exchange rate, poultry meat, and fish were investigated using the data from OECD-FAO for the years 1990-2019, to establish the existence of long-term relationships between them and identify their directions of causality, in order to elicit investmentaiding facts. The augmented Dickey-Fuller (ADF) test, the Johansen cointegration approach and the Granger causality test were employed. Following the ADF test, all series are I(1), while the cointegration test indicates short-run dynamics between them. The Vector Autoregressive (VAR) system reveals that poultry meat price influences all variables, prices of poultry meat and exchange rate relate positively to their own lags, and exchange rate relates positively to lags of poultry meat prices. A positive relationship was noticed between fish price and lags of poultry meat price, while corn price relates positively with lags of poultry meat price. Granger causality tests indicate unidirectional drives from poultry price to fish price, the exchange rate to fish price and poultry meat price to corn price. Responses from prices of fish, corn and poultry to innovations from exchange rate are negative, while positive responses exist in other scenarios. Exchange rate stabilization will mitigate external risks, especially to the fisheries sector, while corn farmers can increase profits in the short-run by exploring knowledge of poultry meat price movements.

scholarly journals Learning Coefficient of Vandermonde Matrix-Type Singularities in Model Selection

Entropy ◽  
2019 ◽  
Vol 21 (6) ◽  
pp. 561
Author(s):  
Miki Aoyagi
Keyword(s):  
Model Selection ◽  
Information Criteria ◽  
Learning Systems ◽  
Vandermonde Matrix ◽  
Selection Methods ◽  
Learning Models ◽  
Matrix Type ◽  
Log Canonical Threshold ◽  
Log Canonical ◽  
Blowing Up

In recent years, selecting appropriate learning models has become more important with the increased need to analyze learning systems, and many model selection methods have been developed. The learning coefficient in Bayesian estimation, which serves to measure the learning efficiency in singular learning models, has an important role in several information criteria. The learning coefficient in regular models is known as the dimension of the parameter space over two, while that in singular models is smaller and varies in learning models. The learning coefficient is known mathematically as the log canonical threshold. In this paper, we provide a new rational blowing-up method for obtaining these coefficients. In the application to Vandermonde matrix-type singularities, we show the efficiency of such methods.

Bitcoin, Litecoin, and the Euro: an annualized volatility analysis

2019 ◽  
Vol 37 (2) ◽  
pp. 229-242 ◽  
Author(s):  
Cynthia Miglietti ◽  
Zdenka Kubosova ◽  
Nicole Skulanova
Keyword(s):  
Exchange Rate ◽  
Financial Markets ◽  
Design Methodology ◽  
Daily Basis ◽  
Information Criteria ◽  
Content Type ◽  
Statistical Measures ◽  
Augmented Dickey Fuller ◽  
Volatility Analysis ◽  
Exchange Rate Changes

Purpose This paper aims to empirically investigate the volatility of Bitcoin, Litecoin and the Euro. Design/methodology/approach The authors use quantitative methodologies to assess the annualized volatility of two cryptocurrencies and one international fiat currency. The exchange rate of the currencies is monitored on a daily basis using 1,460 observations from January 1, 2014 to December 31, 2017. The models used include the augmented Dickey–Fuller test, Akaike Information Criteria, autocorrelation function and exchange rate changes determining which currency is the most volatile. Findings The findings indicate, based on the statistical measures used, including the standard deviation of selected currencies and annualized volatility, that Litecoin is more volatile than Bitcoin and the Euro and that Bitcoin is more volatile than the Euro. This furthers previous research on cryptocurrency volatility. Originality/value The paper provides compelling evidence about the volatility of Litecoin and Bitcoin. The volatility of cryptocurrencies is furthered with data that are more current. The findings are important for investors, financial markets and central banks.

scholarly journals Effect of Interest Rate on Stock Prices in Ghana

2021 ◽  
Vol 12 (1(S)) ◽  
pp. 1-7
Author(s):  
Peter Arhenful ◽  
Augustine Kwadwo Yeboah ◽  
Kofi Sarfo Adjei
Keyword(s):  
Interest Rate ◽  
Interest Rates ◽  
Stock Prices ◽  
Time Series Data ◽  
Stock Exchange ◽  
Ordinary Least Squares ◽  
Series Data ◽  
Augmented Dickey Fuller ◽  
Ghana Stock Exchange ◽  
Adf Test

The paper assesses the effect of interest rate on stock prices, with emphases on Ghana Stock Exchange; using monthly time series data from July 2007 to December 2019. The Augmented Dickey-Fuller (ADF) test was employed to establish the stationarity properties of the data or otherwise. Using the Ordinary Least Squares (OLS) estimation technique of Multiple Regression, the results (? = – 0.891, p < 0.05) revealed an indirect association between interest rates and stock prices in the Ghanaian context; which is consistent with the theoretical conclusion that an increase in interest rate results in a decrease in stock prices. Thus, in the light of this finding, it was recommended that policymakers should consider the stock market dynamics due to the significant relationship that exists between the two macroeconomic variables.

scholarly journals Dynamic Interaction Between Nifty 50 and Nifty Sectoral Indices: An Empirical Study on Indian Stock Indices

2021 ◽  
Vol 29 (02) ◽  
pp. 17-24
Author(s):  
Ramya K ◽  
◽  
Bhuvaneshwari D ◽  
Keyword(s):  
Stock Exchange ◽  
Granger Causality Test ◽  
Dynamic Interaction ◽  
Stock Index ◽  
Causality Test ◽  
Financial Planners ◽  
Augmented Dickey Fuller ◽  
Johansen Cointegration Test ◽  
Financial Awareness ◽  
Adf Test

This study aims to determine the cointegrating and causal relationship between Nifty 50 and Nifty sectoral indices. Historical index data of the select indices were collected from the National Stock Exchange (NSE) database for the period Jan 2014 - Dec 2018. Appropriate Econometric tools - Augmented Dickey-Fuller (ADF) test, Phillips and Perron (PP) test, regression model, Granger causality test, and Johansen cointegration test were used to analyze the data. The findings of the study imply that the movements of Nifty sectoral index prices could determine the flow of stock index prices, i.e., Nifty 50 and vice versa during the period of the study which could also help the policymakers and financial planners in providing financial awareness to investors and clients in decision making.

scholarly journals Investigating the Impact of External Debt on Economic Growth: A Case Study of Pakistan

2021 ◽  
Vol 4 (2) ◽  
pp. 41-51
Author(s):  
IRUM SAJJAD ◽  
IRUM SAJJAD ◽  
DR. MUHAMMAD AZAM KHAN
Keyword(s):  
Economic Growth ◽  
Growth Rate ◽  
External Debt ◽  
Gdp Growth ◽  
Policy Makers ◽  
Explanatory Variables ◽  
Gdp Growth Rate ◽  
Augmented Dickey Fuller ◽  
The Impact ◽  
Adf Test

This article is an attempt to evaluate the effect of external debt on economic growth for during the period of 1980–2016. The Augmented Dickey Fuller (ADF) test is used for determining stationarity, whereas the ADF test results exhibit that the variables used found are . The empirical results indicate that external debt and total debt service have deleterious and statistically significant impacts on GDP growth rate. The other explanatory variables namely human capital by life expectancy, exports, and Foreign Direct Investment (FDI)reveals significantly positive significant influence on GDP growth rate. Appropriate policy should be adopted by the policy makers to reduce external debt, increase volume of exports and enhance more foreign investment, it will boost economic growth in the country.

Sign in / Sign up

Export Citation Format

Share Document