scholarly journals A Nonlinear Autoregressive Distributed Lag (NARDL) Analysis of West Texas Intermediate Oil Prices and the DOW JONES Index

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 4011
Author(s):  
David E. Allen ◽  
Michael McAleer
Keyword(s):  
Crude Oil ◽  
Oil Prices ◽  
Stationary Time Series ◽  
Bounds Testing ◽  
Jones Index ◽  
Distributed Lag ◽  
Price Series ◽  
Autoregressive Distributed Lag ◽  
West Texas ◽  
Nonlinear Autoregressive

The paper features an examination of the link between the behaviour of oil prices and DowJones Index in a nonlinear autoregressive distributed lag nonlinear autoregressive distributed lag (NARDL) framework. The attraction of NARDL is that it represents the simplest method available of modelling combined short- and long-run asymmetries. The bounds testing framework adopted means that it can be applied to stationary and non-stationary time series vectors, or combinations of both. The data comprise a monthly West Texas Intermediate (WTI) crude oil series from Federal Reserve Bank of St Louis (FRED), commencing in January 2000 and terminating in February 2019, and a corresponding monthly DOW JONES index adjusted-price series obtained from Yahoo Finance. Both series are adjusted for monthly USA CPI values to create real series. The results of the analysis suggest that movements in the lagged real levels of monthly WTI crude oil prices have very significant effects on the behaviour of the DOW JONES Index. They also suggest that negative movements have larger impacts than positive movements in WTI prices, and that long-term multiplier effects take about 9 to 12 months to take effect.

scholarly journals A Nonlinear Autoregressive Distributed Lag (NARDL) Analysis of the FTSE and S&P500 Indexes

Risks ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 195
Author(s):  
David Allen ◽  
Michael McAleer
Keyword(s):  
Weak Form ◽  
Stationary Time Series ◽  
Bounds Testing ◽  
Distributed Lag ◽  
Price Series ◽  
Autoregressive Distributed Lag ◽  
Long Run ◽  
Quantile Regression Analysis ◽  
The Impact ◽  
Nonlinear Autoregressive

The paper features an examination of the link between the behaviour of the FTSE 100 and S&P500 Indexes in both an autoregressive distributed lag ARDL, plus a nonlinear autoregressive distributed lag NARDL framework. The attraction of NARDL is that it represents the simplest method available of modelling combined short- and long-run asymmetries. The bounds testing framework adopted means that it can be applied to stationary and non-stationary time series vectors, or combinations of both. The data comprise a daily FTSE adjusted price series, commencing in April 2009 and terminating in March 2021, and a corresponding daily S&P500 Index adjusted-price series obtained from Yahoo Finance. The data period includes all the gyrations caused by the Brexit vote in the UK, beginning with the vote to leave in 2016 and culminating in the actual agreement to withdraw in January 2020. It was then followed by the impact of the global spread of COVID-19 from the beginning of 2020. The results of the analysis suggest that movements in the contemporaneous levels of daily S&P500 Index levels have very significant effects on the behaviour of the levels of the daily FTSE 100 Index. They also suggest that negative movements have larger impacts than do positive movements in S&P500 levels, and that long-term multiplier impacts take about 10 days to take effect. These effects are supported by the results of quantile regression analysis. A key result is that weak form market efficiency does not apply in the second period.

Factors Determining Gold Prices in Malaysia

2019 ◽  
Vol 1 (2) ◽  
pp. 75-82
Author(s):  
Anis Mat Dalam ◽  
Noorhaslinda Kulub Abd Rashid ◽  
Jaharudin Padli
Keyword(s):  
Crude Oil ◽  
Time Series Data ◽  
Oil Prices ◽  
Series Data ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Crude Oil Prices ◽  
Inflation Rates ◽  
Ardl Approach ◽  
Gold Reserve

Gold is a valuable asset to a country because of its liquidity. Gold reserve can stabilize the currency in a country. The objective of this paper is to identify the factors contributing to the volatility of gold prices, such as Real Malaysia GDP, inflation rates, crude oil prices and exchange rates. The data was analysed using Autoregressive Distributed Lag (ARDL) approach with time series data, with 30-year coverage from 1987 to 2016. Findings showed that only Real Malaysia GDP and crude oil prices were significantly related to gold prices. As a conclusion, this study can be used as reference by other investors. The author suggests to other researchers to further improve upon this study by adding more variables or diversifying the variables that relate to volatility of gold prices.

scholarly journals ASYMMETRIC EFFECT OF CRUDE OIL AND PALM OIL PRICES ON ECONOMIC GROWTH: EVIDENCE FROM INDONESIA

2020 ◽  
Vol 23 (2) ◽  
pp. 253-268
Author(s):  
KP Prabheesh ◽  
Nisful Laila
Keyword(s):  
Economic Growth ◽  
Crude Oil ◽  
Palm Oil ◽  
Oil Prices ◽  
Asymmetric Effect ◽  
Linear Effect ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Non Linear ◽  
The Impact

This paper empirically examines the impact of the price of crude oil petrol and palm oil on Indonesia's economic growth. Using quarterly data from 2000 to 2019 and linear, and non-linear autoregressive distributed lag (ARDL) model to cointegration, the study finds 1) A significant non-linear effect of oil prices on country's output. 2) The palm oil price changes have a higher effect on the country's output as compared to petroleum prices. 3) A decline in palm price in the international market leads to a higher adverse effect on the country's economic growth as compared to petroleum prices.

scholarly journals FDI location and exchange rates. is there really a relationship between the two?

2015 ◽  
Vol 13 (1) ◽  
pp. 642-651
Author(s):  
Kunofiwa Tsaurai
Keyword(s):  
South Africa ◽  
Exchange Rates ◽  
Coming Out ◽  
Causal Relation ◽  
Exact Nature ◽  
Bounds Testing ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Long Run ◽  
Short Run

The exchange rate led foreign direct investment (FDI), FDI led exchange rates and feedback effect hypotheses summarise the literature around the nature of the relationship between FDI and exchange rates. So many authors on this subject over a long period have been found to generally side with of the above-mentioned hypothesis or another without a consensus. Despite this lack of consensus with regard to the exact nature of the causal relation between these two variables, what is coming out clearly from the literature is that there indeed exist a relationship between FDI and exchange rates. The lack of consensus has prompted this current study that used the ARDL (Autoregressive distributed lag)-bounds testing approach. The study revealed the existence of causality from (1) the rand value to FDI in the long run and (2) FDI to the rand value only in the short run in South Africa. The author recommends that policies which strengthen the value of the rand should be put in place in order to attract FDI in the long run. The flow of FDI into South Africa will in turn not only stabilises the value of the rand.

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