This work concerns itself with the intervention analysis of the British pound, GBP, and the Unite... more This work concerns itself with the intervention analysis of the British pound, GBP, and the United States dollar, USD.It has been observed that the GBP has fallen sharply after June 23, 2016 relative to the USD. It is being speculated that this is due to the recent exit of Great Britain from the European Union EU. A realization of the daily exchange rate series from 17 th March to 12 th September. 2016 is analyzed by ARIMA methods. The intervention point is June 23, 2016, after which there is a sharp fall in the relative value of the GBP. This fall is shown to be statistically significant. The pre-intervention series is observed to follow an ARIMA(1,1,0) model. Following the nature of this fall, an adequate intervention model has been proposed and fitted.
Management and Administrative Sciences Review, 2017
An examination of the daily exchange rates of the Japanese Yen and the Nigerian Naira between May... more An examination of the daily exchange rates of the Japanese Yen and the Nigerian Naira between May 1, 2016 and October 28, 2016 reveals an abrupt change on June 20, 2016 in further favour of the Yen. This change is significant as the pre-intervention series has a mean of 1.845 with a standard deviation of 0.0335 and the post-intervention mean of 2.9941 and standard deviation of 0.1965. A situation like this calls for an intervention on the part of the Nigerian Government. The pre-intervention data is modelled as an ARIMA(13,1,0) model. Post-intervention forecasts on the basis of the afore-mentioned model are obtained. The difference between these forecasts and the corresponding observations is modelled for the intervention model. The model parameters are observed significant indicating the significance of the model. Intervention may be carried out on the basis of the fitted model.
We consider a dynamic stochastic knapsack problem with the aim of minimizing the cost of the sele... more We consider a dynamic stochastic knapsack problem with the aim of minimizing the cost of the selected items whose weights follow a mixture of Poisson and Exponential distribution using additive model. A graphical presentation of our contagious distribution with different values of both parameters and range of X is made to show their behaviors. We also propose an algebraic model for the problem.
International Journal of Sustainable Construction Engineering and Technology, 2017
Variations in approved cost of projects are common and could be triggered by a fluctuation in int... more Variations in approved cost of projects are common and could be triggered by a fluctuation in interest rates and variation project duration. The paper aimed to explain the effect of time overrun (TO) and inflation rate on project completion cost (PCO). Variations in costs and durations of projects were calculated for 250 government and private building projects executed between 2005 and 2015, while inflation rates for the last quarter of these years were used. A multiple regression analysis of cost overrun as the endogenous variable, with time overrun and inflation rates as the exogenous variable was conducted for private and government funded projects. The result revealed that the cost overrun can be predicted by the equations; predicted private cost overrun = -669673.60 + 50182.35 (time overrun) + 106690.20 (inflation rate), and predicted government cost overrun = -9805996 – 148721.90 (time overrun) + 1266038 (inflation rate) respectively for private and government funded projects...
Monthly distribution of household kerosene (HHK) in Nigeria from January 2009 to December 2015 ex... more Monthly distribution of household kerosene (HHK) in Nigeria from January 2009 to December 2015 experienced a sudden jump as from January 2013. It is believed that this increase was caused by the deregulation of the downstream sector of the petroleum industry of Nigeria in January 2012. This is an intervention case with January 2013 as the point of intervention. It is being speculated that what is responsible for this is the deregulation of the downstream sector of the petroleum industry. The pre-intervention distribution is adjudged stationary and follows an ARMA(1,1) model. Post-intervention forecasts based on this model are computed and the difference between these forecasts and their corresponding actual observations is modelled to obtain the intervention transfer function. The overall intervention model is observed to generate forecasts that agree closely with the original data. Intervention measures may therefore be based on this model.
A realisation, TBR, of Nigeria Treasury Bill Rates from January 2006 to December 2014 is analysed... more A realisation, TBR, of Nigeria Treasury Bill Rates from January 2006 to December 2014 is analysed by seasonal ARIMA methods. The time plot of the realisation reveals an overall downward trend from 2006 to 2009 followed by an overall upward trend up to 2013. Twelve-monthly differencing of TBR yields the series SDTBR which has an overall upward trend. Nonseasonal differencing of SDTBR yields the series DSDTBR with an overall horizontal trend and no clear seasonality. By the Augmented Dickey-Fuller Unit Root Test both TBR and SDTBR are adjudged non-stationary whereas DSDTBR is adjudged stationary. The correlogram of DSDTBR has a negative significant spike in the autocorrelation function at lag 12, an indication of seasonality of period 12 months and the presence of a seasonal moving average component of order one. By a novel proposal credited to Suhartono, initially the (0, 1, 1)x(0, 1, 1)12 SARIMA model is fitted. The non-significance of the lag 13 coefficient suggests the additive SA...
The daily exchange rates of the Nigerian Naira (NGN) and West African CFA franc (XOF) from Thursd... more The daily exchange rates of the Nigerian Naira (NGN) and West African CFA franc (XOF) from Thursday, 14 th March, 2013 to Saturday, 23 rd November 2013 are being modeled by Seasonal Autoregressive Integrated Moving Average (SARIMA) methods. This realization of the time series, referred to as NXOF, is a generally decreasing one, reflecting the relative depreciation of the Naira within the period of interest. As expected the Augmented Dickey Fuller (ADF) Tests adjudge it to be non-stationary. There is indication that NXOF is seasonal of period 7 days, there being a tendency for weekly maximums around Mondays and minimums around Sundays. A seasonal (i.e. 7-day) differencing produces a series SDNXOF with an overall horizontal trend. A non-seasonal differencing of SDNXOF yields a series DSDNXOF with an overall horizontal trend. Both SDNXOF and DSDNXOF are adjudged stationary by the ADF test. By the autocorrelation functions of SDNXOF and DSDNXOF two SARIMA models are suggestive: the (1, ...
Nigerian unemployment data is modelled by Box-Jenkins approach and the use of automatic model sel... more Nigerian unemployment data is modelled by Box-Jenkins approach and the use of automatic model selection criteria Akaike Information criterion (AIC) and Schwarz Information Criterion (SIC). It is inferred that the most adequate model is autoregressive integrated moving average of orders 1, 2 and 1(ARIMA(1 ,2 ,1)). Forecasts are obtained on the basis of the model.
Sudanese Monthly Inflation series is modelled by Seasonal Autoregressive Integrated Moving Averag... more Sudanese Monthly Inflation series is modelled by Seasonal Autoregressive Integrated Moving Average methodology. The realization analyzed spans from 2005 to 2015. The time plot shows a generally positive trend. An inspection of the series reveals a yearly seasonal pattern. Augmented Dickey Fuller test suggests that this original series is not stationary. A seasonal (i.e. twelve-monthly) differencing proves not to be enough to render the series stationary. A further non-seasonal differencing renders the series stationary. The autocorrelation structure of this resultant time series suggests some SARIMA models including those of orders: (1,1,0)x(1,1,1) 12 , (1,1,1)x(1,1,1) 12 and (0,1,1)x(1,1,1) 12 . Diagnostic checking procedures applied suggest the comparative adequacy of the SARIMA(1,1,0)x(1,1,1) 12 model. Forecasting and simulation of the series may therefore be based on it.
International Journal of Hydrology Science and Technology, 2017
Time series analysis and forecasting has become a major tool in different applications in hydrolo... more Time series analysis and forecasting has become a major tool in different applications in hydrology and environmental management fields. Linear stochastic models known as multiplicative seasonal autoregressive integrated moving average (SARIMA) model were used to simulate and forecast monthly streamflow of Rahad River, Sudan. For the analysis, monthly streamflow data for the years 1972 to 2009 were used. A visual inspection of the time plot gives the expected impression of a generally horizontal trend and 12-month seasonal periodicity. The seasonality observed in auto correlation function (ACF) and partial auto correlation function (PACF) plots of monthly streamflow data was removed using first order seasonal differencing prior to the development of the SARIMA model. Interestingly, the SARIMA (2, 0, 0) × (0, 1, 1)12 model developed was found to be most suitable for simulating monthly streamflow for Rahad River. The model was found appropriate to forecast three years of monthly streamflow and assist decision makers to establish priorities for water demand.
This study looked into the supremacy of GARCH modelling over ARIMA modelling of Nigerian export c... more This study looked into the supremacy of GARCH modelling over ARIMA modelling of Nigerian export commodity price index series. Data was collected from the Central Bank database from January 2000 to December 2020 and was analyzed using EVIEWS statistical software. The time plot of Nigerian export commodity price index (figure 1) shows that the series changes over time indicating that there is clearly a secular trend in it. By the Augmented Dickey-Fuller Test in Table 1, the series is non-stationary with p = 0.8989 > 0.05. Therefore there was need for differencing (see figure 2). After the series was differenced, a stationarity test was ran for the differenced series. The Augmented Dickey Fuller test of Table 2 shows that the differenced series is stationary with p = 0.0000 < 0.05, indicating that the trend has been removed through differencing. The EVIEWS statistical software was used in estimating the model. The correlogram of Figure 3 has spikes at lag 1 for the Autocorrelation function as well as for the partial autocorrelation function suggesting an ARMA (1,1). Then ARMA (1,1) was estimated for the differenced series (table 3) which showed that the series does not follow an ARMA(1,1) as suspected, the coefficients of the parameters are both non-significant statistically. After the failure of the ARIMA(1,1,1) we fitted the ARIMA(1,1,0) and ARIMA(0,1,1) to the original data. ARIMA(1, 1, 0), ARIMA (0,1, 1) and GARCH (1,1) having met the required assumptions as the appropriate model was used to estimate its parameters. From the result obtained, it was reveal that by the AIC, SC and HQ terms, the GARCH (1,1) model when compared to other models has proven to be adequate model for the modelling of differenced Nigerian Export Commodity Price Index series.
The paper sought to investigate the effect of the bureau de change (United State Dollar, USD) and... more The paper sought to investigate the effect of the bureau de change (United State Dollar, USD) and Nigeria naira (NGN) exchange rate on economic recession using intervention analysis from June 2017 to March 2021. The data was taken from the website of the central bank of Nigeria (cbn.org). The study adopted augmented dickey fuller test for checking the stationarity. The pre-intervention data spectacles a negative slope and it was non-stationary but after the first difference occurred it became stationary.
Many economic and business time series exhibit seasonal tendencies. Analytical techniques for suc... more Many economic and business time series exhibit seasonal tendencies. Analytical techniques for such series which take into account these tendencies have engaged the attention of researchers of recent. One such modelling technique is the Box-Jenkins seasonal autoregressive integrated moving average (SARIMA) technique. A novel algorithm is hereby proposed. This algorithm which is based on autoregressive-moving average duality arguments is applied to model daily exchange rates of the British pound sterling and the European Euro currencies. The data analyzed are 178 daily pound/euro exchange rates 13 th December 2015 to 7 th June 2016. Application of the algorithm using the SARIMA(1,1,1)x(1,1,1) 7 template as proposed yields a SARIMA(1,1,1)x(0,1,1) 7 model. Further 8 values from 8 th June to 15 th June 2016 are used for out-of-sample comparison of observations with forecasts. The adequacy of the chosen model is not in doubt since the residuals are uncorrelated and are normally distribute...
A seasonal autoregressive integrated moving average (SARIMA) model proposed and fitted to observe... more A seasonal autoregressive integrated moving average (SARIMA) model proposed and fitted to observed lemon Autochton monthly prices has been included among marketing information system tools for citrus production in the Lattakia Region of Syria. The order of the model is (2, 1, 0)x(1, 0, 1) 12 chosen on the basis of minimum mean square error (MSE) and mean absolute error (MAE) among the set of SARIMA models of orders (using the MINITAB software. In this work a re-analysis of the data using Eviews 7 confirms that the chosen model is still the best on minimum Akaike Information Criterion (AIC) grounds, each of the rest of the models being non-stationary. Moreover based on the observed autocorrelation structure the SARIMA(0, 1, 1)x(1, 0, 1) 12 model is even better than the chosen model on all counts. Hence it is hereby proposed as the most adequate model to adopt for the purpose of the price prediction.
This research is about an intervention on daily exchange rates of the Nigerian Naira (NGN) and it... more This research is about an intervention on daily exchange rates of the Nigerian Naira (NGN) and its Ugandan counterpart, the Shilling (UGX) observed on 22 nd June 2016. The realization of this time series studied spans from 19 th May 2016 to 17 th November 2016. There is an abrupt jump in the amount of Naira exchanged for a shilling from 0.0509 to 0.0609 from 20 th June to 21 st June 2016 and then to 0.0840 the next day. Instead of coming down it has been moving up. The proposal of an intervention or interrupted time series model to explain this trend of events is the aim of this work. The pre-intervention exchange rates show an initial downward trend up to 26 th May 2016 and then an upward trend. They are adjudged to be non-stationary by the Augmented Dickey Fuller (ADF) test, necessitating their first order differencing. These differences are now stationary and are observed to have a random error fit. Post-intervention forecasts are made on the basis of this pre-intervention model....
This work concerns itself with the intervention analysis of the British pound, GBP, and the Unite... more This work concerns itself with the intervention analysis of the British pound, GBP, and the United States dollar, USD.It has been observed that the GBP has fallen sharply after June 23, 2016 relative to the USD. It is being speculated that this is due to the recent exit of Great Britain from the European Union EU. A realization of the daily exchange rate series from 17 th March to 12 th September. 2016 is analyzed by ARIMA methods. The intervention point is June 23, 2016, after which there is a sharp fall in the relative value of the GBP. This fall is shown to be statistically significant. The pre-intervention series is observed to follow an ARIMA(1,1,0) model. Following the nature of this fall, an adequate intervention model has been proposed and fitted.
Management and Administrative Sciences Review, 2017
An examination of the daily exchange rates of the Japanese Yen and the Nigerian Naira between May... more An examination of the daily exchange rates of the Japanese Yen and the Nigerian Naira between May 1, 2016 and October 28, 2016 reveals an abrupt change on June 20, 2016 in further favour of the Yen. This change is significant as the pre-intervention series has a mean of 1.845 with a standard deviation of 0.0335 and the post-intervention mean of 2.9941 and standard deviation of 0.1965. A situation like this calls for an intervention on the part of the Nigerian Government. The pre-intervention data is modelled as an ARIMA(13,1,0) model. Post-intervention forecasts on the basis of the afore-mentioned model are obtained. The difference between these forecasts and the corresponding observations is modelled for the intervention model. The model parameters are observed significant indicating the significance of the model. Intervention may be carried out on the basis of the fitted model.
We consider a dynamic stochastic knapsack problem with the aim of minimizing the cost of the sele... more We consider a dynamic stochastic knapsack problem with the aim of minimizing the cost of the selected items whose weights follow a mixture of Poisson and Exponential distribution using additive model. A graphical presentation of our contagious distribution with different values of both parameters and range of X is made to show their behaviors. We also propose an algebraic model for the problem.
International Journal of Sustainable Construction Engineering and Technology, 2017
Variations in approved cost of projects are common and could be triggered by a fluctuation in int... more Variations in approved cost of projects are common and could be triggered by a fluctuation in interest rates and variation project duration. The paper aimed to explain the effect of time overrun (TO) and inflation rate on project completion cost (PCO). Variations in costs and durations of projects were calculated for 250 government and private building projects executed between 2005 and 2015, while inflation rates for the last quarter of these years were used. A multiple regression analysis of cost overrun as the endogenous variable, with time overrun and inflation rates as the exogenous variable was conducted for private and government funded projects. The result revealed that the cost overrun can be predicted by the equations; predicted private cost overrun = -669673.60 + 50182.35 (time overrun) + 106690.20 (inflation rate), and predicted government cost overrun = -9805996 – 148721.90 (time overrun) + 1266038 (inflation rate) respectively for private and government funded projects...
Monthly distribution of household kerosene (HHK) in Nigeria from January 2009 to December 2015 ex... more Monthly distribution of household kerosene (HHK) in Nigeria from January 2009 to December 2015 experienced a sudden jump as from January 2013. It is believed that this increase was caused by the deregulation of the downstream sector of the petroleum industry of Nigeria in January 2012. This is an intervention case with January 2013 as the point of intervention. It is being speculated that what is responsible for this is the deregulation of the downstream sector of the petroleum industry. The pre-intervention distribution is adjudged stationary and follows an ARMA(1,1) model. Post-intervention forecasts based on this model are computed and the difference between these forecasts and their corresponding actual observations is modelled to obtain the intervention transfer function. The overall intervention model is observed to generate forecasts that agree closely with the original data. Intervention measures may therefore be based on this model.
A realisation, TBR, of Nigeria Treasury Bill Rates from January 2006 to December 2014 is analysed... more A realisation, TBR, of Nigeria Treasury Bill Rates from January 2006 to December 2014 is analysed by seasonal ARIMA methods. The time plot of the realisation reveals an overall downward trend from 2006 to 2009 followed by an overall upward trend up to 2013. Twelve-monthly differencing of TBR yields the series SDTBR which has an overall upward trend. Nonseasonal differencing of SDTBR yields the series DSDTBR with an overall horizontal trend and no clear seasonality. By the Augmented Dickey-Fuller Unit Root Test both TBR and SDTBR are adjudged non-stationary whereas DSDTBR is adjudged stationary. The correlogram of DSDTBR has a negative significant spike in the autocorrelation function at lag 12, an indication of seasonality of period 12 months and the presence of a seasonal moving average component of order one. By a novel proposal credited to Suhartono, initially the (0, 1, 1)x(0, 1, 1)12 SARIMA model is fitted. The non-significance of the lag 13 coefficient suggests the additive SA...
The daily exchange rates of the Nigerian Naira (NGN) and West African CFA franc (XOF) from Thursd... more The daily exchange rates of the Nigerian Naira (NGN) and West African CFA franc (XOF) from Thursday, 14 th March, 2013 to Saturday, 23 rd November 2013 are being modeled by Seasonal Autoregressive Integrated Moving Average (SARIMA) methods. This realization of the time series, referred to as NXOF, is a generally decreasing one, reflecting the relative depreciation of the Naira within the period of interest. As expected the Augmented Dickey Fuller (ADF) Tests adjudge it to be non-stationary. There is indication that NXOF is seasonal of period 7 days, there being a tendency for weekly maximums around Mondays and minimums around Sundays. A seasonal (i.e. 7-day) differencing produces a series SDNXOF with an overall horizontal trend. A non-seasonal differencing of SDNXOF yields a series DSDNXOF with an overall horizontal trend. Both SDNXOF and DSDNXOF are adjudged stationary by the ADF test. By the autocorrelation functions of SDNXOF and DSDNXOF two SARIMA models are suggestive: the (1, ...
Nigerian unemployment data is modelled by Box-Jenkins approach and the use of automatic model sel... more Nigerian unemployment data is modelled by Box-Jenkins approach and the use of automatic model selection criteria Akaike Information criterion (AIC) and Schwarz Information Criterion (SIC). It is inferred that the most adequate model is autoregressive integrated moving average of orders 1, 2 and 1(ARIMA(1 ,2 ,1)). Forecasts are obtained on the basis of the model.
Sudanese Monthly Inflation series is modelled by Seasonal Autoregressive Integrated Moving Averag... more Sudanese Monthly Inflation series is modelled by Seasonal Autoregressive Integrated Moving Average methodology. The realization analyzed spans from 2005 to 2015. The time plot shows a generally positive trend. An inspection of the series reveals a yearly seasonal pattern. Augmented Dickey Fuller test suggests that this original series is not stationary. A seasonal (i.e. twelve-monthly) differencing proves not to be enough to render the series stationary. A further non-seasonal differencing renders the series stationary. The autocorrelation structure of this resultant time series suggests some SARIMA models including those of orders: (1,1,0)x(1,1,1) 12 , (1,1,1)x(1,1,1) 12 and (0,1,1)x(1,1,1) 12 . Diagnostic checking procedures applied suggest the comparative adequacy of the SARIMA(1,1,0)x(1,1,1) 12 model. Forecasting and simulation of the series may therefore be based on it.
International Journal of Hydrology Science and Technology, 2017
Time series analysis and forecasting has become a major tool in different applications in hydrolo... more Time series analysis and forecasting has become a major tool in different applications in hydrology and environmental management fields. Linear stochastic models known as multiplicative seasonal autoregressive integrated moving average (SARIMA) model were used to simulate and forecast monthly streamflow of Rahad River, Sudan. For the analysis, monthly streamflow data for the years 1972 to 2009 were used. A visual inspection of the time plot gives the expected impression of a generally horizontal trend and 12-month seasonal periodicity. The seasonality observed in auto correlation function (ACF) and partial auto correlation function (PACF) plots of monthly streamflow data was removed using first order seasonal differencing prior to the development of the SARIMA model. Interestingly, the SARIMA (2, 0, 0) × (0, 1, 1)12 model developed was found to be most suitable for simulating monthly streamflow for Rahad River. The model was found appropriate to forecast three years of monthly streamflow and assist decision makers to establish priorities for water demand.
This study looked into the supremacy of GARCH modelling over ARIMA modelling of Nigerian export c... more This study looked into the supremacy of GARCH modelling over ARIMA modelling of Nigerian export commodity price index series. Data was collected from the Central Bank database from January 2000 to December 2020 and was analyzed using EVIEWS statistical software. The time plot of Nigerian export commodity price index (figure 1) shows that the series changes over time indicating that there is clearly a secular trend in it. By the Augmented Dickey-Fuller Test in Table 1, the series is non-stationary with p = 0.8989 > 0.05. Therefore there was need for differencing (see figure 2). After the series was differenced, a stationarity test was ran for the differenced series. The Augmented Dickey Fuller test of Table 2 shows that the differenced series is stationary with p = 0.0000 < 0.05, indicating that the trend has been removed through differencing. The EVIEWS statistical software was used in estimating the model. The correlogram of Figure 3 has spikes at lag 1 for the Autocorrelation function as well as for the partial autocorrelation function suggesting an ARMA (1,1). Then ARMA (1,1) was estimated for the differenced series (table 3) which showed that the series does not follow an ARMA(1,1) as suspected, the coefficients of the parameters are both non-significant statistically. After the failure of the ARIMA(1,1,1) we fitted the ARIMA(1,1,0) and ARIMA(0,1,1) to the original data. ARIMA(1, 1, 0), ARIMA (0,1, 1) and GARCH (1,1) having met the required assumptions as the appropriate model was used to estimate its parameters. From the result obtained, it was reveal that by the AIC, SC and HQ terms, the GARCH (1,1) model when compared to other models has proven to be adequate model for the modelling of differenced Nigerian Export Commodity Price Index series.
The paper sought to investigate the effect of the bureau de change (United State Dollar, USD) and... more The paper sought to investigate the effect of the bureau de change (United State Dollar, USD) and Nigeria naira (NGN) exchange rate on economic recession using intervention analysis from June 2017 to March 2021. The data was taken from the website of the central bank of Nigeria (cbn.org). The study adopted augmented dickey fuller test for checking the stationarity. The pre-intervention data spectacles a negative slope and it was non-stationary but after the first difference occurred it became stationary.
Many economic and business time series exhibit seasonal tendencies. Analytical techniques for suc... more Many economic and business time series exhibit seasonal tendencies. Analytical techniques for such series which take into account these tendencies have engaged the attention of researchers of recent. One such modelling technique is the Box-Jenkins seasonal autoregressive integrated moving average (SARIMA) technique. A novel algorithm is hereby proposed. This algorithm which is based on autoregressive-moving average duality arguments is applied to model daily exchange rates of the British pound sterling and the European Euro currencies. The data analyzed are 178 daily pound/euro exchange rates 13 th December 2015 to 7 th June 2016. Application of the algorithm using the SARIMA(1,1,1)x(1,1,1) 7 template as proposed yields a SARIMA(1,1,1)x(0,1,1) 7 model. Further 8 values from 8 th June to 15 th June 2016 are used for out-of-sample comparison of observations with forecasts. The adequacy of the chosen model is not in doubt since the residuals are uncorrelated and are normally distribute...
A seasonal autoregressive integrated moving average (SARIMA) model proposed and fitted to observe... more A seasonal autoregressive integrated moving average (SARIMA) model proposed and fitted to observed lemon Autochton monthly prices has been included among marketing information system tools for citrus production in the Lattakia Region of Syria. The order of the model is (2, 1, 0)x(1, 0, 1) 12 chosen on the basis of minimum mean square error (MSE) and mean absolute error (MAE) among the set of SARIMA models of orders (using the MINITAB software. In this work a re-analysis of the data using Eviews 7 confirms that the chosen model is still the best on minimum Akaike Information Criterion (AIC) grounds, each of the rest of the models being non-stationary. Moreover based on the observed autocorrelation structure the SARIMA(0, 1, 1)x(1, 0, 1) 12 model is even better than the chosen model on all counts. Hence it is hereby proposed as the most adequate model to adopt for the purpose of the price prediction.
This research is about an intervention on daily exchange rates of the Nigerian Naira (NGN) and it... more This research is about an intervention on daily exchange rates of the Nigerian Naira (NGN) and its Ugandan counterpart, the Shilling (UGX) observed on 22 nd June 2016. The realization of this time series studied spans from 19 th May 2016 to 17 th November 2016. There is an abrupt jump in the amount of Naira exchanged for a shilling from 0.0509 to 0.0609 from 20 th June to 21 st June 2016 and then to 0.0840 the next day. Instead of coming down it has been moving up. The proposal of an intervention or interrupted time series model to explain this trend of events is the aim of this work. The pre-intervention exchange rates show an initial downward trend up to 26 th May 2016 and then an upward trend. They are adjudged to be non-stationary by the Augmented Dickey Fuller (ADF) test, necessitating their first order differencing. These differences are now stationary and are observed to have a random error fit. Post-intervention forecasts are made on the basis of this pre-intervention model....
Uploads
Papers by ette H etuk