Category Archives: Commodities

WTI Break Analysis…

In the following I us an R package BFAST designed to detect strucutural breaks in time series.The script Iteratively detects breaks in the seasonal and trend component of a time series. The first chart shows the various break and fitted regressions. The second chart shows the deviations from the regression lines and 95% interval of confidence. This could be used as an overbought/oversold indicator. Anyway, just work in progress…so any input / suggestions are always welcome as usual. Feel free to contact me at:Pierre@argonautae.com

plot of chunk plot plot of chunk plot

Oil update….

Whatever the market being traded, there always will be a a question being asked at one moment: How far can this thing go ? Clearly not an easy question to answer as this will invariably depends on factors that are partly unknown or difficult to estimate, such as fundamentals, market positioning or market risk amongst others. The first part is obviously to assess how atypical the move experienced in the given instrument is. This report aims to contribute to this.

The below chart shows the WTI Spot Price over the period of January 1986 to April 2016 . On the 21 April 2016 it was trading around 44.21.

plot of chunk chartdata

In the below I plot the previous 125 days against other similar historical periods that would have closely matched the recent history. The data has been normalised so as to be on the same scale. The chart shows the latest 125 days in black, and overlay similar historical patterns in grey. It Also shows what has been the price path for the following 125 days as well as the observed quartiles.

plot of chunk pattern

Finally I plot the last 125 days and a trend forecast derived from an ARIMA(1,1,0) model as well as the 95% confidence intervals. The ARIMA model is fitted to the past 625 historical values whilst ignoring the last 125 days, therefore we can look at the recent price path against the trend forecast and its confidence intervals to gauge how (a)typical the recent move has been.

plot of chunk arimaplot

Oil Break Analysis…

In the following I us an R package BFAST designed to detect strucutural breaks in time series.The script Iteratively detects breaks in the seasonal and trend component of a time series. The first chart shows the various break and fitted regressions. The second chart shows the deviations from the regression lines and 95% interval of confidence. This could be used as an overbought/oversold indicator. Anyway, just work in progress…so any input / suggestions are always welcome as usual. Feel free to contact me at:Pierre@argonautae.com

plot of chunk plot plot of chunk plot

Oil update….

Whatever the market being traded, there always will be a a question being asked at one moment: How far can this thing go ? Clearly not an easy question to answer as this will invariably depends on factors that are partly unknown or difficult to estimate, such as fundamentals, market positioning or market risk amongst others. The first part is obviously to assess how atypical the move experienced in the given instrument is. This report aims to contribute to this.

The below chart shows the WTI Spot Price over the period of January 1986 to April 2016 . On the 12 April 2016 it was trading around 42.16.

plot of chunk chartdata

In the below I plot the previous 125 days against other similar historical periods that would have closely matched the recent history. The data has been normalised so as to be on the same scale. The chart shows the latest 125 days in black, and overlay similar historical patterns in grey. It Also shows what has been the price path for the following 125 days as well as the observed quartiles.

plot of chunk pattern

Finally I plot the last 125 days and a trend forecast derived from an ARIMA(0,1,2) model as well as the 95% confidence intervals. The ARIMA model is fitted to the past 625 historical values whilst ignoring the last 125 days, therefore we can look at the recent price path against the trend forecast and its confidence intervals to gauge how (a)typical the recent move has been.

plot of chunk arimaplot

Oil update….

Whatever the market being traded, there always will be a a question being asked at one moment: How far can this thing go ? Clearly not an easy question to answer as this will invariably depends on factors that are partly unknown or difficult to estimate, such as fundamentals, market positioning or market risk amongst others. The first part is obviously to assess how atypical the move experienced in the given instrument is. This report aims to contribute to this.

The below chart shows the WTI Spot Price over the period of January 1986 to March 2016 . On the 22 March 2016 it was trading around 41.39.

plot of chunk chartdata

In the below I plot the previous 125 days against other similar historical periods that would have closely matched the recent history. The data has been normalised so as to be on the same scale. The chart shows the latest 125 days in black, and overlay similar historical patterns in grey. It Also shows what has been the price path for the following 125 days as well as the observed quartiles.

plot of chunk pattern

Finally I plot the last 125 days and a trend forecast derived from an ARIMA(1,1,1) model as well as the 95% confidence intervals. The ARIMA model is fitted to the past 625 historical values whilst ignoring the last 125 days, therefore we can look at the recent price path against the trend forecast and its confidence intervals to gauge how (a)typical the recent move has been.

plot of chunk arimaplot

Oil Break-out Analysis…

In the following I us an R package BFAST designed to detect strucutural breaks in time series.The script Iteratively detects breaks in the seasonal and trend component of a time series. The first chart shows the various break and fitted regressions. The second chart shows the deviations from the regression lines and 95% interval of confidence. This could be used as an overbought/oversold indicator. Anyway, just work in progress…so any input / suggestions are always welcome as usual. Feel free to contact me at:Pierre@argonautae.com

plot of chunk plot plot of chunk plot

OIl and USD TWI relationship

The below plot is a bi-density chart of the WTI spot rate versus the Fed USD Trade weighted index. The contour lines delimit the empirical joint distribution. The yellow line is the best fit derived from a quantile regression (akin to a measure of fair value). The dotted red lines delimit the quantiles for the Oil price. The bold red cross hair lines show where both the USD TWI and the oil Price is at the most recent point….

plot of chunk bidensity2

Gold & US TWI relationship

The below plot is a bi-density chart of the Gold spot rate in US$ versus the Fed USD Trade weighted index. The contour lines delimit the empirical joint distribution. The yellow line is the best fit derived from a quantile regression (akin to the historical fair value). The dotted red lines delimit the quantiles for the Gold price. The bold red cross hair lines show where both the USD TWI and the Gold Price is at the most recent point.

plot of chunk bidensity2

Norway and oil price…

The below plot is a bi-density chart of the USDNOK spot rate versus the WTI spot price. The contour lines delimit the empirical joint distribution. The yellow line is the best fit derived from a quantile regression (akin to the historical fair value). The dotted red lines delimit the quantiles for the oil price. This aims to answer the question: Is the Norwegian Krona more sensitive to the price of oil when the barrel trades below/above a given price ?Clearly the chart shows that low oil price are bad for the Norwegian currencies and vice versae. The crosshair shows the current level of oil versus USDNOK….

plot of chunk bidensity2

Canadian dollar and oil …

The below plot is a bi-density chart of the USDCAD spot rate versus the WTI spot price. The contour lines delimit the empirical joint distribution. The yellow line is the best fit derived from a quantile regression (akin to the historical fair value). The dotted red lines delimit the quantiles for the oil price. This aims to answer the question: Is the Canadian dollar more sensitive to the price of oil when the barrel trades below/above a given price ? Clearly the chart shows that low oil price are bad for the Canadian dollar and vice versae. The crosshair shows the current level of oil versus USDCAD….

plot of chunk bidensity2