Monthly Archives: January 2017

GBPUSD 1-month Implied Volatility and Steepness of Volatility Curve

I was recently reading a paper titled The yen/dollar exchange rate in 1998: views from options markets written by the Bank of England back in November 1998. This got me to think on how I could best represent in one chart the relationship between the slope of the implied volatility term structure of and the nominal level o the 1-month volatility.

To do this I regressed the 1, 3, 6 and 12-month GBP-USD implied volatilies against their time values for the period 1996 to December 2016 (i.e 5427 volatility curves). I derived the volatility curve slopes t_stats for each day and then classified the 1-month volatilities into three groups as a function of the significance level of the slope t-stats. The chart below shows the 1-month implied volatiliy over the full period. When the volatility curve slope was positvely significant at 95% critical threshold the data is shown in green, When there was a signicantly negative slope at the 95% critical threshold the data is shown in red and pale blue for the remainder. I think this is a neat way highlight that time of high volatility are associated with a volatility curve that slope downwardly and vice-versa.

plot of chunk stretch line chart

GBP-USD Update ahead of May’s BREXIT Speech

Whatever the market being traded, there always will be a a question being asked at one moment: How far can  this 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. This  analysis aims to provide an assessments of how atypical the move experienced in GBPUSD is.

The below chart shows the GBP-USD over the period of January 1975 to January 2017 . On the 13 January 2017 it was trading around 1.218472.

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.

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Finally I plot the last 125 days and a trend forecast derived from an ARIMA(0,1,5) 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

% Changes of GBPUSD across 250 to 5-day time-horizon – Quick GBP-USD Update ahead of May’s BREXIT Speech….

As a follow up of my previous post on boxplots I thought that I would expand my script to visualise the appreciation/depreciation of one specific values accross differnt time frames. In the below analysis I use the daily GBPUSD exchange rate that I grab from the Bank of England Website.

The blue dots represent the most recent observations for the given time frames, the orange dots are the outliers over the period 1975 to date. The boxes emcompasses the observations that fall between the 25% and 75% quantiles. The Blue lines in the box are the median value over the sample and the “wiskers” represent an interval of close to 95%.

 

plot of chunk chartdata

% Changes of GBPUSD across 250 to 5-day time-horizon

As a follow up of my previous post on boxplots I thought that I would expand my script to visualise the appreciation/depreciation of one specific instrument accross differnt time frames. In the below analysis I use the daily GBPUSD exchange rate that I grab from the Bank of England Website.

The blue dots represent the most recent observations for the given time frames, the orange dots are the outliers over the period 1975 to date. The boxes emcompasses the observations that fall between the 25% and 75% quantiles. The Blue lines in the box are the median value over the sample and the “wiskers” represent an interval of close to 95%.

The % change is presented in terms of USD relative to GBP. So from the below chart we can see that the USD appreciated by close to 17% against GBP  across the last 250 days which is within a 95% interval of confidence. And so on for other time frames….

plot of chunk chartdata

Weekly Changes in G10 FX Trade Weighted Indices

I always liked boxplots. I think they provide a great and very visual way to position current data relative to their history whilst highlighting outliers. This is particularly useful as it helps to put recent moves in context of their past opportunities and possibly highly reversals and/or opportunities. To illustrate this I wrote a quick script in R to grab the BOE G10 Trade weighted indices from the website of the bank of England and posititon the most recent one week move relative to its history of weekly move going back to 1990.
The blue dots represent the most recent observations, the orange dots are the outliers over the period 1990 to date. The boxes emcompasses the observations that fall between the 25% and 75% quantiles. The Blue lines in the box are the median value over the sample and the “wiskers” represent an interval of close to 95%.