Really Useful Correlations

It is not news that news moves financial markets. This blog will publish research on how, when, why, and which news moves what financial markets.

A couple of days ago Tom Yeomans commented on my blog that correlations can be tools for fundamental traders. He pointed me to Mataf who publish a running website update on the correlations of forex pairs.

I looked at these correlations between FX rates for 5, 20 and 100 days. These would be useful for normal markets. But often contagion effects hit financial markets. During periods of high volatility or market stress correlations have a tendency to go to 1 (or -1).

After a major economic announcement, there are, as I have demonstrated, some interesting relationships. I thought, following Tom’s suggestion, I would look at correlations just following announcements. So here are a couple of the correlations that should be really useful to those trading announcements.

As an example, from Mataf the 5, 20, and 100 day correlations between AUD-USD and the USD-CAD were (when I pulled them on Monday, February 05, 2007 at 11:58 PM), 0.21, 0.47, and 0.68. According to the notes “If the correlation is low (below 60) then the currencies don't move in the same way.” Now the time horizon should match your holding period. So what if your holding period is a few minutes after an announcement?

Look at the same pairs 1, 5, 10, 20 and 30 minutes following a U.S. CPI announcement. I have calculated the correlations of the returns in the currency pairs (not the levels). If you are trading this announcement, these are the correlations you should care about. The numbers are -0.9035, -0.8479, -0.6696, -0.7454, and -0.6992.

As a sampler here is the return correlation matrix for 1 minute after an 8:30am U.S. CPI announcement:

AUD	CAD	CHF	EUR	GBP	JPY
1	-0.9035	-0.9429	0.9339	0.9552	-0.9135	AUD
	1	0.9051	-0.8678	-0.859	0.8414	CAD
		1	-0.9796	-0.9675	0.9065	CHF
			1	0.9746	-0.915	EUR
				1	-0.9431	GBP
					1	JPY

And here it is 30 minutes after:

AUD	CAD	CHF	EUR	GBP	JPY
1	-0.6992	-0.8205	0.8551	0.85	-0.8357	AUD
	1	0.7108	-0.6963	-0.6182	0.7065	CAD
		1	-0.9831	-0.9072	0.9329	CHF
			1	0.9318	-0.9465	EUR
				1	-0.8725	GBP
					1	JPY

One To Watch - CPI News

It is not news that news moves financial markets. This blog will publish research on how, when, why, and which news moves what financial markets.

Around June 2006 the CME and Goldman Sachs introduced an auction of derivatives based on the Consumer Price Index - Core CPI ex Food and Energy announcement. More information can be found here.

This is an announcement to watch.

Because there is not much data yet it is early days to make decisions based on statistical analysis but indications are that this is becoming the key news event for the EURUSD.

Here is a summary of the findings:

• The nonfarm payrolls (NFP) news was, as always highly significant.
• The average move associated with the NFP announcement though was small.
• Initial jobless claims had the smallest, and least significant impact on the exchange rate.
• GDP and retail sales (RSX) news had large impacts.
• The CPI however appears to have a huge impact. Because there have only been a couple of auctions, the effect needs to be confirmed.

There are some other interesting explanatory variables in this test that I will write more about soon.

For those that are interested, below are some details of the test.

The test was to take the change in the EUR very close to the 8:30 am time that many key U.S. numbers are released (CPI, GDP, nonfarm payrolls, retail sales, initial jobless claims, and the trade balance).

The change is taken as the 8:31am close minus the 8:29 am close. For the CPI, as an example, the resulting numbers are close to, but not exactly the same as those shown on the Forex Resource Guide for the CPI:

Then try to explain the move in pips (defined as the change the EUR times 10,000) or return (defined as the ratio of the natural logs times 100) with the news (actual minus the mean expectation from the derivatives auction).

This test uses all days, not just announcement days, and includes data for the news as explanatory variables. Because there are sometimes two announcements on one day, I threw all variables into one big regression and let the data sort out the best model. As I mentioned above there are some other ingredients that help explain how the market moves.

With news and other explanatory variables taken from the distribution of market expectations the model explains around 45% (adjusted R²) of the move in the EUR. I think this is quite impressive. Even more so because I have only six announcements included to explain the exchange rate.