Wednesday, December 27, 2006

Hidden Relationships

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.

On Monday, November 06, 2006 in a post entitled “Recent Developments in How Economic Announcements Affect Financial Markets” I noted that the EUR and the CHF move in opposite directions when the U.S. trade news is announced.

Here is that relationship of the USD/CHF vs. EUR/USD 1-minute returns after International Trade Balance announcements:

In another similar relationship, the Swiss Franc and the Euro appear, on average, to move in opposite directions to the U.S. Dollar when non-farm payrolls are announced. Both these effects are large and statistically significant. The graphs below shows initial returns of the two series just after the NFP announcement.

Time Series Graph of the USD/CHF and EUR/USD 1-minute returns after Non-Farm Payroll (NFP) announcements:

USD/CHF Vs. EUR/USD 1-minute returns after NFP announcements:In these case the announcement effect relationship, embodied in the estimate news parameters for each currency, can be subsumed in one estimate that is the ratio of the parameters, and assuming that the news coefficients are constant, so are the above relationships.

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Friday, December 22, 2006

For the FX Traders Part II - A Watch List of the Biggest Movers

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.

In the last post I gave a table of the most statistically significant FX moves. Another way of showing this information is to rank the table by the biggest moves. Since all of the results are highly significant anyway, and the results are for standardized news (see the post from Thursday, October 12, 2006 - Standardized News), we can compare them. Here is the ranking of the other top results (again ranked by the size of the response to news):
Financial Market Announcement
CHF NFP
EUR NFP
AUD NFP
JPY NFP
GBP NFP
CHF ITB
EUR ITB
CAD NFP
JPY ITB
GBP ITB
CAD ITB
AUD ITB
CAD GDP
CHF RSX
JPY GDP
CHF IJC
JPY RSX
CAD IJC
EUR HICP
JPY HICP
The biggest average historical move is for the Swissy (USD/CHF - Swiss franc) in response to the U.S. Non-farm payrolls (NFP). A bit of a surprise n'est-ce pas? And as a teaser, the coefficient is 0.291584. From this coefficient we can anticipate future moves once we have a view of the next announcement and the market expectation (from an economic derivatives auction). What else am I working on? I'm writing the specification and use case for an application that speculators and hedgers may find useful. This application would incorporate the results of my research and make the results more useful. More of this as it takes shape in the New Year.

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Monday, December 18, 2006

For the FX Traders - A Watch List of Currency-Announcement Pairs

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.

Today I thought all the forex traders who read this blog might be interested in which FX rates move the most to which announcements.

The top 20 effects for foreign exchange rates (ranked by the statistically significant news effects –measured by the absolute value of the t-statistic) are given below:

FX Rate

Announce-ment

EUR

NFP

CHF

NFP

CAD

NFP

JPY

ITB

GBP

NFP

JPY

NFP

AUD

NFP

CHF

ITB

EUR

ITB

CAD

GDP

GBP

ITB

AUD

ITB

CAD

ITB

JPY

HICP

EUR

HICP

JPY

RSX

CAD

IJC

CHF

RSX

CHF

IJC

JPY

GDP

The releases are as follows:

Announcements

Source

Frequency

Units

Release Time (Zone)

GDP (Advance Release)

BEA

Quarterly

% change qoq2

8:30am (ET)

Initial Jobless Claims (IJC)

ETA

Weekly

Thousands

8:30am (ET)

Non-farm Payrolls (NFP)

BLS

Monthly

Change in thousands

8:30am (ET)

Retail Sales Excluding Automobiles (RSX)

Census

Monthly

% change mom

8:30am (ET)

International Trade Balance (ITB)

BEA

Monthly

$ billion

8:30am (ET)

Harmonized Indices of Consumer Prices (HICP)

ES

Monthly

Index

11:00am (CET)

Manufacturing PMI (ISM)

ISM

Monthly

Change in the index

10:00am (ET)

1: Acronyms are as follows: BEA (U.S. Department of Commerce Bureau of Economic Analysis), BLS (U.S. Department of Labor Bureau of Labor Statistics), Census (U.S. Census Bureau), ETA (U.S. Department of Labor Employment & Training Administration), ISM (Institute for Supply Management), PMI used to be an acronym for Purchasing Managers’ Index, ES (European Union Eurostat), CET (Central European Time), ET (Eastern Time)

2: Expressed at an annualized rate.

Here the news coefficients were standardized. I define standardized news (S) as the surprise divided the sample standard deviation of the news

Standardized news allows for comparisons of responses of different asset prices (here exchange rates) to different news.

A couple of comments on these results:

1. Non-farm payrolls (NFP) is a very important release for currencies.

2. The international trade balance (ITB) is also important.

3. The ISM Manufacturing PMI Index (ISM), which does not show up in this list, is still statistically significant for some currencies.

4. The combinations of: CHF/GDP; AUD/GDP; GBP/GDP; GBP/ISM; JPY/ISM; GBP/HICP; EUR/GDP are not statistically different from zero.

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How Quickly Do Financial Markets React To 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.

Most researchers to data have taken a fixed window over which to measure the announcement effect. An exception is Kim and Sheen (2001) who calculate minute-by-minute returns for the Australian bond futures market. The size of the window is a testable hypothesis so I ran regressions using cumulative returns starting with the close one minute before an announcement up to half an hour after the announcement. As an example, for non-farm payrolls, the ability of news to explain movements in the 5-Year Treasury Bond futures contract can be improved by 6% by changing the definition of the window from the 30 minutes (from 8:25am, 5 minutes before the announcement to 8:55am, as used by Gürkaynak and Wolfers (2006)) traditionally used in the academic literature to a 20-minute window (from 8:25am to 8:45am). The same change for the EUR/USD exchange rate results in a 25% improvement in explanatory power. For the S&P 500 futures contract, a movement from a 30-minute window to a 10-minute window yields a 37% improvement.

For FX markets, in general, I have found that shortening the window even more works well. A minute or two is when the best relationship is found for most foreign exchange rate pairs.

Interval

R2 improvement

Length

over 30-minute

(minutes)

Coefficient

t-Statistic

R2

window

5Year Bond

20

-0.00371

-7.983

0.589563

6%

10

-0.00359

-7.865

0.583629

5%

25

-0.00365

-7.629

0.566652

2%

30

-0.00357

-7.328

0.55454

0%

15

-0.00339

-7.178

0.538909

-3%

EUR

20

-0.00307

-6.065

0.456968

25%

15

-0.00307

-6.065

0.456968

25%

10

-0.00307

-6.065

0.456968

25%

25

-0.00338

-5.04

0.373143

2%

30

-0.00338

-4.998

0.366464

0%

S&P 500

10

0.002926

5.656

0.441865

37%

20

0.002694

5.081

0.375972

17%

15

0.002426

4.909

0.353967

10%

25

0.002729

4.66

0.334129

4%

30

0.002825

4.524

0.321928

0%

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Friday, December 08, 2006

On the shoulders of others: What others have said about the Announcement Effect (Part 2 of 2)

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.

All references cited below will be published in full in a separate post.

Gürkaynak and Wolfers (2006) use expectations data from economic derivatives, which they show, is an improvement over survey data used almost universally by all other authors. Gürkaynak and Wolfers (2006) conclude that “The evidence presented … shows that economic derivatives option prices are accurate and efficient predictors of the densities of underlying events” (p. 29). That “the option prices that we observe in this market are a reasonable approximation to the risk-neutral distribution” (p. 40). And finally, that “… positive shocks to non-farm payrolls, business confidence and retail trade are positive shocks to wealth, while higher initial claims is a negative shock. … the non-farm payrolls surprise is easily the most important shock. The coefficient is also directly interpretable: a one standard deviation shock to nonfarm payrolls raises wealth (measured by the percentage change in the S&P 500 in a 30-minute window) by 0.37% and the 95% confidence interval extends from +0.17% to +0.54%.” (pp. 34-35)

Fair’s (2003) work also considers high frequency intra-day data on a range of asset prices over a long period (1982 to 1999). Using the reverse methodology to the above and previous authors who look at asset prices around announcements, Fair identifies occasions on which the five-minute change in asset prices exceeded 0.75 percentage points, and then does a newswire searches to match to an event that occurred at that time. The events are often U.S. macroeconomic announcements.

Several studies have linked economic news to exchange rates jumps. One example, using one year of high frequency dollar-sterling exchange rates is Goodhart, Hall, Henry, and Pesaran (1993) who link the news of a U.S. trade figure announcement and a U.K. interest rate change to an exchange rate jump.

Bond markets research includes Balduzzi, Elton and Green (2001) who use intraday data from the inter-dealer government bond market to investigate macroeconomic announcements on prices, trading volume, and bid-ask spreads. They find that the surprise in 17 news releases has a significant impact on the price of at least one of the following: a three-month bill, a two-year note, a 10-year note, and a 30-year bond. Their estimated effects vary significantly according to maturity. The news can explain a substantial fraction of price volatility after the announcements, and the price adjustment to news generally occurs within one minute after the announcement. By contrast, they document significant and persistent increases in volatility and trading volume after the announcements. Bid-ask spreads, on the other hand, widen at the time of the announcements, but then revert to normal values after five to 15 minutes.

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On the shoulders of others: What others have said about the Announcement Effect (References)

Here are the full references for the two posts that bracket this one:

Balduzzi, P., Elton, E.J., Green, T.C., (2001) “Economic News and Bond Prices: Evidence from the U.S. Treasury Market”, Journal of Financial and Quantitative Analysis, Vol. 36, pp.523-543.

Baumohl, Bernard, (2004) The Secrets of Economic Indicators: Hidden Clues to Future Economic Trends and Investment Opportunities, Wharton School Publishing.

Fair, R., (2003) “Shock Effects on Stocks, Bonds and Exchange Rates”, Journal of International Money and Finance, Vol. 22, pp.307-341.

Faust, Jon, Rogers, John H., Wang, Shing-Yi B., Wright, Jonathan H., (2003) “The high-frequency response of exchange rates and interest rates to macroeconomic announcements” U.S. Board of Governors of the Federal Reserve System, International Finance Discussion Papers, number 784.

Federal Reserve Board of San Francisco, (2006) “New Uses for New Macro Derivatives” FRBSF Economic Letter, 2006-21; August 25.

Goodhart, C.A.E., Hall, S.G., Henry S.G.B. and Pesaran, B.. (1993) “News Effects in a High-Frequency Model of the Sterling-Dollar Exchange Rate,” Journal of Applied Econometrics, Vol. 7, pp. 199-211.

Gürkaynak, Refet S., Wolfers, Justin, (2006) “Macroeconomic Derivatives: An Initial Analysis of Market-Based Macro Forecasts, Uncertainty and Risk” NBER Working Paper Series, NBER Working Paper 11929, January 2006.

Kim, Suk-Joong, Sheen, Jeffrey, (2001) “Minute-by-minute dynamics of the Australian bond futures market in response to new macroeconomic information” Journal of Multinational Financial Management, Vol. 11, pp. 117-137.

Parker, John C., Li, Huirong (CoCo), “How Bad is Bad News; How Good is Good News?” unpublished research paper available from the author (john.parker@relevanteconomics.com) upon request.

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Wednesday, December 06, 2006

On the shoulders of others: What others have said about the Announcement Effect (Part 1 of 2)

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.

All references cited below will be published in full in a separate post.

Bernard Baumohl’s (2004) book “The Secrets of Economic Indicators: Hidden Clues to Future Economic Trends and Investment Opportunities” provides a fascinating description the economic announcement process and how it affects financial markets. The secrecy, the regimented process of the “lock-up” all show how important the release of economic statistics. Economic announcements are usually published according to a release schedule that is published in advance. Financial markets anticipate, speculate, and analyze the releases. Teams of economists spend their entire careers interpreting, dissecting, and forecasting these indicators of the economy’s health. Legions of journalists report on the latest numbers, collect reactions of economists and traders, and endure the stress of release lock-ups to get their stories out with the numbers. The release of economic data is so important it is tightly controlled. Often along with the journalists, governments will get a sneak preview, monetary and fiscal policy makers, politicians, and others who need advance access are granted it. The advanced release, as well as the release itself is always under tight security arrangements that stop agents from using the information for profit. And it should be noted that the literature proves that these arrangements work. The literature has not found any evidence of an anticipation effect (see for example Kim and Sheen (2001) for Australian bond futures market returns, volatilities and volumes before and after economic announcements).

A rather quaint anachronism is that releases in the U.S. are usually at 8:30am, “before the market opens”. But these days the market never closes. Foreign exchange markets operate around the clock, futures markets likewise. Nonetheless, an attractive feature of economic announcements is that they are fair. The information is available to everyone, essentially without cost, at exactly, and Baumohl stresses it is exactly, the same time. So a hedge fund, and investment bank, day trader, risk manager, and you and I all learn about the news at the same time and all have the same opportunity to profit. The ability to profit or hedge though, comes from an investment in information and understanding about: i) what the economic statistic will be, ii) what the market expectation is (and perhaps an appreciation of the range and distribution of opinion), and iii) how our portfolio of asset holdings will change in response to the likely news, or surprise.

As Faust et. al. point out, the literature measuring the effects of macro announcements on asset prices at daily or intra-day frequency is vast. The reader is directed to their paper for a sample of the contributions. Some of the papers cited also document a relationship between the announcements and the conditional variance of asset returns.

One of the earliest announcement effect studies is by Pearce and Roley (1985) who examine the daily response of stock prices to announcements about the money supply, inflation, real economic activity, and the discount rate. Roley had published articles earlier looking at the impact of monetary policy changes on asset prices. Pearce and Roley (1985), using survey data on market participants' expectations of these announcements, find that the unexpected component of the announcements, the surprise, moves stock prices. They also conclude that the surveys are more accurate, in the sense of having lower mean squared errors, than the forecasts from standard autoregressive time series models.

For the period 1985 to 2005 survey data was used for most studies. Gürkaynak and Wolfers (2006) introduced the concept of using derivative data to measure market expectations.

Pearce and Roley (1985) used daily stock price data and found that there is only limited evidence of an impact from inflation surprises and no evidence of an impact from real activity surprises on the announcement days. There is also only weak evidence of stock price responses to surprises beyond the announcement day. Since 1985 there has been an increased use of intra-day data. For example, people have started to capture the quoted price for the exchange rates from Reuters or other data providers, recording, as an example, some 130,000 observations over an 8-week period (Goodhart, Hall, Pesaran (1993)).

Andersen, Bollerslev, Diebold and Vega (2002) use a high frequency exchange rate data set, 5-minute return series for U.S. dollar spot exchange rates versus German Mark, British Pound, Japanese Yen, Swiss Franc, and the Euro, to model announcement surprises (that is, divergences between expectations and actuals, or “news”). Andersen et. al. use their high frequency data to isolate the impact on financial markets around an announcement. They find that announcement surprises produce conditional mean jumps and they characterize the speed and path of adjustment. They find that the market reacts to news in an asymmetric fashion: bad news has greater impact than good news.

Andersen et. al. conclude that “Throughout, news exerts a generally statistically significant influence on exchange rates, whereas expected announcements generally do not. That is, only unanticipated shocks to fundamentals affect exchange rates, in accordance with the predictions of rational expectations theory. Many U.S. indicators have statistically significant news effects across all currencies, including payroll employment, durable goods orders, trade balance, initial unemployment claims, NAPM index, retail sales, consumer confidence, and advance GDP. The general pattern is one of very quick exchange rate conditional mean adjustment, characterized by a jump immediately following the announcement, and little movement thereafter. Favorable U.S. “growth news” tends to produce dollar appreciation, and conversely.” (pp. 9-10)

Faust, Rogers, Wang and Wright (2003) add to the announcement effects literature in two ways. First, they study the joint announcement effects across a broad range of assets - exchange rates and U.S. and foreign term structures. Also they use a longer span of high frequency data than has been common in previous announcement work. This allows them to explore the possibility that the effects of news on asset prices have varied over economic booms and busts. Faust et. al. conclude that: “Stronger than expected real releases (e.g. nonfarm payrolls, retail sales, GDP) tend to appreciate the dollar and raise short and long-term interest rates in the U.S. and, to a lesser extent, overseas. Higher than expected inflation (CPI or PPI) is estimated to have little effect on the exchange rate, but to raise U.S. interest rates significantly. Tighter than expected monetary policy (i.e. a higher than expected target Fed Funds rate) is estimated to appreciate the dollar and to raise the term structure of U.S. interest rates.” (p. 4)

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Saturday, December 02, 2006

Thresholds, Tipping Points, Good & Bad 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.

Traders often will set threshold for action and in aggregate this might explain why some announcements are a “scratch” from a trader’s perspective that is there is a move but not enough to act upon. Once the threshold is breached though, lots of people want in.

The move from disorder to order or the contagion effect has been used to explain financial crises. Perhaps it can also be used to explain markets reactions to news too.

Looking at the impact of the Non-Farm Payrolls (“NFP”) announcements in the U.S. on the Euro (EURUSD) exchange rate, a couple of thresholds appear to be important. Interestingly the threshold is larger for bad news than for good news.

Good news and bad news have different effects also the skew of the expectations is important. These effects have been discussed before but if the news is very good or exceptionally bad there is an extra kicker. So, negative news is more likely to be a non-event than good news from a trading perspective.

The thresholds that were found to be statistically significant were when news was greater than one standard deviation and when news was less than two standard deviations from what was expected (as measured by the economic derivatives auction for NFP).

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