Economic Indicators

Do country economic fundamentals provide exploitable information about future changes in associated currency exchange rates? In the June 2013 version of their paper entitled “Currency Risk Premia and Macro Fundamentals”, Lukas Menkhoff, Lucio Sarno, Maik Schmeling and Andreas Schrimpf investigate the usefulness of economic fundamentals in currency trading by measuring the performance of multi-currency hedge portfolios formed by sorting on lagged economic variables across 35 countries. They take the perspective of a U.S. investor by measuring all exchange rates versus the U.S. dollar. The country economic variables they consider are: (1) interest rates; real Gross Domestic Product (GDP) growth; real money growth (from currency in circulation); and, real exchange rates. They calculate growth rates based on 20-quarter rolling averages. They form hedge portfolios from extreme fourths (quartiles) of ranked currencies, rebalanced annually at year end, and calculate returns in excess of short-term interest rates. Using quarterly currency exchange rate, short-term interest rate, real GDP, Consumer Price Index (CPI) and currency in circulation for 35 countries/currencies for out-of-sample testing from the first quarter of 1974 through the third quarter of 2010, they find that: Keep Reading

How does central bank quantitative easing (QE) affect various financial markets? In the May 2013 preliminary and incomplete version of his paper entitled “The Time Horizon of Price Responses to Quantitative Easing”, Harry Mamaysky investigates how U.S. Federal Reserve (Fed), European Central Bank (ECB) and Bank of England (BoE) QE announcements affect the prices of asset classes, including government bills and bonds, currencies, equities, equity volatilities and credit products. He focuses on how long it takes different asset classes to respond to QE announcements (events). He first decomposes the sample period into non-overlapping event windows and non-event windows ranging in duration from two trading days before to 21 trading days after QE events. He then aggregates changes in financial market proxies separately to compare event window and non-event window changes. Using dates for 20 Fed, nine ECB and 11 BoE events and contemporaneous daily values for U.S. and European bill/bond, currency, equity, equity volatility and credit indexes during March 2008 through December 2012, he finds that: Keep Reading

The Federal Reserve states that open market operations regulate “the aggregate level of balances available in the banking system,” thereby keeping the effective Federal Funds Rate close to a target level. The operations are predominantly repurchases, whereby the Federal Reserve provides liquidity. Do Permanent Open Market Operations (POMO) systematically affect the nominal or real yields on 10-year Treasury notes (T-notes)? Using monthly amounts of Treasuries repurchases via POMO during August 2005 through May 2013 (94 months) and contemporaneous monthly T-note yields and 12-month trailing inflation rates, we find that: Keep Reading

A reader hypothesized that the Federal Reserve uses Open Market Operations repurchases to stimulate, or prop up, the stock market. The hypothesis supposes that private parties, such as prime brokers, use the funds released by these repurchases to buy (highly leveraged) stock futures contracts, immediately attracting arbitrageurs who simultaneously short futures and purchase stock indexes. Trend followers then pile on. The Federal Reserve states that open market operations regulate “the aggregate level of balances available in the banking system,” thereby keeping the effective Federal Funds Rate close to a target level. The operations are predominantly repurchases, whereby the Federal Reserve provides liquidity. Do these Permanent Open Market Operations (POMO) and Temporary Open Market Operations (TOMO) affect the U.S. stock market? In other words, do the managers of POMO and TOMO transactions act as a “Plunge Protection Team?” Using accepted Treasuries repurchase transaction data for POMO during August 2005 through May 2013 (over 600 transactions) and TOMO during July 2000 through May 2013 (over 2,600 transactions) and contemporaneous daily and monthly closes of the S&P 500 Index, we find that: Keep Reading

Does P/E10, current real (inflation-adjusted) level of a stock market index divided by associated average real earnings over the last ten years, usefully predict stock market returns for non-U.S. markets? In the July 2012 revision of his paper entitled “Does the Shiller-PE Work in Emerging Markets?”, Joachim Klement assesses the validity of P/E10 as a long-term stock market return predictor in local currencies for 19 developed and 16 emerging equity markets. He calculates P/E10 in each market monthly using overlapping return and earnings measurement intervals. Using monthly data for country stock market indexes, earnings and inflation as available (with start dates ranging from January 1910 for the U.S. to January 2005 for China and Columbia) through April 2012, he finds that: Keep Reading

The employment-population ratio (percentage of those age 16 or older who are employed) is arguably a better measure of the U.S.employment situation than either employment or the unemployment rate. Is this series usefully predictive of U.S. stock market behavior in subsequent months, quarters and years? Using monthly seasonally adjusted employment-population ratio data from the Bureau of Labor Statistics and contemporaneous S&P 500 Index data for the period January 1950 through June 2012 (750 months), we find that: Keep Reading

Does anticipation of Federal Open Market Committee (FOMC) monetary policy announcements move the market? Is any such anticipation permanent? In the June 2012 revision of their paper entitled “The Pre-FOMC Announcement Drift”, David Lucca and Emanuel Moench investigate the effects of FOMC announcements on global equity markets. They focus on the U.S. stock market during the 24-hour interval from 2 PM on the day before to 2 PM on the day of scheduled FOMC announcements. Using FOMC announcement dates and intraday returns for the S&P 500 Index, other major stock market indexes and other asset classes, and daily returns for individual U.S. stocks and 49 industries, during February 1994 through March 2011 (131 scheduled FOMC meetings), they find that: Keep Reading

How do general economic conditions and economy-wide default risk shocks affect corporate bond returns, especially past winners and losers? In the May 2012 draft of their paper entitled “Sources of Momentum in Bonds”, Hwagyun Kim, Arvind Mahajan and Alex Petkevich investigate the relationship between U.S. corporate bond momentum portfolio returns and U.S. aggregate default risk. They measure the momentum effect as average monthly gross returns of overlapping hedge portfolios formed each month by buying (selling) the equally weighted tenth of bonds with the highest (lowest) total cumulative returns over the past six months and holding for six months, with a skip-month between ranking and holding intervals. They measure aggregate default risk as the prior-month yield spread between the Moody’s CCC corporate bond index and the 10-year U.S. Treasury note. They define default risk shocks as deviations from the linear relationships between default risk this month and its values the prior two months. They define high (low) default risk shock conditions as those above (below) the inception-to-date median value of the series. Using price and yield data for all listed U.S. corporate bonds (excluding convertible bonds, asset-backed securities and bonds with very low capitalization) during January 1995 (101 bonds) through December 2010 (2,513 bonds), they find that: Keep Reading

Are there economic conditions that favor stock price momentum investing? In the May 2012 draft of their paper entitled “Momentum and Aggregate Default Risk”, Arvind Mahajan, Alex Petkevich and Ralitsa Petkova investigate the relationship between stock momentum portfolio returns and U.S. aggregate default risk. They measure the momentum effect as average monthly gross returns of overlapping hedge portfolios formed each month by buying (selling) the equally weighted tenth of stocks with the highest (lowest) cumulative returns over the past six months and holding for six months, with a skip-month between ranking and holding intervals. They measure aggregate default risk as the prior-month yield spread between the Moody’s CCC corporate bond index and the 10-year U.S. Treasury note. They define default risk shocks as deviations from the linear relationships between default risk this month and its values the prior two months. They define high (low) default risk shock conditions as those above (below) the inception-to-date median value of the series. Using monthly returns for a very broad sample of AMEX/NYSE/NASDAQ stocks during 1960 through 2009 and monthly default risk spreads since 1954, they find that: Keep Reading

Which consensus forecast of U.S. economic indicators is best? How does the U.S. equity market react to consensus forecast errors? In their April 2012 paper entitled “Market Reaction to Information Shocks: Does the Bloomberg and Briefing.com Survey Matter?”, Linda Chen, George Jiang and Qin Wang investigate the accuracy of, and equity futures market reactions to, competing Bloomberg and Briefing.com survey-based forecasts for the values of scheduled weekly, biweekly, monthly and quarterly economic announcements. They focus on 14 announcements commonly treated as important: Building Permits, Capacity Utilization, Case-Shiller 20-city Index, Consumer Confidence, Consumer Price Index, Durable Goods Orders, Existing Home Sales, GDP Advance, Leading Indicators, Non-farm Payrolls, Personal Spending, Producer Price Index, Retail Sales and Unemployment Rate. They introduce standardization to compare errors across different indicator scales. Using consensus forecasts and announced values of 59 economic indicators, along with contemporaneous high-frequency price and volume data for the nearest S&P 500 futures contract (as available), over the period January 1998 through August 2010, they find that: Keep Reading