Economic Indicators

Do economic indicators usefully predict government bond returns? In the January 2014 version of their paper entitled “What Drives the International Bond Risk Premia?”, Guofu Zhou and Xiaoneng Zhu examine whether OECD-issued leading economic indicators predict government bond returns at a one-month horizon. They focus on a four-country (U.S., UK, Japan and Germany) aggregate leading economic indicator (LEI4). They test whether LEI4 outperforms historical averages and individual country LEIs in predicting term premiums (relative to a one-year bond) for U.S., UK, Japanese and German government bonds with terms of two, three, four and five years. Their test methodology employs monthly inception-to-date regressions of annual change in LEI4 versus next-month bond return for an out-of-sample test period of 1990 through 2011. Using end-of-month total return data for 1-year, 2-year, 3-year, 4-year and 5-year government bonds since 1962 for the U.S., 1970 for the UK, 1980 for Japan and 1975 for GM, all through 2011, they find that: Keep Reading

Has easy access to commodity allocations via exchange-traded instruments (financialization) changed the way commodity prices interact with the economy? In his February 2014 paper entitled “Macroeconomic Determinants of Commodity Returns in Financialized Markets”, Adam Zaremba investigates relationships between commodity returns and economic conditions in pre-financialization (before 2004) and post-financialization (2004 and after) environments. He defines an increase (decrease) in the nominal U.S. Industrial Production Index as economic growth (contraction). He employs the U.S. Consumer Price Index (CPI) to measure inflation. Using monthly levels of various global and sector commodity indexes in U.S. dollars as available, the nominal U.S. Industrial Production Index and CPI during December 1970 through November 2013, he finds that: Keep Reading

What factors truly explain movements in the price of gold? In his January 2014 paper entitled “Facts and Fantasies about Gold”, Joachim Klement checks the validity of common explanations for changes in gold price. Specifically, he investigates whether gold price responds to: change in inflation expectation; change in real interest rate; financial crises; changes in currency exchange rates; change in the marginal cost of gold production; central bank gold sales and purchases; and, change in the demand for gold-linked exchange-traded funds (ETF). Using monthly data for gold price and these potentially explanatory factors as available during 1970 through 2013, he finds that: Keep Reading

Do investors reliably reallocate between equities and cash in response to changes in government monetary stance? In their July 2013 paper entitled “Asset Allocation and Monetary Policy: Evidence from the Eurozone”, Harald Hau and Sandy Lai apply regressions to examine how variations in the tightness of monetary policy (real short-term interest rates) affect investor allocations to stock and money market funds. Specifically, they examine relationships among real short-term interest rates, equity and money market fund flows, stock index returns and estimates of local institutional ownership of stocks in eight countries: Austria, Finland, France, Germany, Italy, the Netherlands, Portugal and Spain. Using quarterly data for these variables during 2003 through 2010 (32 quarters), they find that: Keep Reading

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