Gold

What steps should investors consider to mitigate impact of inevitable large U.S. stock market corrections? In their May 2019 paper entitled “The Best of Strategies for the Worst of Times: Can Portfolios be Crisis Proofed?”, Campbell Harvey, Edward Hoyle, Sandy Rattray, Matthew Sargaison, Dan Taylor and Otto Van Hemert compare performances of an array of defensive strategies with focus on the eight worst drawdowns (deeper than -15%) and three NBER recessions during 1985 through 2018, including:

1. Rolling near S&P 500 Index put options, measured via the CBOE S&P 500 PutWrite Index.
2. Credit protection portfolio that is each day long (short) beta-adjusted returns of duration-matched U.S. Treasury futures (BofAML US Corp Master Total Return Index), scaled retrospectively to 10% full-sample volatility.
3. 10-year U.S. Treasury notes (T-notes).
4. Gold futures.
5. Multi-class time-series (intrinsic or absolute) momentum portfolios applied to 50 futures contract series and reformed monthly, with:
   • Momentum measured for 1-month, 3-month and 12-month lookback intervals.
   • Risk adjustment by dividing momentum score by the standard deviation of security returns.
   • Risk allocations of 25% to currencies, 25% to equity indexes, 25% to bonds and 8.3% to each of agricultural products, energies and metals. Within each group, markets have equal risk allocations.
   • Overall scaling retrospectively to 10% full-sample volatility.
   • With or without long equity positions.
6. Beta-neutral factor portfolios that are each day long (short) stocks of the highest (lowest) quality large-capitalization and mid-capitalization U.S. firms, based on profitability, growth, balance sheet safety and/or payout ratios.

They further test crash protection of varying allocations to the S&P 500 Index and a daily reformed hedge consisting of equal weights to: (1) a 3-month time series momentum component with no long equity positions and 0.7% annual trading frictions; and, (2) a quality factor component with 1.5% annual trading frictions. For this test, they scale retrospectively to 15% full-sample volatility. Throughout the paper, they assume cost of leverage is the risk-free rate. Using daily returns for the S&P 500 Index and inputs for the specified defensive strategies during 1985 through 2018, they find that:

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A subscriber requested testing of the relationship between U.S. M2 Money Stock and gold, offered in one form via “Why Gold May Be Looking Cheap”: “[O]ne measure I’ve found useful is the ratio of the price of gold to the U.S. money supply, measured by M2, which includes cash as well as things like money market funds, savings deposits and the like. The logic is that over the long term the price of gold should move with the change in the supply of money… That equilibrium level is also relevant for future price action. When the ratio is low, defined as 25% below equilibrium, the medium 12-month return has been over 12%. Conversely, when the ratio is high, defined as 25% above equilibrium, the 12-month median return has been -6%. …This measure can be refined further. [G]old tends to trade at a higher ratio to M2 when inflation is elevated.” Because it defines specific valuation thresholds, this approach is susceptible to data snooping bias in threshold selection. We consider an alternative setup that relates monthly change in M2 to monthly gold return. We also consider the effect of inflation on this relationship. Using monthly seasonally adjusted M2 and end-of-month London gold price fix during January 1976 (to ensure a free U.S. gold market) through June 2018 (510 months), we find that: Keep Reading

Are there any gold trading strategies that reliably beat buy-and-hold? In their April 2018 paper entitled “Investing in the Gold Market: Market Timing or Buy-and-Hold?”, Viktoria-Sophie Bartsch, Dirk Baur, Hubert Dichtl and Wolfgang Drobetz test 4,095 seasonal, 18 technical, and 15 fundamental timing strategies for spot gold and gold futures. These strategies switch at the end of each month as signaled between spot gold or gold futures and U.S. Treasury bills (T-bill) as the risk-free asset. They assume trading frictions of 0.2% of value traded. To control for data snooping bias, they apply the superior predictive ability multiple testing framework with step-wise extensions. Using monthly spot gold and gold futures prices and T-bill yield during December 1979 through December 2015, with out-of-sample tests commencing January 1990, they find that:

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What is the interplay among investable proxies for the U.S. dollar, gold and crude oil? Do changes in the value of the dollar lead those in hard assets? To investigate, we relate the return series of three exchange-traded funds: (1) the futures-based PowerShares DB US Dollar Index Bullish (UUP); (2) the spot-based SPDR Gold Shares (GLD); and, (3) the spot-based United States Oil (USO). Using monthly, weekly and daily prices for these funds during March 2007 (limited by inception of UUP) through April 2018 (134 months), we find that: Keep Reading

What research is available bearing on silver, platinum and palladium as investments? In their April 2017 paper entitled “The Financial Economics of White Precious Metals – A Survey”, Samuel Vigne, Brian Lucey, Fergal O’Connor and Larisa Yarovaya summarize the body of academic research on the financial economics of silver, platinum and palladium. The survey covers relevant studies of market efficiency, predictability, behavioral influences, diversification benefits, volatility drivers, macroeconomic influences and relationships with other assets. Based on this research, they conclude that: Keep Reading

In their February 2017 paper entitled “Bayesian Model Averaging, Ordinary Least Squares and the Price of Gold”, Dirk Baur and Brian Lucey analyze a large set of factors that potentially influence the price of gold via two methods: Ordinary Least Squares (OLS, scatter plot) and Bayesian Model Averaging (BMA, accounting for model uncertainty). They include as potential influencers three other precious metals futures, crude oil spot and futures, two commodity indexes, U.S. and world stock indexes, currency exchange rates, 10-year U.S. Treasury note (T-note) yield, U.S. Federal Funds Rate (FFR), a volatility index (VIX) and U.S. and world consumer price indexes. To test robustness of influencers, they consider: (1) subsamples to test consistency over time; (2) daily and monthly measurements to test consistency across sampling frequencies (except consumer price indexes, available only monthly); and, (3) contemporaneous and one period-lagged (predictive) relationships. Using daily and monthly prices for the specified assets during January 1980 through September 2016, they find that: Keep Reading

Are precious metals effective safe havens, preserving capital when stocks and bonds crash? In their January 2017 paper entitled “Reassessing the Role of Precious Metals as Safe Havens – What Colour is Your Haven and Why?”, Sile Li and Brian Lucey assess whether four precious metals (gold, silver, platinum and palladium) are safe havens relative to stock market indexes and 10-year government bonds across 11 countries. The 11 countries are: U.S., UK, Germany, France, Italy, Switzerland, Canada, Japan, China, India and South Africa. They focus on stock and bond market crashes specified as daily returns in the bottom 5% of respective return distributions over the entire sample period. They define weak and strong safe haven behaviors based on moderate and high statistical confidence in crash protection, respectively. They consider different economic and political causes of stock and bond market crashes. Using daily returns for stock market indexes, 10-year government bond indexes and precious metals spot markets for the 11 countries, all in local currencies, during January 1994 through July 2016, they find that: Keep Reading

Do changes in the dollar-euro exchange rate reliably interact with the U.S. stock market and gold? For example, do declines in the dollar relative to the euro indicate increases in the dollar value of hard assets? Are the interactions coincident or exploitably predictive? To investigate, we relate changes in the dollar-euro exchange rate to returns for U.S. stock indexes and spot gold. Using end-of-month and end-of-week values of the dollar-euro exchange rate, levels of the S&P 500 Index and Russell 2000 Index and spot prices for gold during January 1999 (limited by the exchange rate series) through October 2016, we find that: Keep Reading

“Central Bank Gold Reserves, Gold Lending and Gold Price” finds some conditional relationships between aggregate world central bank gold reserves and gold price. Can investors exploit these relationships? To check, we relate recent quarterly estimates of central bank gold reserves and quarterly spot gold price, noting that there is roughly a one quarter delay in availability of the former. Using these data from the end of the first quarter of 2000 through the end of the first quarter of 2016, we find that: Keep Reading

Do central banks predictably influence the price of gold? In the July 2016 revision of his paper entitled “Central Banks and Gold”, Dirk Baur examines interactions of central bank gold reserves, gold carry trade profitability and gold price. Using monthly data for central bank gold reserves and gold prices since 1968 and for 1-month and 6-month gold lease rates since 1989, as available through 2015, he finds that: Keep Reading