Gold

A subscriber asked which exchange-traded fund (ETF) asset class proxies make the best safe havens for the U.S. stock market as proxied by the S&P 500 Index. To investigate, we consider the following 12 ETFs as potential safe havens:

Utilities Select Sector SPDR ETF (XLU)
iShares 20+ Year Treasury Bond (TLT)
iShares 7-10 Year Treasury Bond (IEF)
iShares 1-3 Year Treasury Bond (SHY)
iShares Core US Aggregate Bond (AGG)
iShares TIPS Bond (TIP)
Vanguard REIT ETF (VNQ)
SPDR Gold Shares (GLD)
PowerShares DB Commodity Tracking ETF (DBC)
United States Oil (USO)
iShares Silver Trust (SLV)
PowerShares DB G10 Currency Harvest ETF (DBV)

We consider three ways of testing these ETFs as safe havens for the U.S. stock market based on daily or monthly returns:

1. Contemporaneous return correlation with the S&P 500 Index during all market conditions at daily and monthly frequencies.
2. Performance during S&P 500 Index bear markets as defined by the index being below its 10-month simple moving average (SMA10) at the end of the prior month.
3. Performance during S&P 500 Index bear markets as defined by the index falling -20%, -15% or -10% below its most recent peak at the end of the prior month.

Using daily and monthly dividend-adjusted closing prices for the 12 ETFs since respective inceptions, and contemporaneous daily and monthly levels of the S&P 500 Index since 10 months before the earliest ETF inception, all through November 2018, we find that: Keep Reading

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

A subscriber asked which asset (short stocks, cash, bonds by subclass) is best to hold during equity bear markets, defined simply as intervals when SPDR S&P 500 (SPY) is below its 10-month simple moving average (SMA10). To investigate, we test the following nine alternatives, five of which are bond-like mutual funds and two of which are gold-related:

Short SPY
Cash, with return estimated as the yield on 13-week U.S. Treasury bills (T-bill)
Vanguard GNMA Securities (VFIIX)
T. Rowe Price International Bonds (RPIBX)
Vanguard Long-Term Treasury Bonds (VUSTX)
Fidelity Convertible Securities (FCVSX)
T. Rowe Price High-Yield Bonds (PRHYX)
Fidelity Select Gold Portfolio (FSAGX)
Spot Gold

Specifically, we compare monthly return statistics, cumulative performances and maximum (peak-to-trough) drawdowns of these nine alternatives for months during which SPY is below its SMA10. Using monthly T-bill yield and monthly dividend-adjusted closing prices for the above assets during January 1993 (as limited by SPY) through Mar 2018, we find that: Keep Reading

How might an investor construct a portfolio of very risky assets? To investigate, we consider:

• Diversifying (based on pairwise correlations) by combining: (1) Bitcoin Investment Trust (GBTC), representing a very long-term option on Bitcoins; (2) VanEck Vectors Junior Gold Miners ETF (GDXJ), representing a very long-term option on gold; and, (3) ProShares Short VIX Short-Term Futures (SVXY), to capture the U.S. stock market volatility risk premium by shorting short-term S&P 500 Index implied volatility (VIX) futures.
• Capturing upside volatility and managing portfolio drawdown via monthly rebalancing and gain-skimming to a cash position.

We assume equal initial allocations of $10,000 to each of the three risky assets and $0 to cash. If the risky assets have a month-end combined value less than the combined initial allocations, we rebalance them to equal weights for next month. If the risky assets have a combined month-end value greater than the combined initial allocations, we rebalance to the initial allocations and move the excess permanently (skim) to cash. We assume monthly portfolio reformation frictions of 2% of month-end combined values of risky assets. We assume accrued, skimmed cash earns the 3-month U.S. Treasury bill (T-bill) yield. Using monthly adjusted values of GBTC, GDXJ and SVXY and contemporaneous T-bill yield during May 2015 (limited by GBTC) through mid-February 2018, we find that:

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How are behaviors of physically backed gold and gold miner exchange-traded funds (ETF) similar and different? To investigate we consider SPDR Gold Shares (GLD) and Market Vectors Gold Miners (GDX). Using weekly returns for these assets, and for SPDR S&P 500 (SPY), over the available sample period of May 2006 (limited by GDX) through October 2017, we find that:

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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