Currency Trading

How might an investor construct a portfolio of very risky assets? To investigate, we revisit ideas first considered six years ago:

• First, diversify with monthly rebalancing of:
  1. Grayscale Bitcoin Trust ETF (GBTC), an indirect Bitcoin holding.
  2. SPDR Gold Shares (GLD), an indirect gold holding.
  3. ProShares Short VIX Short-Term Futures ETF (SVXY), to capture part of the U.S. stock market volatility risk premium by shorting short-term VIX futures.
• Second, capturing upside volatility and managing drawdown of this portfolio via gain-skimming to a cash position.

We assume equal initial allocations of $10,000 to each of the three assets. We perform a monthly skim as follows: (1) if the risky assets have month-end combined value less than combined initial allocations ($30,000), we rebalance to equal weights for next month; or, (2) if the risky assets have combined month-end value greater than combined initial allocations, we rebalance to initial allocations and move the excess permanently (skim) to cash. We very conservatively assume monthly portfolio reformation frictions of 1% of month-end combined value of risky assets. We assume accrued skimmed cash earns the 3-month U.S. Treasury bill (T-bill) yield. Using monthly prices of GBTC, GLD and SVXY adjusted for splits/dividends and monthly T-bill yield during May 2015 (limited by GBTC) through July 2026, we find that:

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Does economic growth logically and reliably anchor asset class returns? In his July 2026 paper entitled “A General, Scientific Unified Theory of Economic Growth, Asset Valuation and Return: A Common Necessary Constant Evidence for a Natural Law”, Julian Van Erlach presents theoretical and empirical evidence connecting real economic growth (change in real Gross Domestic Product, GDP) to stock market, bond, gold and bitcoin valuations. Based on theory and empirical data for relevant economic variables and asset class returns spanning different sample periods, he concludes that: Keep Reading

How do different asset classes interact with the Japanese yen-U.S. dollar exchange rate? To investigate, we consider relationships between Invesco CurrencyShares Japanese Yen (FXY) and the exchange-traded fund (ETF) asset class proxies used in the Simple Asset Class ETF Momentum Strategy (SACEMS) or the Simple Asset Class ETF Value Strategy (SACEVS) at a monthly measurement frequency. Using monthly dividend-adjusted closing prices for FXY and the asset class proxies since March 2007 as available through June 2026, we find that: Keep Reading

How do different asset classes interact with euro-U.S. dollar exchange rate? To investigate, we consider relationships between Invesco CurrencyShares Euro Currency (FXE) and the exchange-traded fund (ETF) asset class proxies used in the Simple Asset Class ETF Momentum Strategy (SACEMS) or the Simple Asset Class ETF Value Strategy (SACEVS) at a monthly measurement frequency. Using monthly dividend-adjusted closing prices for FXE and the asset class proxies since February 2006 as available through June 2026, we find that: Keep Reading

How do different asset classes interact with U.S. dollar valuation? To investigate, we consider relationships between Invesco DB US Dollar Index Bullish Fund (UUP) and the exchange-traded fund (ETF) asset class proxies used in the Simple Asset Class ETF Momentum Strategy (SACEMS) or the Simple Asset Class ETF Value Strategy (SACEVS) at a monthly measurement frequency. Using monthly dividend-adjusted closing prices for UUP and the asset class proxies since March 2007 as available through June 2026, we find that: Keep Reading

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 test 16 ETFs/funds as potential safe havens:

State Street Utilities Select Sector SPDR (XLU)
iShares 20+ Year Treasury Bond (TLT)
iShares 7-10 Year Treasury Bond (IEF)
iShares 1-3 Year Treasury Bond (SHY)
State Street SPDR Bloomberg 1-3 Month T-Bill (BIL)
iShares iBoxx $ Investment Grade Corporate Bond (LQD)
iShares Core US Aggregate Bond (AGG)
iShares TIPS Bond (TIP)
Vanguard Short-Term Inflation-Protected Securities Index Fund (VTIP)
Vanguard Real Estate Index Fund (VNQ)
SPDR Gold Shares (GLD)
iShares Silver Trust (SLV)
Invesco DB Commodity Index Tracking Fund (DBC)
United States Oil Fund, LP (USO)
Invesco DB US Dollar Index Bullish Fund (UUP)
Grayscale Bitcoin Trust (GBTC)

We consider three ways to find 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 being -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 above 16 funds since their respective inceptions, and contemporaneous daily and monthly levels of the S&P 500 Index since 10 months before the earliest inception, all through April 2026, we find that: Keep Reading

In response to “Bitcoin Trend Predicts U.S. Stock Market Return?”, a subscriber suggested that bitcoin (BTC) price trend/return may be more strongly predictive of NASDAQ 100 Index (NDX) returns than of S&P 500 Index returns. To investigate, we relate BTC returns to NDX returns at daily, weekly and monthly frequencies. We rationalize the different trading schedules for these two series by excluding BTC trading dates that are not also NDX trading days. Most results are conceptual, but we test three versions of an NDX timing strategy based on prior BTC returns focused on compound annual growth rate (CAGR) and maximum drawdown (MaxDD). Using daily NDX levels and (pruned) BTC prices during 9/17/2014 (limited by the BTC series) through 3/4/2026, we find that:

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What is the interplay among exchange-traded fund (ETF) proxies for the U.S. dollar, gold and crude oil? Do changes in the value of the dollar lead or lag those in hard assets? To investigate, we relate returns of Invesco DB US Dollar Index Bullish Fund (UUP) to those for each of:

1. SPDR Gold Shares (GLD).
2. United States Oil Fund, LP (USO).
3. Invesco DB Commodity Index Tracking Fund (DBC), as a broader hard asset proxy for comparison.

We look at contemporaneous and lead-lag relationships. Using monthly dividend-adjusted prices for these funds during March 2007 (limited by UUP) through February 2026, we find that: Keep Reading

A subscriber asked about an assertion that bitcoin (BTC) price trend/return predicts return of the S&P 500 Index (SP500). To investigate, we relate BTC returns to SP500 returns at daily, weekly and monthly frequencies. We rationalize the different trading schedules for these two series by excluding BTC trading dates that are not also SP500 trading days. Most results are conceptual, but we test three versions of an SP500 timing strategy based on prior BTC returns focused on compound annual growth rate (CAGR) and maximum drawdown (MaxDD). Using daily SP500 levels and (pruned) BTC prices during 9/17/2014 (limited by the BTC series) through 3/4/2026, we find that:

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Are there cryptocurrencies that are so alike that they generally track each other and reliably revert whenever they diverge? In their December 2025 paper entitled “Pairs Trading in Crypto”, Sasha Stoikov, Dora Xu, Shijie Shao, Yourui Wang, Tongshu Zhang and Jinxuan Hu show how to identify cryptocurrency pairs with stable relationships and execute mean reversion strategies in real time. Specifically, they:

• Identify pairs to trade by combining correlation behaviors, structural metadata and stability diagnostics.
• Generate entry thresholds, exit rules and risk controls (stop-loss, pair suspension and pair abandonment) for long-short trades that exploit overvaluation and undervaluation of pairs based on rolling window divergences.

Starting with hourly data for a sample of 543 cryptocurrency perpetual futures contract series (147,153 potential pairs), with 800 days through February 2025 as a training set and March through September 2025 as a test set (plus some short live tests during late November and early December 2025), they find that:

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