Currency Trading

Are managed futures, as implemented by exchange-traded funds (ETF), attractive? To investigate, we consider six managed futures ETFs, five live and one dead:

1. WisdomTree Managed Futures Strategy (WTMF) – seeks positive total returns in rising or falling markets that are uncorrelated with broad market equity and fixed income returns via diversified combination of commodities, currencies and interest rates futures.
2. First Trust Morningstar Managed Futures Strategy (FMF) – seeks positive returns that are uncorrelated to broad market equity and fixed income returns via a portfolio of exchange-listed futures.
3. ProShares Managed Futures Strategy (FUT) – seeks to profit in rising and falling markets by long and short positions in futures across asset classes such as commodities, currencies and fixed income such that each contributes equally to portfolio risk. (Dead as of May 2022.)
4. iM DBi Managed Futures Strategy (DBMF) – seeks long-term capital appreciation via long and short positions in futures across equities, fixed income, currencies and commodities. Fund positions approximate the current asset allocation of a pool of the largest commodity trading advisor hedge funds.
5. KraneShares Mount Lucas Managed Futures Index Strategy ETF (KMLM) – seeks to track an index comprised of 22 liquid futures contracts traded on U.S. and foreign exchanges. The index includes groups of 11 commodities, six currencies, and five global bonds, with groups weighted by relative historical volatility and individual contracts weighted equally within each group.
6. Simplify Managed Futures Strategy (CTA) – seeks long term capital appreciation by systematically investing in futures in an attempt to create an absolute return profile, that also has a low correlation to equities, and can provide support in risk-off events.

We focus on average return, standard deviation of returns, reward/risk (average return divided by standard deviation), compound annual growth rate (CAGR), maximum drawdown (MaxDD) and correlations of returns with those of SPDR S&P 500 (SPY) and iShares iBoxx $ Investment Grade Corporate Bond (LQD), all based on monthly data, as key performance statistics. We use a monthly rebalanced 60% SPY-40% LQD portfolio (60-40) as a benchmark. Using monthly returns for the six managed futures funds as available through August 2026, and contemporaneous monthly returns for SPY and LQD, we find that:

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Does bitcoin (BTC) return exhibit any exploitable leading or lagging roles with respect to gold (SPDR Gold Shares – GLD) return, change in the all-items consumer price index (CPI) or change in the effective federal funds rate (EFFR) for a monthly measurement interval? To investigate, we compute correlations between monthly BTC return and each of monthly GLD return, change in CPI and change in EFFR for various lead-lag relationships, ranging from BTC return leads other variables by six months (-6) to other variables lead BTC return by six months (6). Using monthly BTC, GLC, CPI and EFFR levels during September 2014 (limited by BTC) through July 2026, we find that: Keep Reading

A subscriber suggested adding a simple 1-month or 3-month momentum filter to the BGSV portfolio, which each month rebalances to equal weight the following three very risky assets:

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.

We choose a momentum filter requiring that an asset must have a positive return the prior month, or its allocation goes to cash. Initial allocations to each of the three assets is $10,000. Cash earns the 3-month U.S. Treasury bill (T-bill) yield. We very conservatively assume monthly portfolio reformation frictions of 1% of month-end portfolio value. 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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A subscriber asked whether the Turn-of-the-Month (TOTM) effect applies to currencies. To investigate, as in the past, we define TOTM as the interval from the close five trading days before to the close four trading days after the last trading day of the month (a total of eight trading days, centered on the monthly close). We measure TOTM returns for the following three exchange-traded funds (ETF):

Invesco DB US Dollar Bullish (UUP)
Invesco CurrencyShares Euro Currency (FXE)
Invesco CurrencyShares Japanese Yen (FXY)

Using daily dividend-adjusted prices for these ETFs from their respective inceptions through mid-July 2026, we find that: Keep Reading

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