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Currency Trading

Currency trading (forex or FX) offers investors a way to trade on country or regional fiscal/monetary situations and tendencies. Are there reliable ways to exploit this market? Does it represent a distinct asset class?

Machine Learning for Bitcoin/Ethereum Daily Trading

Can machine learning usefully inform daily crypto-asset trading? In their August 2021 paper entitled “Boosting Cryptocurrency Return Prediction”, Ilias Filippou, David Rapach and Christoffer Thimsen apply the XGBoost algorithm to decision trees to generate next-day forecasts of bitcoin and Ethereum excess returns. They consider 39 potential predictor inputs, including: valuation ratios (network value-to-transactions, addresses-to-network value and fee-to-price); return volatilities over the past one, two or three months; deviations of prices from moving averages for four lookback intervals; cumulative excess returns (momentum) for three lookback intervals; and, sentiment indicators based on Google Trends searches, Reddit comments or Factiva articles. They further explore the relative importance of individual predictors. Their benchmark predictors are inception-to-date mean past returns. Using daily prices from CoinMetrics for bitcoin since since mid-July 2010 and for Ethereum since early August 2015, both through January 2021, along with the contemporaneous risk-free rate and data needed to calculate non-price input predictors, they find that:

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Is Crypto-asset Wealth Real?

Does over $1 trillion in crypto-assets (having no fundamental value and paying no interest, but trading freely) now held by Americans represent new wealth? In his brief June 2021 paper entitled “Bubble Wealth”, Bradford Cornell addresses the apparent paradox between the view of economic theory (no new wealth) and the fact that those holding crypto-assets can use them for consumption (yes new wealth). He defines “bubble wealth” as the difference between wealth convertible to future consumption (real assets) and perceived wealth (not founded on real assets). Using a simple numerical example involving bubble wealth creation and destruction, he concludes that: Keep Reading

Bitcoin Price Forecasting Models

Are there plausible ways to forecast the price of bitcoin? In their March 2021 paper entitled “Bitcoin Price Forecast Using Quantitative Models”, Daniele Bernardi and Ruggero Bertelli examine fundamental bitcoin value from four perspectives:

  1. Stock-to-Flow modeling that addresses evolving scarcity based on quantity of bitcoin already present in the world (Stock) and quantity of bitcoin extracted each year (Flow).
  2. How bitcoin price bubbles relate to the halving rule (planned 50% reductions in the reward for successfully mining bitcoins).
  3. Demand modeling based on the rate of bitcoin adoption.
  4. Supply modeling based on costs and revenues of bitcoin production, emphasizing the role of hash rate (evolving system security).

Based on Bitcoin design and bitcoin price data spanning 2009 through 2020, they conclude that: Keep Reading

U.S. Dollar Seasonal Strength/Weakness and Stock Market Returns

A subscriber asked whether currency exchange rates exhibit reliable seasonality that may be used to time equities (with a stronger currency implying lower asset prices). To investigate, we look for reliable calendar month effects for the U.S. dollar (USD)-euro exchange rate and for Invesco DB US Dollar Index Bullish Fund (UUP). We further look at how monthly returns for these variables relate to those for SPDR S&P 500 ETF Trust (SPY) as a proxy for the U.S. stock market. Using monthly data for the USD-euro exchange rate since January 1999 and for UUP since March 2007 and corresponding data for SPY, all through August 2021, we find that: Keep Reading

Speculator Attention and Bitcoin Return

Speculator level of interest (attention) is plausibly key to bitcoin price behavior. Does the level of online searches for “bitcoin” as a proxy for attention usefully predict bitcoin return? To investigate, we examine interactions between monthly worldwide search intensity for “bitcoin” as measured by Google Trends to represent speculator attention and monthly bitcoin returns. Using monthly Google Trends data starting September 2014 (to coincide with inception of source price tracking) as retrieved on 9/6/2021 and end-of-month bitcoin prices during September 2014 through August 2021, we find that: Keep Reading

Predictable Bitcoin Momentum or Reversion?

Does bitcoin (BTC) price predictably exhibit momentum or reversion? To investigate, we try three tests:

  1. Calculate autocorrelations (serial correlations) between daily, weekly and monthly (4-week) BTC returns and BTC returns for the next five respective intervals (for example, correlation of daily return with returns the next five days). Positive and negative correlations suggest momentum and reversion, respectively.
  2. Calculate correlations between next-week BTC return and current BTC price relative to its high or low over the last 13 weeks. A positive correlation for closeness to the recent high (low) suggests momentum (reversion).
  3. Calculate average next-week BTC returns by ranked fifth (quintile) of BTC price relative to its high or low over the last 13 weeks.

Using daily, weekly and monthly (4-week) BTC closing prices during September 14, 2014 (the earliest available from the source) through August 31, 2021, we find that:

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Bitcoin Displacing Gold?

Is Bitcoin beginning to displace gold as a U.S. dollar hedge? To investigate, we look at rolling correlations of returns for the following pairs of exchange-traded funds (ETF):

  1. Grayscale Bitcoin Trust (GBTC) and SPDR Gold Shares (GLD). This relationship should perhaps trend negative if investors are shifting from gold to Bitcoin.
  2. GBTC and Invesco DB US Dollar Index Bullish Fund (UUP). This relationship should perhaps trend negative if investors are hedging currency weakness with Bitcoin.
  3. GLD and UUP. This relationship should perhaps trend less negative if investors are shifting away from gold as a currency hedge.

Using daily and monthly adjusted prices for these three ETFs during May 2015 (limited by GBTC) through mid-August 2021, we find that: Keep Reading

Are Managed Futures ETFs Working?

Are managed futures, as implemented by exchange-traded funds (ETF), attractive? To investigate, we consider three managed futures ETFs, all currently available:

  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.
  4. iM DBi Managed Futures Strategy (DBMF) – seeks long-term capital appreciation via long and short positions in futures across the asset classes such as equities, fixed income, currencies and commodities. Fund positions approximate the current asset allocation of a pool of the largest commodity trading advisor hedge funds.

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 Barclays 20+ Year Treasury Bond (TLT), all based on monthly data, as key performance statistics. We use Eurekahedge CTA/Managed Futures Hedge Fund Index (Eurekahedge) as a benchmark. Using monthly returns for the four managed futures funds as available through July 2021, and contemporaneous monthly returns for the benchmark index, SPY and TLT, we find that:

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Future of Stablecoins?

The National Bank Act of 1863 created a national currency backed by U.S. Treasury bonds and curtailed the era of Free Banking (wildcat private currencies), which resembles the current environment of stablecoins (such as Tether and Diem). Subsequent legislation taxed private currencies out of existence. Does this history offer lessons for the future of stablecoins? In their July 2021 paper entitled “Taming Wildcat Stablecoins”, Gary Gorton and Jeffery Zhang explore the feasibility of stablecoins as a medium of exchange, with focus on acceptance at par and susceptibility to runs. They also present proposals to address  systemic stablecoin risks. Based on lessons from history, they conclude that: Keep Reading

Defi Risks and Crypto-asset Growth

What Decentralized Finance (DeFi) issues may dampen associated interest in crypto-assets by undermining its promises of lower costs and risks compared to traditional, centralized financial intermediaries? In their June 2021 book chapter entitled “DeFi Protocol Risks: the Paradox of DeFi”, Nic Carter and Linda Jeng discuss five sources of DeFi risk:

  1. Interconnections with the traditional financial system.
  2. Blockchain-related operational issues.
  3. Smart contract vulnerabilities.
  4. Other governance and regulatory concerns.
  5. Scalability challenges.

A general objective of DeFi is automating rules for behavior in a publicly available financial system, eliminating human discretion from financial transactions/contracts. In practice, however, core DeFi protocols retain some human oversight to address unpredictable problems as they emerge, but such retention allows incompetent or malicious governance, administration and validation (see the figure below). Based on review of the body of research and opinion, they conclude that:

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