Objective research to aid investing decisions

Value Investing Strategy (Strategy Overview)

Allocations for May 2022 (Final)

Momentum Investing Strategy (Strategy Overview)

Allocations for May 2022 (Final)
1st ETF 2nd ETF 3rd ETF

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?

Patterns in Short-term Bitcoin Returns?

Are there short-term patterns in bitcoin returns? In their April 2022 paper entitled “Seasonality, Trend-following, and Mean Reversion in Bitcoin”, Matus Padysak and Radovan Vojtko explore short-term bitcoin return behaviors. They look at:

  • Daily patterns with respect to NYSE trading hours, defining intraday return as 10:00-16:00, overnight return as 16:00-10:00 and daily return as 1600-16:00 (all New York times).
  • Next-day trend-following/reversal based on proximity to maximum or minimum price over the previous 10, 20, 30, 40 or 50 days.

Using hourly and daily bitcoin prices in U.S. dollars from the Gemini exchange during mid-September 2015 through early March 2022, they find that:

Keep Reading

Investor Preferences and Bitcoin Allocations

Should investors consider allocations to bitcoin (BTC) in their investment portfolios? In their February 2022 paper entitled “Asset Allocation with Crypto: Application of Preferences for Positive Skewness”, Andrew Ang, Tom Morris and Raffaele Savi investigate how investors should think about allocations to BTC based on features of its historical return distribution. Specifically, they model optimal holdings of BTC, stocks and bonds for investors with either power utility or Cumulative Prospect Theory (CPT, loss aversion) preferences. Using monthly returns for BTC, the S&P 500 Index as a proxy for stocks and the Bloomberg Barclays Treasury Index as a proxy for bonds during July 2010 through December 2021, they find that: Keep Reading

NFT Return Behaviors

What are the return behaviors of non-fungible tokens (NFT), which employ blockchain technology to convey ownership of unique digital or physical items? In their March 2022 paper entitled “The Economics of Non-Fungible Tokens”, Nicola Borri, Yukun Liu and Aleh Tsyvinski assemble a comprehensive dataset of NFT transactions (including digital art/media and objects related to virtual worlds) and create NFT overall market and sector indexes based on a repeat sales method. They then test:

  • NFT market exposure to cryptocurrency market, size, value, momentum and attention factors.
  • NFT market exposure to traditional equity, commodity and currency market factors.
  • NFT market return predictability based on NFT market volatility, index-to-transaction valuation ratio, volume, momentum and attention factors.
  • Individual NFT return predictability based on size and momentum/reversal.

Using blockchain-validated weekly data from major NFT exchanges during January 2018 through December 2021, encompassing about 1.3 million repeat sales, they find that: Keep Reading

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:

Keep Reading

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:

Keep Reading

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

Daily Email Updates
Filter Research
  • Research Categories (select one or more)