New strategies:
#408 – Cointegrated Cryptocurrency Portfolios
Period of rebalancing: daily
Markets traded: cryptos
Instruments used for trading: cryptos
Complexity: Complex strategy
Bactest period: 2017-2018
Indicative performance: 42.68%
Estimated volatility: not stated
Source paper:
Leung, Tim and Nguyen, Hung: Constructing Cointegrated Cryptocurrency Portfolios for Statistical Arbitrage
https://ssrn.com/abstract=3235890
Abstract:
In this paper, we analyze the process of constructing cointegrated portfolios of cryptocurrencies. Our procedure involves a series of statistical tests, including the Johansen cointegration test and Engle-Granger two-step approach. Among our results, we construct cointegrated portfolios involving four cryptocurrencies: Bitcoin (BTC), Ethereum (ETH), Bitcoin Cash (BCH), and Litecoin (LTC). We develop a number of trading strategies under different entry/exit thresholds and risk constraints, and examine their performance in details through backtesting and comparison analysis. Our methodology can be applied more generally to create new cointegrated portfolio using other cryptocurrencies.
#409 – Trading Volume in Cryptocurrency Markets and Reversals
Period of rebalancing: daily
Markets traded: cryptos
Instruments used for trading: cryptos
Complexity: Complex strategy
Bactest period: 2017-2018
Indicative performance: 34.26%
Estimated volatility: 11.56%
Source paper:
Bianchi, Daniele and Dickerson, Alexander: Trading Volume in Cryptocurrency Markets
https://ssrn.com/abstract=3239670
Abstract:
We study the information content of trading volume in cryptocurrency markets and contribute to a growing literature that aims to understand the role of digital currencies as financial assets. The main results show that the interaction between shocks to volume and past returns have a substantial predicting power for future returns, both in the time series and in the cross-section. Such predictive power is economically significant both intraday and on a daily basis; an investment strategy that double sort on past volume and returns generates a substantial Sharpe ratio with almost zero correlation with Bitcoin dollar returns. These results are broadly consistent with established theoretical models where investors have incomplete and asymmetric information as well as different trading motives.
New research papers related to existing strategies:
#200 – Classical Equity Anomalies Combined with Trendfollowing Filter
Jiang, Qi, Tang, Huang: It Takes Two to Tango: Fundamental Timing in Stock Market
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3252887
Abstract:
In this paper, we propose a fundamental timing strategy in both U.S. and Chinese stock market to trade the fundamental sorted portfolios such as value and profitability portfolios in the time series dimension. We find that fundamental timing strategies based on moving average (MA) timing signals could generate substantial performance improvements relative to corresponding buy-and-hold fundamental strategies. The annualized average return of the 20-day MA fundamental timing strategies reaches about 37% with Sharpe ratio nearly 1.30. These findings are robust to Fama-French factor model adjustment, alternative lag lengths of MA signals, holding days, and transaction costs. Moreover, we find that the fundamental timing premium cannot be explained by market timing ability or business cycle, and fundamental timing is more profitable among firms with high idiosyncratic volatility and high illiquidity measures.
#334 – Volatility-Adjusted Momentum in Corporate Bonds
Fang: Bond Return, Spread Change, and the Momentum Effect in Corporate Bond and Stock Markets
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3184704
Abstract:
This paper examines the momentum effect and its causes, the persistence in default risk change in particular, in both corporate bond and stock markets. Using a comprehensive bond dataset, we observe a significant momentum effect in corporate bond returns and bond credit spread changes. The momentum effect in bond total returns, however, is confined to low-grade bonds and can be attributed to compensation for bearing a varying default risk and term risk. This paper shows that the change in bond credit spread, not the total return, is a more appropriate proxy to examine the response of bond prices to new information of firm fundamentals. Past spread changes have robust predictive power for future spread changes even after controlling for risk characteristics such as duration and yield-to-maturity. This paper also documents the integration of the momentum effect across bond and stock markets. Equity returns, bond returns and bond spread changes are contemporaneously correlated. Equity winners (losers) are also bond winners (losers) with improved (deteriorated) credit quality and vice versa. Equity return momentum exhibits spillover to both bond returns and spread changes, although the spillover to bond returns can only be observed after controlling for default risk. Firms earning extremely low equity returns over the past six months increase bond spreads significantly in the next six months. After controlling for the yield-to-maturity, extreme equity winners (losers) earn high (low) bond returns. Although past bond returns have no predictive power for future stock returns, there is a significant momentum spillover from spread changes to stock returns. Past spread changes can explain half of momentum profit in future stock returns. This result indicates that the persistence in the default risk change may play an important role in understanding the source of momentum profits in equity returns.
And three additional related research papers have been included into existing free strategy reviews during last 2 weeks:
#33 – Post-Earnings Announcement Effect
Li: Does Too Much Arbitrage Destablize Stock Price? Evidence from Short Selling and Post Earnings Announcement Drift.
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3249254
Abstract:
Stein (2009) suggests that too much arbitrage capital exploiting underreaction can lead to overreaction, pushing price further away from fundamental value. I test this hypothesis by investigating the relation between changes in short interest ratio around earning announcement and the subsequent drift return. There are two main findings in this paper. First, my results suggest that too much arbitrage capital does contribute to overreaction (with a t-statistics around 4 on average). These findings are robust to alternative sample periods or length of the window for drift calculation. Second, contrary to the findings in prior literature that show that short sellers mitigate the magnitude of drift, my results show that almost all of this effect are actually contributed by the observations that are more likely to represent overreaction.
We have mentioned it several times – we are quants but we love history and we love research papers like this:
McQuarrie: The First Eighty Years of the US Bond Market: Investor Total Return from 1793, Combining Federal, Municipal, and Corporate Bonds
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3260733
Abstract:
US securities markets took root after Alexander Hamilton’s refunding of the Federal debt in the early 1790s. Accordingly, a market in bonds has been in operation in the US for over two centuries. Until recently, however, little was known about the bond market prior to 1857. This paper focuses on investor holding period returns, using newly compiled data on bond prices, rather than focusing on the movement of yields, as in Homer (1963). It incorporates the relatively familiar Treasury securities from before President Andrew Jackson paid off the debt in 1835, but also includes state and city debt, which ballooned beginning in the 1820s, as well as corporate debt, from its beginnings about 1830 to its explosion after 1850. I find that all three classes of bonds provided investors with similar total returns, excepting a brief period in the 1840s when state securities plunged before recovering. I also find that real returns in the eight decades following 1793 were generally higher than the long-term average return of 3.6% proposed for bonds in Siegel (2014). I further find that in these early years, bonds sometimes out-performed stocks over periods of several decades, again contrary to Siegel’s thesis. The paper considers the implications of a demonstration that stocks and bonds performed differently in the nineteenth century as compared to the twentieth century.
Do you invest in emerging market bonds? A new interesting academic research paper just for you:
Kang, So, Tziortziotis: Embedded Betas and Better Bets: Factor Investing in Emerging Market Bonds
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3196018
Abstract:
We document novel empirical insights driving the prices of sovereign external emerging market bonds. In the time series, we examine the market portfolio’s time-varying exposures to a broad set of macro factors (rates, credit, currency, and equity) and identify these embedded betas as key drivers of its excess returns. In the cross-section, we construct complementary value and momentum style factors and demonstrate their ability to explain country expected returns. Building off these insights, we introduce a simple risk-on versus risk-off framework to characterize the correlation structure spanning our macro and style factors. Lastly, we show how our style factors can be incorporated in an optimized long-only portfolio to generate outperformance relative to a value-weighted benchmark portfolio.
