What is the best strategy when investor detects a bubble? Step outside, short it, or ride it? Academic research shows it is best to ride as excess returns, which investor gains during bubble riding more than offsets risk of a subsequent crash (which always follows).
However, it is essential to be rational and to stop riding bubble when it starts to pop and do not fall in love with the particular industry. A bubble is identified as a structural break in the industry’s alpha return compared to the overall market return. A small part of the industry‘s return could be explained by a momentum factor. Still, the strategy of riding bubbles is distinct from momentum, and it, therefore, offers good diversification benefits.
A system’s validity seems strong as research shows that the industry bubbles are a different phenomenon than industry momentum. Since bubbles end with large negative abnormal returns, they cannot be explained by an underreaction to the good news.
Industry bubbles do not result from a misspecification of the asset pricing models used in research study: the bubbles cannot be explained by an omitted risk factor, an omitted structural break, or by a combination of factors, therefore, the trading strategy could be used as an independent add-on to the portfolio of strategies with potential for diversification.
Backtest period from source paper
Confidence in anomaly's validity
Notes to Confidence in Anomaly's Validity
Notes to Indicative Performance
per annum, calculated as average strategy abnormal return (8% from table 4 – using CAPM model) plus average nominal equity performance (~10%), average raw return for industry in bubble is ~30% per annum
Period of Rebalancing
Notes to Period of Rebalancing
Notes to Estimated Volatility
Number of Traded Instruments
Notes to Number of Traded Instruments
average number of industries held in one moment
Notes to Maximum drawdown
Moderately complex strategy
Notes to Complexity Evaluation
Simple trading strategy
The investment universe consists of equity industry funds (or ETFs), which are proxy for equity industry indexes. An investor uses ten years of past data to calculate the industry’s alpha based on the CAPM model (from the regression model industry_return = alpha + beta*market return, it is possible to use alternative models like the Fama/French 3 factor model). A bubble in an industry is detected if the industry’s alpha is statistically significant (academic source paper uses a 97,5% significance threshold, but it is possible to use other values). The investor is long in each industry experiencing a bubble by applying 1/N rule (investment is divided equally between industries in a bubble). If no bubble is detected, then he/she makes no investment. Data examination, alpha calculation, and portfolio rebalancing is done monthly.
Hedge for stocks during bear markets
No - The selected strategy is long-only. As such has a strong exposition to equity market risk, therefore it can’t be used as a hedge/diversification during the time of market crisis.
Out-of-sample strategy's implementation/validation in QuantConnect's framework