Learning and Predictability via Technical Analysis: Evidence from Bitcoin and Stocks with Hard-to-Value Fundamentals
51 Pages Posted: 13 Feb 2018 Last revised: 31 Jan 2020
Date Written: January 29, 2020
What predicts returns on assets with "hard-to-value" fundamentals, such as Bitcoin and stocks in new industries? We propose an equilibrium model that shows how rational learning enables return predictability through technical analysis. We document that ratios of prices to their moving averages forecast daily Bitcoin returns in- and out-of sample. Trading strategies based on these ratios generate an economically significant alpha and Sharpe ratio gains relative to a buy-and-hold position. Similar results hold for small-cap, young-firm, and low-analyst-coverage stocks as well as NASDAQ stocks during the dotcom era.
Keywords: Bitcoin, Cryptocurrency, Technical Analysis
JEL Classification: G11, G12, G14
Suggested Citation: Suggested Citation