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Andrew L. Detzel

Researcher at University of Denver

Publications -  22
Citations -  1725

Andrew L. Detzel is an academic researcher from University of Denver. The author has contributed to research in topics: Capital asset pricing model & Sharpe ratio. The author has an hindex of 7, co-authored 21 publications receiving 1205 citations. Previous affiliations of Andrew L. Detzel include University of Washington.

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The Asset Pricing Implications of Government Economic Policy Uncertainty

TL;DR: It is found that EPU positively forecasts log excess market returns and innovations in EPU earn a significant negative risk premium in the Fama-French 25 size-momentum portfolios.
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The Asset-Pricing Implications of Government Economic Policy Uncertainty

TL;DR: Jiang et al. as mentioned in this paper used the news-based measure of Baker et al.'s EPU to capture economic policy uncertainty in the United States, and found that EPU positively forecasts log excess market returns.
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Learning and predictability via technical analysis: Evidence from bitcoin and stocks with hard-to-value fundamentals

TL;DR: In this paper, the authors propose an equilibrium model that shows how rational learning enables return predictability through technical analysis, showing 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.
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Do limits to arbitrage explain the benefits of volatility-managed portfolios?

TL;DR: In this article, the authors investigate whether transaction costs, arbitrage risk, and short-sale impediments explain the abnormal returns of volatility-managed equity portfolios and show that volatility management of asset-pricing factors besides the market return generally produces zero abnormal returns and significantly reduces Sharpe ratios.
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Combination Return Forecasts and Portfolio Allocation with the Cross-Section of Book-to-Market Ratios

TL;DR: In this article, the authors forecast industry returns out-of-sample using the cross-section of book-to-market ratios and investigate whether investors can exploit this predictability in portfolio allocation.