Estimating The Anomaly Base Rate / Alexander M. Chinco, Andreas Neuhierl, Michael Weber.

By:

Chinco, Alexander M

Contributor(s):

Material type: Text

TextSeries: Working Paper Series (National Bureau of Economic Research) ; no. w26493.Publication details: Cambridge, Mass. National Bureau of Economic Research 2019.Description: 1 online resource: illustrations (black and white)Subject(s):

Online resources:

Available additional physical forms:

Hardcopy version available to institutional subscribers

Abstract: The academic literature literally contains hundreds of variables that seem to predict the cross-section of expected returns. This so-called "anomaly zoo" has caused many to question whether researchers are using the right tests of statistical significance. But, here's the thing: even if researchers use the right tests, they will still draw the wrong conclusions from their econometric analyses if they start out with the wrong priors---i.e., if they start out with incorrect beliefs about the ex ante probability of encountering a tradable anomaly.Abstract: So, what are the right priors? What is the correct anomaly base rate?Abstract: We develop a first way to estimate the anomaly base rate by combining two key insights: 1) Empirical-Bayes methods capture the implicit process by which researchers form priors based on their past experience with other variables in the anomaly zoo. 2) Under certain conditions, there is a one-to-one mapping between these prior beliefs and the best-fit tuning parameter in a penalized regression. We study trading-strategy performance to verify our estimation results. If you trade on two variables with similar one-month-ahead return forecasts in different anomaly-base-rate regimes (low vs. high), the variable in the low base-rate regime consistently underperforms the otherwise identical variable in the high base-rate regime.

Tags from this library: No tags from this library for this title. Log in to add tags.

Average rating: 0.0 (0 votes)

Holdings
Item type	Home library	Collection	Call number	Status	Date due	Barcode	Item holds
Working Paper	Biblioteca Digital	Colección NBER	nber w26493 (Browse shelf(Opens below))	Not For Loan

Total holds: 0

Collection: Colección NBER Close shelf browser (Hides shelf browser)

Previous	No cover image available	No cover image available	No cover image available	No cover image available	No cover image available	No cover image available	No cover image available	Next
Previous	nber w26490 Spillover Effects of IP Protection in the Inter-war Aircraft Industry /	nber w26491 The Effects of Foreign-Born Peers in US High Schools and Middle Schools /	nber w26492 Where Have All the Children Gone? An Empirical Study of Child Abandonment and Abduction in China /	nber w26493 Estimating The Anomaly Base Rate /	nber w26494 Commonality in Credit Spread Changes: Dealer Inventory and Intermediary Distress /	nber w26495 Does Stock Market Listing Impact Investment in Japan? /	nber w26496 Inflation Dynamics: Dead, Dormant, or Determined Abroad? /	Next

November 2019.

The academic literature literally contains hundreds of variables that seem to predict the cross-section of expected returns. This so-called "anomaly zoo" has caused many to question whether researchers are using the right tests of statistical significance. But, here's the thing: even if researchers use the right tests, they will still draw the wrong conclusions from their econometric analyses if they start out with the wrong priors---i.e., if they start out with incorrect beliefs about the ex ante probability of encountering a tradable anomaly.

So, what are the right priors? What is the correct anomaly base rate?

We develop a first way to estimate the anomaly base rate by combining two key insights: 1) Empirical-Bayes methods capture the implicit process by which researchers form priors based on their past experience with other variables in the anomaly zoo. 2) Under certain conditions, there is a one-to-one mapping between these prior beliefs and the best-fit tuning parameter in a penalized regression. We study trading-strategy performance to verify our estimation results. If you trade on two variables with similar one-month-ahead return forecasts in different anomaly-base-rate regimes (low vs. high), the variable in the low base-rate regime consistently underperforms the otherwise identical variable in the high base-rate regime.