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- February 2025
- Case
Fly, Fix, Fly at True Anomaly
By: Joshua Lev Krieger, Jim Matheson, Fiona Murray and David Allen
How should companies learn from failure? Founded by four U.S. Space Force warfighters, the tough tech startup True Anomaly wanted to compete with major defense contractors to supply the U.S. Department of Defense with satellites and software that could help protect... View Details
- 2024
- Working Paper
Behavioral Attenuation
By: Thomas Graeber, Benjamin Enke, Ryan Oprea and Jeffrey Yang
We report a large-scale examination of behavioral attenuation: due to information-processing constraints, the elasticity of people’s decisions with respect to economic fundamentals is generally too small. We implement more than 30 experiments, 20 of which were... View Details
- April 2024
- Article
A Machine Learning Algorithm Predicting Risk of Dilating VUR among Infants with Hydronephrosis Using UTD Classification
By: Hsin-Hsiao Scott Wang, Michael Lingzhi Li, Dylan Cahill, John Panagides, Tanya Logvinenko, Jeanne Chow and Caleb Nelson
Backgrounds: Urinary Tract Dilation (UTD) classification has been designed to be a more objective grading system to evaluate antenatal and post-natal UTD. Due to unclear association between UTD classifications to specific anomalies such as vesico-ureteral reflux (VUR),... View Details
- 2023
- Working Paper
Complexity and Time
By: Benjamin Enke, Thomas Graeber and Ryan Oprea
We provide experimental evidence that core intertemporal choice anomalies -- including extreme short-run impatience, structural estimates of present bias, hyperbolicity and transitivity violations -- are driven by complexity rather than time or risk preferences. First,... View Details
- 2022
- Article
Nonparametric Subset Scanning for Detection of Heteroscedasticity
By: Charles R. Doss and Edward McFowland III
We propose Heteroscedastic Subset Scan (HSS), a novel method for identifying covariates that are responsible for violations of the homoscedasticity assumption in regression settings. Viewing the problem as one of anomalous pattern detection, we use subset scanning... View Details
- March–April 2022
- Article
Uncovering the Mitigating Psychological Response to Monitoring Technologies: Police Body Cameras Not Only Constrain but Also Depolarize
By: Shefali V. Patil and Ethan Bernstein
Despite organizational psychologists’ long-standing caution against monitoring (citing its reduction in employee autonomy and thus effectiveness), many organizations continue to use it, often with no detriment to performance and with strong support, not protest, from... View Details
- March 2022
- Supplement
Anomalie (C) – An Interview with Leslie Voorhees
By: Jeffrey F. Rayport and Thomas O. Jones
- January–February 2022
- Article
Operational Disruptions, Firm Risk, and Control Systems
By: William Schmidt and Ananth Raman
Operational disruptions can impact a firm's risk, which manifests in a host of operational issues, including a higher holding cost for inventory, a higher financing cost for capacity expansion, and a higher perception of the firm's risk among its supply chain partners.... View Details
- January 2021
- Case
Anodot: Autonomous Business Monitoring
By: Antonio Moreno and Danielle Golan
Autonomous business monitoring platform Anodot leveraged machine learning to provide real-time alerts regarding business anomalies. Anodot’s solution was used in various industries in order to primarily monitor business health, such as revenue and payments, product... View Details
- November–December 2020
- Article
The Risks You Can't Foresee: What to Do When There's No Playbook
By: Robert S. Kaplan, Herman B. Leonard and Anette Mikes
No matter how good their risk management systems are, companies can’t plan for everything. Some risks are outside people’s realm of experience or so remote no one could have imagined them. Some result from a perfect storm of coinciding breakdowns, and some materialize... View Details
- August 2020
- Article
Leverage and the Beta Anomaly
By: Malcolm Baker, Mathias F. Hoeyer and Jeffrey Wurgler
The well-known weak empirical relationship between beta risk and the cost of equity—the beta anomaly—generates a simple tradeoff theory: As firms lever up, the overall cost of capital falls as leverage increases equity beta, but as debt becomes riskier the marginal... View Details
- February 2020 (Revised August 2022)
- Case
Anomalie
By: Jeffrey F. Rayport and Thomas O. Jones
In early 2019, the founders of Anomalie, an online direct-to-consumer provider of bridal gowns, have just agreed to a $13.6 million Series A investment from a Silicon Valley VC. They are considering three major initiatives as they move forward. (1) To scale their very... View Details
- Article
Multivariate Unsupervised Machine Learning for Anomaly Detection in Enterprise Applications
By: Daniel Elsner, Pouya Aleatrati Khosroshahi, Alan MacCormack and Robert Lagerström
Existing application performance management (APM) solutions lack robust anomaly detection capabilities and root cause analysis techniques that do not require manual efforts and domain knowledge. In this paper, we develop a density-based unsupervised machine learning... View Details
- November 2018
- Case
Swissgrid: Enterprise Risk Management in a Digital Age
By: Robert S. Kaplan and Anette Mikes
Kurt Meyer, chief risk officer of Swissgrid, the Swiss national electricity transmission system operator, reflects on the risk management system he installed after the deregulation and liberalization of the European energy market. With 41 connections to other European... View Details
- 2018
- Working Paper
Detecting Anomalies: The Relevance and Power of Standard Asset Pricing Tests
By: Malcolm Baker, Patrick Luo and Ryan Taliaferro
The two standard approaches for identifying capital market anomalies are cross-sectional coefficient tests, in the spirit of Fama and MacBeth (1973), and time-series intercept tests, in the spirit of Jensen (1968). A new signal can pass the first test, which we label a... View Details
- Fourth Quarter 2017
- Article
Optimal Tilts: Combining Persistent Characteristic Portfolios
By: Malcolm Baker, Ryan Taliaferro and Terry Burnham
We examine the optimal weighting of four tilts in U.S. equity markets from 1968 through 2014. We define a “tilt” as a characteristic-based portfolio strategy that requires relatively low annual turnover. This is a continuum, with small size (a very persistent... View Details
- 2017
- Working Paper
Optimal Tilts: Combining Persistent Characteristic Portfolios
By: Malcolm Baker, Ryan Taliaferro and Terry Burnham
We examine the optimal weighting of four tilts in US equity markets from 1968 through 2014. We define a “tilt” as a characteristic-based portfolio strategy that requires relatively low annual turnover. This is a continuum, with small size, a very persistent... View Details
- Article
Do Strict Capital Requirements Raise the Cost of Capital? Bank Regulation, Capital Structure and the Low Risk Anomaly
By: Malcolm Baker and Jeffrey Wurgler
Traditional capital structure theory predicts that reducing banks' leverage reduces the risk and cost of equity but does not change the weighted average cost of capital, and thus the rates for borrowers. We confirm that the equity of better-capitalized banks has lower... View Details
- Article
A Case for Contextual Intelligence
By: Tarun Khanna
In this perspective, I make a case for entrepreneurs and academics alike to focus on what I have referred to elsewhere as Contextual Intelligence, the ability to understand the limits of our knowledge, and to adapt that knowledge to a context different from the one in... View Details