Research


May 7, 2024

We formulate quantum computing solutions to a large class of dynamic nonlinear asset pricing models using algorithms, in theory exponentially more efficient than classical ones, which leverage the quantum properties of superposition and entanglement. The equilibrium asset pricing solution is a quantum state. We introduce quantum decision-theoretic foundations of ambiguity and model/parameter uncertainty to deal with model selection.

Eric Ghysels

March 16, 2022

Although artificial intelligence (AI) has become a crucial component of digital transformation efforts tied to organizational strategy, many firms struggle to articulate the strategic value of emerging AI systems. In this article we argue that the power of AI as a strategic resource lies in its self-learning capabilities. Such learning capabilities are only realized in partnership with humans through mutual learning. By building on a learning-centered framework, we elaborate on how AI can contribute to organizational learning to create a competitive advantage. We formulate the concept of artificial capital and the ways artificial and human capital can together drive routinization and strategic learning processes that connect internal and external environments of the organization. Finally, we use this conception to formulate practical recommendations for managing and developing AI to meet strategic business goals.

Mohammad Hossein JarrahiChelsea Donahue

September 15, 2021

In the wake of the pandemic, global supply chain challenges have driven massive product shortages and rising prices on goods, from cars and building supplies to electronics, medicine and more. As the Delta variant causes COVID-19 surges across the United States, and the global response continues to be slow and uneven, hear from two of our leading experts on global supply chains.

April 1, 2021

Recent advancements are making artificial intelligence (AI) ripe to disrupt all facets of our world, forcing us to reimagine how we live and work. Within the business sector, AI has long been hyped by developers, but has been slow to integrate into practice. Now, corporate executives are honing in on the strategic value of AI and, as technology and applications have matured, investing in its development and implementation.

Mohammad Hossein Jarrahi

March 22, 2021

A term originated in meteorology, nowcasting pertains to the prediction of the present and very near future. Nowcasting applications in economics and finance are intrinsically a mixed frequency data problem as the object of interest is a low-frequency data series (e.g., quarterly), whereas the information is real-time high frequency (e.g., daily, weekly, or monthly).

Eric Ghysels

December 14, 2020

The tremendous growth in cryptocurrency trading has included frequent pump-and-dump (P&D) schemes, a form of price manipulation that is currently unregulated in this market. New research reveals that cryptocurrency P&Ds lead to price and volume inflations that last mere minutes, creating volatility that only benefits traders who have advance notice of the scheme.

Donghwa Shin

December 10, 2020

The cryptocurrency industry has evolved significantly over the last five years. It is no longer purely speculative; use cases that add real value are emerging, and with them, significant institutional interest. Rethinc. Fintech Labs Faculty Director and Professor of Finance Eric Ghysels recently sat down with Zoe Cruz, former co-president of Morgan Stanley, to discuss the impact of adding cryptocurrencies to a traditional portfolio.

Donghwa ShinEric Ghysels

November 7, 2020

The financial industry has eagerly adopted machine learning algorithms to improve on traditional predictive models. In this paper we caution against blindly applying such techniques. We compare forecasting ability of machine learning methods in evaluating future payoffs on synthetic variance swaps. Standard machine learning methods tend to identify contracts which are illiquid, and hard to trade.

Eric Ghysels

October 16, 2020

The importance of asymmetries in prediction problems arising in economics has been recognized for a long time. In this paper, we focus on binary choice problems in a data-rich environment with general loss functions.

Eric Ghysels

October 7, 2020

The list of stores that have closed or gone bankrupt in 2020 reads like a “who’s who” of venerable retail giants. Although retailing has been experiencing tectonic shifts for several years, the COVID-19 pandemic has accelerated both challenges and opportunities. In this Kenan Insight, we explore four major trends in retail, with a particular focus on food retailing.

September 24, 2020

With global investment in AI systems expected to double over the next four years, effectively integrating these algorithmic systems in organizations will require a change in how enterprises think about their technology. If a company uses AI technology as a particular point solution, it will gain experience and skills in the field of AI, but miss an opportunity to capitalize on the benefits of a partnership between employees and the intelligent agent. A shift in perspective is needed for organizations to treat AI as an employee with the ability to learn and grow within the company. Interacting as a member of the team, AI’s function is not to eliminate jobs, but to enrich the role of employees as it becomes a part of the culture and fabric of a company.

Mohammad Hossein Jarrahi

September 10, 2020

A received wisdom is that automated decision-making serves as an anti-bias intervention. The conceit is that removing humans from the decision-making process will also eliminate human bias. The paradox, however, is that in some instances, automated decision-making has served to replicate and amplify bias. With a case study of the algorithmic capture of hiring as heuristic device, this Article provides a taxonomy of problematic features associated with algorithmic decision-making as anti-bias intervention and argues that those features are at odds with the fundamental principle of equal opportunity in employment.

May 28, 2020

Traditional contact tracing, where workers query patients about their interactions to see who else might have been infected — and perhaps to find out where they got the infection — is being widely used. But for the first time, many public health authorities are considering, or have implemented, smart phone apps to partially automate and scale contact tracing.

Eric Ghysels

May 22, 2020

Apple and Google, whose operating systems power the vast majority of smart phones, have unlocked software protocols to allow their phones — if owners have installed the right apps — to monitor when someone who is infected or possibly infected has contact with someone else. But digital contact tracing also raises difficult ethical, legal and technical questions.

February 3, 2020

Digital technologies are changing the nature of teamwork in ways that have important implications for leadership. Though conceptually rich and multi-disciplinary, much of the burgeoning work on technology has not been fully integrated into the leadership literature.

August 15, 2019

This article lays out a research agenda in the sociology of work for a type of data and organizational intermediary: work platforms. As an example, we employ a case study of the adoption of Automated Hiring Platforms (AHPs) in which we distinguish between promises and existing practices.

July 9, 2019

Recent work technology advancements such as productivity monitoring platforms and wearable technology have given rise to new organizational behavior regarding the management of employees and also prompt new legal questions regarding the protection of workers’ privacy rights. In this Essay, I argue that the proliferation of productivity monitoring applications and wearable technologies will lead to new legal controversies for employment and labor law.

July 6, 2019

Artificial intelligence, or AI, enhancements are increasingly shaping our daily lives. Financial decision-making is no exception to this. We introduce the notion of AI Alter Egos, which are shadow robo-investors, and use a unique data set covering brokerage accounts for a large cross-section of investors over a sample from January 2003 to March 2012, which includes the 2008 financial crisis, to assess the benefits of robo-investing.

Eric Ghysels

May 8, 2019

This study examines the performance consequences of web personalization (WP), a type of personalization in which web content is personalized and recommendations are offered based on customer preferences.

May 1, 2019

Certification by online analysts and early investors can generate excitement among potential token investors, leading to successful initial coin offerings (ICOs). We test the general notion of "wisdom of crowds" using novel data on nearly 3,400 ICOs, including sequential investor subscriptions during token sales. We find that favorable analyst opinions on the underlying projects are associated with aggressive initial token subscriptions, fundraising success, and exchange listing. Analyst ratings also predict long-run token performance. Our results hold during the ICO market's boom-and-bust cycle. Overall, our results suggest analysts' intermediary role in ICOs, a type of direct placement in the FinTech era.

Donghwa Shin

March 14, 2019

We examine trends in the use of predictive analytics for a sample of more than 25,000 manufacturing plants using proprietary data from the US Census.

Mark Lang

October 23, 2018

Pump-and-dump schemes (P&Ds) are pervasive in the cryptocurrency market. We find that P&Ds lead to short-term bubbles featuring dramatic increases in prices, volume, and volatility. Prices peak within minutes and quick reversals follow. The evidence we document, including price run-ups before P&Ds start, implies significant wealth transfers between insiders and outsiders. Bittrex, a cryptocurrency exchange, banned P&Ds on November 24, 2017. Using a difference-in-differences approach, we provide causal evidence that P&Ds are detrimental to the liquidity and price of cryptocurrencies. We discuss potential mechanisms why outsiders are willing to participate and describe how our findings shed light on manipulation theories.

Donghwa Shin

October 1, 2018

This paper examines price discovery and liquidity provision in the secondary market for bitcoin — an asset that has no observable fundamentals and is associated with a high level of speculative trading.

Eric Ghysels

September 27, 2018

Electricity end-users have been increasingly generating their own electricity via rooftop solar panels. Our paper studies the implications of such “distributed renewable energy” for utility profits and social welfare under net metering that has sparked heated debates in practice. The common belief is that such type of generation significantly decreases utility profits because (i) distributed generation reduces utility’s market size, and (ii) under net metering, utilities must buy back the excess generation of their customers at a rate typically larger than their procurement cost.

September 19, 2018

Widespread adoption of electronic medical record (EMR) systems is increasing. EMR implementation can be costly and typically requires workflow redesign. To our knowledge, no studies to date have examined the impact of EMR implementation using advanced cost accounting methods or the impact of its implementation on orthopaedic surgeons in an outpatient setting. Time-driven activity-based costing (TD-ABC) was used to evaluate the effect of EMR implementation in an outpatient adult reconstruction clinic.

September 18, 2018

We argue that behavioral strategy can learn a great deal from the Theory of Computational Complexity and Artificial Intelligence. Also, a concept of “organizational intractability” may be useful in determining what analytical decision technologies are actually intractable in real organizations with constraints on time and managerial attention.

August 15, 2018

We show that blockchain can be more effective than pricing strategy in eliminating the post-purchase regret and improving social welfare.

August 1, 2018

While previous research has investigated various drivers of electronic word of mouth (eWOM), the firm's offline competitive environment has not been considered. The authors explore this new horizon and examine the different effects of firms’ geographic concentration, or agglomeration, on the volume of eWOM received. They distinguish three types of agglomeration—density agglomeration (number of firms in the industry in an area), product agglomeration (overlap in product types offered by the firms in the area), and temporal agglomeration (overlap in moment of consumption).

June 27, 2018

We study how the government of a developing country optimizes its local content requirement (LCR) policy to maximize social welfare in a setting where foreign original equipment manufacturers (OEMs) produce and sell multicomponent products in the developing country. The foreign OEMs’ local sourcing of components is more costly than global sourcing because of technology gaps between local and global suppliers.

June 1, 2018

We use the GARCH-MIDAS model to extract the long- and short-term volatility components of cryptocurrencies. As potential drivers of Bitcoin volatility, we consider measures of volatility and risk in the US stock market as well as a measure of global economic activity. We find that S&P 500 realized volatility has a negative and highly significant effect on long-term Bitcoin volatility. The finding is atypical for volatility co-movements across financial markets.

Eric Ghysels

April 26, 2018

We use the GARCH-MIDAS model to extract the long- and short-term volatility components of cryptocurrencies. As potential drivers of Bitcoin volatility, we consider measures of volatility and risk in the US stock market as well as a measure of global economic activity. We find that S&P 500 realized volatility has a negative and highly significant effect on long-term Bitcoin volatility. The finding is atypical for volatility co-movements across financial markets. Moreover, we find that the S&P 500 volatility risk premium has a significantly positive effect on long-term Bitcoin volatility. Finally, we find a strong positive association between the Baltic dry index and long-term Bitcoin volatility. This result shows that Bitcoin volatility is closely linked to global economic activity. Overall, our findings can be used to construct improved forecasts of long-term Bitcoin volatility.

Eric Ghysels

July 17, 2017

It is generally accepted that operating with a combined (i.e., pooled) queue rather than separate (i.e., dedicated) queues is beneficial mainly because pooling queues reduces long-run average throughput time. In fact, this is a well-established result in the literature, e.g., when servers and jobs are identical. We consider an observable multi-server queueing system which can be operated with either dedicated queues or a pooled one.

July 1, 2017

Firms are increasingly offering engagement initiatives to facilitate firm–customer interactions or interactions among customers, with the primary goal of fostering emotional and psychological bonds between customers and the firm. Unlike traditional marketing interventions, which are designed to prompt sales, assessing returns on engagement initiatives (RoEI) is more complex because sales are not the primary goal and, often, direct sales are not associated with such initiatives.

March 16, 2017

Markets today are flooded with an increasing number of products and brands, making it difficult for companies to track how their products compete in the market. In this article, the authors describe how they used clickstream data to visualize competition in product categories containing more than 1,000 products.

January 1, 2017

With the explosion of Internet users, growing from 360 million (5.9 % of the world’s population) in 2000 to 3.4 billion (46.4 %) in 2016, the digital space is reshaping how organizations go global with their brands. Any chapter written about digital branding strategies runs the risk of obsolescence before it hits the printer. Specific digital platforms and tools for global brand building change rapidly over time.

June 1, 2015

Much of the recent empirical IO research has been conducted in the context of relatively mature, stable (often consumer packaged goods) markets. In these markets, consumer preferences and competitive interaction are often characterized by relatively stable patterns over time.

June 1, 2014

Existing models of industry evolution describe a smooth pattern over time in which initial growth in the number of firms is followed by a sharp decrease due to a shakeout and an eventual stabilization as the industry reaches maturity.

January 1, 2005

Multinational companies increasingly rely upon the work of virtual teams to manage their global intellectual assets and encourage innovation. Spanning functional, geographical and corporate boundaries, virtual team members work together on various projects but are based in different locations nationwide or worldwide. Virtual teams allow companies to leverage their global expertise, take the pulse of diverse markets, promote broader participation in key strategic decision making, increase job flexibility, lower travel costs and pool the knowledge of experts.