K B Hansen
Biographic Data
| ID | 69130 |
|---|---|
| NAME | K B Hansen |
| GIVEN NAMES | K B |
| FAMILY NAME | Hansen |
| SIGNATURE | HANSEN K B |
| AFFILIATIONS | Copenhagen Business School |
| ORCID | 0000-0002-9536-6050 |
| VERIFIED | Yes |
| TOTAL WORKS | 18 |
| TOTAL CITATIONS | 123 |
| AUTHOR COUNT | 18 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2015 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 6 |
Governing synthetic data in the financial sector
Synthetic datasets, artificially generated to mimic real-world data while maintaining anonymization, have emerged as a promising technology in the financial sector, attracting support from regulators and market participants as a solution to data privacy and scarcity challenges limiting machine learning (ML) deployment. This article argues that synthetic data's effects on financial markets depend critically on how these technologies are embedded w…
The Stack Inversion
In this article, I argue that devoting analytical attention to the natively technical concept of "the stack" can help re-sensitize studies of algorithms in Science and Technology Studies (STS) and adjacent fields to the depths of interdependence between different layers and elements of computational systems. Inspired by Bowker and Star's three-decades old methodological gestalt-switch concept of "infrastructural inversion," I propose a "stack inv…
Hybrid materialities, power, and expertise in the era of general purpose technologies
This article proposes three distinct perspectives on and approaches to the study of hybridisation across society, industries, and academia enabled by General Purpose Technologies like AI and blockchain. The term hybridisation is frequently invoked to describe and prescribe human-machine interaction and technological interoperability. Critically assessing processes of hybridisation through the perspectives of (1) materiality, (2) power and (3) exp…
Not so 'dumb money'? Constituting professionals and amateurs in the history of finance capitalism
This article examines the historically contentious relationship between the financial market and the public as discussed in academic literature, financial journalism and prescriptive how-to invest handbooks during the late 19th and early 20th centuries. Although financial markets thrive off active public participation, speculating at stock and commodity exchanges has been a sanctioned ritual reserved for a privileged minority. We argue that the f…
Stack bricolage and infrastructural impermanence in financial machine-learning modelling
Hoping that the promises of machine-learning can be realised in financial markets, investment management and trading firms increasingly employ machine-learning techniques to extract exploitable informational edge from large datasets. In addition to heavy investments in technology and the human resources capable of manipulating it, this development has led to increased use of open-source machine-learning and data-management resources. Drawing on 4…
Expectations, competencies and domain knowledge in data- and machine-driven finance
Expectations about the economy and financial markets are often cast as figments of imaginaries of the future. While the sociology of finance have predominantly dealt with expectation formation in relation to calculative devices used in practices of valuation and prediction, this paper concerns the expectations finance professionals form about their work in data- and machine-driven finance. We examine how high-skilled professionals reflexively for…
Politics of data reuse in machine learning systems
Policy discussions and corporate strategies on machine learning are increasingly championing data reuse as a key element in digital transformations. These aspirations are often coupled with a focus on responsibility, ethics and transparency, as well as emergent forms of regulation that seek to set demands for corporate conduct and the protection of civic rights. And the Protective measures include methods of traceability and assessments of 'good'…
Alternative data and sentiment analysis
Social media commentary, satellite imagery and GPS data are a part of 'alternative data', that is, data that originate outside of the standard repertoire of market data but are considered useful for predicting stock prices, detecting different risk exposures and discovering new price movement indicators. With the availability of sophisticated machine-learning analytics tools, alternative data are gaining traction within the investment management …
The market and the masses
In this essay, I examine and discuss the relationship between the market and the masses in light of recent retail-driven surges in the stock prices of firms like GameStop and AMC. Using two historical snapshots, I draw out similarities and differences between the way the collective power and rationality (or lack thereof) of the masses was portrayed in late-nineteenth and early-twentieth-century market literature and in recent debates about retail…
On some antecedents of behavioural economics
Since its inception in the late 1970s, behavioural economics has gone from being an outlier to a widely recognized yet still contested subset of the economic sciences. One of the basic arguments in behavioural economics is that a more realistic psychology ought to inform economic theories. While the history of behavioural economics is often portrayed and articulated as spanning no more than a few decades, the practice of utilizing ideas from psyc…
The absorption and multiplication of uncertainty in machine-learning-driven finance
Uncertainty about market developments and their implications characterize financial markets. Increasingly, machine learning is deployed as a tool to absorb this uncertainty and transform it into manageable risk. This article analyses machine-learning-based uncertainty absorption in financial markets by drawing on 182 interviews in the finance industry, including 45 interviews with informants who were actively applying machine-learning techniques …
Model Talk
This paper explores how calculative cultures shape perceptions of models and practices of model use in the financial industry. A calculative culture comprises a specific set of practices and norms concerning data and model use in an organizational setting. Drawing on interviews with model users (data scientists, software developers, traders, and portfolio managers) working in algorithmic securities trading, I argue that the introduction of comple…
Financial contagion
Financial contagion is often defined as the propagation of shocks among actors in markets, while excessive correlation and interconnectivity of markets, actors or investment strategies are seen as reasons for its spread. In this article, I examine uses of the concept of contagion across academic, practical and popular discourses on financial markets and speculation from the late nineteenth century through the first couple of decades of the twenti…
Imitation, Contagion, Suggestion
Terrorist attacks seem to mimic other terrorist attacks. Mass shootings appear to mimic previous mass shootings. Financial traders seem to mimic other traders. It is not a novel observation that people often imitate others. Some might even suggest that mimesis is at the core of human interaction. However, understanding such mimesis and its broader implications is no trivial task. Imitation, Contagion, Suggestion sheds important light on the ways …
Can they all be 'Shit-heads
This article seeks to explain one of the sensibilities or dispositions that novices learn in the process of becoming financiers, namely, to be a contrarian. We will review investment pitches from an American undergraduate collegiate investment fund, interviews with some members of the club, and field notes from a few of their outings, and treat instances of their contrariness as moments in their process of going from non-investors to investors, m…
The politics of algorithmic finance
This dystopic and disturbing prophecy is the company slogan of the (fictional) Geneva-based hedge fund Hoffmann Investment Technologies, as revealed in the concluding chapter of Robert Harris's 2011 sci-fi thriller The Fear Index. Briefly stated, The Fear Index tells the story of a scientist and hedge fund owner, Dr Alexander Hoffmann, whose ground-breaking invention, the 1081
Markets, bodies, and rhythms
This article explores the relationship between bodily rhythms and market rhythms in two distinctly different financial market configurations, namely the open-outcry pit (prevalent especially in the early 20th century) and present-day high-frequency trading. Drawing on Henri Lefebvre's rhythmanalysis, we show how traders seek to calibrate their bodily rhythms to those of the market. We argue that, in the case of early-20th-century open-outcry trad…
Contrarian investment philosophy in the American stock market
This paper contributes to the understanding of the role of crowds in the financial market by examining the historical origins and theoretical underpinnings of contrarian investment philosophy. Developed in non-scientific, practice-oriented ‘how to’ handbooks in 1920s and 1930s America, contrarian investment advice was aimed at so-called small investors rather than well-established market practitioners. Emerging out of late-nineteenth- and early-t…
Markets, bodies, and rhythms
This article explores the relationship between bodily rhythms and market rhythms in two distinctly different financial market configurations, namely the open-outcry pit (prevalent especially in the early 20th century) and present-day high-frequency trading. Drawing on Henri Lefebvre's rhythmanalysis, we show how traders seek to calibrate their bodily rhythms to those of the market. We argue that, in the case of early-20th-century open-outcry trad…
Model Talk
This paper explores how calculative cultures shape perceptions of models and practices of model use in the financial industry. A calculative culture comprises a specific set of practices and norms concerning data and model use in an organizational setting. Drawing on interviews with model users (data scientists, software developers, traders, and portfolio managers) working in algorithmic securities trading, I argue that the introduction of comple…
The absorption and multiplication of uncertainty in machine-learning-driven finance
Uncertainty about market developments and their implications characterize financial markets. Increasingly, machine learning is deployed as a tool to absorb this uncertainty and transform it into manageable risk. This article analyses machine-learning-based uncertainty absorption in financial markets by drawing on 182 interviews in the finance industry, including 45 interviews with informants who were actively applying machine-learning techniques …
Contrarian investment philosophy in the American stock market
This paper contributes to the understanding of the role of crowds in the financial market by examining the historical origins and theoretical underpinnings of contrarian investment philosophy. Developed in non-scientific, practice-oriented ‘how to’ handbooks in 1920s and 1930s America, contrarian investment advice was aimed at so-called small investors rather than well-established market practitioners. Emerging out of late-nineteenth- and early-t…
Alternative data and sentiment analysis
Social media commentary, satellite imagery and GPS data are a part of 'alternative data', that is, data that originate outside of the standard repertoire of market data but are considered useful for predicting stock prices, detecting different risk exposures and discovering new price movement indicators. With the availability of sophisticated machine-learning analytics tools, alternative data are gaining traction within the investment management …
Imitation, Contagion, Suggestion
Terrorist attacks seem to mimic other terrorist attacks. Mass shootings appear to mimic previous mass shootings. Financial traders seem to mimic other traders. It is not a novel observation that people often imitate others. Some might even suggest that mimesis is at the core of human interaction. However, understanding such mimesis and its broader implications is no trivial task. Imitation, Contagion, Suggestion sheds important light on the ways …
Expectations, competencies and domain knowledge in data- and machine-driven finance
Expectations about the economy and financial markets are often cast as figments of imaginaries of the future. While the sociology of finance have predominantly dealt with expectation formation in relation to calculative devices used in practices of valuation and prediction, this paper concerns the expectations finance professionals form about their work in data- and machine-driven finance. We examine how high-skilled professionals reflexively for…
Politics of data reuse in machine learning systems
Policy discussions and corporate strategies on machine learning are increasingly championing data reuse as a key element in digital transformations. These aspirations are often coupled with a focus on responsibility, ethics and transparency, as well as emergent forms of regulation that seek to set demands for corporate conduct and the protection of civic rights. And the Protective measures include methods of traceability and assessments of 'good'…
Financial contagion
Financial contagion is often defined as the propagation of shocks among actors in markets, while excessive correlation and interconnectivity of markets, actors or investment strategies are seen as reasons for its spread. In this article, I examine uses of the concept of contagion across academic, practical and popular discourses on financial markets and speculation from the late nineteenth century through the first couple of decades of the twenti…
Hybrid materialities, power, and expertise in the era of general purpose technologies
This article proposes three distinct perspectives on and approaches to the study of hybridisation across society, industries, and academia enabled by General Purpose Technologies like AI and blockchain. The term hybridisation is frequently invoked to describe and prescribe human-machine interaction and technological interoperability. Critically assessing processes of hybridisation through the perspectives of (1) materiality, (2) power and (3) exp…
Stack bricolage and infrastructural impermanence in financial machine-learning modelling
Hoping that the promises of machine-learning can be realised in financial markets, investment management and trading firms increasingly employ machine-learning techniques to extract exploitable informational edge from large datasets. In addition to heavy investments in technology and the human resources capable of manipulating it, this development has led to increased use of open-source machine-learning and data-management resources. Drawing on 4…
The market and the masses
In this essay, I examine and discuss the relationship between the market and the masses in light of recent retail-driven surges in the stock prices of firms like GameStop and AMC. Using two historical snapshots, I draw out similarities and differences between the way the collective power and rationality (or lack thereof) of the masses was portrayed in late-nineteenth and early-twentieth-century market literature and in recent debates about retail…
On some antecedents of behavioural economics
Since its inception in the late 1970s, behavioural economics has gone from being an outlier to a widely recognized yet still contested subset of the economic sciences. One of the basic arguments in behavioural economics is that a more realistic psychology ought to inform economic theories. While the history of behavioural economics is often portrayed and articulated as spanning no more than a few decades, the practice of utilizing ideas from psyc…
Can they all be 'Shit-heads
This article seeks to explain one of the sensibilities or dispositions that novices learn in the process of becoming financiers, namely, to be a contrarian. We will review investment pitches from an American undergraduate collegiate investment fund, interviews with some members of the club, and field notes from a few of their outings, and treat instances of their contrariness as moments in their process of going from non-investors to investors, m…
The Stack Inversion
In this article, I argue that devoting analytical attention to the natively technical concept of "the stack" can help re-sensitize studies of algorithms in Science and Technology Studies (STS) and adjacent fields to the depths of interdependence between different layers and elements of computational systems. Inspired by Bowker and Star's three-decades old methodological gestalt-switch concept of "infrastructural inversion," I propose a "stack inv…
The politics of algorithmic finance
This dystopic and disturbing prophecy is the company slogan of the (fictional) Geneva-based hedge fund Hoffmann Investment Technologies, as revealed in the concluding chapter of Robert Harris's 2011 sci-fi thriller The Fear Index. Briefly stated, The Fear Index tells the story of a scientist and hedge fund owner, Dr Alexander Hoffmann, whose ground-breaking invention, the 1081
Markets, bodies, and rhythms
This article explores the relationship between bodily rhythms and market rhythms in two distinctly different financial market configurations, namely the open-outcry pit (prevalent especially in the early 20th century) and present-day high-frequency trading. Drawing on Henri Lefebvre's rhythmanalysis, we show how traders seek to calibrate their bodily rhythms to those of the market. We argue that, in the case of early-20th-century open-outcry trad…
Contrarian investment philosophy in the American stock market
This paper contributes to the understanding of the role of crowds in the financial market by examining the historical origins and theoretical underpinnings of contrarian investment philosophy. Developed in non-scientific, practice-oriented ‘how to’ handbooks in 1920s and 1930s America, contrarian investment advice was aimed at so-called small investors rather than well-established market practitioners. Emerging out of late-nineteenth- and early-t…
Imitation, Contagion, Suggestion
Terrorist attacks seem to mimic other terrorist attacks. Mass shootings appear to mimic previous mass shootings. Financial traders seem to mimic other traders. It is not a novel observation that people often imitate others. Some might even suggest that mimesis is at the core of human interaction. However, understanding such mimesis and its broader implications is no trivial task. Imitation, Contagion, Suggestion sheds important light on the ways …
Can they all be 'Shit-heads
This article seeks to explain one of the sensibilities or dispositions that novices learn in the process of becoming financiers, namely, to be a contrarian. We will review investment pitches from an American undergraduate collegiate investment fund, interviews with some members of the club, and field notes from a few of their outings, and treat instances of their contrariness as moments in their process of going from non-investors to investors, m…
On some antecedents of behavioural economics
Since its inception in the late 1970s, behavioural economics has gone from being an outlier to a widely recognized yet still contested subset of the economic sciences. One of the basic arguments in behavioural economics is that a more realistic psychology ought to inform economic theories. While the history of behavioural economics is often portrayed and articulated as spanning no more than a few decades, the practice of utilizing ideas from psyc…
The absorption and multiplication of uncertainty in machine-learning-driven finance
Uncertainty about market developments and their implications characterize financial markets. Increasingly, machine learning is deployed as a tool to absorb this uncertainty and transform it into manageable risk. This article analyses machine-learning-based uncertainty absorption in financial markets by drawing on 182 interviews in the finance industry, including 45 interviews with informants who were actively applying machine-learning techniques …
Model Talk
This paper explores how calculative cultures shape perceptions of models and practices of model use in the financial industry. A calculative culture comprises a specific set of practices and norms concerning data and model use in an organizational setting. Drawing on interviews with model users (data scientists, software developers, traders, and portfolio managers) working in algorithmic securities trading, I argue that the introduction of comple…
Financial contagion
Financial contagion is often defined as the propagation of shocks among actors in markets, while excessive correlation and interconnectivity of markets, actors or investment strategies are seen as reasons for its spread. In this article, I examine uses of the concept of contagion across academic, practical and popular discourses on financial markets and speculation from the late nineteenth century through the first couple of decades of the twenti…
Politics of data reuse in machine learning systems
Policy discussions and corporate strategies on machine learning are increasingly championing data reuse as a key element in digital transformations. These aspirations are often coupled with a focus on responsibility, ethics and transparency, as well as emergent forms of regulation that seek to set demands for corporate conduct and the protection of civic rights. And the Protective measures include methods of traceability and assessments of 'good'…
Alternative data and sentiment analysis
Social media commentary, satellite imagery and GPS data are a part of 'alternative data', that is, data that originate outside of the standard repertoire of market data but are considered useful for predicting stock prices, detecting different risk exposures and discovering new price movement indicators. With the availability of sophisticated machine-learning analytics tools, alternative data are gaining traction within the investment management …
The market and the masses
In this essay, I examine and discuss the relationship between the market and the masses in light of recent retail-driven surges in the stock prices of firms like GameStop and AMC. Using two historical snapshots, I draw out similarities and differences between the way the collective power and rationality (or lack thereof) of the masses was portrayed in late-nineteenth and early-twentieth-century market literature and in recent debates about retail…
Expectations, competencies and domain knowledge in data- and machine-driven finance
Expectations about the economy and financial markets are often cast as figments of imaginaries of the future. While the sociology of finance have predominantly dealt with expectation formation in relation to calculative devices used in practices of valuation and prediction, this paper concerns the expectations finance professionals form about their work in data- and machine-driven finance. We examine how high-skilled professionals reflexively for…
Hybrid materialities, power, and expertise in the era of general purpose technologies
This article proposes three distinct perspectives on and approaches to the study of hybridisation across society, industries, and academia enabled by General Purpose Technologies like AI and blockchain. The term hybridisation is frequently invoked to describe and prescribe human-machine interaction and technological interoperability. Critically assessing processes of hybridisation through the perspectives of (1) materiality, (2) power and (3) exp…
Not so 'dumb money'? Constituting professionals and amateurs in the history of finance capitalism
This article examines the historically contentious relationship between the financial market and the public as discussed in academic literature, financial journalism and prescriptive how-to invest handbooks during the late 19th and early 20th centuries. Although financial markets thrive off active public participation, speculating at stock and commodity exchanges has been a sanctioned ritual reserved for a privileged minority. We argue that the f…
Stack bricolage and infrastructural impermanence in financial machine-learning modelling
Hoping that the promises of machine-learning can be realised in financial markets, investment management and trading firms increasingly employ machine-learning techniques to extract exploitable informational edge from large datasets. In addition to heavy investments in technology and the human resources capable of manipulating it, this development has led to increased use of open-source machine-learning and data-management resources. Drawing on 4…
Governing synthetic data in the financial sector
Synthetic datasets, artificially generated to mimic real-world data while maintaining anonymization, have emerged as a promising technology in the financial sector, attracting support from regulators and market participants as a solution to data privacy and scarcity challenges limiting machine learning (ML) deployment. This article argues that synthetic data's effects on financial markets depend critically on how these technologies are embedded w…
The Stack Inversion
In this article, I argue that devoting analytical attention to the natively technical concept of "the stack" can help re-sensitize studies of algorithms in Science and Technology Studies (STS) and adjacent fields to the depths of interdependence between different layers and elements of computational systems. Inspired by Bowker and Star's three-decades old methodological gestalt-switch concept of "infrastructural inversion," I propose a "stack inv…
Economics (13 works) · Finance (12 works) · Computer Science (8 works) · FinTech, Crowdfunding, Digital Finance (7 works) · Sociology (7 works) · Business (6 works) · Political science (6 works) · Blockchain Technology Applications and Security (5 works) · Complex Systems and Time Series Analysis (5 works) · Epistemology (5 works)