scholarly journals Estimating a Structural Model of Herd Behavior in Financial Markets

2014 ◽  
Vol 104 (1) ◽  
pp. 224-251 ◽  
Author(s):  
Marco Cipriani ◽  
Antonio Guarino
Keyword(s):  
Financial Markets ◽  
Structural Model ◽  
Expected Value ◽  
Herd Behavior ◽  
Transaction Data ◽  
Financial Transaction ◽  
Information Event ◽  
Event Uncertainty ◽  
Using Data

We develop a new methodology to estimate herd behavior in financial markets. We build a model of informational herding that can be estimated with financial transaction data. In the model, rational herding arises because of information-event uncertainty. We estimate the model using data on a NYSE stock (Ashland Inc.) during 1995. Herding occurs often and is particularly pervasive on some days. On average, the proportion of herd buyers is 2 percent; that of herd sellers is 4 percent. Herding also causes important informational inefficiencies in the market, amounting, on average, to 4 percent of the asset's expected value. (JEL C58, D82, D83, G12, G14)

scholarly journals Estimating a Structural Model of Herd Behavior in Financial Markets

2010 ◽  
Vol 10 (288) ◽  
pp. 1 ◽  
Author(s):  
Antonio Guarino ◽  
Marco Cipriani ◽  
◽  
Keyword(s):  
Financial Markets ◽  
Structural Model ◽  
Herd Behavior

Thirty years of herd behavior in financial markets: A bibliometric analysis

2022 ◽  
Vol 59 ◽  
pp. 101506
Author(s):  
Enkhbayar Choijil ◽  
Christian Espinosa Méndez ◽  
Wing-Keung Wong ◽  
João Paulo Vieito ◽  
Munkh-Ulzii Batmunkh
Keyword(s):  
Financial Markets ◽  
Bibliometric Analysis ◽  
Herd Behavior

Household Financial Transaction Data

2021 ◽  
Author(s):  
Scott Baker ◽  
Lorenz Kueng
Keyword(s):  
Transaction Data ◽  
Financial Transaction

Projection Bias in Catalog Orders

2007 ◽  
Vol 97 (4) ◽  
pp. 1217-1249 ◽  
Author(s):  
Michael Conlin ◽  
Ted O'Donoghue ◽  
Timothy J Vogelsang
Keyword(s):  
Field Data ◽  
Structural Model ◽  
Cold Weather ◽  
Change Over Time ◽  
Laboratory Evidence ◽  
Return Probability ◽  
Projection Bias ◽  
Using Data ◽  
Over Time

Evidence suggests that people understand qualitatively how tastes change over time, but underestimate the magnitudes. This evidence is limited, however, to laboratory evidence or surveys of reported happiness. We test for such projection bias in field data. Using data on catalog orders of cold-weather items, we find evidence of projection bias over the weather—specifically, people's decisions are overinfluenced by the current weather. Our estimates suggest that if the order-date temperature declines by 30°F, the return probability increases by 3.95 percent. We also estimate a structural model to measure the magnitude of the bias. (JEL D12, L81)

scholarly journals ANALISIS POLA PENJUALAN DENGAN MENGGUNAKAN ALGORITMA APRIORI PADA KOPERASI KARYAWAN YAYASAN ANAKKU

2019 ◽  
Vol 2 (1) ◽  
pp. 31-36
Author(s):  
Arfianto Darmawan ◽  
Titin Kristiana
Keyword(s):  
Data Mining ◽  
Strong Association ◽  
Apriori Algorithm ◽  
Business Unit ◽  
Savings And Loans ◽  
Transaction Data ◽  
Existing Problems ◽  
A Value ◽  
Transaction Database ◽  
Using Data

The Anakku Foundation Cooperative is a multi-business cooperative consisting of shop businesses, savings and loans, and student shuttle services. Every sale of stuff services will be inputted data directly to each business unit. The Anakku Foundation Cooperative still has problems, including store transactions that cannot yet answer what items are often sold, when stock items are still difficult to determine the items that are still available or almost running out. Data mining techniques have been mostly used to overcome existing problems, one of which is the application of the Apriori algorithm to obtain information about the associations between products from a transaction database. Transaction data on school equipment sales at Cooperative Employees of Anakku Foundation can be reprocessed using Data mining applications so as to produce strong association rules between itemset sales of school supplies so that they can provide recommendations for item alignment and simplify the arrangement or strong item placement related to interdependence. The results are found that the highest value of support and confidence is if buying MUSLIM L1.5P1, so it would buy AL-IZHAR II LOGO with a value of 14.5% support and 79.5% confidence

Using social distancing technology in hotels: a social exchange perspective

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Cristian Morosan ◽  
Agnes DeFranco
Keyword(s):  
Social Exchange ◽  
Health Risks ◽  
Social Exchange Theory ◽  
Structural Model ◽  
Content Type ◽  
Privacy Concerns ◽  
Social Distancing ◽  
Using Data ◽  
Social Rewards

Purpose As social distancing procedures can be facilitated by various hotel technologies, the purpose of this paper is to investigate the extent to which consumers develop perceptions of value regarding the use of certain hotel technologies for social distancing in hotels. Design/methodology/approach Drawing from the social exchange theory, this study conceptualized the benefits of using technologies for social distancing, health risks, social rewards and privacy concerns as antecedents of value of using technologies for social distancing in hotels. The structural model was validated by using data from more than 1,000 nationwide US consumers. Findings Benefits and consumers’ privacy concerns of using technologies for social distancing in hotels were the strongest predictors of value. Social rewards also had a significant but relatively lower effect on value. Health risks was found to have no influence on value. Originality/value The study is the first to examine the role of technologies in mitigating the effects of coronavirus. Thus, it extends the information technology and hospitality literature by examining the role of these technologies in safeguarding individual and public health.

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