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dc.date.accessioned2021-09-24T14:47:43Z
dc.date.available2021-09-24T14:47:43Z
dc.identifier.urihttps://fif.hebis.de/xmlui/handle/123456789/2082
dc.description.abstractWe use proprietary investor transaction-level data from two large German retail banks. For a large random sample of clients at the banks, we observe all their trades, including information on the securities traded, the type of trade (buy or sell), day and time of the trade execution, price and units of each transaction, and, importantly for our analysis, the platform used for each trade. This data covers about sixty-five million transactions during the years from 1999 to 2017 by more than two hundred and twenty-five thousand investors. At the investor level, we observe monthly snapshots of portfolio holdings and demographic characteristics such as gender, age, wealth, and income.
dc.rightsAttribution-ShareAlike 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by-sa/4.0/
dc.subjectHousehold Finance
dc.titleWP303_tradingdata
dc.typeResearch Data
dcterms.isReferencedByhttps://fif.hebis.de/xmlui/handle/123456789/2409?Smart (Phone) Investing? A Within Investor-Time Analysis of New Technologies and Trading Behavior
dc.subject.keywordsfintech
dc.subject.keywordsinvestor behavior
dc.subject.keywordsfinancial risk-taking
dc.subject.keywordslottery-type assets
dc.subject.keywordsinvestment biases
dc.subject.keywordstrend chasing
dc.subject.keywordsspillover effects
dc.subject.jelG11
dc.subject.jelG40
dc.subject.jelG50
dc.subject.jelH31
dc.subject.topic1loser
dc.subject.topic1smartphone
dc.subject.topic1exception
dc.subject.topic2risk
dc.subject.topic2framework
dc.subject.topic2associate
dc.subject.topic3loo
dc.subject.topic3expect
dc.subject.topic3execution
dc.subject.topic1nameFiscal Stability
dc.subject.topic2nameInvestor Behaviour
dc.subject.topic3nameSaving and Borrowing
dc.identifier.urlhttp://dx.doi.org/10.2139/ssrn.3765652


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