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Using Daily Stock Returns: The Case of Event Studies
 Journal of Financial Economics
, 1985
"... This paper examines properties of daily stock returns and how the particular characteristics of these data affect event study methodologies. Daily data generally present few difficulties for event studies. Standard procedures are typically wellspecified even when special daily data characteristics ..."
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Cited by 763 (2 self)
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This paper examines properties of daily stock returns and how the particular characteristics of these data affect event study methodologies. Daily data generally present few difficulties for event studies. Standard procedures are typically wellspecified even when special daily data characteris
Unrealistic optimism about future life events
 Journal of Personality and Social Psychology
, 1980
"... Two studies investigated the tendency of people to be unrealistically optimistic about future life events. In Study 1, 258 college students estimated how much their own chances of experiencing 42 events differed from the chances of their classmates. Overall, they rated their own chances to be above ..."
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Cited by 493 (0 self)
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average for positive events and below average for negative events, ps<.001. Cognitive and motivational considerations led to predictions that degree of desirability, perceived probability, personal experience, perceived controllability, and stereotype salience would influence the amount of optimistic
Earthquake Shakes Twitter Users: Realtime Event Detection by Social Sensors
 In Proceedings of the Nineteenth International WWW Conference (WWW2010). ACM
, 2010
"... Twitter, a popular microblogging service, has received much attention recently. An important characteristic of Twitter is its realtime nature. For example, when an earthquake occurs, people make many Twitter posts (tweets) related to the earthquake, which enables detection of earthquake occurrence ..."
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Cited by 484 (3 self)
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promptly, simply by observing the tweets. As described in this paper, we investigate the realtime interaction of events such as earthquakes, in Twitter, and propose an algorithm to monitor tweets and to detect a target event. To detect a target event, we devise a classifier of tweets based on features
A comparison of event models for Naive Bayes text classification
, 1998
"... Recent work in text classification has used two different firstorder probabilistic models for classification, both of which make the naive Bayes assumption. Some use a multivariate Bernoulli model, that is, a Bayesian Network with no dependencies between words and binary word features (e.g. Larkey ..."
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Cited by 1002 (27 self)
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Recent work in text classification has used two different firstorder probabilistic models for classification, both of which make the naive Bayes assumption. Some use a multivariate Bernoulli model, that is, a Bayesian Network with no dependencies between words and binary word features (e.g. Larkey and Croft 1996; Koller and Sahami 1997). Others use a multinomial model, that is, a unigram language model with integer word counts (e.g. Lewis and Gale 1994; Mitchell 1997). This paper aims to clarify the confusion by describing the differences and details of these two models, and by empirically comparing their classification performance on five text corpora. We find that the multivariate Bernoulli performs well with small vocabulary sizes, but that the multinomial performs usually performs even better at larger vocabulary sizesproviding on average a 27% reduction in error over the multivariate Bernoulli model at any vocabulary size.
The omnet++ discrete event simulation system
 In ESM’01
, 2001
"... performance analysis, computer systems, telecommunications, hierarchical The paper introduces OMNeT++, a C++based discrete event simulation package primarily targeted at simulating computer networks and other distributed systems. OMNeT++ is fully programmable and modular, and it was designed from t ..."
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Cited by 405 (1 self)
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performance analysis, computer systems, telecommunications, hierarchical The paper introduces OMNeT++, a C++based discrete event simulation package primarily targeted at simulating computer networks and other distributed systems. OMNeT++ is fully programmable and modular, and it was designed from
Market Efficiency, LongTerm Returns, and Behavioral Finance
, 1998
"... Market efficiency survives the challenge from the literature on longterm return anomalies. Consistent with the market efficiency hypothesis that the anomalies are chance results, apparent overreaction to information is about as common as underreaction, and postevent continuation of preevent abnor ..."
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Cited by 749 (4 self)
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Market efficiency survives the challenge from the literature on longterm return anomalies. Consistent with the market efficiency hypothesis that the anomalies are chance results, apparent overreaction to information is about as common as underreaction, and postevent continuation of preevent
Studies of transformation of Escherichia coli with plasmids
 J. Mol. Biol
, 1983
"... Factors that affect he probability of genetic transformation f Escherichia coli by plasmids have been evaluated. A set of conditions is described under which about one in every 400 plasmid molecules produces a transformed cell. These conditions include cell growth in medium containing elevated level ..."
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Cited by 1609 (1 self)
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Factors that affect he probability of genetic transformation f Escherichia coli by plasmids have been evaluated. A set of conditions is described under which about one in every 400 plasmid molecules produces a transformed cell. These conditions include cell growth in medium containing elevated
Extensional versus intuitive reasoning: The conjunction fallacy in probability judgment
 Psychological Review
, 1983
"... Perhaps the simplest and the most basic qualitative law of probability is the conjunction rule: The probability of a conjunction, P(A&B), cannot exceed the probabilities of its constituents, P(A) and.P(B), because the extension (or the possibility set) of the conjunction is included in the exten ..."
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Cited by 427 (4 self)
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Perhaps the simplest and the most basic qualitative law of probability is the conjunction rule: The probability of a conjunction, P(A&B), cannot exceed the probabilities of its constituents, P(A) and.P(B), because the extension (or the possibility set) of the conjunction is included
Bayes Factors
, 1995
"... In a 1935 paper, and in his book Theory of Probability, Jeffreys developed a methodology for quantifying the evidence in favor of a scientific theory. The centerpiece was a number, now called the Bayes factor, which is the posterior odds of the null hypothesis when the prior probability on the null ..."
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Cited by 1766 (74 self)
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In a 1935 paper, and in his book Theory of Probability, Jeffreys developed a methodology for quantifying the evidence in favor of a scientific theory. The centerpiece was a number, now called the Bayes factor, which is the posterior odds of the null hypothesis when the prior probability on the null
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