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Empirical tests of the Gradual Learning Algorithm
 LINGUISTIC INQUIRY 32.45–86
, 2001
"... The Gradual Learning Algorithm (Boersma 1997) is a constraint ranking algorithm for learning Optimalitytheoretic grammars. The purpose of this article is to assess the capabilities of the Gradual Learning Algorithm, particularly in comparison with the Constraint Demotion algorithm of Tesar and Smol ..."
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Cited by 383 (37 self)
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The Gradual Learning Algorithm (Boersma 1997) is a constraint ranking algorithm for learning Optimalitytheoretic grammars. The purpose of this article is to assess the capabilities of the Gradual Learning Algorithm, particularly in comparison with the Constraint Demotion algorithm of Tesar and Smolensky (1993, 1996, 1998, 2000), which initiated the learnability research program for Optimality Theory. We argue that the Gradual Learning Algorithm has a number of special advantages: it can learn free variation, deal effectively with noisy learning data, and account for gradient wellformedness judgments. The case studies we examine involve Ilokano reduplication and metathesis, Finnish genitive plurals, and the distribution of English light and dark /l/.
Universals in the content and structure of values: theoretical advances and empirical tests in 20 countries
 ADVANCES IN EXPERIMENTAL SOCIAL PSYCHOLOGY
, 1992
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Implied Volatility Functions: Empirical Tests
, 1995
"... Black and Scholes (1973) implied volatilities tend to be systematically related to the option's exercise price and time to expiration. Derman and Kani (1994), Dupire (1994), and Rubinstein (1994) attribute this behavior to the fact that the Black/Scholes constant volatility assumption is violat ..."
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Cited by 303 (4 self)
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Black and Scholes (1973) implied volatilities tend to be systematically related to the option's exercise price and time to expiration. Derman and Kani (1994), Dupire (1994), and Rubinstein (1994) attribute this behavior to the fact that the Black/Scholes constant volatility assumption is violated in practice. These authors hypothesize that the volatility of the underlying asset's return is a deterministic function of the asset price and time. Since the volatility function in their model has an arbitrary specification, the deterministic volatility (DV) option valuation model has the potential of fitting the observed crosssection of option prices exactly. Using a sample of S&P 500 index options during the period June 1988 and December 1993, we attempt to evaluate the economic significance of the implied volatility function by examining the predictive and hedging performance of the DV option valuation model. Discussion draft: September 8, 1995 ____________________________________________...
The capital asset pricing model: Some empirical tests
, 1972
"... Considerable attention has recently been given to general equilibrium models of the pricing of capital assets. Of these, perhaps the best known is the meanvariance formulation originally ..."
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Cited by 354 (3 self)
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Considerable attention has recently been given to general equilibrium models of the pricing of capital assets. Of these, perhaps the best known is the meanvariance formulation originally
Efficient intrahousehold allocation: a general characterization and empirical tests,
 Econometrica
, 1998
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Empirical Tests
"... This appendix contains the formal details of definitions, postulates, and theorems along with proof traces. Key Functions α̃(l,x,y, t) intrinsic appeal of producer x’s offering in category l to audience member y at time t. α(l,x,y, t) actual appeal to audience member y of producer x’s offering in ca ..."
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of the unaugmented argument.) This logic is designed for testing the validity of inferences from arguments that build on ruleswithexceptions. The logic uses a quantifier, denoted by N, that parallels the standard universal quantifier of firstorder logic (∀). It tells what is normally the case. Because more
An Empirical Test
, 2016
"... an improve conflict manesearchers have also wited interest in management al context (see Adler and yet the existing literature research is not as rich in ent as in other fields ..."
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an improve conflict manesearchers have also wited interest in management al context (see Adler and yet the existing literature research is not as rich in ent as in other fields
EMPIRICAL TESTS
"... Black and Scholes (1973) implied volatilities tend to be systematically related to the option’s exercise price and time to expiration. Derman and Kani (1994), Dupire (1994), and Rubinstein (1994) attribute this behavior to the fact that the Black/Scholes constant volatility assumption is violated in ..."
Abstract
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Black and Scholes (1973) implied volatilities tend to be systematically related to the option’s exercise price and time to expiration. Derman and Kani (1994), Dupire (1994), and Rubinstein (1994) attribute this behavior to the fact that the Black/Scholes constant volatility assumption is violated in practice. These authors hypothesize that the volatility of the underlying asset’s return is a deterministic function of the asset price and time. Since the volatility function in their model has an arbitrary specification, the deterministic volatility (DV) option valuation model has the potential of fitting the observed crosssection of option prices exactly. Using a sample of S&P 500 index options during the period June 1988 and December 1993, we attempt to evaluate the economic significance of the implied volatility function by examining the predictive and hedging performance of the DV option valuation model.
Comparison of Multiobjective Evolutionary Algorithms: Empirical Results
, 2000
"... In this paper, we provide a systematic comparison of various evolutionary approaches to multiobjective optimization using six carefully chosen test functions. Each test function involves a particular feature that is known to cause difficulty in the evolutionary optimization process, mainly in conver ..."
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Cited by 628 (41 self)
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In this paper, we provide a systematic comparison of various evolutionary approaches to multiobjective optimization using six carefully chosen test functions. Each test function involves a particular feature that is known to cause difficulty in the evolutionary optimization process, mainly
Results 1  10
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