102 research outputs found
Global Polynomial Kernel Hazard Estimation.
No full textThis paper introduces a new bias reducing method for kernel hazard estimation. The method is called global polynomial adjustment (GPA). It is a global correction which is applicable to any kernel hazard estimator. The estimator works well from a theoretical point of view as it symptotically reduces bias with unchanged variance. A simulation study investigates the finite-sample properties of GPA. The method is tested on local constant and local linear estimators both with and without multiplicative bias correction and with the additive bias correction proposed in Nielsen and Tanggaard (2000). From the simulation experiment we conclude that the global estimator improves the goodness-of-fit. An especially encouraging result is that the bias-correction works well for small samples, where traditional bias reduction methods have a tendency to fail.Counting process theory; Kernel estimation; Hazard functions; Local linear estimation; boundary kernels.
Errors in Trade Classification: Consequences and Remedies.
No full textThe consequences of errors in trade classification are potentially worse than documented in existing empirical research. This is demonstrated by the use of a formal model of classification errors in a generic regression-type microstructure model. The bias is a function of the probability of trade-reversal in addition to the probability of an error. These parameters depend on stock and trade characteristics in addition to trading procedures and trade reporting standards. The bias is highly sensitive to the background variables, thus causing concern about the validity of empirical studies applying possibly erroneous classification methods without controlling for such effects. The theory, outlined in the paper, predicts that given empirical evidence on error rates, effective spreads must realistically be expected to be downward biased by more than 50%. However, the bias one can observe from using the TORQ database is less severe and has the opposite sign. This is due to special features of the NYSE trading process which may not carry over to other markets. This research also emphasizes the need for proper adjustment of classification error bias. Therefore, the paper proposes a GMM estimator for improved estimation. Simulation evidence indicates that in medium and larger sized samples the method is capable of removing virtually all the bias in market quality statistics like e¤ective, realized, and adverse selection spreads. This is empirically verified in an application to data from TORQ.Adverse selection; classification error; effective spread; errors-in-variables; International trade; Foreign trade; Nomenclature GMM; measurement errors; realized spread; TORQ; trade indicator;
Risiko for kollaps på aktiemarkedet - eller hvad?
Get PDFMed afsæt i et historisk lavt dividende-pris (D-P) forhold har Tom Engsted & Carsten Tanggaard prædikteret, at det danske aktiemarked vil falde med 50 % i.f.t niveauet i 1996, idet en tilbagevenden af D-P ratioen til det historiske gennemsnit hævdes primært at komme i stand via styrtdykkende aktie kurser. Forecastet bygger på den præmis, at D-P forholdet vil vende tilbage til det historiske gennemsnit, men det behøver ingenlunde at være tilfældet grundet fundamentalt ændrede skatteregler. Vi præsenterer alternative forecasts baseret ikke kun på D-P ratioen, men også på en række andre nøgletal, jf. Olesen & Risager (1998). Disse forecasts er ikke følsomme overfor præmisser vedrørende D-P forholdets tilbagevenden til det historiske gennemsnit
The comovement of US and UK stock markets.
No full textUS and UK stock returns are highly positively correlated over the period 1918-1999. Using VAR-based variance decompositions, we investigate the nature of this comovement. Excess return innovations are decomposed into news about future dividends, real interest rates, and excess returns. We find that the latter news component is the most important in explaining stock return volatility in both the US and the UK and that stock return news is highly correlated across countries. This is evidence against Beltratti and Shiller's (1993) finding that the comovement of US and UK stock markets can be explained in terms of a simple present value model. We interpret the comovement as indicating that equity premia in the two countries are hit by common real stocks.Comovement of stock returns; Variance decomposition; VAR model; Bias-correction; Bootsimulation
The Danish stock and bond markets: comovement, return predictability and variance decomposition
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