Adjoint-based Monte Carlo calibration of financial market models

Adjoint methods have recently gained considerable importance in the finance sector, because they allow to quickly compute option sensitivities with respect to a large number of model parameters. In this paper we investigate how the efficiency of adjoint methods can be exploited to speed up the Monte Carlo-based calibration of financial market models. After analyzing the calibration problem both theoretically and numerically, we derive the associated adjoint equation and propose its application in combination with a multi-layer method, for which we prove convergence to a stationary point of the underlying optimization problem. Detailed numerical examples illustrate the performance of the method. In particular, the proposed algorithm reduces the calibration time for a typical equity market model with time-dependent model parameters from over three hours to less than ten minutes on a usual desktop PC.      

The roles of accounting in collective bargaining

In this paper, the roles that accounting information appeared to play in the negotiations between a not-for-profit organization and the association representing its professional employees are described and assessed. Using a case mode of inquiry, and drawing on the industrial relations and recent accounting literature, the paper explores the impact of accounting on both the process and outcome of the negotiations, and concludes by offering some tentative hypotheses on the roles of accounting in collective bargaining.     

An Investigation of Transactions Data for NYSE Stocks

Using transactions data, the behavior of returns and characteristics of trades at the micro level is examined. A minute-by-minute market return series is formed and tested for normality and autocorrelation. Evidence of differences in return distributions is found among overnight trades, trades during the first 30 minutes following the market opening, trades at the close, and trades during the remainder of the day. The latter distribution is found to be normal. Unusually high returns and standard deviations of returns are found at the beginning and the end of the trading day. When the beginning-and end-of-the-day effects are omitted, autocorrelation in the market return series is reduced substantially. A number of patterns in trading are reported.