School for Advanced Studies in the Social Sciences

About: School for Advanced Studies in the Social Sciences is a facility organization based out in Villejuif, France. It is known for research contribution in the topics: Politics & Context (language use). The organization has 1230 authors who have published 2084 publications receiving 57740 citations. The organization is also known as: Ecole des Hautes Etudes en Sciences Sociales & EHESS.

Financialisation of Valuation

Abstract: This article shows that forms of analysis and calculation specific to finance are spreading, and changing valuation processes in various social settings. This perspective is used to contribute to the study of the recent transformations of capitalism, as financialisation is usually seen as marking the past three decades. After defining what is meant by “financialised valuation,” different examples are discussed. Recent developments concerning the valuation of assets in accounting standards and credit risk in banking regulations are used to suggest that colonisation of financial activities by financialised valuations is taking place. Other changes, concerning the valuation of social or cultural activities and environmental issues are also highlighted in order to support the hypothesis of a parallel colonisation of non-financial activities by financialised valuations. Specifically, the language of finance appears to gradually being incorporated into public policies, especially in Europe—and this trend seems to have gathered pace since the 2000s. Some interpretations are proposed to understand why public policies are seemingly increasingly reliant on financialised valuations.

Libri-Light: A Benchmark for ASR with Limited or No Supervision

Abstract: We introduce a new collection of spoken English audio suitable for training speech recognition systems under limited or no supervision. It is derived from open-source audio books from the LibriVox project. It contains over 60K hours of audio, which is, to our knowledge, the largest freely-available corpus of speech. The audio has been segmented using voice activity detection and is tagged with SNR, speaker ID and genre descriptions. Additionally, we provide baseline systems and evaluation metrics working under three settings: (1) the zero resource/unsupervised setting (ABX), (2) the semi- supervised setting (PER, CER) and (3) the distant supervision setting (WER). Settings (2) and (3) use limited textual resources (10 minutes to 10 hours) aligned with the speech. Setting (3) uses large amounts of unaligned text. They are evaluated on the standard LibriSpeech dev and test sets for comparison with the supervised state-of-the-art.

Bayesian Inference on GARCH Models using the Gibbs Sampler

Abstract: This paper explains how the Gibbs sampler can be used to perform Bayesian inference on GARCH models. Although the Gibbs sampler is usually based on the analytical knowledge of the full conditional posterior densities, such knowledge is not available in regression models with GARCH errors. We show that the Gibbs sampler can be combined with a unidimensional deterministic integration rule applied to each coordinate of the posterior density. The full conditional densities are evaluated and inverted numerically to obtain random draws of the joint posterior. The method is shown to be feasible and competitive compared to importance sampling and the Metropolis-Hastings algorithm. It is applied to estimate an asymmetric GARCH model for the return on a stock exchange index, and to compute predictive densities of option prices on the index.