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Measuring confidence and uncertainty during the financial crisis : evidence from the CFS survey
(2010)
The CFS survey covers individual situations of banks and other companies of the financial sector during the financial crisis. This provides a rare possibility to analyze appraisals, expectations and forecast errors of the core sector of the recent turmoil. Following standard ways of aggregating individual survey data, we first present and introduce the CFS survey by comparing CFS indicators of confidence and predicted confidence to ifo and ZEW indicators. The major contribution is the analysis of several indicators of uncertainty. In addition to well established concepts, we introduce innovative measures based on the skewness of forecast errors and on the share of ‘no response’ replies. Results show that uncertainty indicators fit quite well with pattern of real and financial time series of the time period 2007 to 2010. Business Sentiment , Financial Crisis , Survey Indicator , Uncertainty
This paper provides theory as well as empirical results for pre-averaging estimators of the daily quadratic variation of asset prices. We derive jump robust inference for pre-averaging estimators, corresponding feasible central limit theorems and an explicit test on serial dependence in microstructure noise. Using transaction data of different stocks traded at the NYSE, we analyze the estimators’ sensitivity to the choice of the pre-averaging bandwidth and suggest an optimal interval length. Moreover, we investigate the dependence of pre-averaging based inference on the sampling scheme, the sampling frequency, microstructure noise properties as well as the occurrence of jumps. As a result of a detailed empirical study we provide guidance for optimal implementation of pre-averaging estimators and discuss potential pitfalls in practice. Quadratic Variation , MarketMicrostructure Noise , Pre-averaging , Sampling Schemes , Jumps