This paper investigates the behavior of crude oil prices, government bonds and stock market indices around outbreaks of severe international crises and wars. Using a constant-mean-return event study, we show that these events are associated with positive and significant abnormal returns on oil...

In this paper we provide evidence that the trading activity of small retail investors carries significant genuine information for the short term out-of-sample forecasting of foreign exchange rates. Our findings are based on a unique dataset of around 2000 retail investors from the OANDA FXTrade...

This paper analyzes the inter-temporal relationship between currency price changes and their expectations on intra-day frequencies. We examine how price expectations are transmitted into prices by means of order flow and how order flow is affected by past prices (feedback effects). Based on a...

Whereas the literature on additive measurement error has known a considerable treatment, less work has been done for multiplicative noise. In this paper we concentrate on multiplicative measurement error in the covariates, which contrary to additive error not only modifies proportionally the...

We develop a new general approach for handling multiplicative measurement error in continuous covariates in linear and nonlinear regression models. We apply the Simulation-Extrapolation (SIMEX) approach, which is a simulation based method of estimating and reducing the bias due to additive...

This paper focuses on modelling and estimating the starting point bias in closed-ended follow-up questions, where several bids are presented successively, depending on previous answers. Although the contingent valuation literature took off in the last decade, there is only one study modelling...

Statistical disclosure limitation is widely used by data collecting institutions to provide safe individual data. However, the choice of the disclosure limitation method severely affects the quality of the data and limit their use for empirical research. In particular, estimators for nonlinear...

Data collecting institutions use a large range of masking procedures in order to protect data against disclosure. Generally, a masking procedure can be regarded as a kind of data filter that transforms the true data generating process. Such a transformation severely affects the quality of the...

In this paper we examine the relative importance of trading volume, bid-ask spread, order flow, order imbalance, total quote depth, quote depth difference and trading intensity for high-frequency volatility estimation. By using a best subset regression approach, we fi nd that contemporaneous...

In order to guarantee confidentiality and privacy of firm-level data, statistical offices apply various disclosure limitation techniques. However, each anonymization technique has its protection limits, such that the probability of disclosing the individual information for some observations is...