A substantial body of research suggests that it is difficult to account for all of the volatility of asset prices in terms of news. This paper attempts to explain the excess volatility puzzle as a consequence of competitive interaction between market participants in the presence of noisy...

We present new evidence on the structure of interbank connections across key markets: derivatives, marketable securities, repo, unsecured lending and secured lending. Taken together, these markets comprise two networks: a network of interbank exposures and a network of interbank funding. Network...

type="main" <p>We study the behavior of a mutual fund manager in a discrete-time model, in which new investors may choose to invest in the fund after the fund manager has made trading decisions. We show that under certain conditions the fund manager may choose to buy overvalued assets at the...</p>

We present new evidence on the structure of interbank connections in key markets: derivatives, marketable securities, repo, unsecured lending and secured lending. Taken together, these markets comprise two networks: a network of interbank exposures and a network of interbank funding. Network...

We study the manipulation of stock market prices by fund managers in the presence of potential future fund flows. As investors will make further investment as long as the asset price is not fully revealing, the informed manager has incentives to prevent the asset value to be revealed too early,...

One of the most widely used standard procedures for model evaluation in classification and regression is K-fold cross-validation (CV). However, when it comes to time series forecasting, because of the inherent serial correlation and potential non-stationarity of the data, its application is not...

This paper proposes a class of locally stationary diffusion processes. The model has a time varying but locally linear drift and a volatility coefficient that is allowed to vary over time and space. The model is semiparametric because we allow these functions to be unknown and the innovation...

We investigate a model in which we connect slowly time varying unconditional long-run volatility with short-run conditional volatility whose representation is given as a semi-strong GARCH (1,1) process with heavy tailed errors. We focus on robust estimation of both long-run and short-run...

This paper proposes a class of locally stationary diffusion processes. The model has a time varying but locally linear drift and a volatility coefficient that is allowed to vary over time and space. We propose estimators of all the unknown quantities based on long span data. Our estimation...