The Chinese stock market features an interesting history of divided market segments: domestic (A), foreigners' (B) and overseas (H). This puts forth questions of market integration as well as cross-divisional information transmission. We address these issues in a structural DCC framework, an...

The present study addresses the economic interpretation of stock market volatility. We argue that its character is inherently ambivalent, being considered as an indicator of either information flow or uncertainty.We discriminate between these views by measuring the fraction of price changes that...

This paper employs a new and comprehensive data set to investigate short-term herding behavior of institutional investors. Using data of all transactions made by financial institutions in the German stock market, we show that herding behavior occurs on a daily basis. However, in contrast to...

This is an empirical study on the effect of house price on stock-market participation and its depths based on unique China Household Finance Survey (CHFS) data in 2011 and 2013 including 36213 sample households. We mainly found that, with an increase of one thousand RMB per square meter in macro...

The behaviour of market agents has always been extensively covered in the literature. Risk averse behaviour, described by von Neumann and Morgenstern (1944) via a concave utility function, is considered to be a cornerstone of classical economics. Agents prefer a fixed profit over uncertain...

A great proportion of stock dynamics can be explained using publicly available information. The relationship between dynamics and public information may be of nonlinear character. In this paper we offer an approach to stock picking by employing so-called decision trees and applying them to XETRA...

Pricing kernels play a major role in quantifying risk aversion and investors' preferences. Several empirical studies reported that pricing kernels exhibit a common pattern across different markets. Mostly visual inspection and occasionally numerically summarise are used to make comparison. With...

Bayesian learning provides a core concept of information processing in financial markets. Typically it is assumed that market participants perfectly know the quality of released news. However, in practice, news' precision is rarely disclosed. Therefore, we extend standard Bayesian learning...

This paper analyzes empirical market utility functions and pricing kernels derived from the DAX and DAX option data for three market regimes. A consistent parametric framework of stochastic volatility is used. All empirical market utility functions show a region of risk proclivity that is...