We construct a neural network algorithm that generates price predictions for art at auction, relying on both visual and non-visual object characteristics. We find that higher automated valuations relative to auction house pre-sale estimates are associated with substantially higher...

This paper tests a traditional model of asset pricing, the CCAPM (Consumption Capital Asset Pricing Model), using data from the Spanish stock market. A generalized calibration method is used to test this model. This method allows us to judge the degree of correspondance between the population...

In many traditional financial and economic models, economic agents are assumed to make decisions using expected lifetime utility under rational expectations, where rational expectations are assumed to be formed on the basis of sufficient knowledge of the data generating process. But the mere...

The open financial economic systems of six Asian countries Taiwan, Malaysia, Singapore, Philippines, Indonesia and Japan - over the period 1986 through 1995 are identified from empirical data to determine how their stock markets, economies and financial markets are interrelated. The objective is...

Our study is three-fold: we, first review the non-linear tests that we suggest to use to detect non-linearities. We, next, investigate the empirical power of the tests, using simulations under the null hypothesis that we have a linear AR model. We, then, turn to empirical data: the returns of...

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...

Implications of factor-based asset pricing models for estimation of expecte d returns and for portfolio selection are investigated. In the presence of model mispricing due to a missing factor, the mispricing and the residual covariance matrix are linked together. Imposing a strong form of this...

We apply a logistic smooth transition market model (LSTM) to a sample of returns on Australian industry portfolios to investigate whether bull and bear market betas differ. Unlike other studies, our LSTM model allows for smooth transition between bull and bear states and allows the data to...

The Laplace mixture distribution for stock share returns is derived from conditional N(0,x2) distribution. The conditioning variable, x2, is assumed to be an exponentially distributed random variable. This offers a natural stochastic interpretation of the risk involved with the stock share....