We propose a new estimator for nonparametric regression based on local likelihood estimation using an estimated error score function obtained from the residuals of a preliminary nonparametric regression. We show that our estimator is asymptotically equivalent to the infeasible local maximum...

We show that it is possible to adapt to nonparametric disturbance autocorrelation in time series regression in the presence of long memory in both regressors and disturbances by using a smoothed nonparametric spectrum estimate in frequency-domain generalized least squares. When the collective...

We develop new tests of the capital asset pricing model which are valid under the assumption that the distribution generating returns is elliptically symmetric; this assumption is necessary and sufficient for the validity of the CAPM. Our test is based on semiparametric efficient estimation...

Efficient semiparametric and parametric estimates are developed for a spatial autoregressive model, containing nonstochastic explanatory variables and innovations suspected to be non-normal. The main stress is on the case of distribution of unknown, nonparametric, form, where series...

We consider a time series model involving a fractional stochastic component, whose integration order can lie in the stationary/invertible or nonstationary regions and be unknown, and additive deterministic component consisting of a generalised polynomial. The model can thus incorporate competing...

Many financial applications, such as risk analysis and derivatives pricing, depend on time scaling of risk. A common method for this purpose, though only correct when returns are iid normal, is the square–root–of–time rule where an estimated quantile of a return distribution is scaled to a...

We provide a model that links an asset's market liquidity; i.e., the ease with which it is traded; and traders' funding liquidity, i.e. the ease with which they can obtain funding. Traders provide market liquidity, and their ability to do so depends on their availability of funding. Conversely,...

We provide an equilibrium multi-asset pricing model with micro-founded systemic risk and heterogeneous investors. Systemic risk arises due to excessive leverage and risk taking induced by free-riding externalities. Global risk-sensitive financial regulations are introduced with a view of...

Most financial risk regulations assume that asset returns are exogenous, where risk is estimated from historical data. This assumption fails to take into account the feedback effect of trading decisions on prices. We investigate the consequences of risk constrained trading by means of...

We provide an equilibrium multi-asset pricing model with micro- founded systemic risk and heterogeneous investors. Systemic risk arises due to excessive leverage and risk taking induced by free-riding externalities. Global risk-sensitive financial regulations are introduced with a view of...