We document a highly significant, strongly nonlinear dependence of stock and bond returns on past equity-market volatility as measured by the VIX. We propose a new estimator for the shape of the nonlinear forecasting relationship that exploits additional variation in the cross section of...

This paper estimates the curvature of the Earth, defined as one over its radius, without using any physics. The orthodox model is that the Earth is nearly spherical with a curvature of Û/20, 000 km. By contrast, the heterodox flat-Earth model stipulates a curvature of zero. Abstracting from the...

State price densities (SPD) are an important element in applied quantitative finance. In a Black-Scholes model they are lognormal distributions with constant volatility parameter. In practice volatility changes and the distribution deviates from log-normality. We estimate SPDs using EUREX option...

We use income satisfaction data in order to estimate equivalence scales. Our method differs from previous attempts to use satisfaction data for this purpose in that it can be used to estimate or evaluate any given parametric equivalence scale. It can also be employed to investigate specific...

The state price density is a second derivative of the discounted European options prices with respect to the strike price. We use Maximum Likelihood method to derive a simple estimator of the curve such that it is decreasing, convex and its second derivative integrates to one. Confidence...

The paper analyzes effects of occupational and regional mobility on the matching rate using the monthly panel disaggregated on regional and occupational level. The main contribution of the paper is measuring the effect of substitutability between vacancies for different occupations and vacancies...

Zero coupon rates are not observable in the market for a range of maturities. Therefore, an estimation methodology is required to derive the zero coupon yield curves from observable data. If we deal with approximations of empirical data to create yield curves it is necessary to choose suitable...

While classical measurement error in the dependent variable in a linear regression framework results only in a loss of precision, non-classical measurement error can lead to estimates which are biased and inference which lacks power. Here, we consider a particular type of non-classical...

Estimation and inference for weighted nonlinear least squares regressions are examined for the case in which the regressors are stochastic, rather than fixed, and where erros may be both heteroscedastic and serially correlated. The usual least squares parameter covarience matrix estimator may be...

In this paper, we examine the Nigerian stock market sector returns and estimate the bull and bear betas using the Logistic Smooth Threshold Market (LSTM) model. The LSTM model specification follows from the linear Constant Risk Market (CRM) model. We estimate the LSTM model for the overall...