We investigate predictive abilities of nonlinear models for stock returns when density forecasts are evaluated and compared instead of the conditional mean point forecasts. The aim of this paper is to show whether the in-sample evidence of strong nonlinearity in mean may be exploited for...

Using high-frequency intraday data, we construct, test and model seven new realized volatility estimators for six international equity indices. We detect jumps in these estimators, construct the jump components of volatility and perform various tests on their properties. Then we use the class of...

We develop an empirically highly accurate discrete-time daily stochastic volatility model that explicitly distinguishes between the jump and continuous time components of price movements using nonparametric realized variation and Bipower variation measures constructed from high-frequency...

In the paper, we research on the presence of long-range dependence in returns and volatility of BUX, PX and WIG between years 1997 and 2009 with use of classical and modified rescaled range. Moving block bootstrap with pre-whitening and postblackening is used for the construction of confidence...

In the paper, we research on the presence of long-range dependence in returns and volatility of BUX, PX and WIG between years 1997 and 2009 with use of classical and modified rescaled range. Moving block bootstrap with pre-whitening and postblackening is used for the construction of confidence...

As a preliminary study of the effect of return and sampling on chaos and stochastic data pattern, this research tests chaos pattern by using Henon attractor as a sample of two-dimensional discrete chaos data with an assumption that economic and finance data are generated by low dimensional chaos...

Assume asset returns follow a VARMA_MARCH structure, this paper derives the proper multi-horizon mean and covariance matrix estimations that can be used as inputs to mean-variance optimization problem for investors with different horizons. The result is further extended to vector...

In this paper we develop new dynamic factor models to forecast multiple yield curves. Our methodology is based on a thorough empirical study of daily tenor-dependent term structures over the time period 2005-2017 which reveals important cross-tenor dependencies of yields. The suggested...