Inspired by findings of low–dimensional nonlinearities and the Theorem of Takens (1983) forecasting models of financial time series are often built upon nonparametric, i.e. universal nonlinear, univariate relationships. Empirical investigations, however, are seriously contaminated by the...

Employing an augmented univariate EGARCH model, we estimate the dynamic impact of information arrival as measured by volume on asymmetric news in the pre and post 2009 global financial crisis in the Athens Stock Exchange (ASE). Our results reveal that trading volume appears to capture a...

We estimate in this paper a non probabilistic Markovien model of stocks prices with an evolutionary selection of heterogeneous strategies. We chose to proceed by estimation relating on 27 companies from the CAC 40 and the composite index corresponding to these 27 companies to avoid the risk of...

La courbe de structure des taux d'interet est une des composantes fondamentales de la theorie economique et financiere. Celle-ci, en etablissant une relation entre les taux d'interet et les maturites, permet d'evaluer de nombreux actifs financiers. Or, les methodes de revelation sont nombreuses...

Bayesian Acceptance Sampling Approach is associated with utilization of prior process history for the selection of Distributions (viz., Gamma Poisson, Beta Binomial) to describe the random fluctuations involved in Acceptance Sampling. Calvin (1984) provides procedures and tables for implementing...

This paper presents evidence suggesting that artificial neural networks approach (ANNs) outperform traditional statistical methods and can forecast equity premiums reasonably well. The study replicates out-of-sample estimates of regression using ANN with economic fundamentals as inputs. The...

This paper provides a general framework for integration of high-frequency intraday data into the measurement forecasting of daily and lower frequency volatility and return distributions. Most procedures for modeling and forecasting financial asset return volatilities, correlations, and...

Volatility has been one of the most active and successful areas of research in time series econometrics and economic forecasting in recent decades. This chapter provides a selective survey of the most important theoretical developments and empirical insights to emerge from this burgeoning...

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...

This study investigates the linearity and stationarity properties of government bond returns for the G7 economies. Our results from Luukkonen et al. (1988) linearity test reveal the nonlinear nature of all of the G7 bond returns. Furthermore, we had determined that they are stationary by the...