In this study we investigate using the mean reversion processes in financial risk management, as they provide an good description of stock price uctuations and market risks. This paper does not aim at being exhaustive, but gives examples for practically implementable models allowing for stylised...

Stylized facts on financial time series data are the volatility of returns that follow non-normal conditions such as leverage effects and heavier tails leading returns to have heavier magnitudes of extreme losses. Value-at-risk is a standard method of forecasting possible future losses in...

This study is an attempt to review the theory and applications of autoregressive fractionally integrated moving average (ARFIMA) and fractionally integrated generalized autoregressive conditional heteroskedasticity (FIGARCH) models, mainly for the purpose of the description of the observed...

Low-frequency financial returns can be modelled as centered around piecewise-constant trend functions which change at certain points in time. We propose a new stochastic time series framework which captures this feature. The main ingredient of our model is a hierarchically-ordered oscillatory...

The way in which market participants form expectations affects the dynamic properties of financial asset prices and therefore the appropriateness of different econometric tools used for empirical asset pricing. In addition to standard rational expectations models, this thesis studies a class of...

We use Bayesian factor regression models to construct a financial conditions index (FCI) for the U.S. Within this context we develop Bayesian model averaging methods that allow the data to select which variables should be included in the FCI or not. We also examine the importance of different...

Extracting and forecasting the volatility of financial markets is an important empirical problem. Time series of realized volatility or other volatility proxies, such as squared returns, display long range dependence. Exponential smoothing (ES) is a very popular and successful forecasting and...

During the recent decades, neural network models have been focused upon by researchers due to their more real performance and on this basis different types of these models have been used in forecasting. Now, there is this question that which kind of these models has more explanatory power in...

Sornette et al. (1996), Sornette and Johansen (1997), Johansen et al. (2000) and Sornette (2003a) proposed that, prior to crashes, the mean function of a stock index price time series is characterized by a power law decorated with log-periodic oscillations, leading to a critical point that...

This paper analyzes the behavior of Moroccan bank’s liquidity during the period 2001 – 2012. The research aims to identify the determinants of Moroccan bank’s liquidity. We first evaluate Moroccan banks’ liquidity positions through different liquidity ratios to determine the effects of...