In this paper we performed an analysis in order the make an evidence of GARCH modeling on the performances of trading rules applied for a stock market index. Our study relays on the overlap between econometrical modeling, technical analysis and a simulation computing technique. The non-linear structures presented in the daily returns of the analyzed index and also in other financial series, together with the phenomenon of volatility clustering are premises for applying a GARCH model. In our approach the standardized GARCH innovations are resampled using the bootstrap method. On the simulated data are then applied technical analysis trading strategies. For all the simulated paths the “p-values” are computed in order to verify tha...
ARCH and GARCH models have become important tools in the analysis of time series data, particularly ...
A comparative study has been conducted to examine the performance of the GARCH (Generalized Autoregr...
This thesis is comprised of five papers that are all related to the subject of financial time series...
In this paper we performed an analysis in order the make an evidence of GARCH modeling on the perfor...
This paper studies the performance of GARCH model and its modifications, using the rate of returns f...
Financial series tend to be characterized by volatility and this characteristic affects both financi...
his study aims to develop a predictive model for stock prices using time-series analysis. The primar...
Volatility in financial markets has attracted growing attention by academics, policy makers and prac...
In this paper, we apply the Generalized autoregressive conditional Heteroscedasticity (GARCH) model ...
One of the challenging aspects of conditional heteroskedasticity series is that if we were to plot t...
The paper aims to analyze and forecast the Budapest Stock Exchange volatility with the use of gener...
In the presented paper GARCH class models were considered for describing and forecasting market vola...
This paper investigates conditional variance patterns in daily return series of stock market indices...
Volatility is integral for the financial market. As an emerging market, the Chinese stock market is ...
We tested different GARCH models in modeling the volatility of stock returns in London Stock Exchang...
ARCH and GARCH models have become important tools in the analysis of time series data, particularly ...
A comparative study has been conducted to examine the performance of the GARCH (Generalized Autoregr...
This thesis is comprised of five papers that are all related to the subject of financial time series...
In this paper we performed an analysis in order the make an evidence of GARCH modeling on the perfor...
This paper studies the performance of GARCH model and its modifications, using the rate of returns f...
Financial series tend to be characterized by volatility and this characteristic affects both financi...
his study aims to develop a predictive model for stock prices using time-series analysis. The primar...
Volatility in financial markets has attracted growing attention by academics, policy makers and prac...
In this paper, we apply the Generalized autoregressive conditional Heteroscedasticity (GARCH) model ...
One of the challenging aspects of conditional heteroskedasticity series is that if we were to plot t...
The paper aims to analyze and forecast the Budapest Stock Exchange volatility with the use of gener...
In the presented paper GARCH class models were considered for describing and forecasting market vola...
This paper investigates conditional variance patterns in daily return series of stock market indices...
Volatility is integral for the financial market. As an emerging market, the Chinese stock market is ...
We tested different GARCH models in modeling the volatility of stock returns in London Stock Exchang...
ARCH and GARCH models have become important tools in the analysis of time series data, particularly ...
A comparative study has been conducted to examine the performance of the GARCH (Generalized Autoregr...
This thesis is comprised of five papers that are all related to the subject of financial time series...