Forecasting One Day Ahead Var And Intra Day Realized Volatility In The Athens Stock Exchange Market PDF Download
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| Author | : Timotheos Angelidis |
| Publisher | : |
| Total Pages | : 18 |
| Release | : 2007 |
| Genre | : |
| ISBN | : |
Download Forecasting One-Day-Ahead VAR and Intra-Day Realized Volatility in the Athens Stock Exchange Market Book in PDF, ePub and Kindle
We evaluate the performance of symmetric and asymmetric ARCH models in forecasting one-day-ahead Value-at-Risk (VaR) and realized intra day volatility of two equity indices in the Athens Stock Exchange (ASE). Under the framework of three distributional assumptions, we find out that the most appropriate method for the Bank index in forecasting the one-day-ahead VaR is the symmetric model with normally distributed innovations, while the asymmetric model with asymmetric conditional distribution applies for the General index. On the other hand, the asymmetric model tracks closer the one-step-ahead intra day realized volatility with conditional normally distributed innovations for the Bank index but with asymmetric and leptokurtic distributed innovations for the General index. Therefore, as concerns the Greek stock market, there are adequate methods for predicting market risk but it does not seem to be a specific model that is the most accurate for all the forecasting tasks.
| Author | : Timotheos Angelidis |
| Publisher | : |
| Total Pages | : 12 |
| Release | : 2005 |
| Genre | : |
| ISBN | : |
Download VaR and Intra-Day Volatility Forecasting Book in PDF, ePub and Kindle
We evaluate the performance of symmetric and asymmetric ARCH models in forecasting one-day-ahead Value-at-Risk (VaR) and realized intra-day volatility of two equity indices in the Athens Stock Exchange (ASE). Under the framework of three distributional assumptions, we find out that the most appropriate method for the Bank index in forecasting the one-day-ahead VaR is the symmetric model with normally distributed innovations, while the asymmetric model with asymmetric conditional distribution applies for the General index. On the other hand, the asymmetric model tracks closer the one-step-ahead intra-day realized volatility with conditional normally distributed innovations for the Bank index but with asymmetric and leptokurtic distributed innovations for the General index. Therefore, as concerns the Greek stock market, there are adequate methods for predicting market risk but it does not seem to be a specific model that is the most accurate for all the forecasting tasks.
| Author | : Timotheos Angelidis |
| Publisher | : |
| Total Pages | : 12 |
| Release | : 2018 |
| Genre | : |
| ISBN | : |
Download VAR and Intraday Volatility Forecasting Book in PDF, ePub and Kindle
We evaluate the performance of symmetric and asymmetric ARCH models in forecasting one-day-ahead Value-at-Risk (VaR) and realized intra day volatility of two equity indices in the Athens Stock Exchange (ASE). Under the framework of three distributional assumptions, we find out that the most appropriate method for the Bank index in forecasting the one-day-ahead VaR is the symmetric model with normally distributed innovations, while the asymmetric model with asymmetric conditional distribution applies for the General index. On the other hand, the asymmetric model tracks closer the one-step-ahead intra day realized volatility with conditional normally distributed innovations for the Bank index but with asymmetric and leptokurtic distributed innovations for the General index. Therefore, as concerns the Greek stock market, there are adequate methods for predicting market risk but it does not seem to be a specific model that is the most accurate for all the forecasting tasks.
| Author | : Stavros Antonios Degiannakis |
| Publisher | : |
| Total Pages | : 32 |
| Release | : 2018 |
| Genre | : |
| ISBN | : |
Download The One-Trading-Day-Ahead Forecast Errors of Intra-Day Realized Volatility Book in PDF, ePub and Kindle
Two volatility forecasting evaluation measures are considered; the squared one-day ahead forecast error and its standardized version. The mean squared forecast error is the widely accepted evaluation function for the realized volatility forecasting accuracy. Additionally, we explore the forecasting accuracy based on the squared distance of the forecast error standardized with its volatility. The statistical properties of the forecast errors point the standardized version as a more appropriate metric for evaluating volatility forecasts. We highlight the importance of standardizing the forecast errors with their volatility. The predictive accuracy of the models is investigated for the FTSE100, DAX30 and CAC40 European stock indices and the exchange rates of Euro to British Pound, US Dollar and Japanese Yen. Additionally, a trading strategy defined by the standardized forecast errors provides higher returns compared to the strategy based on the simple forecast errors. The exploration of forecast errors is paving the way for rethinking the evaluation of ultra-high frequency realized volatility models.
| Author | : Thi Le |
| Publisher | : Springer Nature |
| Total Pages | : 350 |
| Release | : 2021-04-13 |
| Genre | : Business & Economics |
| ISBN | : 3030712427 |
Download Analysing Intraday Implied Volatility for Pricing Currency Options Book in PDF, ePub and Kindle
This book focuses on the impact of high-frequency data in forecasting market volatility and options price. New technologies have created opportunities to obtain better, faster, and more efficient datasets to explore financial market phenomena at the most acceptable data levels. It provides reliable intraday data supporting financial investment decisions across different assets classes and instruments consisting of commodities, derivatives, equities, fixed income and foreign exchange. This book emphasises four key areas, (1) estimating intraday implied volatility using ultra-high frequency (5-minutes frequency) currency options to capture traders' trading behaviour, (2) computing realised volatility based on 5-minute frequency currency price to obtain speculators' speculation attitude, (3) examining the ability of implied volatility to subsume market information through forecasting realised volatility and (4) evaluating the predictive power of implied volatility for pricing currency options. This is a must-read for academics and professionals who want to improve their skills and outcomes in trading options.
| Author | : Barbara Bedowska-Sojka |
| Publisher | : |
| Total Pages | : |
| Release | : 2017 |
| Genre | : |
| ISBN | : |
Download Daily VAR Forecasts with Realized Volatility and GARCH Models Book in PDF, ePub and Kindle
In this paper we evaluate alternative volatility forecasting methods under Value at Risk (VaR) modelling. We calculate one-step-ahead forecasts of daily VaR for the WIG20 index quoted on the Warsaw Stock Exchange within the period from 2007 to 2011. Our analysis extends the existing research by broadening the class of the models, including both the GARCH class models based on daily data and models for realized volatility based on intraday returns (HAR-RV, HAR-RV-J and ARFIMA). We find that the VaR estimates obtained from the models for daily returns and realized volatility give comparable results. Both long memory features and asymmetry are found to improve the VaR forecasts. However, when loss functions are considered, the models based on daily data allow minimizing regulatory loss function, whereas the models based on realized volatility allow minimizing the opportunity cost of capital.
| Author | : Ana-Maria Fuertes |
| Publisher | : |
| Total Pages | : 72 |
| Release | : 2013 |
| Genre | : |
| ISBN | : |
Download Forecasting Daily Stock Volatility Book in PDF, ePub and Kindle
Several recent studies advocate the use of nonparametric estimators of daily price variability that exploit intraday information. This paper compares four such estimators, realised volatility, realised range, realised power variation and realised bipower variation, by examining their in-sample distributional properties and out-of-sample forecast ranking when the object of interest is the conventional conditional variance. The analysis is based on a 7-year sample of transaction prices for 14 NYSE stocks. The forecast race is conducted in a GARCH framework and relies on several loss functions. The realized range fares relatively well in the in-sample fit analysis, for instance, regarding the extent to which it brings normality in returns. However, overall the realised power variation provides the most accurate 1-day-ahead forecasts. Forecast combination of all four intraday measures produces the smallest forecast errors in about half of the sampled stocks. A market conditions analysis reveals that the additional use of intraday data on day t-1 to forecast volatility on day t is most advantageous when day t is a low volume or an up-market day. The results have implications for value-at-risk analysis.
| Author | : Pierre Giot |
| Publisher | : |
| Total Pages | : 25 |
| Release | : 2003 |
| Genre | : |
| ISBN | : |
Download Modelling Daily Value-at-Risk Using Realized Volatility and Arch Type Models Book in PDF, ePub and Kindle
In this paper we show how to compute a daily VaR measure for two stock indexes (CAC40 and SP500) using the one-day-ahead forecast of the daily realized volatility. The daily realized volatility is equal to the sum of the squared intraday returns over a given day and thus uses intraday information to define an aggregated daily volatility measure. While the VaR specification based on an ARFIMAX(0,d,1)-skewed Student model for the daily realized volatility provides adequate one-day-ahead VaR forecasts, it does not really improve on the performance of a VaR model based on the skewed Student APARCH model and estimated using daily data. Thus, for the two financial assets considered in an univariate framework, both methods seem to be equivalent. This paper also shows that daily returns standardized by the square root of the one-day-ahead forecast of the daily realized volatility are not normally distributed.
| Author | : Stavros Antonios Degiannakis |
| Publisher | : |
| Total Pages | : 24 |
| Release | : 2018 |
| Genre | : |
| ISBN | : |
Download Forecasting Realized Intra-Day Volatility and Value at Risk Book in PDF, ePub and Kindle
Predicting the one-step-ahead volatility is of great importance in measuring and managing investment risk more accurately. Taking into consideration the main characteristics of the conditional volatility of asset returns, I estimate an asymmetric Autoregressive Conditional Heteroscedasticity (ARCH) model. The model is extended to also capture i) the skewness and excess kurtosis that the asset returns exhibit and ii) the fractional integration of the conditional variance. The model, which takes into consideration both the fractional integration of the conditional variance as well as the skewed and leptokurtic conditional distribution of innovations, produces the most accurate one-day-ahead volatility forecasts. The study recommends to portfolio managers and traders that extended ARCH models generate more accurate volatility forecasts of stock returns.
| Author | : Dimitrios D. Thomakos |
| Publisher | : |
| Total Pages | : 27 |
| Release | : 2015 |
| Genre | : |
| ISBN | : |
Download Realized Volatility and Jumps in the Athens Stock Exchange Book in PDF, ePub and Kindle
We test for and model volatility jumps for three major indices of the Athens Stock Exchange (ASE).Using intraday data we rst construct several, state-of-the-art realized volatility estimators. We use these estimators to construct the jump components of volatility and perform various tests on their properties. Then we use the class of Heterogeneous Autoregressive (HAR) models for assessing the relevant effects of jumps on volatility. Our results expand and complement the previous literature on the ASE market and, in particular, this is the rst time, to the best of our knowledge, that volatility jumps are examined and modeled for the Greek market, using a variety of realized volatility estimators.
