Conditional Variance

This paper will discuss the current research in building models of conditional variances using the Autoregressive Conditional Heteroskedastic (ARCH) and Generalized ARCH (GARCH) formulations. The discussion will be motivated by a simple asset pricing theory which is ...

Recent research suggests that realised volatility measures improve the statistical accuracy of daily conditional volatility forecasts. This paper provides a …nancial evaluation of the role of intraday prices and volume in volatility forecasting. The framework allows for individual stock timing based on volatility signals. The results suggest very low correlation between statistical accuracy and pro…tability when volatility forecasts are utilized

This paper studies the volatility implications of the introduction of derivatives on stock market volatility in India using the S&P CNX Nifty Index as a benchmark. To account for non-constant error variance in the return series, a GARCH model is fitted by incorporating futures and options dummy variables in the conditional variance equation. We find clustering and persistence of volatility before and after derivatives, while listing seems to have no stabilisation or destabilisation effects on market volatility. The post-derivatives period shows that the sensitivity of the index returns to market returns and any day-of-the-week effects have disappeared. That is, the nature of the volatility patterns has altered during the post-derivatives period.

The paper aimed at modelling the density of inflation based on time-varying conditional variance, skewness and kurtosis model developed by Leon, Rubio, and Serna (2005) who model higher-order moments as GARCH-type processes by applying a Gram-Charlier series expansion of the normal density function. Additionally, it extended their work by allowing both conditional skewness and kurtosis to have an asymmetry term.

Liquidity is one of the key ingredients of any stock market. Lack of liquidity or illiquidity is a concern to the investing community. This paper, using impact cost as a proxy to illiquidity, addresses a few key areas of stock market illiquidity of the National Stock Exchange (NSE) of India. ...

This paper reviews the literature on GARCH-type models proposed to represent the dynamic evolution of conditional variances. Effects of level outliers on the diagnostic and estimation of GARCH models are also studied. Both outliers and conditional heteroscedasticity can generate time series with excess kurtosis and autocorrelated squared observations. Consequently, both phenomena can be confused. However, since outliers are generated by

Abstract: This study investigates the day of the week effect on return and volatility for Istanbul Stock Exchange (ISE) throught the period 1986 and 2003. Using generalized autoregressive conditional heteroskedasticity (GARCH) model, we find statistically significant evidence to report that there is the day of the week effect. Friday has the highest effect on return with 0,015 while Monday has the lowest return with-0,003 compared to return on Wednesday. When volatility of return is concerned, Monday has the highest volatility with 0,933 and Tuesday has the lowest volatility with –0,716 compared to return on Wednesday.

This work investigates the performance of different models of Value at Risk (VaR). We include a wider range of methods (Parametric, Historical simulation, Monte Carlo simulation, and Extreme value theory models) and several models to compute the conditional variance (exponential moving averages, GARCH and asymmetric GARCH models) under Normal and Student�s t-distribution of returns. We analyse four European indexes (IBEX-35, CAC40, DAX and FTSE100), the American Dow Jones and S&P 500 indexes, the Japanese Nikkei 225 index and the Hong Kong Hang Seng index. We examine two periods: a stable period and a volatile one. To choose the best model, we employ a two-stage selection approach. First, we test the accuracy of different models of VaR. We use the unconditional and conditional coverage test, the Back-Testing criterion and the dynamic quantile test. A model survived if all tests indicated the model is accurate. With regard to the first stage, the best models are Parametric and Extrem...

The present article intend to verify the presence of speculative rational bubbles, starting from the identification of switching regime of the returns generation process in the brazilian market exchange, BOVESPA, for the Plano Real period (July of 1994 to March of 2004). In order to achieve this end, it was used of the model of markovian switching regime that allows to verify the nonlinear structure of the data and it is relation to the conditional mean and conditional variance. As result the dynamics of the data generation process, the returns can be described as function of two regimes (“bull markets” and “bear markets”). These cycles, however, they could be decomposed in other cycles, initial and final phases of the growth cycle (“bull”) and decrease (“bear”). This decomposition was shown more coherent with the concept of speculative bubble, in which there is a nonlinear relationship between the price and their foundations

This study estimates two models of Chilean inflation with time-varying parameters during the sample period 1990-1999. The first model is based on the Phillips curve and the second represents a small open economy with an inflation-targeting framework. The out-of-sample inflation forecasts of the two models are compared with the out-of-sample inflation forecasts produced by simple time series models à la

There is continuing debate in east and southern Africa about the effects of food market reform on the welfare of small-scale farmers and low-income consumers. At the center of this debate is the perception that food prices have become more unstable in countries that have liberalized their staple food markets, thereby exacerbating the plight of poor consumers and farmers. This perception has led many governments in the region to shun an open maize borders policy and pursue a variety of food marketing and trade policy tools to stabilize food prices. Unfortunately, there remains a dearth of empirical evidence on the effects of alternative food marketing and trade policies, including that of liberalization, on price stability and predictability. Assessments of this issue are complicated by the fact that market reform programs are not monolithic in their design or implementation – impacts of reform on price instability may depend on variations in implementation. It would be particularly ...

The paper aimed at modelling the density of inflation based on time-varying conditional variance, skewness and kurtosis model developed by Leon, Rubio, and Serna (2005) who model higher-order moments as GARCH-type processes by applying a Gram-Charlier series expansion of the normal density function. Additionally, it extended their work by allowing both conditional skewness and kurtosis to have an asymmetry term.

The economies of Hong Kong, Singapore and Taiwan have become known as “East Asian Tigers,” enjoyed a remarkable record of high and sustained economic growth over three decades from 1965 to the early 1990s. Their ability to achieve a speedy development with equity has intrigued many economists who attempted to understand the drive of growth. Most of this miraculous growth is believed due to a combination of fundamentally sound development policies, tailored interventions, and an unusually rapid accumulation of physical and human capital, as well as rapid intra-regional trade integration. Recently GARCH-type models have been applied to analyze growth rates of real gross domestic product (GDP) in developed and under-developed countries. However, few studies actually employ multivariate GARCH-type models such as the constant conditional correlation (CCC) model by Bollerslev (1990), dynamic conditional correlation (DCC) model by Engel (2002) and varying correlation MGARCH (VC-MGARCH) by ...

Abstract Many regression programs include a tolerance test that does not allow a variable to enter the regression if its correlation with the previously entered variables exceeds a specified level. This is done to achieve computational stability by assuring that the correlation matrix C of the independent variables is not nearly singular. However, for any specified tolerance level, there is an example in which the entering variables pass the tolerance test but the computation is extremely unstable. A bound for the condition of C is p times the trace of C -1, which can be monitored instead of tolerance to assure stability.

We propose a new combined semiparametric estimator, which incorporates the parametric and nonpara-metric estimators of the conditional variance in a multiplicative way. We derive the asymptotic bias, variance, and normality of the combined estimator under general conditions. We ...

We propose a new combined semiparametric estimator, which incorporates the parametric and nonpara-metric estimators of the conditional variance in a multiplicative way. We derive the asymptotic bias, variance, and normality of the combined estimator under general conditions. We ...

... A long-run Pure Variance Common Features model for the common volatilities of the Dow Jones. ... a, Department of Finance, New York University, Leonard N. Stern School of Business, 44 West Fourth Street, Suite 9-62, New York, NY 10012-1126, USA. ...

The paper presents GARCH models for the Euro-Polish zloty and US dollar-Polish zloty currency rates. It applies the approach within which both the conditional variance function and the mean equation of the ARCH class model are expanded simultaneously. The basic regression equation incorporates causal dependencies between currency prices and the main characteristics of domestic and international currency, money and capital markets. The paper provides an insight into the currency market microstructure as the presented investigation takes into account the intradaily features of the market. Model selection and performance has been evaluated by the use of direction quality measures.