Author: Shahid Ahmed
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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This study is an attempt to model the volatility of stock returns in Indian market for the period 1997-2006 using GARCH, TARCH and E-GARCH. Results point out that returns exhibit persistence and volatility clustering in both NSE Nifty and BSE Sensex. Asymmetric volatility effect has been observed in both the series using TARCH and E-GARCH model. While forecasting returns it is found that GARCH-M performs better compared to alternative econometric models, namely, RW, OLS, GARCH, GARCH-M, TARCH and E-GARCH models. It is revealed that one-step ahead forecast improves by using GARCH and its variant models, which goes against the concept of random walk hypothesis. Results of this study also indicate that certain anomalies still exist which makes the stock market inefficient. In this context, SEBI is expected to play proactive role in a manner, which makes market capable to value the intrinsic price of assets.
Author: Thomas Lux
Publisher:
ISBN: 9783931052027
Category :
Languages : en
Pages : 28
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Author: Allan Timmermann
Publisher:
ISBN:
Category : Rate of return
Languages : en
Pages : 32
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Book Description
Author: Gilles Teyssière
Publisher: Springer Science & Business Media
ISBN: 3540346252
Category : Business & Economics
Languages : en
Pages : 394
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Book Description
Assembles three different strands of long memory analysis: statistical literature on the properties of, and tests for, LRD processes; mathematical literature on the stochastic processes involved; and models from economic theory providing plausible micro foundations for the occurrence of long memory in economics.
Author: Ben Jacobsen
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
We investigate volatility clustering using a modeling approach based on the temporal aggregation results for generalized autoregressive conditional heteroscedasticity (GARCH) models in Drost and Nijman [Econometrica, 1993]. Our findings highlight that volatility clustering, contrary to widespread belief, is not only present in high-frequency financial data. Monthly data also exhibit significant serial dependence in the second moments. We show that the use of temporal aggregation to estimate low-frequency models reduces parameter uncertainty substantially.
Author: Frank K. Reilly
Publisher:
ISBN:
Category : Stocks
Languages : en
Pages : 92
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Book Description
General price studies on the level of volatility for aggregate stock market have derived conflicting results. Using daily stock price changes for the period 1926-1975, the paper examines the characteristics of the distribution of daily stock price changes. Subsequently we examined changes in several measures of stock price volatility. The results indicated significant changes over time and especially in 1973-1975.
Author: Michel Crouhy
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Encompassing a very broad family of ARCH-GARCH models we show that heteroskedasticity, already well documented for the US market, is a worldwide phenomenon. The AT-GARCH (1,1) model, where volatility rises more in response to bad news than to good news, and where news is considered bad only below a certain level, is found to be a remarkably robust representation of worldwide stock market returns. The residual structure is then captured by extending ATGARCH (1,1) to an hysteresis model, HGARCH, where we model structured memory effects from past innovations. Obviously, this feature relates to the psychology of the markets and the way traders process information. For the French stock market we show that a shock of either sign may affect volatility differently, depending on the recent past being characterized by either all positive or all negative returns. In the same way a longer term trend of either sign may also influence the impact on volatility of current innovations. It is found that bad news is discounted very quickly in volatility, this effect is reinforced when it comes after a negative trend in the stock index. On the opposite, good news has a very small impact on volatility except when it is clustered over a few days, which in this case reduces volatility substantially.
Author: Robert A. Connolly
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
We study volatility clustering in daily stock returns at both the index and firm level over 1985 to 2000. We find that the relation between today's index return shock and next period's volatility decreases when important macroeconomic news is released today and increases with the shock in today's stock market turnover. Collectively, our results suggest that volatility clustering tends to be stronger when there is more uncertainty and disperse beliefs about the market's information signal. Our findings also contribute to a better understanding of the joint dynamics of stock returns and trading volume.
Author: Greg N. Gregoriou
Publisher: CRC Press
ISBN: 1420099558
Category : Business & Economics
Languages : en
Pages : 654
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Book Description
Up-to-Date Research Sheds New Light on This Area Taking into account the ongoing worldwide financial crisis, Stock Market Volatility provides insight to better understand volatility in various stock markets. This timely volume is one of the first to draw on a range of international authorities who offer their expertise on market volatility in devel
Author: Ben Jacobsen
Publisher:
ISBN:
Category :
Languages : en
Pages : 31
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