More than You Ever Wanted to Know About the VIX: Bringing Together Serial Correlation and Volatility Clustering

Estimation of Persistence and Predictability of Volatility in The Indian Banking Sector

Adhyayan A Journal of Management Sciences ◽

10.21567/adhyayan.v4i2.10207 ◽

2014 ◽

Vol 4 (2) ◽

Author(s):

Dr. Vandana Dangi

Keyword(s):

Serial Correlation ◽

Banking Sector ◽

Stock Exchange ◽

Conditional Heteroskedasticity ◽

Arch Model ◽

Stock Market Returns ◽

Volatility Clustering ◽

Arch Effect ◽

Autoregressive Conditional Heteroskedasticity ◽

Augmented Dickey Fuller

The impulsiveness in investment’s price is volatility and its meticulous estimation and forecasting is valuable to investors in the risk management of their portfolio. Earlier volatility of an asset was assumed to be constant. However, the pioneering studies of Mandelbrot, Engle and Bollerslev on the property of stock market returns did not support this assumption. The family of autoregressive conditional heteroskedasticity models were developed to capture time-varying characteristics of volatility. The present treatise attempts to study the presence of autoregressive conditional heteroskedasticity in four Indian banking sector indices viz. BSE Bankex, BSE PSU, CNX bank and CNX PSU. The daily banking sector indices for the period of January 2004 to December 2013 were taken from the online database maintained by the Bombay Stock Exchange and the National Stock Exchange. The data of four indices was studied for stationarity, serial correlation in the returns and serial correlation in the squares of returns with the help of Augmented Dickey–Fuller test, Box-Jenkins methodology and autoregressive conditional heteroscedasticity models respectively. The results of ACF, PACF and Ljung–Box Q test indicates that there is a tendency of the periods of high and low volatility to cluster in the Indian banking sector. All the four banking sector indices display the presence of ARCH effect indicating the presence of volatility clustering. Engle's ARCH test (i.e Lagrange multiplier test) and Breush-Godfrey-Pagan test and ARCH model confirmed the high persistence and predictability of volatility in the Indian banking sector.

Download Full-text

Serial Correlation between the Ultrasonographic and Pathologic Findings of Intramuscular Hemorrhaging in an Experimental Rabbit

Journal of the Korean Radiological Society ◽

10.3348/jkrs.2008.58.5.519 ◽

2008 ◽

Vol 58 (5) ◽

pp. 519 ◽

Cited By ~ 1

Author(s):

Kyungran Ko ◽

Kyung Nam Ryu ◽

Ji Seon Park ◽

Wook Jin ◽

Dong Wook Sung ◽

...

Keyword(s):

Serial Correlation ◽

Pathologic Findings

Download Full-text

Non-Performing Loans, Banking System and Macroeconomy

Studia Universitatis Babe-Bolyai Oeconomica ◽

10.2478/subboec-2018-0009 ◽

2018 ◽

Vol 63 (2) ◽

pp. 67-86

Author(s):

Akinola Morakinyo ◽

Colette Muller ◽

Mabutho Sibanda

Keyword(s):

Exchange Rate ◽

Serial Correlation ◽

Banking System ◽

Impulse Response Function ◽

Credit Market ◽

Variance Decomposition ◽

Structural Var ◽

Long Run ◽

Correlation Tests ◽

The Exchange Rate

Abstract The study builds on previous studies of the consequences of non-performing loans on an economy. Using a seven-by-seven matrix in the impulse response function (IRF) of the structural autoregressive model, we find a long-run impact of an impulse to non-performing loans on the banking system and the macroeconomy in Nigeria. Conversely, non-performing loans also respond to the innovation of all macro-banking variables aside from the exchange rate and the growth rate to GDP. Also, the level of non-performing loans grows in influence in relation to the changes to the exchange rate using the variance decomposition tool of Structural VAR. Hence, a prominent role is assigned to the level of NPLs in linking the friction in the credit market to the susceptibility of both the banking system and the macroeconomy. This study passes the serial correlation tests and the three tests of normality.

Download Full-text