Lead-Lag Relationship between Volatility Index and Stock Market Index

2005 ◽  
Vol 13 (2) ◽  
pp. 87-105
Author(s):  
Jae Ha Lee ◽  
Je Ryun Chung
Keyword(s):  
Stock Market ◽  
Implied Volatility ◽  
Daily Basis ◽  
Sample Period ◽  
Stock Market Index ◽  
Market Index ◽  
Volatility Index ◽  
Asymmetric Response ◽  
Daily Data

This study examines the lead-lag relationship between KOSPI200 and the volatility index based on the implied volatility from the KOSPI200 options. The sample period covers from January 2, 2003 to June 30, 2004. Both daily and minute-by-minute data were used for the lead-lag analysis. The study also determines whether the response of volatil ity index to KOSPI200 is symmetric or not. The most important findings may be summarized as follows. First, there is no lead-lag relationship between the change in volatility index and the KOSPI200 returns on a daily basis. However, on a minute-by-minute basis, volatility index leads KOSPI200 for the group of largest increases in volatility index, and the opposite is true for the group of largest decreases and least changes in volatility index. The option market appears to react more quickly to volatility increases, while the stock market seems more sensitive to volatility decreases. Second, the volatility increase in response to the stock market decline is more severe than the volatility decrease in response to the stock market rise for daily data. This evidence of asymmetry suggests that volatility index plays a role of investors’fear gauge. Our results show no asymmetric response of volatility index to stock market movements for weekly data.

DISTRIBUTION OF DETRENDED STOCK MARKET DATA

2010 ◽  
Vol 09 (03) ◽  
pp. 245-257 ◽  
Author(s):  
BOON LEONG LAN ◽  
EE VON YEOH ◽  
JIN AUN NG
Keyword(s):  
Stock Market ◽  
Stock Price ◽  
Empirical Distribution ◽  
Characteristic Exponent ◽  
Principal Component ◽  
Stock Market Index ◽  
Market Data ◽  
Market Index ◽  
Daily Data ◽  
Stock Volume

For stock market data, the empirical distribution of the return for stock price and the empirical distribution of the return for stock market index are well known. However, for the detrended data (defined as data divided by trend), which is a different fluctuating quantity compared to the return, only the distribution of detrended daily stock volume is known so far. In this paper, we show that for both stock price and stock market index, the detrended daily data is well fitted by a stable probability density with characteristic exponent parameter less than 2. The trend was modeled using either cubic smoothing spline or principal component analysis. The significance of our results for stock market modeling is discussed.

scholarly journals MENGKAJI PERUBAHAN NILAI TUKAR RUPIAH DAN PASAR SAHAM

2008 ◽  
Vol 10 (4) ◽  
Author(s):  
Untoro Untoro ◽  
Priyo R. Widodo
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Stock Index ◽  
Stock Market Index ◽  
Vector Autoregressive ◽  
Market Index ◽  
Daily Data ◽  
Exchange Rate Movements ◽  
The Exchange Rate ◽  
The Relationship

This paper analyzes the relationship between the Exchange rate and the stock market in Jakarta, Singapore, Malaysia, Thailand, Philippine and Hongkong using a high frequency data. We applied the Vector Autoregressive method on the daily data covering 1 July 1997 to 30 June 2006.The analysis provides several results as follows: (i) the exchange rate movements is influenced by the regional and the Hongkong stock market index, except Thailand, (ii) Jakarta stock market index is influenced by the regional stock market except Thailand, (iii) the Rupiah rate influence the regional and Hongkong stock index, (iv) the Jakarta's stock market index is integrated to the regional stock market index. These results may be a usefull as an additional guidance to evaluate the Rupiah's exchange rate and the regional stock market movement in general.JEL Classification: C32, F31, G15                 Keywords: Stock, Vector Autoregressive, exchange rate.

DO INTERNATIONAL GOLD PRICES AND NSE NIFTY 50 MOVE TOGETHER?

2021 ◽  
Vol 10 (1) ◽  
pp. 497-506
Author(s):  
A. Sidhu ◽  
R. Katoch
Keyword(s):  
Stock Market ◽  
Global Financial Crisis ◽  
Stock Market Index ◽  
Causality Test ◽  
Significant Information ◽  
Market Index ◽  
Test Study ◽  
Daily Data ◽  
Short Run ◽  
The Times

With gold’s persistence performance over erratic periods since the catastrophic event of global financial crisis in 2008, attention is focussed on gold to substitute stock market investments in the times of crisis. Exploring such causal nexus between NSE NIFTY 50 index and Gold prices in Indiapost 2008 crisis is the main focus of the present research. The daily data of International Bloom berg Gold prices and NSE NIFTY 50 Index series has been used over the time period of November 13, 2008 to January 24, 2020. By applying unit root and Toda-Yamamoto granger causality test, study primarily shows stationarity of the variables at different order. The study evidenced the significant bidirectional short-run causal relationship in between NSE NIFTY 50 prices and International Gold prices. Hence, International Gold prices hold significant information which can be used to predict NSE NIFTY 50 returns and vice-versa. The results of present study can be used by Indian stock market policymakers to implement new structural restructuring to augment efficiency of Indian equity sector. Present study is limited in scope to account for gold’s nexus with only stock market index which in future can be furthered by establishing association with other commodity markets, mutual funds, exchange rate, derivative, etc.

Tests of The FAMA French Model in Indian Stock Market

2016 ◽  
Vol 11 (02) ◽  
Author(s):  
Anubha Srivastava
Keyword(s):  
Stock Market ◽  
Stock Exchange ◽  
Test Validity ◽  
Stock Market Index ◽  
Expected Return ◽  
Market Index ◽  
Daily Data ◽  
Significant Difference ◽  
Actual Return ◽  
French Model

This paper has considered a sample of 30 stocks which are listed in Bombay Stock Exchange (BSE) SENSEX Index. The SandP BSE SENSEX (SandP Bombay Stock Exchange Sensitive Index), also-called the BSE 30 , is a free-float market capitalization-weighted stock market index of 30 well-established and financially sound companies listed on BSE Ltd. Daily data allow us to more authentic data to measure stock’s performance over shorter time horizons. In this paper an attempt has been made to test validity FAMA French inIndian stock market to check how far the forecasting of expected return will match the actual return. This paper concludes that though FAMAFrench model is an extension of CAPM and can be used for forecasting of expected return but there is significant difference between the expected return as per FAMA French Model and actual return.

On the sensibility of the Pairs Trading strategy: the case of the FTS stock market index

2020 ◽  
Vol 38 (3) ◽  
Author(s):  
Ainhoa Fernández-Pérez ◽  
María de las Nieves López-García ◽  
José Pedro Ramos Requena
Keyword(s):  
Standard Deviation ◽  
Stock Market ◽  
Trading Strategy ◽  
Stock Market Index ◽  
Pairs Trading ◽  
Empirical Application ◽  
Statistical Arbitrage ◽  
Market Index ◽  
Standard Deviations ◽  
Using Data

In this paper we present a non-conventional statistical arbitrage technique based in varying the number of standard deviations used to carry the trading strategy. We will show how values of 1 and 1,2 in the standard deviation provide better results that the classic strategy of Gatev et al (2006). An empirical application is performance using data of the FST100 index during the period 2010 to June 2019.

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