Suchergebnisse

Past research suggests that US stock market volatility was greater during the 1930s than in any other 10-year time period and the post-WWII era is a period of relative stability, despite slightly higher volatility levels during the 1970s and 1980s. More recent evidence suggests that volatility levels from 1998 to 2001 have more in common with 1930s levels than with any other time period. We extend this body of research to include the volatility experiences of seven equity markets in the US, Europe, and Asia. For each market, we compare the average monthly volatility of each five-year period, beginning with January 1923, with that for the most recent period in the study, January 1998 to August 2001. We find that when there are statistical differences between current and past levels of volatility, recent volatility is usually significantly greater than past volatility. In only a small number of cases do we find current volatility to be less than past volatility. This suggests that the 1998–2001 period was unusually volatile for most markets examined. We also find that volatility behavior tends to be country-specific and cannot be generalized on an aggregate basis.

Preface --Figures and Tables --Summary --Acknowledgments --Chapter 1.Introduction --Chapter 2.Methods --Chapter 3.Developing a Framework to Assess Vulnerability:Framework Foundation: Seven Domains and Associated Factors --Assembling the Framework and Assigning Weights --Chapter 4.Results:Initial Results --Results from the Sensitivity Analysis --Implications of the Findings --Chapter 5.Conclusions and Next Steps --APPENDIXES --Abbreviations --Data Sources --Bibliography.

Purpose
– The purpose of this paper is to analyze the asymmetric contemporaneous relationship between implied volatility index (India VIX) and Equity Index (S
&
P CNX Nifty Index). In addition, the study also analyzes the seasonality of implied volatility index in the form of day-of-the-week effects and option expiration cycle.


Design/methodology/approach
– This study employs simple OLS estimation to analyze the contemporaneous relationship among the volatility index and stock index. In order to obtain robust results, the analysis has been presented for the calendar years and sub-periods. Moreover, the international evidenced presented for other Asian markets (Japan and China).


Findings
– The empirical evidences reveal a strong persistence of asymmetry among the India VIX and Nifty stock index, at the same time the magnitude of asymmetry is not identical. The results show that the changes in India VIX occur bigger for the negative return shocks than the positive returns shocks. The similar kinds of results are recorded for the Japan and China volatility index. Particularly, the analysis also supports that India VIX holds seasonality, on the market opening VIX observed to be at its high level, and on the subsequent days it remains low. The results on the options expiration unfold the facts that India VIX remains more normal on the day of expiration.


Practical implications
– The asymmetric relation and seasonal patterns are quite useful to the volatility traders to price the financial assets when market trades in the high- and low-volatility periods.


Originality/value
– There is a lack of studies of this kind in the context of emerging markets like India; hence, this is an attempt in this direction. The study provides an insight to the NSE to launch some derivative products (i.e. F
&
Os) on India VIX that can generate more liquidity in the market for the volatility traders.

This article introduces a model for forecasting future volatility using fundamental factors, including the extent to which the market's valuation deviates from its predicted value, the losses reported by companies with negative earnings, projected earnings growth rates, and Treasury bill rates. The main result is that fundamental factors provide significant incremental explanatory power for predicting volatility relative to that provided by past volatility realizations alone. The explanatory power of fundamental factors is greatest when the VIX Index is at moderate rather than extreme levels so there is no expectation of long-term mean reversion for volatility. In addition, the explanatory power of fundamental factors is greatest when the model forecasts an increase in VIX. The overall conclusion of this study is that forecasts of future volatility should incorporate fundamental factors.

Economic policy drives investment, production, employment, and other macroeconomic indicators of the economy. The study examines the equity, commodity, interest rates, and currency markets, taking into consideration the US economic policy uncertainty (EPU) index. The present work determines the association among policy uncertainty and volatility index, expressed in terms of generalized autoregressive conditional heteroscedasticity and period of empirical work spanning from 2000 to 2018. The results suggest that equity markets' volatility tends to be very high based on a high degree of policy uncertainty. The findings on the commodity market indicate that crude oil and gold prices remain more volatile during the presidential election and financial crisis. One of the essential results shows that the 2000s boom, early credit crunch, Lehman's collapse and recession, and fiscal policy battles have significantly affected the equity, currency, and commodity markets. The interest rates and currency markets have responded considerably to Feds' and EPU index. The empirical outcome provides evidence that implied volatility index is a forward looking expectation of future stock market volatility, and it uncovers that policy uncertainty affects investor sentiment. The present work holds some practical implications for the government to formulate policies to regulate the US market.