The Relationship Between Implied and Realized Volatility in the Danish Option and Equity Markets

2000 ◽  
Author(s):  
Charlotte Strunk Hansen
Keyword(s):  
Equity Markets ◽  
Realized Volatility ◽  
The Relationship

Using Neural Networks to Discover Patterns in International Equity Markets

2002 ◽  
pp. 205-219 ◽  
Author(s):  
Mary E. Malliaris ◽  
Linda Salchenberger
Keyword(s):  
Neural Networks ◽  
Equity Markets ◽  
Time Frame ◽  
Exact Nature ◽  
Statistical Tools ◽  
New Approach ◽  
International Equity Markets ◽  
International Equity ◽  
The Relationship

The use of neural networks represents a new approach to how this type of problem can be investigated. The economics and finance literature is full of studies that require the researcher to prespecify the exact nature of the relationship and select specific variables to test. In this study, we use a multistage approach that requires no prespecification of the model and allows us to look for associations and relationships that may not have been considered. Previous studies have been limited by the nature of statistical tools, which require the researcher to determine the variables, time frame, and markets to test. An intelligent guess may lead to the desired outcome, but neural networks are used to produce a more thorough analysis of the data, thus improving the researcher’s ability to uncover unanticipated relationships and associations.

ENDOGENOUS CROSS CORRELATIONS

2007 ◽  
Vol 11 (S1) ◽  
pp. 124-153 ◽  
Author(s):  
STEPHEN E. SATCHELL ◽  
STEFFI J.-H. YANG
Keyword(s):  
Financial Regulation ◽  
Equity Markets ◽  
Portfolio Diversification ◽  
Current View ◽  
Investment Behavior ◽  
Portfolio Risk ◽  
Herd Effect ◽  
Cross Correlations ◽  
Asymmetric Correlation ◽  
The Relationship

This paper studies the relationship between rational herding and cross correlations in security returns. It demonstrates analytically and numerically that herding, as a temporary, fragile convergence of investment behavior, can endogenously induce asset dependency. Furthermore, there exists a self-reinforcing process, in which market extreme events amplify the herd effect, which further exacerbates asset dependency. Considering the Taiwan and U.K. equity markets, we find that the simulated markets in the presence of herding have results closer to the real patterns of asset dependency than a static model with isolated, noninteracting individuals. Our findings cast doubts on the current view that transparent financial regulation is always desirable. Moreover, this paper finds statistical evidence of asymmetric correlation patterns in both the top 50 stocks in the U.K. and Taiwan equity markets. This suggests that portfolio diversification as a means of managing portfolio risk is unlikely to be effective in periods of extreme losses in these markets.

scholarly journals Investigating the impact of Covid-19 on stock markets

2021 ◽  
Vol 10 (7) ◽  
pp. 199-219
Author(s):  
Mustapher Faque ◽  
Umit Hacioglu
Keyword(s):  
Stock Markets ◽  
Equity Markets ◽  
Adverse Impact ◽  
Vector Error Correction ◽  
Vector Error ◽  
Clear Sign ◽  
Vector Error Correction Models ◽  
Equity Indices ◽  
The Impact ◽  
The Relationship

This paper aims to examine the impact of Covid-19 pandemic on stock markets. This paper also analyses the stock market cointegration of selected global equity indices that performed better and have a quick speed of recovery during the pandemic. This paper also questions how increasing uncertainty and volatility deters investors’ perception of the diversification of equity investments. The dataset for the selected 12 global equity indices has been used from Thompson Reuters’s EIKON database in a given period of time between 2010 and 2021. This paper employs Vector Error Correction Models to assess the relationship among the selected global equity indices. Findings demonstrate that (i) there is an adverse impact of Covid-19 on the Global Equity markets, (ii) there is a clear sign of cointegration in global equity indices, (ii) investors can benefit from investing in particular equity indices that have exhibited quick speed of recovery from the pandemic records lows. The findings finally provide a strong foundation for constructing a resilient equity portfolio in a highly uncertain market environment.

scholarly journals The performance of debt and equity markets in Anglo American Plc and BHP Billiton Plc in the period 2006 to 2015 through the lens of Merton’s structural model

2019 ◽  
Vol 22 (1) ◽  
Author(s):  
Leon B. Sanderson
Keyword(s):  
Structural Model ◽  
Equity Markets ◽  
Investment Strategy ◽  
Market Prices ◽  
Merton Model ◽  
Statistical Support ◽  
Anglo American ◽  
The Relationship ◽  
Market Behaviour

This article applies the Merton structural model in evaluating the performance of the debt and equity markets in Anglo American Plc and BHP Billiton Plc in the period 2006 to 2015. We consider statistical and economic measures of the efficacy of the Merton model in explaining observed market behaviour. We find strong but unstable statistical support for the Merton model as a descriptor of market behaviour. We generated superior risk adjusted returns when applying the results of our analysis to an investment strategy. Market prices deviate from model behaviour; however, the relationship appears to be mean reverting which supports the investment thesis.

THE RELATIONSHIP AMONG EQUITY MARKETS: COMMENT

1974 ◽  
Vol 29 (4) ◽  
pp. 1311-1317 ◽  
Author(s):  
Michael Adler ◽  
Reuven Horesh
Keyword(s):  
Equity Markets ◽  
The Relationship

scholarly journals Realized Measures to Explain Volatility Changes over Time

2020 ◽  
Vol 13 (6) ◽  
pp. 125
Author(s):  
Christos Floros ◽  
Konstantinos Gkillas ◽  
Christoforos Konstantatos ◽  
Athanasios Tsagkanos
Keyword(s):  
High Frequency ◽  
Realized Volatility ◽  
High Frequency Data ◽  
Leverage Effect ◽  
Frequency Data ◽  
Specific Group ◽  
Volatility Feedback ◽  
Changes Over Time ◽  
The Relationship ◽  
Over Time

We studied (i) the volatility feedback effect, defined as the relationship between contemporaneous returns and the market-based volatility, and (ii) the leverage effect, defined as the relationship between lagged returns and the current market-based volatility. For our analysis, we used daily measures of volatility estimated from high frequency data to explain volatility changes over time for both the S&P500 and FTSE100 indices. The period of analysis spanned from January 2000 to June 2017 incorporating various market phases, such as booms and crashes. Based on the estimated regressions, we found evidence that the returns of S&P500 and FTSE100 indices were well explained by a specific group of realized measure estimators, and the returns negatively affected realized volatility. These results are highly recommended to financial analysts dealing with high frequency data and volatility modelling.

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