Pricing Multivariate European Equity Option Using Gaussians Mixture Distributions and EVT-Based Copulas

In this article, we present an approach which allows taking into account the effect of extreme values in the modeling of financial asset returns and in the valorisation of associated options. Specifically, the marginal distribution of asset returns is modelled by a mixture of two Gaussian distributions. Moreover, we model the joint dependence structure of the returns using a copula function, the extremal one, which is suitable for our financial data, particularly the extreme values copulas. Applications are made on the Atos and Dassault Systems actions of the CAC40 index. Monte Carlo method is used to compute the values of some equity options such as the call on maximum, the call on minimum, the digital option, and the spreads option with the basket (Atos, Dassault systems) as underlying.

Stock Return Autocorrelation and Individual Equity Option Prices

This study demonstrates empirically the impact of stock return autocorrelation on the prices of individual equity option. The option prices are characterized by the level and slope of implied volatility curves, and the stock return autocorrelation is measured by variance ratio and first-order serial return autocorrelation. Using a large sample of U.S. stocks, we show that there is a clear link between stock return autocorrelation and individual equity option prices: a higher stock return autocorrelation leads to a lower level of implied volatility (compared to realized volatility) and a steeper implied volatility curve. The stock return autocorrelation is more important in explaining the level of implied volatility curve for relatively small stocks. The relation between stock return autocorrelation and option price structure is more pronounced when market is volatile, especially during financial crisis. The stock return autocorrelation is more important in explaining the level of implied volatility curve for relatively small stocks. Thus, stock return autocorrelation can help differentiate the price structure across individual equity options.

Investor’s Behavior and Mutual Fund - A Study in Cuttack City

In the fastest-growing economy of India, the mutual fund industry puts an emerging footprint in economic growth and development. Mutual funds create a simple and viable path for saving and investment. The mutual fund includes various investment benefits like liquidity, timely return, fund diversification, widespread analysis monetary allocation vis-à-vis a full disclosure of fund management. There are various investment products available for investment in the financial market. However, all these investment products must be able to meet an investor’s expectations? Hence to know the investor’s perception and expectation, it is necessary to study the implications of mutual funds from a unique perspective. This paper explains how different factors are affecting an individual’s perception of mutual funds. As per the findings, individuals are more inclined to traditional investment than an investment in a mutual fund. Those who have invested in mutual funds, most of them were selected equity option and Systematic investment plan or SIP. Another finding is that investors don’t want to analyze the inherent risks associated with the investment and need their fund managers and broker’s advice.

Equity Option Pricing with Systematic and Idiosyncratic Volatility and Jump Risks

Recently, a large number of empirical studies indicated that individual equity options exhibit a strong factor structure. In this paper, the importance of systematic and idiosyncratic volatility and jump risks on individual equity option pricing is analyzed. First, we propose a new factor structure model for pricing the individual equity options with stochastic volatility and jumps, which takes into account four types of risks, i.e., the systematic diffusion, the idiosyncratic diffusion, the systematic jump, and the idiosyncratic jump. Second, we derive the closed-form solutions for the prices of both the market index and individual equity options by utilizing the Fourier inversion. Finally, empirical studies are carried out to show the superiority of our model based on the S&P 500 index and the stock of Apple Inc. on options. The out-of-sample pricing performance of our proposed model outperforms the other three benchmark models especially for short term and deep out-of-the-money options.