جستجوی مقالات مرتبط با کلیدواژه « conditional variance » در نشریات گروه « مالی »

Although a positive mean-variance relation is a cornerstone of traditional finance theory, empirical evidence supporting it is controversial and mixed. According to behavioral finance theory, the mixed risk-return tradeoffs attributes to investor sentiment in the financial market. In this paper, we investigated the effect of individual investor sentiment on the mean-variance relationship in 103 Tehran Stock Exchange firms using the BSI index. Meanwhile, we examined the relationship between small and large companies, high and low-priced firms, and growth and value stocks. The conditional volatility of stocks was calculated with GARCH models, and the research hypotheses were examined using a panel data method. The results show that the risk-return relationship in the total sample, growth stocks, and high-priced entities are less affected by sentiments, but sentiments strengthen the positive mean-variance relation in value stocks, low capitalization, and low-priced firms. However, sentiment does weaken the positive relation in high-capitalization firms. According to the research results, in constructing portfolios based on variance, investors should consider not only the sentiment of investors but also the features of the share in terms of value and growth, the market value of the company, and the stock price of the companies.

The effect of the contagion between financial assets is one of the most important challenges that investors are faced with. Financial markets have been severely affected by economic, political, and social events and they are subject to volatility and turmoil that causes financial investors and analysts to be disturbed. Therefore, the main objective of the present study is to investigate the effect of shocks on the return volatility of the selected indices. The main objective of this study is to use random simulation techniques for GARCH models considering multivariate skewed distributions using the Bayesian approach. For this purpose, we used the daily return data of selected Tehran Stock Exchange (TSE) indices during the period from December 13, 2009 to Jan 29, 2003 and also the flexible types of multivariate distributions that can model both skewedness and fat tail. The results of the Bayesian DCC GARCH (1.1) model showed that the effect of shocks on the return volatility is not the same  for the selected indices and this situation implies different risk conditions and uncertainty in the returns of these groups. The results also showed that the stock returns of the automotive group spread more volatility from the previous day to the current day in comparison to Banking group and Petroleum group respectively. Shocks on variables affects the correlations among them. Also, GED distribution was identified as an appropriate distribution in line with the characteristics of the skewedness of the studied indices. Therefore, in estimating the risk of assets and portfolio optimization, one can exploit the main idea used in this study.

This study empirically examined the effect of week days on future contracts of Bahar Azadi Coin in Iran Merchandise Exchange. We used the classic Linear Autoregressive and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) to show that there isnt a standard pattern for the return of future contracts of Bahar Azadi Coin. Also, we presented that the daily return of future contracts depended on previous day and even the day before. Thus we concluded that the prices didnt follow "Random Walk" phenomenon in the future market of Bahar Azadi Coin and we couldn’t find any evidence for market information efficiency in weak level.