Volatility Spillover

Measuring the dynamic relationship between banking and industries with systemic importance has attracted much attention after the recent financial crisis. This paper examines the dynamic conditional correlations and volatility spillover using three popular multivariate GARCH models in the twelve-year period (from the beginning of 2005 to the beginning of 2016) among the fourteen systemically important industries in Iran’s capital market. The purpose of this study is to understand and identify the volatility spillover between industries to predict financial fluctuations, as well as policy decisions and risk management. The results of this study confirm the spillover between “Banking” and the five industries of "Basic Metals", "Industrial Multidisciplinary", "Investments", "Computers", and "Transportation & Warehousing". There is also an asymmetric spillover between “Banking” index and the "Chemical Industry", the "Extraction of Metal Ores", "Pharmaceuticals" and "Communications Devices". The results are used for mapping fundamental analysis and risk programming.

Financial markets are one of the most fundamental markets in any country. In the financial markets, the securities market and the foreign exchange market are sensitive sectors. These two markets are affected by fluctuations and economic cycles so reflect economic changes rapidly. Changes in the returns of one market due to arbitrage conditions during time lead to changes in the returns of other markets. This paper by dividing the spillover effect into two parts, mean effect and volatility effect, employing DCC-GARCH method, aimed to capture the spillover effects of dollar return, global market and Iran financial market in the period 1394-1398. Mean conditional results show that stock returns react negatively to dollar returns. In other words, there is a substitution between dollar returns and stock returns among economic agents. For the global economy, the stock market returns decreases with the fluctuations of the global economy index, but for the dollar, the relationship is reversed so that increase in the global economy index volatility increases the dollar return. For the volatility spillover, the results also supported strong spillover between each market pairs.

One of the characteristics of the financial market, especially the stock market, is the effects of behavioral factors and on other financial and non-financial markets. There are several factors that affect the return of a stock exchange. We can refer to political, socio-cultural, technological and finally economic factors. A stock market is an economic market in which securities are traded under specific rules and regulations. Accordingly, in this study, the effect of behavioral financial arguments and other financial markets on stock market returns based on quantitative analysis has been studied. This article tries to examine how exchange rates, gold, and oil as key factors of a model can explain fluctuations of the stock market index. so the effect of those variables on the stock market index in the period 2008 to the first six months of 2018 has been analyzed using the FIAPGARCH-X model. The results of the analysis show that the effect of exchange rates on the stock market fluctuations is greater than the other two factors. The results also indicate that there are asymmetric effects of increased returns on the stock market, which is consistent with behavioral bias in behavioral finance.

Financial markets are currently experiencing sharp volatility. Studying how the returns and volatility in one market affect other markets has always been one issue that helps investors and policymakers to make optimal decisions. Given the importance of volatility spillovers in the Iranian financial market, this study aimed to investigate the mechanisms behind the volatility spillovers in the foreign exchange, gold, and stock markets to the oil market in Iran. This descriptive study was conducted using the daily and monthly data from the oil, foreign exchange, gold, and capital markets from 2010 to 2019 and to analyze the data, ARCH and GARCH models have been used. The results of this study showed that the abnormal volatility of the foreign exchange and gold in the previous day positively affects the abnormal volatility of the oil market today, this indicates that money flows in the currency market, spilling over the fluctuations into the oil market. hey also found that the abnormal volatility of the capital market in the previous day negative affects the abnormal volatility of the oil market today, indicating that if money flows in the capital market, which indicates the flow of money in the capital market from yesterday, increasing the transfer of emotions to the current capital market but does not spillover into the oil market and volatility is not transferred into the oil market. Overall, the findings of this study confirmed the positive impact of the foreign exchange and gold markets on the abnormal volatility in the oil market in the short term (daily) and long term (monthly), but did not confirm the positive impact of the capital market on the abnormal volatility in the oil market.

The spread of volatility between financial indices indicates the process of information transfer between markets. Despite the relationship between financial markets, the information created in one market can affect other markets as well. Therefore, the main purpose of this study is to investigate the volatility of energy and steel prices and the experimental test of inter-market volatility spillover. To do this, the monthly data of steel and energy price (oil and gas) during 2009 to 2019 were collected from valid databank using VECM and GARCH Family and VAR model and ICSS algorithm were analyzed by considering and without considering structural failure. Then, the causal relationship between them is examined through Granger causality test. The results show that there is volatility in the energy market (oil and gas) as well as the steel market during the studied time period. Results also show that the price of steel as well as its return and index are changed significantly by energy price effect. However, there is a causal link between energy prices and steel products and these results are consistent with the theoretical basics of the study and review of literature.