Dynamic Conditional Correlation

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.

One of the features of a financial market, the stock market, in particular, is the market sentiment which is the overall attitude of investors toward a particular security or financial market. Investors always seek to create a portfolio with minimum risk while maintaining the expected return level. Therefore, perceiving the relationship between the stock returns and markets returns can be helpful for investors to create an optimal portfolio. On this basis, the present study aims at investigating the Dynamic Conditional Correlation (DCC) between the returns on the domestic markets (industry stock market and exchange rate) and foreign markets using monthly data of oil and base metals including total metals, copper, steel and returns on the stock price index in Iran during March 2001 to April 2017 using the Dynamic Conditional Correlation Fractionally Integrated Asymmetric Power ARCH (DCC-FIAPARCH) approach. The obtained results indicate a statistically significant and positive DCC coefficient between metals, industrial products, and copper returns with the stocks returns. Consequently, it is not possible to put each of these assets with the stocks in an identical situation (purchase or sale), but instead they should be always situations for risk control. However, in connection with other markets, DCC is not significant; accordingly, assets can be placed in the investment portfolio together with the stocks.

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.

In this study, we examine the correlation between stock returns of Export-oriented (EOIs) and Import-oriented (IOIs) industries and exchange rates, to derive stock-exchange optimal weights, attempting to manage the risk of investors in the capital market. To do so, the ADCC and DCC models are used. The data consists of the stock return of the listed industries, and the daily exchange rate from 2008 to 2020. The results suggest that EOIs have a dynamic asymmetric conditional correlation, and IOIs have a dynamic symmetric conditional correlation with the exchange rate. Moreover, the results indicate that in both currency crises, the weight of optimal portfolio in all industries except pharmaceuticals, in non-crisis period is over 50% and in the crisis period is less than 50%. Accordingly, and to reduce the risk of the portfolio, in the non-crisis period, investors should invest more than half of a one-Rial portfolio to dollar exchange, and in the crisis period, they should allocate less than half of a one-Rial portfolio to this currency. In case of the currency crisis, it is suggested that investors invest in the stock of basic metals, because this industry is a pioneer in attracting currency crisis and increasing stock value of the industry through future cash flow and replacement value, and reduce the stock of pharmaceuticals and computers in their portfolio, due to attracting negative effects of the exchange market.

The aim of this study was to assess the performance of the Iranian currency exchange market by analyzing the dynamic conditional correlation (DCC) between the Iranian currency exchange rate and the free market exchange rate of the US dollar in Iran. This analysis was conducted for both the same day and with a one-day lag, spanning from June 20 to October 30, 2022. The results of the study indicate that the DCC for concurrent days (denoted as dcc0) stood at 48%. Meanwhile, the DCC for the Iranian currency exchange rate with a one-day delay compared to the free market US dollar exchange rate in Iran (referred to as dcc+1) was 17%, and the DCC for the free market US dollar exchange rate with a one-day lag behind the Iranian currency exchange rate (referred to as dcc-1) was 35%.