One of the most important tasks of the financial economy is modeling and forecasting of the price volatility of risky assets. For analysts and policymakers, price volatility is a key variable that helps to understand market fluctuations. Therefore, the analysts need to
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One of the most important tasks of the financial economy is modeling and forecasting of the price volatility of risky assets. For analysts and policymakers, price volatility is a key variable that helps to understand market fluctuations. Therefore, the analysts need to be able to predict the correctness of price volatility as an essential input for tasks such as risk management, portfolio assignment, value at risk and transaction option pricing and future contracts. Accordingly, in the present research, return on stocks of Tehran Stock Exchange has been dealt with using PLS and TVP-SV models and its comparison with OLS method in MATLAB and XLSTAT software from March 2003 till August 2013 (monthly) using true variables (industrial output, real estate investment in housing, economic growth, government spending share in GDP and Non-oil exports growth rate) and monetary variables (inflation, money supply, exchange rate, oil price and domestic price of gold). Based on PLS model, the result was that the variables of economic growth and oil price have more influence of return of Tehran Stock Exchange in comparison with other variables. Then, we entered the variables of economic growth and oil price in TVP-SV model. Based on the results, TVP-SV model has more efficiency in comparison with OLS model. Based on the results of TVP-SV model after the first interruption of stock returns, the economic growth has the highest effect on stock returns.
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