Abstract
Compared to GARCH, ARDL, VAR, and similar methods that are commonly used for stock market analysis and portfolio pricing, the quantile regression has proven to be more advantageous. In this study, we combine the quantile regression with wavelet decomposition to analyze different investment horizons in Tehran Stock Exchange. The discrete wavelet decomposition is used to divide the indices time series into short-term (2–16 days), mid-term (16–128 days), and long-term (128–512 days) horizons. The investment horizons are then accurately studied in a bear, normal, and bull market. Since Iran is an oil-exporting country and its economy is highly impacted by fluctuations in the USD exchange rate return, it is of crucial importance to analyze the effects of oil price and free-market USD exchange rate return on the stock market for investment policy-making and portfolio management. The results demonstrate how the exchange rate return volatility and the OPEC basket price fluctuation affect the stock market. The results illustrate strong evidence on the assumption of a long-term strong positive correlation between TSE and the USD exchange rate return increase.
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