wavelet analysis

The aim of this paper is to analyze the multiscale pricing model with the wavelet analysis approach, Fama-French three-factor model, and nonliquidity in Tehran Stock Exchange. It was also desirable to figure out how stock returns, Fama-French factors, and nonliquidity were related in different intervals. According to the results, various outcomes were obtained at different intervals. Stock returns had significant relationships with  (the ratio of book value to market value) and nonliquidity in the long term. Stock returns had significant relationships with the beta,  , and company size in the midterm, too. There was also a significant relationship between stock returns and the company size in the short term. The proposed methodology suggests that investors should employ dynamic portfolio management strategy and multiscale risk-return evaluation to seize investment opportunities.

Identification of persistence component of inflation and prediction about future inflation structure is a crucial ingredient of an inflation targeting strategies or other related monetary policies. Monetary policy makers perform this task by extracting the measure known as “core inflation”. This measure is a good indicator for tracking trend of inflation and forecasting future inflation. Measures of core inflation was developed by using wavelet methods in our research. The maximum overlap discrete wavelet transformation (MOWT) and multi resolution analysis (MRA) methods are performed for extracting core inflation in period 1381(1)-1400(3) in Iran by monthly data. Using this methods is relatively new in the literature and are ideally appropriated for this task. The best wavelet in each wavelet families choose in accordance with Shannon entropy and logarithm of energy. On the other hand the properties of wavelet-based core inflation measure was evaluated by some tests. The results reveal that our new measure is more superior to the traditional approaches that used in previous studies in Iran.