AN ANALYSIS OF U.S. STOCK PRICE BEHAVIOR USING WAVELETS

摘要: Using wavelets we re-examine the U.S. stock market price index for any evidence of self-similarity or order that might be revealed at different scales. The wavelet transform localized in time can used to indicate how power projection signal onto kernel varies with scale observation. By comparing local scales vary over much information about structure data obtained. Such is not all evident from standard analyses untransformed data, including projections a Fourier basis. Wavelets detect structures are highly and therefore non-detectable by transforms. main conclusion while clearly complex, there seems some non-randomness data. There also limited quasi-periodicity occurrence large amplitude shocks system.