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  • application of wavelet method in de-noising option prices

    جزئیات بیشتر مقاله
    • تاریخ ارائه: 1391/01/01
    • تاریخ انتشار در تی پی بین: 1391/01/01
    • تعداد بازدید: 620
    • تعداد پرسش و پاسخ ها: 0
    • شماره تماس دبیرخانه رویداد: -
     in so much financial time series are known to carry noise, elimination of noise is necessary. due to multi-scaling property, the wavelet method is very efficient in dealing with noisy data series. in specific, we propose to use the wavelet method to de-noise option prices before estimating the option-implied risk neutral density (rnd) and forecasting future option prices. we use of two rnds estimated from the perturbed prices and the filtered prices to forecast the out-of-sample options, respectively. moreover, we compare them with the true black-scholes option prices. results of this study show that, through the use of monte carlo simulations, the power of the wavelet method in the de-noising of option price data. it is clearly seen that, by de-noising the perturbed option prices using the wavelet method, most of the noise is removed and the wavelet de-noising method is robust to different levels of noise variance.

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