基于WA-ANN的股票非線性價(jià)格預(yù)測(cè)研究.pdf

1、叮1128503分類g————』生———帥cLu眥)——土塹—學(xué)號(hào)：04：30811000密絨無(wú)河海大萼碩i‘學(xué)位淪殳基于WA一人NN的股票非線性價(jià)格預(yù)測(cè)研究沈媛蛭指甘教師姓以量型盟—塑叢一婭趕叢蟄翌堂～一—————上堪劃i齟生墮上笠——————申請(qǐng)學(xué)位級(jí)別—塑：L專業(yè)名稱塑量絲透堂—蹬文提交舊娟：—墊業(yè)j二旦H論丈答辯『劃：!蚴』韭上L!!—岜學(xué)位授r單位和Ⅲ二羽7Ⅱ海大T2007“46月替辯委9j會(huì)土瞎：葛久研皓文F閱人：葛久d『、

2、林輝、、AbstractInthestockmanet，stockpricesarethefocusoftheshareholdersItisnecessarytopeflbrmscientificandmathematicalanalysis，identifythetrendsandthekeyfactors，guidinginvestorstothestockinvestmentsItwouldbenotSOsuitableanda

3、ppropriatetoapplygeneraltiminganalysismethodologyindescribingthealterationofstockpricesthankstoitsmacro，microanduncertaintyInrecentyears，twohotmathematicaltools——waveletanalysisandartificialneuralnetworkswerefounded，whic

4、hcaneffectivelydescribethetrendofstockpricesquotation，andareprovedtobeeffectiveintheanalysisofthepricecurveInthispaperwaveletanalysisandartificialneuralnetworksareusedastwomathematicaltoolstOanalyzeinstockpricesandforeca

5、stsItintroducestheobjective，significanceandresearchmethodsofthisstudyThenitpresentstherolethatthewaveletanalysisandartificialneuralnetworktheoryplayinthelbrecastsofstockpriceAsregardstheproblemsofneuralnetwork，theauthora

6、nalyzesandhastriedtosolveitWaveletanalysisandArtificialnellralnetworksareusedforanalysisaboutthepriceofselectedstocksAfterdiscountingthenoiseofthepricecurve，itbecomesgenerallysmooth，andthenusedtOforecastandmaketrainingFi