COV,0.016395634468666223
GOOG,0.014856884972771652
BIDU,0.01627905928367886
MSFT,0.014749242696524133
AAPL,0.015694780271549094
GS,0.015319319873685792
UTSI,0.016815195734629747
WMT,0.016305917647503054
BABA,0.017499242107467235
PEP,0.01515410031518215
XOM,0.014563757536247108
BA,0.018123526691904698
NKE,0.016668563962443195
QCOM,0.015591538887332978
APA,0.017720786132879453
SBUX,0.014297458853233962
AVP,0.015021995690228366
HSY,0.016792976247771638
MAT,0.0159148656630708
GCI,0.01799372315391859
SNP,0.016909847477596412
SOHU,0.018819964947724605
OXY,0.013423694375492547
KMI,0.015067426102958031
UPS,0.016840528192845053
FDX,0.017810936846259166
DSX,0.023600387518481602
AAL,0.017159676453976678
NTES,0.014160203577720156
SINA,0.018611588884055362
EDU,0.01944206501028227
JD,0.017401773787818136
JRJC,0.01497309714498908
AMZN,0.013831618293024022
INTC,0.018262747505650784
IBM,0.015645563164977207
EBAY,0.01695921920108918
ORCL,0.016167400096697086
TXN,0.013587087539784073
CSCO,0.018028035045803612
C,0.01612645437149649
BAC,0.015429541369307352
JPM,0.013493275770805538
MS,0.014078693368945943
AIG,0.018887427506504833
JNJ,0.01640863789917456
PFE,0.016263089406323105
KO,0.0157885426788303
MDT,0.016085287308327374
ABT,0.020267907473408387
COP,0.015374567532545904
SLB,0.014787800944951867
DUK,0.01482897298969452
HMC,0.015096048550813276
TM,0.017122584149210612
TSLA,0.013686913744277732
GE,0.014634433131617275
PG,0.016528175092659875
EL,0.02075764645216891
GD,0.018121551640675075
CL,0.014180678346439001
DD,0.014401835025723203
T,0.015948267553468665
HPQ,0.016235287435573564
S,0.01549562838412856
ERIC,0.01701306549010894
XRX,0.014526422471025424
VOD,0.015045048615440312
ADS,0.015087993490698328
CTSH,0.01524020658742816
NOK,0.01819672991223403
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EMC,0.014323733613111116
VZ,0.021056007701592945
USB,0.016101891667102994
RF,0.014882261387745274
V,0.018271060304910255
BK,0.018955793839893244
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ALL,0.015540811083946114
HIG,0.01754488483082151
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AXP,0.016531540853882525
MA,0.0162733907228913
CI,0.017259891220167165
COF,0.014081990873022254
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MO,0.0166811857813069
UNH,0.01578636060848347
MRK,0.016587553666173333
AMGN,0.017789746323755715
CVS,0.015307071903622656
BAX,0.01797272163389584
CPB,0.01922675848128275
HNZ,0.015477195622658256
MCD,0.016650552376276707
SLE,0.01586086263360898
GM,0.015692630653238723
F,0.014813209879380316
CVX,0.013898054589521812
CAT,0.017049564407795006
HAL,0.013502713626423664
AES,0.013965887639729127
WMB,0.015076283361037222
SO,0.02033027770484603
EP,0.01780894668348074
ETR,0.01809734007070128
EXC,0.014262782072846574
AEP,0.017128074685175687
TWX,0.01953267053134846
DIS,0.013636780489640106
CCU,0.018394723724248913
NWS,0.01592940781701414
CBS,0.013675212277386975
CMCSA,0.015516133061672158
AA,0.015786556650040407
HON,0.015519206926026135
RTN,0.016998224126639816
MMM,0.015093335256349035
HD,0.016736110874996823
ROK,0.015621273229765125
IP,0.018774093430007847
TGT,0.01687815378069714
ATI,0.01440033198424606
NSC,0.014414412120081344
WY,0.015777310080497896
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CYD,0.017616986145465946
CEO,0.018365453332230254
HNP,0.014821376553514645
ZNH,0.015544840330063573
SHI,0.01828003962976417
JOBS,0.014572414576284604
CHNR,0.015214735864599484
LFC,0.01686112078233954
XIN,0.014622779477326856
CEA,0.01380007919211552
CHA,0.015683967825886224
ASX,0.014836582332455958
CHT,0.014990833130288263
TSM,0.01938618028783457
HIMX,0.015774430824175817
UMC,0.01901956773188716
SPIL,0.016060066509680712
SIMO,0.01784074402726184
GIGM,0.015954432014577538
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毕业设计-股票价格预测-python 股票价格预测是一个复杂的问题,通常需要使用统计学、机器学习和时间序列分析等技术。在Python中,有许多库可以用于股票价格预测,例如numpy、pandas用于数据处理,statsmodels用于统计分析,sklearn用于机器学习,以及tensorflow或keras用于深度学习。 以下是一个简单的股票价格预测的Python代码示例,该示例使用了pandas和statsmodels库来处理数据和进行线性回归分析:请注意,这个示例使用了线性回归模型,它假设股票价格与日期之间的关系是线性的。然而,股票价格通常受到多种因素的影响,包括市场情绪、经济指标、公司业绩等,因此使用更复杂的模型(如ARIMA、LSTM等)可能更准确。 此外,股票市场是高度复杂的,且存在很多不确定性,因此任何预测都应谨慎对待。
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毕业设计-股票价格预测-python (1713个子文件)
2-News-Stream-of-GS 462KB
AA 131KB
AAL 131KB
AAPL 131KB
ABT 131KB
ADBE 131KB
ADS 131KB
AEP 131KB
AES 131KB
AIG 131KB
ALL 131KB
AMGN 131KB
AMZN 131KB
APA 131KB
ASX 131KB
ATI 131KB
AVP 131KB
AXP 131KB
BA 131KB
BABA 67KB
BAC 131KB
BAX 131KB
BIDU 131KB
BK 131KB
BMY 131KB
C 131KB
CAT 131KB
CBS 131KB
CCU 131KB
CEA 131KB
CEO 131KB
CHA 131KB
CHNR 131KB
CHT 131KB
CI 131KB
CL 131KB
CMCSA 131KB
COF 131KB
COP 131KB
COV 131KB
CPB 131KB
CSCO 131KB
featuresF.csv 608KB
featuresCOV.csv 607KB
featuresGM.csv 602KB
featuresT.csv 600KB
featuresEBAY.csv 600KB
featuresPFE.csv 599KB
featuresVOD.csv 598KB
featuresBAC.csv 596KB
featuresHPQ.csv 595KB
featuresUTSI.csv 595KB
featuresVZ.csv 594KB
featuresKO.csv 594KB
featuresMRK.csv 594KB
featuresBAX.csv 593KB
featuresEXC.csv 593KB
featuresCMCSA.csv 593KB
featuresWY.csv 592KB
featuresORCL.csv 592KB
featuresTM.csv 592KB
featuresBA.csv 592KB
featuresGE.csv 592KB
featuresEDU.csv 592KB
featuresCBS.csv 591KB
featuresBIDU.csv 591KB
featuresUMC.csv 591KB
featuresSO.csv 591KB
featuresCVX.csv 590KB
featuresUPS.csv 590KB
featuresHIMX.csv 590KB
featuresGS.csv 590KB
featuresAAPL.csv 590KB
featuresAA.csv 590KB
featuresLFC.csv 589KB
featuresWMT.csv 589KB
featuresINTC.csv 589KB
featuresAES.csv 588KB
featuresCSCO.csv 588KB
featuresTGT.csv 588KB
featuresAMGN.csv 588KB
featuresXRX.csv 588KB
featuresMSFT.csv 588KB
featuresTSM.csv 588KB
featuresAAL.csv 587KB
featuresIBM.csv 587KB
featuresERIC.csv 587KB
featuresJOBS.csv 587KB
featuresHMC.csv 587KB
featuresMMM.csv 587KB
featuresMET.csv 586KB
featuresNOK.csv 586KB
featuresPG.csv 586KB
featuresC.csv 586KB
featuresSPIL.csv 586KB
featuresFDX.csv 585KB
featuresCHA.csv 585KB
featuresJNJ.csv 585KB
featuresJPM.csv 585KB
featuresHSY.csv 585KB
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