多因子系列报告：量价因子有效性与相关性问题探讨

1、1. 62. 62.1.62.2.73. 83.1.83.2.94. 18 HYPERLINK l _TOC_250002 Alpha18 HYPERLINK l _TOC_250001 Alpha19 HYPERLINK l _TOC_250000 Alpha205. 221Alpha . 72Alpha003113Alpha003114Alpha013115Alpha013116Alpha015127Alpha015128Alpha016129Alpha0161210Alpha0361211Alpha0361212Alpha0401213Alpha0401214Alpha0421315Al

2、pha0421316Alpha0441317Alpha0441318Alpha0501319Alpha0501320Alpha0551321Alpha0551322Alpha0661423Alpha0661424Alpha0941425Alpha0941426Alpha0031527Alpha0031528Alpha0131629Alpha0131630Alpha0151631Alpha0151632Alpha0161633Alpha0161634Alpha0361635Alpha0361636Alpha0401737Alpha0401738Alpha0421739Alpha0421740Al

3、pha0441741Alpha0441742Alpha0501743Alpha0501744Alpha0551845Alpha0551846Alpha0941847Alpha0941848AlphaVIF . 1949. 2150. 221. 82. 93alpha. 94alpha. 145VIF196. 197Alpha. 208AlphaVIF209. 2010. 211. WorldQuant Alpha 2. 2.1. openclosehighlowvolumereturnvwapadvd AlphaAlpharankcorrelationsign(x):x01x10 VIF 12

4、VIF5alpha013 alpha015 alpha01610alpha050VIF7VIF = 1 25VIF003013015016036040042044050055094VIF1.7316.3711.9817.936.893.131.052.6913.142.052.7848AlphaVIF17.916.412.013.16.93.11.72.72.81.02.020.015.0VIF10.05.00.0 WindAlphaAlpha11BarraVIFAlphaPearson 6sizebetaCAPM historical_sigmalCAPM one_month_share_t

5、urnover21momentum504 er historical_sigm20%alphaAlphaone_month_share_turnov al betamomentumsizeVIFalpha7Alpha one_ month_share_turnoverhistorical_sigmabetamomentumsizealpha003-0.14-0.03-0.050.030.06alpha013-0.11-0.05-0.040.040.12alpha015-0.090.06-0.160.060.03alpha016-0.13-0.05-0.060.040.15alpha036-0.

6、030.01-0.030.010.05alpha040-0.18-0.06-0.15-0.050.05alpha0420.03-0.01-0.04-0.060.02alpha044-0.080.00-0.040.060.05alpha050-0.11-0.01-0.060.080.08alpha055-0.07-0.01-0.040.050.02alpha094-0.12-0.15-0.07-0.15-0.08Alpha 11Alpha VIF 58AlphaVIF003013015016036040042044050055094VIF1.212.893.652.993.741.881.021

7、.474.221.311.94Alpha11G5G5/G15alpha003alpha013alpha015 alpha01698%alpha044 alpha050 alpha055alpha003 alpha013 alpha015 alpha016alpha044alpha050alpha055alpha015alpha016 0.996 9alpha003alpha013alpha015alpha016alpha036alpha040alpha042alpha044alpha050alpha055alpha094alpha031.0000.9900.9920.9940.9800.990

8、0.9690.9920.9950.9920.959alpha130.9901.0000.9830.9860.9710.9920.9650.9860.9860.9850.948alpha150.9920.9831.0000.9960.9740.9860.9670.9930.9930.9920.957alpha160.9940.9860.9961.0000.9770.9870.9660.9950.9930.9920.957alpha360.9800.9710.9740.9771.0000.9680.9590.9740.9790.9800.963alpha400.9900.9920.9860.987

9、0.9681.0000.9700.9870.9890.9850.955alpha420.9690.9650.9670.9660.9590.9701.0000.9620.9660.9690.957alpha440.9920.9860.9930.9950.9740.9870.9621.0000.9910.9910.953alpha500.9950.9860.9930.9930.9790.9890.9660.9911.0000.9940.961alpha550.9920.9850.9920.9920.9800.9850.9690.9910.9941.0000.960alpha940.9590.948

10、0.9570.9570.9630.9550.9570.9530.9610.9601.000Wind49Windalpha003 013 015 016044 050 0550.5alpha 015alpha0160.69910alpha003alpha013alpha015alpha016alpha036alpha040alpha042alpha044alpha050alpha055alpha094alpha031.0000.6590.4260.6150.2160.5650.1410.6340.6740.5460.164alpha130.6591.0000.2690.4510.0770.717

11、0.1380.5180.4380.3230.077alpha150.4260.2691.0000.6990.0960.277-0.140.6360.6720.4980.051alpha160.6150.4510.6991.0000.1970.5120.2050.7680.7200.5990.289alpha360.2160.0770.0960.1971.000-0.020.1380.2270.1940.3010.111alpha400.5650.7170.2770.512-0.021.0000.4820.4600.4950.3630.472alpha420.1410.138-0.1390.20

12、50.1380.4821.0000.0700.0510.1060.461alpha440.6340.5180.6360.7680.2270.4600.0701.0000.7010.6760.148alpha500.6740.4380.6720.7200.1940.4950.0510.7011.0000.6980.242alpha550.5460.3230.4980.5990.3010.3630.1060.6760.6981.0000.250alpha940.1640.0770.0510.2890.1110.4720.4610.1480.2420.2501.000Wind50WindAlpha5

13、. AlphaRank_IC201722 11 Alpha Alphaalpha003: 1 correlation rank open , rank volume , 10 alpha004:(1 Ts_Rank(rank low , 9)alpha006:(1 correlation(open, volume, 10)alpha013:(1 rank(covariance(rank(close), rank(volume),5)alpha014:(1 rank(delta(returns,3) correlation(open, volume, 10)alpha015:(1 sum(ran

14、k(correlation(rank(high),rank(volume),3),3)alpha016:(1 rank(covariance(rank(high), rank(volume),5)alpha024:(delta(sum(close,100)/100),100)/delay(close,100)0.05)|(delta(sum(close,100)/100),100)/delay(close,100)=0.05)?(-1*(close-ts_min (close,100):(-1*delta(close,3)alpha026:(1 ts_max(correlation(ts_ra

15、nk(volume, 5), ts_rank(high,5),5),3)alpha027:(0.5 (), (),6),2)/2.0)?(1 1): 1)alpha028:scale(correlation(adv20,low, 5) + (high + low)/2) close)alpha031:(rank(rank(rank(decay_linear(1 rank(rank(delta(close, 10),10) + rank(1 delta(close, 3)+sign(scale(correlation(adv20,low, 12)alpha032:(scale(sum(close

16、, 7)/7) close) + (20 scale(correlation(vwap, delay(close, 5),230)alpha036:(2.21 rank(correlation(close open), delay(volume, 1),15)+ (0.7 rank(open close)+(0.73 rank(Ts_Rank(delay(1 returns),6),5) + rank(abs(correlation(vwap, adv20,6)+(0.6 rank(sum(close, 200)/200) open) (close open)alpha040:(1 rank(

17、stddev(high,10) correlation(high, volume, 10)alpha042:(rank(vwap close)/rank(vwap + close)alpha043:(ts_rank(volume/adv20),20) ts_rank(1 delta(close, 7),8)alpha044:(1 correlation(high, rank(volume),5)alpha047:(rank(1/close)*volume)/adv20)*(high*rank(high-close)/(sum(high,5)/5)-rank(vwap-delay(vwap,5)alpha050:(1 ts_max(rank(correlation(rank(volume), rank(vwap),5),5)alpha055:(-1*correlation(rank(close-ts_min (low,12)/(ts_max(high,12)-ts_min(low,12),rank(volume),6)alpha066:(rank(de