Factors that influence the volatility of stock prices
Role, importance and place of volatility in risk management. Features and characteristics of volatility risk management using financial instruments, the prices of which depend on the volatility of the financial asset. Building a risk management system.
| Рубрика | Финансы, деньги и налоги |
| Вид | дипломная работа |
| Язык | английский |
| Дата добавления | 09.08.2018 |
| Размер файла | 773,2 K |
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0
0
0
-9.6885141310744e-05
0
BAMLEMFSFCRPIEY
0.000361918763827714
0
0.000544896115346618
0
0
0.000259008874051788
0
0
0
0.000361918763827714
0
BAMLEMNSNFCRPIOAS
0
0
-0.000132716605407946
0
0
0
0
0
0
0
0
BAMLEMPBPUBSICRPIEY
-0.00227826905052291
0
-0.00232005269016468
0
-0.00192840578054462
-0.00225347110492975
0
0
0
-0.00227826905052291
-0.00192840578054462
BAMLEMPUPUBSLCRPIUSEY
-0.000488897079330122
0
-0.000600911834661386
0
-2.55384630136611e-05
-0.000558470968525112
0
0
0
-0.000488897079330122
-2.55384630136611e-05
BAMLEMPUPUBSLCRPIUSOAS
-0.000296195072243656
0
-0.000422523816073251
0
0
-0.000191222698925375
0
0
0
-0.000296195072243656
0
BAMLCC1A013YTRIV
-0.0200843774004196
-0.00121947368557261
-0.022056980111355
-0.00121947368557261
-0.0144317350394391
-0.0191517159671691
-0.00222388724467212
-0.00341871432982573
-0.00341871432982573
-0.0200843774004196
-0.0144317350394391
BAMLCC0A1AAATRIV
0.00172636471293165
0
0.00203449242760604
0
0.00123150864880952
0.00167330876248274
0
0
0
0.00172636471293165
0.00123150864880952
BAMLEMCLLCRPIUSTRIV
-0.00865244536391259
-0.00849699076634026
-0.0088959466881778
-0.00849699076634026
-0.00731014786585193
-0.00818014848162527
-0.00847608527055962
-0.00856821587402383
-0.00856821587402383
-0.00865244536391259
-0.00731014786585193
BAMLHYH0A1BBTRIV
0
0
-7.41507504491133e-05
0
0
0
0
0
0
0
0
BAMLHYH0A2BTRIV
-0.00136752067549077
-0.00260969717058347
-0.00141637153631841
-0.00260969717058347
-0.000497603449932663
-0.00123694507605729
-0.00240506868676015
-0.00215533307179745
-0.00215533307179745
-0.00136752067549077
-0.000497603449932663
BAMLHYH0A3CMTRIV
-0.000759339343491833
0
-0.000902992443111632
0
-0.00021309298938406
-0.000684296451830143
0
0
0
-0.000759339343491833
-0.00021309298938406
BAMLH0A0HYM2SYTW
-0.00170337979836019
0
-0.00244836288651441
0
0
-0.00130247206814601
0
0
0
-0.00170337979836019
0
THREEFFTP10
8.34650637431828e-06
0
3.9454176205885e-05
0
0
0
0
0
0
8.34650637431828e-06
0
DJFUELUSGULF
6.64410393713264e-05
0
0.000167410700588653
0
0
3.66517996800326e-05
0
0
0
6.64410393713264e-05
0
DEXMAUS
-0.00115854916764474
0
-0.0012945056828692
0
-0.000679177317151372
-0.00107505054250299
0
0
0
-0.00115854916764474
-0.000679177317151372
DHOILNYH
0
0
-7.4376531810519e-05
0
0
0
0
0
0
0
0
DEXNOUS
-0.0006049603475446
0
-0.000635947452990873
0
-0.000481041974136546
-0.000580840267088675
0
0
0
-0.0006049603475446
-0.000481041974136546
DPROPANEMBTX
-6.63013862445946e-05
0
-5.90086743182855e-05
0
-7.49984336042526e-06
-5.96193145480095e-05
0
0
0
-6.63013862445946e-05
-7.49984336042526e-06
RU1000VPR
0
-0.00022006320949815
0
-0.00022006320949815
0
0
-0.000177527105857405
-9.1283931347197e-05
-9.1283931347197e-05
0
0
DEXSIUS
-0.000483783136760737
0
-0.000809111440107033
0
0
-0.000322018209528669
0
0
0
-0.000483783136760737
0
DEXSFUS
-0.000283505831624546
0
-0.000390223696671819
0
-2.6858132681471e-05
-0.000239813336618076
0
0
0
-0.000283505831624546
-2.6858132681471e-05
DEXSLUS
0
0
-1.82723227484529e-05
0
0
0
0
0
0
0
0
DEXSDUS
-0.000890089417322695
0
-0.000874866939127778
0
-0.00109433321850472
-0.000941056836293635
-0.000129339142874462
-0.000453385697360113
-0.000453385697360113
-0.000890089417322695
-0.00109433321850472
DTWEXO
0.00205148094355871
0
0.0029818130523023
0
0
0.00160473493345217
0
0
0
0.00205148094355871
0
DEXUSNZ
0.000259286313012578
0
0.000386347550586249
0
0
0.000189081130911396
0
0
0
0.000259286313012578
0
DEXVZUS
-2.25586148135583e-05
0
-3.42311827050877e-05
0
0
-1.80356507356447e-05
0
0
0
-2.25586148135583e-05
0
WILLREITPR
0
0
0.000112029278090918
0
0.000109747303845332
0
0
0
0
0
0.000109747303845332
WILLRESIPR
0.0011896703916659
0
0.00123931996842874
0
0.00055119120332238
0.0010910860134257
0
0
0
0.0011896703916659
0.00055119120332238
BAMLEM1RAAA2ALCRPIUSTRIV
-0.00585594280661499
0
-0.00593550676105152
0
-0.00390837268025232
-0.00625565765870631
0
0
0
-0.00585594280661499
-0.00390837268025232
RU3000VPR
-0.000570412940527483
0
-0.00104451868517693
0
-6.1611691023504e-05
-0.000455222764955695
0
0
0
-0.000570412940527483
-6.1611691023504e-05
WILLLRGCAPVAL
-0.0020355060602823
-0.00137783753701064
-0.00247867153302924
-0.00137783753701064
-0.00206511131855582
-0.00188039839894961
-0.00149023238984755
-0.00160889447129163
-0.00160889447129163
-0.0020355060602823
-0.00206511131855582
RTOP200GTR
0
0
4.37734471180471e-05
0
0
0
0
0
0
0
0
WILLLRGCAPGRPR
0.000163761786083982
0
0.000716690575433139
0
0
0
0
0
0
0.000163761786083982
0
CNYJPY
0.000237384315044761
0
0.000349381274098611
0
0
0.000168300098359331
0
0
0
0.000237384315044761
0
CNYUSD
-0.000273004809493344
0
-0.00030306201628177
0
0
-0.000224448243410614
0
0
0
-0.000273004809493344
0
EURAUD
0.000530187012357987
0
0.000588880759666018
0
0.00026703212919622
0.000488489045657005
3.57852009155903e-05
6.2834623475046e-05
6.2834623475046e-05
0.000530187012357987
0.00026703212919622
USDCAD
7.94839294115927e-06
0
0.000285423497964061
0
0
0
0
0
0
7.94839294115927e-06
0
USDMXN
0.000475780515661158
0
0.000429420274621013
0
0.00054894886163099
0.000501057738790309
0
6.9850390018345e-05
6.9850390018345e-05
0.000475780515661158
0.00054894886163099
USDRUB
-0.000136168799293645
0
-0.000222934002098406
0
0
-9.72865105297988e-05
0
0
0
-0.000136168799293645
0
DCOILWTICO
-3.29603799035906e-05
0
-6.16265106380164e-05
0
0
-1.22028988147214e-05
0
0
0
-3.29603799035906e-05
0
RPONTSYD
5.49439662264301e-07
0
2.75914240383233e-06
0
0
0
0
0
0
5.49439662264301e-07
0
GOLDPMGBD230NLBM
0
0
5.52875662640593e-05
0
0
0
0
0
0
0
0
BAMLH0A0HYM2
0.00100018807314369
0
0.0014489612738382
0
0.000261426366103479
0.000791144814420889
0
0
0
0.00100018807314369
0.000261426366103479
DJTA
0.00314295963675814
0
0.00390397034682327
0
0
0.00267466370846516
0
0
0
0.00314295963675814
0
3) Variable description:
volatility risk management
|
Variable |
Date of publication |
Notation |
Type |
|
|
10-Year 0-1/4% Treasury Inflation-Indexed Note |
4/10/18 |
DTP10J25 |
Treasury securities |
|
|
10-Year 1-1/8% Treasury Inflation-Indexed Note |
4/10/18 |
DTP10J21 |
Treasury securities |
|
|
12-Month London Interbank Offered Rate (LIBOR), British pound |
4/10/18 |
GBP12MD156N |
LIBOR |
|
|
12-Month London Interbank Offered Rate (LIBOR), Euro |
4/10/18 |
EUR12MD156N |
LIBOR |
|
|
12-Month London Interbank Offered Rate (LIBOR), Japanese Yene |
4/10/18 |
JPY12MD156N |
LIBOR |
|
|
12-Month London Interbank Offered Rate (LIBOR), Swiss Frank |
4/10/18 |
CHF12MD156N |
LIBOR |
|
|
1-Month AA Financial Commercial Paper Rate |
4/9/18 |
DCPF1M |
Commercial paper |
|
|
1-Month AA Nonfinancial Commercial Paper Rate |
4/9/18 |
DCPN30 |
Commercial paper |
|
|
1-Month Certificate of Deposit: Secondary Market Rate (DISCONTINUED) |
7/1/13 |
DCD1M |
Securities |
|
|
1-Month Eurodollar Deposit Rate (London) (DISCONTINUED) |
10/11/16 |
DED1 |
Securities |
|
|
1-Month London Interbank Offered Rate (LIBOR), Australian dollar |
3/11/15 |
AUD1MTD156N |
LIBOR |
|
|
1-Month London Interbank Offered Rate (LIBOR), British pound |
4/10/18 |
GBP1MTD156N |
LIBOR |
|
|
1-Month London Interbank Offered Rate (LIBOR), Canadian dollar |
3/11/15 |
CAD1MTD156N |
LIBOR |
|
|
1-Month London Interbank Offered Rate (LIBOR), Euro |
4/10/18 |
EUR1MTD156N |
LIBOR |
|
|
1-Month London Interbank Offered Rate (LIBOR), Japanese Yen |
4/10/18 |
JPY1MTD156N |
LIBOR |
|
|
1-Month London Interbank Offered Rate (LIBOR), Swiss franc |
4/10/18 |
CHF1MTD156N |
LIBOR |
|
|
1-Week London Interbank Offered Rate (LIBOR), US dollar |
4/10/18 |
USD1WKD156N |
LIBOR |
|
|
1-Year Swap Rate (DISCONTINUED) |
10/31/16 |
DSWP1 |
Securities |
|
|
1-Year Treasury Bill: Secondary Market Rate (DISCONTINUED) |
8/24/01 |
DTB1 |
Treasury securities |
|
|
1-Year Treasury Constant Maturity Minus Federal Funds Rate |
4/9/18 |
T1YFF |
Treasury securities |
|
|
20-Year Treasury Inflation-Indexed Security |
4/9/18 |
DFII20 |
Treasury securities |
|
|
2-Month London Interbank Offered Rate (LIBOR), US dollar |
4/10/18 |
USD2MTD156N |
LIBOR |
|
|
2-Week London Interbank Offered Rate (LIBOR), US dollar |
6/7/13 |
USD2WKD156N |
LIBOR |
|
|
2-Year Swap Rate (DISCONTINUED) |
10/31/16 |
DSWP2 |
Securities |
|
|
30-Day A2/P2 Nonfinancial Commercial Paper Interest Rate |
4/9/18 |
RIFSPPNA2P2D30NB |
Commercial paper |
|
|
30-Day AA Asset-backed Commercial Paper Interest Rate |
4/9/18 |
RIFSPPAAAD30NB |
Commercial paper |
|
|
30-Day AA Financial Commercial Paper Interest Rate |
4/9/18 |
RIFSPPFAAD30NB |
Commercial paper |
|
|
30-Day AA Nonfinancial Commercial Paper Interest Rate |
4/9/18 |
RIFSPPNAAD30NB |
Commercial paper |
|
|
30-Year 2-1/8% Treasury Inflation-Indexed Bond |
4/10/18 |
DTP30F41 |
Treasury securities |
|
|
30-Year 3-5/8% Treasury Inflation-Indexed Bond |
4/10/18 |
DTP30A28 |
Treasury securities |
|
|
30-Year Swap Rate (DISCONTINUED) |
10/31/16 |
DSWP30 |
Securities |
|
|
3-Month Bankers Acceptance Rate (DISCONTINUED) |
7/3/00 |
DBKAC |
Securities |
|
|
3-Month Certificate of Deposit: Secondary Market Rate (DISCONTINUED) |
7/1/13 |
DCD90 |
Securities |
|
|
3-Month Commercial Paper Minus Federal Funds Rate |
4/9/18 |
CPFF |
Commercial paper |
|
|
3-Month Eurodollar Deposit Rate (London) (DISCONTINUED) |
10/11/16 |
DED3 |
Securities |
|
|
3-Month London Interbank Offered Rate (LIBOR), Australian dollar |
3/11/15 |
AUD3MTD156N |
LIBOR |
|
|
3-Month London Interbank Offered Rate (LIBOR), Canadian dollar |
3/11/15 |
CAD3MTD156N |
LIBOR |
|
|
3-Month London Interbank Offered Rate (LIBOR), Japanese Yen |
4/10/18 |
JPY3MTD156N |
LIBOR |
|
|
3-Month London Interbank Offered Rate (LIBOR), Swiss franc |
4/10/18 |
CHF3MTD156N |
LIBOR |
|
|
3-Month Treasury Constant Maturity Minus Federal Funds Rate |
4/9/18 |
T3MFF |
Treasury securities |
|
|
3-Year Swap Rate (DISCONTINUED) |
10/31/16 |
DSWP3 |
Securities |
|
|
4-Month London Interbank Offered Rate (LIBOR), US dollar |
6/7/13 |
USD4MTD156N |
LIBOR |
|
|
4-Year Swap Rate (DISCONTINUED) |
10/31/16 |
DSWP4 |
Securities |
|
|
5-Year Treasury Constant Maturity Minus Federal Funds Rate |
4/9/18 |
T5YFF |
Treasury securities |
|
|
60-Day A2/P2 Nonfinancial Commercial Paper Interest Rate |
4/9/18 |
RIFSPPNA2P2D60NB |
Commercial paper |
|
|
6-Month Certificate of Deposit: Secondary Market Rate (DISCONTINUED) |
7/1/13 |
DCD6M |
Securities |
|
|
6-Month Eurodollar Deposit Rate (London) (DISCONTINUED) |
10/7/16 |
DED6 |
Securities |
|
|
6-Month London Interbank Offered Rate (LIBOR), British pound |
4/10/18 |
GBP6MTD156N |
LIBOR |
|
|
6-Month London Interbank Offered Rate (LIBOR), Euro |
4/10/18 |
EUR6MTD156N |
LIBOR |
|
|
6-Month London Interbank Offered Rate (LIBOR) , Japanese Yen |
4/10/18 |
JPY6MTD156N |
LIBOR |
|
|
6-Month London Interbank Offered Rate (LIBOR), Swiss franc |
4/10/18 |
CHF6MTD156N |
LIBOR |
|
|
6-Month Treasury Constant Maturity Minus Federal Funds Rate |
4/9/18 |
T6MFF |
Treasury securities |
|
|
7-Day AA Nonfinancial Commercial Paper Interest Rate |
4/6/18 |
RIFSPPNAAD07NB |
Commercial paper |
|
|
7-Year Swap Rate (DISCONTINUED) |
10/31/16 |
DSWP7 |
Securities |
|
|
7-Year Treasury Inflation-Indexed Security |
4/9/18 |
DFII7 |
Treasury securities |
|
|
90-Day A2/P2 Nonfinancial Commercial Paper Interest Rate |
4/6/18 |
RIFSPPNA2P2D90NB |
Commercial paper |
|
|
90-Day AA Asset-backed Commercial Paper Interest Rate |
4/9/18 |
RIFSPPAAAD90NB |
Commercial paper |
|
|
90-Day AA Financial Commercial Paper Interest Rate |
4/9/18 |
RIFSPPFAAD90NB |
Commercial paper |
|
|
90-Day AA Nonfinancial Commercial Paper Interest Rate |
4/9/18 |
RIFSPPNAAD90NB |
Commercial paper |
|
|
9-Month London Interbank Offered Rate (LIBOR), US dollar |
6/7/13 |
USD9MTD156N |
LIBOR |
|
|
CBOE 10-Year Treasury Note Volatility Futures |
4/9/18 |
VXTYN |
Treasury securities |
|
|
CBOE Brazil ETF Volatility Index |
4/9/18 |
VXEWZCLS |
Index |
|
|
CBOE China ETF Volatility Index |
4/9/18 |
VXFXICLS |
Index |
|
|
CBOE Crude Oil ETF Volatility Index |
4/9/18 |
OVXCLS |
Oil and precious metals |
|
|
CBOE DJIA Volatility Index |
4/9/18 |
VXDCLS |
Index |
|
|
CBOE Emerging Markets ETF Volatility Index |
4/9/18 |
VXEEMCLS |
Index |
|
|
CBOE Energy Sector ETF Volatility Index |
4/9/18 |
VXXLECLS |
Index |
|
|
CBOE Equity VIX on Amazon |
4/9/18 |
VXAZNCLS |
Securities |
|
|
CBOE Equity VIX on Apple |
4/9/18 |
VXAPLCLS |
Securities |
|
|
CBOE Equity VIX on Google |
4/9/18 |
VXGOGCLS |
Securities |
|
|
CBOE EuroCurrency ETF Volatility Index |
4/9/18 |
EVZCLS |
Index |
|
|
CBOE Gold ETF Volatility Index |
4/9/18 |
GVZCLS |
Oil and precious metals |
|
|
CBOE NASDAQ 100 Volatility Index |
4/9/18 |
VXNCLS |
Index |
|
|
CBOE Russell 2000 Volatility Index |
4/9/18 |
RVXCLS |
Index |
|
|
CBOE Silver ETF Volatility Index |
4/9/18 |
VXSLVCLS |
Oil and precious metals |
|
|
CBOE S&P 100 Volatility Index: VXO |
4/9/18 |
VXOCLS |
Index |
|
|
CBOE S&P 500 3-Month Volatility Index |
4/9/18 |
VXVCLS |
Index |
|
|
Cleveland Financial Stress Index (DISCONTINUED) |
5/6/16 |
CFSI |
Index |
|
|
Contributions to the Cleveland Financial Stress Index: Commercial Paper minus T-Bill Spread (DISCONTINUED) |
5/6/16 |
CPTBSD678FRBCLE |
Commercial paper |
|
|
Contributions to the Cleveland Financial Stress Index: Credit Markets (DISCONTINUED) |
5/6/16 |
CMRKTSD678FRBCLE |
Index |
|
|
Contributions to the Cleveland Financial Stress Index: Interbank Liquidity Spread (DISCONTINUED) |
5/6/16 |
IBLSD678FRBCLE |
Index |
|
|
Contributions to the Cleveland Financial Stress Index: Treasury Yield Curve Spread (DISCONTINUED) |
5/6/16 |
TYCSD678FRBCLE |
Treasury securities |
|
|
Conventional Gasoline Prices: New York Harbor |
4/4/18 |
DGASNYH |
Oil and precious metals |
|
|
Conventional Gasoline Prices: U.S. Gulf Coast |
4/4/18 |
DGASUSGULF |
Oil and precious metals |
|
|
Denmark / U.S. Foreign Exchange Rate |
4/9/18 |
DEXDNUS |
Exchange rate |
|
|
Discount Rate (DISCONTINUED) |
2/7/03 |
DDISCRT |
Key factors |
|
|
Dow Jones Composite Average |
4/9/18 |
DJCA |
Index |
|
|
Dow Jones Utility Average |
4/9/18 |
DJUA |
Index |
|
|
Effective Federal Funds Rate: 1st Percentile |
4/10/18 |
EFFR1 |
Key factors |
|
|
Effective Federal Funds Rate: 99th Percentile |
4/10/18 |
EFFR99 |
Key factors |
|
|
Effective Federal Funds Volume |
4/10/18 |
EFFRVOL |
Key factors |
|
|
Equity Market-related Economic Uncertainty Index |
4/9/18 |
WLEMUINDXD |
Index |
|
|
Fitted Instantaneous Forward Rate 1 Year Hence |
1/18/18 |
THREEFF1 |
Securities |
|
|
Fitted Instantaneous Forward Rate 4 Years Hence |
1/18/18 |
THREEFF4 |
Securities |
|
|
Fitted Yield on a 10 Year Zero Coupon Bond |
1/18/18 |
THREEFY10 |
Securities |
|
|
Fitted Yield on a 1 Year Zero Coupon Bond |
1/18/18 |
THREEFY1 |
Securities |
|
|
Fitted Yield on a 2 Year Zero Coupon Bond |
1/18/18 |
THREEFY2 |
Securities |
|
|
Fitted Yield on a 3 Year Zero Coupon Bond |
1/18/18 |
THREEFY3 |
Securities |
|
|
Fitted Yield on a 5 Year Zero Coupon Bond |
1/18/18 |
THREEFY5 |
Securities |
|
|
Gold Fixing Price 3:00 P.M. (London time) in London Bullion Market |
4/9/18 |
GOLDPMGBD229NLBM |
Oil and precious metals |
|
|
Hong Kong / U.S. Foreign Exchange Rate |
4/9/18 |
DEXHKUS |
Exchange rate |
|
|
ICE BofAML AAA-A US Emerging Markets Liquid Corporate Plus Sub-Index Effective Yield |
4/9/18 |
BAMLEM1RAAA2ALCRPIUSEY |
Index |
|
|
ICE BofAML Asia Emerging Markets Corporate Plus Sub-Index Effective Yield |
4/9/18 |
BAMLEMRACRPIASIAEY |
Index |
|
|
ICE BofAML Asia Emerging Markets Corporate Plus Sub-Index Option-Adjusted Spread |
4/9/18 |
BAMLEMRACRPIASIAOAS |
Index |
|
|
ICE BofAML Asia Emerging Markets Corporate Plus Sub-Index Total Return Index Value |
4/9/18 |
BAMLEMRACRPIASIATRIV |
Index |
|
|
ICE BofAML Asia US Emerging Markets Liquid Corporate Plus Sub-Index Total Return Index Value |
4/9/18 |
BAMLEMALLCRPIASIAUSTRIV |
Index |
|
|
ICE BofAML B and Lower Emerging Markets Corporate Plus Sub-Index Effective Yield |
4/9/18 |
BAMLEM4BRRBLCRPIEY |
Index |
|
|
ICE BofAML B and Lower Emerging Markets Corporate Plus Sub-Index Option-Adjusted Spread |
4/9/18 |
BAMLEM4BRRBLCRPIOAS |
Index |
|
|
ICE BofAML B and Lower US Emerging Markets Liquid Corporate Plus Sub-Index Effective Yield |
4/9/18 |
BAMLEM4RBLLCRPIUSEY |
Index |
|
|
ICE BofAML BBB Emerging Markets Corporate Plus Sub-Index Effective Yield |
4/9/18 |
BAMLEM2BRRBBBCRPIEY |
Index |
|
|
ICE BofAML BBB Emerging Markets Corporate Plus Sub-Index Option-Adjusted Spread |
4/9/18 |
BAMLEM2BRRBBBCRPIOAS |
Index |
|
|
ICE BofAML BBB US Emerging Markets Liquid Corporate Plus Sub-Index Option-Adjusted Spread |
4/9/18 |
BAMLEM2RBBBLCRPIUSOAS |
Index |
|
|
ICE BofAML BB Emerging Markets Corporate Plus Sub-Index Option-Adjusted Spread |
4/9/18 |
BAMLEM3BRRBBCRPIOAS |
Index |
|
|
ICE BofAML Emerging Markets Corporate Plus Index Effective Yield |
4/9/18 |
BAMLEMCBPIEY |
Index |
|
|
ICE BofAML Emerging Markets Corporate Plus Index Total Return Index Value |
4/9/18 |
BAMLEMCBPITRIV |
Index |
|
|
ICE BofAML Euro High Yield Index Semi-Annual Yield to Worst |
4/9/18 |
BAMLHE00EHYISYTW |
Index |
|
|
ICE BofAML Euro High Yield Index Total Return Index Value |
4/9/18 |
BAMLHE00EHYITRIV |
Index |
|
|
ICE BofAML Europe |
4/9/18 |
BAMLEMRECRPIEMEAOAS |
Index |
|
|
ICE BofAML Financial Emerging Markets Corporate Plus Sub-Index Effective Yield |
4/9/18 |
BAMLEMFSFCRPIEY |
Index |
|
|
ICE BofAML Financial Emerging Markets Corporate Plus Sub-Index Option-Adjusted Spread |
4/9/18 |
BAMLEMFSFCRPIOAS |
Index |
|
|
ICE BofAML High Grade Emerging Markets Corporate Plus Sub-Index Option-Adjusted Spread |
4/9/18 |
BAMLEMIBHGCRPIOAS |
Index |
|
|
ICE BofAML High Yield Emerging Markets Corporate Plus Sub-Index Effective Yield |
4/9/18 |
BAMLEMHBHYCRPIEY |
Index |
|
|
ICE BofAML High Yield Emerging Markets Corporate Plus Sub-Index Option-Adjusted Spread |
4/9/18 |
BAMLEMHBHYCRPIOAS |
Index |
|
|
ICE BofAML High Yield US Emerging Markets Liquid Corporate Plus Sub-Index Option-Adjusted Spread |
4/9/18 |
BAMLEMHYHYLCRPIUSOAS |
Index |
|
|
ICE BofAML Latin America Emerging Markets Corporate Plus Sub-Index Effective Yield |
4/9/18 |
BAMLEMRLCRPILAEY |
Index |
|
|
ICE BofAML Latin America Emerging Markets Corporate Plus Sub-Index Option-Adjusted Spread |
4/9/18 |
BAMLEMRLCRPILAOAS |
Index |
|
|
ICE BofAML Non-Financial Emerging Markets Corporate Plus Sub-Index Option-Adjusted Spread |
4/9/18 |
BAMLEMNSNFCRPIOAS |
Index |
|
|
ICE BofAML Public Sector Issuers Emerging Markets Corporate Plus Sub-Index Effective Yield |
4/9/18 |
BAMLEMPBPUBSICRPIEY |
Index |
|
|
ICE BofAML Public Sector Issuers US Emerging Markets Liquid Corporate Plus Sub-Index Effective Yield |
4/9/18 |
BAMLEMPUPUBSLCRPIUSEY |
Index |
|
|
ICE BofAML Public Sector Issuers US Emerging Markets Liquid Corporate Plus Sub-Index Option-Adjusted Spread |
4/9/18 |
BAMLEMPUPUBSLCRPIUSOAS |
Index |
|
|
ICE BofAML US Corp 10-15yr Total Return Index Value |
4/9/18 |
BAMLCC7A01015YTRIV |
Index |
|
|
ICE BofAML US Corp 1-3yr Total Return Index Value |
4/9/18 |
BAMLCC1A013YTRIV |
Index |
|
|
ICE BofAML US Corp 15+yr Total Return Index Value |
4/9/18 |
BAMLCC8A015PYTRIV |
Index |
|
|
ICE BofAML US Corp 3-5yr Total Return Index Value |
4/9/18 |
BAMLCC2A035YTRIV |
Index |
|
|
ICE BofAML US Corp 5-7yr Total Return Index Value |
4/9/18 |
BAMLCC3A057YTRIV |
Index |
|
|
ICE BofAML US Corp AAA Total Return Index Value |
4/9/18 |
BAMLCC0A1AAATRIV |
Index |
|
|
ICE BofAML US Corp AA Total Return Index Value |
4/9/18 |
BAMLCC0A2AATRIV |
Index |
|
|
ICE BofAML US Corp A Total Return Index Value |
4/9/18 |
BAMLCC0A3ATRIV |
Index |
|
|
ICE BofAML US Corp BBB Total Return Index Value |
4/9/18 |
BAMLCC0A4BBBTRIV |
Index |
|
|
ICE BofAML US Corporate 10-15 Year Effective Yield |
4/9/18 |
BAMLC7A0C1015YEY |
Securities |
|
|
ICE BofAML US Corporate 10-15 Year Option-Adjusted Spread |
4/9/18 |
BAMLC7A0C1015Y |
Securities |
|
|
ICE BofAML US Corporate 1-3 Year Effective Yield |
4/9/18 |
BAMLC1A0C13YEY |
Securities |
|
|
ICE BofAML US Corporate 1-3 Year Option-Adjusted Spread |
4/9/18 |
BAMLC1A0C13Y |
Securities |
|
|
ICE BofAML US Corporate 15+ Year Effective Yield |
4/9/18 |
BAMLC8A0C15PYEY |
Securities |
|
|
ICE BofAML US Corporate 15+ Year Option-Adjusted Spread |
4/9/18 |
BAMLC8A0C15PY |
Securities |
|
|
ICE BofAML US Corporate 3-5 Year Effective Yield |
4/9/18 |
BAMLC2A0C35YEY |
Securities |
|
|
ICE BofAML US Corporate 3-5 Year Option-Adjusted Spread |
4/9/18 |
BAMLC2A0C35Y |
Securities |
|
|
ICE BofAML US Corporate 5-7 Year Effective Yield |
4/9/18 |
BAMLC3A0C57YEY |
Securities |
|
|
ICE BofAML US Corporate 5-7 Year Option-Adjusted Spread |
4/9/18 |
BAMLC3A0C57Y |
Securities |
|
|
ICE BofAML US Corporate 7-10 Year Option-Adjusted Spread |
4/9/18 |
BAMLC4A0C710Y |
Securities |
|
|
ICE BofAML US Corporate 7-10yr Total Return Index Value |
4/9/18 |
BAMLCC4A0710YTRIV |
Index |
|
|
ICE BofAML US Corporate A Effective Yield |
4/9/18 |
BAMLC0A3CAEY |
Securities |
|
|
ICE BofAML US Corporate BBB Semi-Annual Yield to Worst |
4/9/18 |
BAMLC0A4CBBBSYTW |
Securities |
|
|
ICE BofAML US Corporate Master Effective Yield |
4/9/18 |
BAMLC0A0CMEY |
Securities |
|
|
ICE BofAML US Emerging Markets Liquid Corporate Plus Index Total Return Index Value |
4/9/18 |
BAMLEMCLLCRPIUSTRIV |
Index |
|
|
ICE BofAML US High Yield BB Semi-Annual Yield to Worst |
4/9/18 |
BAMLH0A1HYBBSYTW |
Securities |
|
|
ICE BofAML US High Yield BB Total Return Index Value |
4/9/18 |
BAMLHYH0A1BBTRIV |
Index |
|
|
ICE BofAML US High Yield B Semi-Annual Yield to Worst |
4/9/18 |
BAMLH0A2HYBSYTW |
Securities |
|
|
ICE BofAML US High Yield B Total Return Index Value |
4/9/18 |
BAMLHYH0A2BTRIV |
Index |
|
|
ICE BofAML US High Yield CCC or Below Semi-Annual Yield to Worst |
4/9/18 |
BAMLH0A3HYCSYTW |
Securities |
|
|
ICE BofAML US High Yield CCC or Below Total Return Index Value |
4/9/18 |
BAMLHYH0A3CMTRIV |
Index |
|
|
ICE BofAML US High Yield Master II Semi-Annual Yield to Worst |
4/9/18 |
BAMLH0A0HYM2SYTW |
Securities |
|
|
Instantaneous Forward Term Premium 10 Years Hence |
1/18/18 |
THREEFFTP10 |
Securities |
|
|
Interest Rate on Required Reserves |
4/9/18 |
IORR |
Key factors |
|
|
Japan Intervention: Japanese Bank purchases of USD against JPY |
2/9/18 |
JPINTDUSDJPY |
Currencies |
|
|
Kerosene-Type Jet Fuel Prices: U.S. Gulf Coast |
4/4/18 |
DJFUELUSGULF |
Oil and precious metals |
|
|
Long-Term Composite Rate of U.S. Treasury Securities Over 10 years (DISCONTINUED) |
6/30/00 |
DLTBOARD |
Treasury securities |
|
|
Malaysia / U.S. Foreign Exchange Rate |
4/9/18 |
DEXMAUS |
Exchange rate |
|
|
Mexican Intervention: Banco de Mexico Purchase on the USD |
7/1/11 |
MEXINTDUSD |
Currencies |
|
|
Moody's Seasoned Aaa Corporate Bond Minus Federal Funds Rate |
4/9/18 |
AAAFF |
Securities |
|
|
Moody's Seasoned Baa Corporate Bond Minus Federal Funds Rate |
4/9/18 |
BAAFF |
Securities |
|
|
NASDAQ 100 Index |
4/9/18 |
NASDAQ100 |
Index |
|
|
NBER based Recession Indicators for the United States from the Peak through the Period preceding the Trough |
4/9/18 |
USRECDP |
Indicator |
|
|
NBER based Recession Indicators for the United States from the Peak through the Trough |
4/9/18 |
USRECDM |
Indicator |
|
|
No. 2 Heating Oil Prices: New York Harbor |
4/4/18 |
DHOILNYH |
Oil and precious metals |
|
|
Norway / U.S. Foreign Exchange Rate |
4/9/18 |
DEXNOUS |
Exchange rate |
|
|
Number of Issues, with a Maturity Between 21 and 40 Days, Used in Calculating the AA Asset-Backed Commercial Paper Rates |
4/9/18 |
AB2140AAVOL |
Commercial paper |
|
|
OECD based Recession Indicators for Australia from the Peak through the Trough |
10/10/17 |
AUSRECDM |
Indicator |
|
|
OECD based Recession Indicators for Brazil from the Period following the Peak through the Trough |
12/12/17 |
BRARECD |
Indicator |
|
|
OECD based Recession Indicators for Canada from the Peak through the Trough |
12/13/17 |
CANRECDM |
Indicator |
|
|
OECD based Recession Indicators for China from the Peak through the Trough |
12/12/17 |
CHNRECDM |
Indicator |
|
|
OECD based Recession Indicators for Euro Area from the Period following the Peak through the Trough |
12/12/17 |
EURORECD |
Indicator |
|
|
OECD based Recession Indicators for Four Big European Countries from the Peak through the Trough |
12/12/17 |
4BIGEURORECDM |
Indicator |
|
|
OECD based Recession Indicators for France from the Period following the Peak through the Trough |
12/12/17 |
FRARECD |
Indicator |
|
|
OECD based Recession Indicators for Germany from the Period following the Peak through the Trough |
12/12/17 |
DEURECD |
Indicator |
|
|
OECD based Recession Indicators for India from the Period following the Peak through the Trough |
10/10/17 |
INDRECD |
Indicator |
|
|
OECD based Recession Indicators for Indonesia from the Peak through the Trough |
12/12/17 |
IDNRECDM |
Indicator |
|
|
OECD based Recession Indicators for Italy from the Period following the Peak through the Trough |
12/12/17 |
ITARECD |
Indicator |
|
|
OECD based Recession Indicators for Japan from the Peak through the Period preceding the Trough |
12/12/17 |
JPNRECDP |
Indicator |
|
|
OECD based Recession Indicators for Korea from the Period following the Peak through the Trough |
11/9/17 |
KORRECD |
Indicator |
|
|
OECD based Recession Indicators for Major 5 Asia from the Period following the Peak through the Trough |
12/12/17 |
MAJOR5ASIARECD |
Indicator |
|
|
OECD based Recession Indicators for Mexico from the Period following the Peak through the Trough |
12/12/17 |
MEXRECD |
Indicator |
|
|
OECD based Recession Indicators for Norway from the Period following the Peak through the Trough |
12/12/17 |
NORRECD |
Indicator |
|
|
OECD based Recession Indicators for Switzerland from the Period following the Peak through the Trough |
10/10/17 |
CHERECD |
Indicator |
|
|
OECD based Recession Indicators for the United Kingdom from the Peak through the Trough |
12/12/17 |
GBRRECDM |
Indicator |
|
|
OECD based Recession Indicators for the United States from the Peak through the Trough |
12/12/17 |
USARECDM |
Indicator |
|
|
Overnight AA Asset-backed Commercial Paper Interest Rate |
4/9/18 |
RIFSPPAAAD01NB |
Commercial paper |
|
|
Overnight AA Financial Commercial Paper Interest Rate |
4/9/18 |
RIFSPPFAAD01NB |
Commercial paper |
|
|
Overnight Bank Funding Volume |
4/10/18 |
OBFRVOL |
Key factors |
|
|
Overnight London Interbank Offered Rate (LIBOR), British pound |
4/10/18 |
GBPONTD156N |
LIBOR |
|
|
Overnight London Interbank Offered Rate (LIBOR), Canadian Dollar (Discontinued) |
6/7/13 |
CADONTD156N |
LIBOR |
|
|
Overnight London Interbank Offered Rate (LIBOR), EURO |
4/10/18 |
EURONTD156N |
LIBOR |
|
|
Overnight Repurchase Agreements: Treasury Securities Purchased by the Federal Reserve in the Temporary Open Market Operations |
5/24/17 |
RPONTSYD |
Treasury securities |
|
|
Overnight Reverse Repurchase Agreements: Total Securities Sold by the Federal Reserve in the Temporary Open Market Operations |
4/9/18 |
RRPONTTLD |
Securities |
|
|
Overnight Reverse Repurchase Agreements: Treasury Securities Sold by the Federal Reserve in the Temporary Open Market Operations |
4/9/18 |
RRPONTSYD |
Treasury securities |
|
|
Propane Prices: Mont Belvieu |
4/4/18 |
DPROPANEMBTX |
Oil and precious metals |
|
|
Reformulated Gasoline Blendstock for Oxygenate Blending (RBOB) Prices: Regular Gasoline: Los Angeles |
4/4/18 |
DRGASLA |
Oil and precious metals |
|
|
Repurchase Agreements: Mortgage-Backed Securities Purchased by the Federal Reserve in the Temporary Open Market Operations |
11/20/17 |
RPMBSD |
Securities |
|
|
Russell 1000® Growth Total Market Index |
4/9/18 |
RU1000GTR |
Index |
|
|
Russell 1000® Price Index |
4/9/18 |
RU1000PR |
Index |
|
|
Russell 1000® Total Market Index |
4/9/18 |
RU1000TR |
Index |
|
|
Russell 1000® Value Price Index |
4/9/18 |
RU1000VPR |
Index |
|
|
Russell 1000® Value Total Market Index |
4/9/18 |
RU1000VTR |
Index |
|
|
Russell 2000® Growth Price Index |
4/9/18 |
RU2000GPR |
Index |
|
|
Russell 2000® Growth Total Market Index |
4/9/18 |
RU2000GTR |
Index |
|
|
Russell 2000® Total Market Index |
4/9/18 |
RU2000TR |
Index |
|
|
Russell 2000® Value Price Index |
4/9/18 |
RU2000VPR |
Index |
|
|
Russell 2000® Value Total Market Index |
4/9/18 |
RU2000VTR |
Index |
|
|
Russell 3000® Price Index |
4/9/18 |
RU3000PR |
Index |
|
|
Russell 3000® Total Market Index |
4/9/18 |
RU3000TR |
Index |
|
|
Russell 3000® Value Total Market Index |
4/9/18 |
RU3000VTR |
Index |
|
|
Russell Midcap® Growth Total Market Index |
4/9/18 |
RMIDGRTR |
Index |
|
|
Russell Midcap® Value Total Market Index |
4/9/18 |
RMIDVLTR |
Index |
|
|
Singapore / U.S. Foreign Exchange Rate |
4/9/18 |
DEXSIUS |
Exchange rate |
|
|
South Africa / U.S. Foreign Exchange Rate |
4/9/18 |
DEXSFUS |
Exchange rate |
|
|
Spot Next London Interbank Offered Rate (LIBOR), Japanese Yen |
4/10/18 |
JPYONTD156N |
LIBOR |
|
|
Spot Next London Interbank Offered Rate (LIBOR), Swiss franc |
4/10/18 |
CHFONTD156N |
LIBOR |
|
|
Sri Lanka / U.S. Foreign Exchange Rate |
4/9/18 |
DEXSLUS |
Exchange rate |
|
|
Sweden / U.S. Foreign Exchange Rate |
4/9/18 |
DEXSDUS |
Exchange rate |
|
|
Taiwan / U.S. Foreign Exchange Rate |
4/9/18 |
DEXTAUS |
Exchange rate |
|
|
Thailand / U.S. Foreign Exchange Rate |
4/9/18 |
DEXTHUS |
Exchange rate |
|
|
Total Value of Issuers of Commercial Paper with a Maturity Between 5 and 9 Days |
4/9/18 |
MKT59MKTAMT |
Commercial paper |
|
|
Total Value of Issues |
4/9/18 |
FIN4180AAAMT |
Key factors |
|
|
Trade Weighted U.S. Dollar Index: Other Important Trading Partners |
4/9/18 |
DTWEXO |
Index |
|
|
Treasury Inflation-Indexed Long-Term Average Yield |
4/9/18 |
DLTIIT |
Treasury securities |
|
|
Ultra-Low-Sulfur No. 2 Diesel Fuel Prices: New York Harbor |
4/4/18 |
DDFUELNYH |
Oil and precious metals |
|
|
Ultra-Low-Sulfur No. 2 Diesel Fuel Prices: U.S. Gulf Coast |
4/4/18 |
DDFUELUSGULF |
Oil and precious metals |
|
|
U.S. Intervention: in Market Transactions in the JPY/USD (Millions of USD) |
3/5/08 |
USINTDMRKTJPY |
Currencies |
|
|
U.S. / New Zealand Foreign Exchange Rate |
4/9/18 |
DEXUSNZ |
Exchange rate |
|
|
Venezuela / U.S. Foreign Exchange Rate |
4/9/18 |
DEXVZUS |
Exchange rate |
|
|
Wilshire 5000 Price Index |
4/10/18 |
WILL5000PR |
Index |
|
|
Wilshire 5000 Total Market Index |
4/10/18 |
WILL5000IND |
Index |
|
|
Wilshire US Large-Cap Total Market Index |
4/10/18 |
WILLLRGCAP |
Index |
|
|
Wilshire US Real Estate Investment Trust Price Index (Wilshire US REIT) |
4/10/18 |
WILLREITPR |
Index |
|
|
Wilshire US Real Estate Investment Trust Total Market Index (Wilshire US REIT) |
4/10/18 |
WILLREITIND |
Index |
|
|
Wilshire US Real Estate Securities Price Index (Wilshire US RESI) |
4/10/18 |
WILLRESIPR |
Index |
|
|
Wilshire US Real Estate Securities Total Market Index (Wilshire US RESI) |
4/10/18 |
WILLRESIND |
Index |
|
|
Wilshire US Small-Cap Value Total Market Index |
4/10/18 |
WILLSMLCAPVAL |
Index |
|
|
ICE BofAML AAA-A US Emerging Markets Liquid Corporate Plus Sub-Index Total Return Index Value |
4/10/18 |
AMLEM1RAAA2ALCRPIUSTRIV |
Index |
|
|
2-Month AA Financial Commercial Paper Rate |
4/10/18 |
DCPF2M |
Commercial paper |
|
|
10-Year 2-1/8% Treasury Inflation-Indexed Note |
4/10/18 |
DTP10J19 |
Treasury securities |
|
|
Russell Midcap® Value Price Index |
4/10/18 |
RMIDVLPR |
Index |
|
|
Russell 1000® Growth Price Index |
4/10/18 |
RU1000GPR |
Index |
|
|
Russell 2500 Total Market Index |
4/10/18 |
RU2500TR |
Index |
|
|
Russell 3000® Growth Total Market Index |
4/10/18 |
RU3000GTR |
Index |
|
|
Russell 3000® Value Price Index |
4/10/18 |
RU3000VPR |
Index |
|
|
Fitted Yield on a 4 Year Zero Coupon Bond |
4/10/18 |
THREEFY4 |
Securities |
|
|
5-Month London Interbank Offered Rate (LIBOR), US dollar |
4/10/18 |
USD5MTD156N |
LIBOR |
|
|
Wilshire 4500 Total Market Index |
4/10/18 |
WILL4500IND |
Index |
|
|
Wilshire US Large-Cap Value Total Market Index |
4/10/18 |
WILLLRGCAPVAL |
Index |
|
|
Wilshire US Micro-Cap Total Market Index |
4/10/18 |
WILLMICROCAP |
Index |
|
|
Wilshire US Mid-Cap Total Market Index |
4/10/18 |
WILLMIDCAP |
Index |
|
|
Wilshire US Small-Cap Value Price Index |
4/10/18 |
WILLSMLCAPVALPR |
Index |
|
|
5-Year 0-1/8% Treasury Inflation-Indexed Note |
4/10/18 |
DTP5A20 |
Treasury securities |
|
|
5-Year Treasury Inflation-Indexed Note |
4/10/18 |
DTP5L02 |
Treasury securities |
|
|
7-Day AA Asset-backed Commercial Paper Interest Rate |
4/10/18 |
RIFSPPAAAD07NB |
Commercial paper |
|
|
60-Day AA Financial Commercial Paper Interest Rate |
4/10/18 |
RIFSPPFAAD60NB |
Commercial paper |
|
|
Russell Top 200® Growth Total Market Index |
4/10/18 |
RTOP200GTR |
Index |
|
|
Term Premium on a 3 Year Zero Coupon Bond |
4/10/18 |
THREEFYTP3 |
Securities |
|
|
10-Year 2-5/8% Treasury Inflation-Indexed Note |
4/10/18 |
DTP10L17 |
Treasury securities |
|
|
10-Year 1-7/8% Treasury Inflation-Indexed Note |
4/10/18 |
DTP10L19 |
Treasury securities |
|
|
20-Year 2-1/2% Treasury Inflation-Indexed Bond |
4/10/18 |
DTP20J29 |
Treasury securities |
|
|
30-1/2-Year 3-3/8% Treasury Inflation-Indexed Bond |
4/10/18 |
DTP3HA32 |
Treasury securities |
|
|
15-Day AA Asset-backed Commercial Paper Interest Rate |
4/10/18 |
RIFSPPAAAD15NB |
Commercial paper |
|
|
Fitted Instantaneous Forward Rate 2 Years Hence |
4/10/18 |
THREEFF2 |
Securities |
|
|
Term Premium on a 7 Year Zero Coupon Bond |
4/10/18 |
THREEFYTP7 |
Securities |
|
|
Term Premium on a 8 Year Zero Coupon Bond |
4/10/18 |
THREEFYTP8 |
Securities |
|
|
Wilshire 4500 Price Index |
4/10/18 |
WILL4500PR |
Index |
|
|
Wilshire US Mid-Cap Growth Price Index |
4/10/18 |
WILLMIDCAPGRPR |
Index |
|
|
Number of Commercial Paper Issues with a Maturity Between 1 and 4 Days |
4/10/18 |
MKT14MKTVOL |
Commercial paper |
|
|
Total Value of Issues |
4/10/18 |
NONFIN59AAAMT |
Key factors |
|
|
15-Day AA Financial Commercial Paper Interest Rate |
4/10/18 |
RIFSPPFAAD15NB |
Commercial paper |
|
|
Wilshire US Large-Cap Growth Price Index |
4/10/18 |
WILLLRGCAPGRPR |
Index |
|
|
China-EU |
1/11/18 |
CNYEUR |
Exchange rate |
|
|
China-Japan |
1/11/18 |
CNYJPY |
Exchange rate |
|
|
China-USA |
1/11/18 |
CNYUSD |
Exchange rate |
|
|
EU-Australia |
1/11/18 |
EURAUD |
Exchange rate |
|
|
EU-Canada |
1/11/18 |
EURCAD |
Exchange rate |
|
|
EU-Russia |
1/11/18 |
EURRUB |
Exchange rate |
|
|
EU-USA |
1/11/18 |
EURUSD |
Exchange rate |
|
|
USA-UAE (United Arab Emirates ) |
1/11/18 |
USDAED |
Exchange rate |
|
|
USA-Australia |
1/11/18 |
USDAUD |
Exchange rate |
|
|
USA-Brazil |
1/11/18 |
USDBRL |
Exchange rate |
|
|
USA-Canada |
1/11/18 |
USDCAD |
Exchange rate |
|
|
USA-India |
1/11/18 |
USDINR |
Exchange rate |
|
|
USA-Mexico |
1/11/18 |
USDMXN |
Exchange rate |
|
|
USA-Russia |
1/11/18 |
USDRUB |
Exchange rate |
|
|
5-Year Treasury Constant Maturity Rate |
10/2/17 |
DSG5 |
Treasury securities |
|
|
Dow Jones Index |
10/2/17 |
DJI |
Index |
|
|
10-Year Breakeven Inflation Rate |
10/2/17 |
T10YIE |
Key factors |
|
|
Effective federal funds rate |
10/2/17 |
EFFR |
Key factors |
|
|
Return on a diversified portfolio of small stocks minus the return on a diversified portfolio of big stocks |
2/25/18 |
SMB |
Securities |
|
|
Difference between the returns on diversified portfolios of high and low B/M stocks |
2/25/18 |
HML |
Securities |
|
|
Difference between the returns on diversified portfolios of stocks with robust and weak profitability |
2/25/18 |
RMW |
Securities |
|
|
Trade Weighted U.S. Dollar Index: Broad |
5/7/18 |
DTWEXB |
Exchange rate |
|
|
Difference between the returns on diversified portfolios of low and high investment stocks |
2/25/18 |
CMA |
Securities |
|
|
Risk free rate |
2/25/18 |
RF |
Key factors |
|
|
25 Portfolios Formed on Size and Book-to-Market |
2/27/18 |
SMALL LoPRIOR |
Fama and French |
|
|
ME1 PRIOR2 |
Fama and French |
|||
|
ME1 PRIOR3 |
Fama and French |
|||
|
ME1 PRIOR4 |
Fama and French |
|||
|
SMALL HiPRIOR |
Fama and French |
|||
|
ME2 PRIOR1 |
Fama and French |
|||
|
ME2 PRIOR2 |
Fama and French |
|||
|
ME2 PRIOR3 |
Fama and French |
|||
|
ME2 PRIOR4 |
Fama and French |
|||
|
ME2 PRIOR5 |
Fama and French |
|||
|
ME3 PRIOR1 |
Fama and French |
|||
|
ME3 PRIOR2 |
Fama and French |
|||
|
ME3 PRIOR3 |
Fama and French |
|||
|
ME3 PRIOR4 |
Fama and French |
|||
|
ME3 PRIOR5 |
Fama and French |
|||
|
ME4 PRIOR1 |
Fama and French |
|||
|
ME4 PRIOR2 |
Fama and French |
|||
|
ME4 PRIOR3 |
Fama and French |
|||
|
ME4 PRIOR4 |
Fama and French |
|||
|
ME4 PRIOR5 |
Fama and French |
|||
|
BIG LoPRIOR |
Fama and French |
|||
|
ME5 PRIOR2 |
Fama and French |
|||
|
ME5 PRIOR3 |
Fama and French |
|||
|
ME5 PRIOR4 |
Fama and French |
|||
|
BIG HiPRIOR |
Fama and French |
|||
|
Crude Oil Prices: Brent - Europe |
5/23/18 |
DCOILBRENTEU |
Oil and precious metals |
|
|
Taiwan / U.S. Foreign Exchange Rate |
5/21/18 |
DEXTAUS |
Exchange rate |
|
|
Thailand / U.S. Foreign Exchange Rate |
5/21/18 |
DEXTHUS |
Exchange rate |
|
|
10-Year Treasury Constant Maturity Rate |
5/25/18 |
DGS10 |
Treasury securities |
|
|
Primary Credit Rate |
5/25/18 |
DPCREDIT |
Key factors |
|
|
4-Week Treasury Bill: Secondary Market Rate |
5/25/18 |
DTB4WK |
Treasury securities |
|
|
Gold Fixing Price 3:00 P.M. (London time) in London Bullion Market, based in U.S. Dollars |
5/25/18 |
GOLDPMGBD228NLBM |
Oil and precious metals |
|
|
60-Day A2/P2 Nonfinancial Commercial Paper Interest Rate |
5/25/18 |
RIFSPPNA2P2D60NB |
Commercial paper |
|
|
90-Day AA Nonfinancial Commercial Paper Interest Rate |
5/25/18 |
RIFSPPNAAD90NB |
Commercial paper |
|
|
10-Year Treasury Constant Maturity Minus 2-Year Treasury Constant Maturity |
5/25/18 |
T10Y2Y |
Treasury securities |
|
|
TED Spread |
5/25/18 |
TEDRATE |
Key factors |
|
|
Bank Prime Loan Rate |
5/25/18 |
DPRIME |
Key factors |
|
|
3-Month Treasury Bill: Secondary Market Rate |
5/21/18 |
DTB3 |
Treasury securities |
4) R-script:
install.packages("readxl")
library(readxl)
DATES <- read_excel("/Users/artembaron/Desktop/DATES.xls")
allod <- read.csv(file = "/Users/artembaron/Desktop/rawdata.csv", header = TRUE)
names_f_ns <- read_excel("/Users/artembaron/Desktop/variables_return.xlsx")
len_nam <- nrow(names_f_ns)
logdif_df<-data.frame(1,1)
logdif_df<-data.frame(1,1)
for (q in 1:len_nam) {
if (names_f_ns[q,2]=="LOGDIF") {last_row<-nrow(logdif_df)+1;logdif_df[last_row,]<-names_f_ns[q,];remove(last_row)}
}
remove(q)
logdif_df<-logdif_df[-1,]
average_df<-data.frame(1,1)
for (q in 1:len_nam) {
if (names_f_ns[q,2]=="AVERAGE") {last_row<-nrow(average_df)+1;average_df[last_row,]<-names_f_ns[q,];remove(last_row)}
}
remove(q)
average_df<-average_df[-1,]
compound_df<-data.frame(1,1)
for (q in 1:len_nam) {
if (names_f_ns[q,2]=="COMPOUND") {last_row<-nrow(compound_df)+1;compound_df[last_row,]<-names_f_ns[q,];remove(last_row)}
}
remove(q)
compound_df<-compound_df[-1,]
cumulative_df<-data.frame(1,1)
for (q in 1:len_nam) {
if (names_f_ns[q,2]=="CUMMULATED") {last_row<-nrow(cumulative_df)+1;cumulative_df[last_row,]<-names_f_ns[q,];remove(last_row)}
}
remove(q)
cumulative_df<-cumulative_df[-1,]
ame_df<-data.frame(1,1)
for (q in 1:len_nam) {
if (names_f_ns[q,2]=="SAME") {last_row<-nrow(same_df)+1;same_df[last_row,]<-names_f_ns[q,];remove(last_row)}
}
remove(q)
same_df<-same_df[-1,]
max_df<-data.frame(1,1)
for (q in 1:len_nam) {
if (names_f_ns[q,2]=="MAX") {last_row<-nrow(max_df)+1;max_df[last_row,]<-names_f_ns[q,];remove(last_row)}
}
remove(q)
max_df<-max_df[-1,]
filtered_names<-logdif_df[,1]
filtered_names=append(filtered_names,average_df[,1])
filtered_names=append(filtered_names,compound_df[,1])
filtered_names=append(filtered_names,cumulative_df[,1])
filtered_names=append(filtered_names,same_df[,1])
filtered_names=append(filtered_names,max_df[,1])
filtered_class<-logdif_df[,2]
filtered_class=append(filtered_class,average_df[,2])
filtered_class=append(filtered_class,compound_df[,2])
filtered_class=append(filtered_class,cumulative_df[,2])
filtered_class=append(filtered_class,same_df[,2])
filtered_class=append(filtered_class,max_df[,2])
names_f<-data.frame(filtered_names,filtered_class)
logdif<-nrow(logdif_df)
lastaverage<-nrow(average_df)+logdif
lastcompound<-nrow(compound_df)+lastaverage
lastcumulative<-nrow(cumulative_df)+lastcompound
lastsame<-nrow(same_df)+lastcumulative
remove(average_df,compound_df,cumulative_df,logdif_df,max_df,names_f_ns,same_df,filtered_class,filtered_names)
od<-data.frame(DATES[,2])
valid_factor<-0
names_of_valid<-names_f[,1]
valid_factors<-c(names_of_valid)
quantity_of_valid<-length(valid_factors)
for (w in 1:quantity_of_valid) {
valid_factor<-valid_factors[w]
od[,w+1]<-allod[,valid_factor]
}
names_plus_date<-append(c("date"),names_of_valid)
colnames(od)<-names_plus_date
remove(w,quantity_of_valid,valid_factors,valid_factor,names_plus_date,names_of_valid)
for (i in 2:ncol(od)) { od[,i]<-as.numeric(od[,i])}
remove(i)
cf<-list(0)
nk<-ncol(od)
remove(DATES)
"all work before"
for (k in 2:nk) {
df<-data.frame(od[,1],od[,k])
df[,3]<-format(df[,1], "%u")
df[,3]<-as.numeric(df[,3])
newday=0
obs<-nrow(od)
for (i in 1:obs) {
if (df[i,3]==4) {newday=append(newday,1)}
else if (df[i,3]==5) {newday=append(newday,2)}
else if (df[i,3]==6) {newday=append(newday,3)}
else if (df[i,3]==7) {newday=append(newday,4)}
else if (df[i,3]==1) {newday=append(newday,5)}
else if (df[i,3]==2) {newday=append(newday,6)}
else {newday=append(newday,7)} }
newday=newday[-1]
df[,4]<-newday
remove(i,newday)
df<-df[,-3]
week=0
counter=0
for (i in 2:obs) { if (df[i,3]<=df[i-1,3]) {counter=counter+1;week=append(week,counter)} else {week=append(week,counter)} }
df[,4]<-week
df[,4]=df[,4]+1
nofw<-max(range(df[,4]))
remove(i,counter,week)
lofwp<-list(1)
prices=0
if (df[1,3]==1) {prices=df[1,2]} else {prices="NA";prices=append(prices,df[1,4])}
for (i in 2:obs) {
if (df[i,4]==df[i-1,4]) {prices<-append(prices,df[i,2])}
else if (df[i,4]!=df[i-1,4] & df[i,3]==1) {lofwp[[df[i-1,4]]]<-prices; prices<-df[i,2]}
else { lofwp[[df[i-1,4]]]<-prices;prices<-"NA";prices=append(prices,c(df[i,2]))}
lofwp[[df[i,4]]]<-prices }
remove(prices,i)
lostr=0
ql=length(lofwp)
for (i in 1:ql) {
lofwp[[i]]<-as.numeric(lofwp[[i]])
lostr=length(lofwp[[i]])
if (lostr==1) {lofwp[[i]][2]<-"NA";lofwp[[i]][3]<-"NA";lofwp[[i]][4]<-"NA";lofwp[[i]][5]<-"NA";lofwp[[i]][6]<-"NA";lofwp[[i]][7]<-"NA"}
else if (lostr==2) {lofwp[[i]][3]<-"NA";lofwp[[i]][4]<-"NA";lofwp[[i]][5]<-"NA";lofwp[[i]][6]<-"NA";lofwp[[i]][7]<-"NA"}
else if (lostr==3) {lofwp[[i]][4]<-"NA";lofwp[[i]][5]<-"NA";lofwp[[i]][6]<-"NA";lofwp[[i]][7]<-"NA"}
else if (lostr==4) {lofwp[[i]][5]<-"NA";lofwp[[i]][6]<-"NA";lofwp[[i]][7]<-"NA"}
else if (lostr==5) {lofwp[[i]][6]<-"NA";lofwp[[i]][7]<-"NA"}
else if (lostr==6) {lofwp[[i]][7]<-"NA"} }
remove(i,lostr,ql)
if (k<=logdif) {
bb=0
be=0
returns<-"NA"
return<-0
for (i in 2:nofw)
{lofwp[[i]]<-as.numeric(lofwp[[i]])
lofwp[[i-1]]<-as.numeric(lofwp[[i-1]])
if (is.na(lofwp[[i-1]][1])==FALSE) {be<-lofwp[[i-1]][1]}
else if ((is.na(lofwp[[i-1]][1])==TRUE) & is.na(lofwp[[i-1]][2])==FALSE) {be<-lofwp[[i-1]][2]}
else if ((is.na(lofwp[[i-1]][1])==TRUE) & is.na(lofwp[[i-1]][2])==TRUE & is.na(lofwp[[i-1]][3])==FALSE) {be<-lofwp[[i-1]][3]}
else if ((is.na(lofwp[[i-1]][1])==TRUE) & is.na(lofwp[[i-1]][2])==TRUE & is.na(lofwp[[i-1]][3])==TRUE & is.na(lofwp[[i-1]][4])==FALSE) {be<-lofwp[[i-1]][4]}
else if ((is.na(lofwp[[i-1]][1])==TRUE) & is.na(lofwp[[i-1]][2])==TRUE & is.na(lofwp[[i-1]][3])==TRUE & is.na(lofwp[[i-1]][4])==TRUE & is.na(lofwp[[i-1]][5])==FALSE) {be<-lofwp[[i-1]][5]}
else if ((is.na(lofwp[[i-1]][1])==TRUE) & is.na(lofwp[[i-1]][2])==TRUE & is.na(lofwp[[i-1]][3])==TRUE & is.na(lofwp[[i-1]][4])==TRUE & is.na(lofwp[[i-1]][5])==TRUE & is.na(lofwp[[i-1]][6])==FALSE) {be<-lofwp[[i-1]][6]}
else {be<-lofwp[[i-1]][7]}
if (is.na(lofwp[[i]][1])==FALSE) {bb<-lofwp[[i]][1]}
else if (is.na(lofwp[[i]][1])==TRUE & is.na(lofwp[[i-1]][7])==FALSE) {be<-lofwp[[i-1]][7]}
else if (is.na(lofwp[[i]][1])==TRUE & is.na(lofwp[[i-1]][7])==TRUE & is.na(lofwp[[i-1]][6])==FALSE) {bb<-lofwp[[i-1]][6]}
else if (is.na(lofwp[[i]][1])==TRUE & is.na(lofwp[[i-1]][7])==TRUE & is.na(lofwp[[i-1]][6])==TRUE & is.na(lofwp[[i-1]][5])==FALSE) {bb<-lofwp[[i-1]][5]}
else if (is.na(lofwp[[i]][1])==TRUE & is.na(lofwp[[i-1]][7])==TRUE & is.na(lofwp[[i-1]][6])==TRUE & is.na(lofwp[[i-1]][5])==TRUE & is.na(lofwp[[i-1]][4])==FALSE) {bb<-lofwp[[i-1]][4]}
else if (is.na(lofwp[[i]][1])==TRUE & is.na(lofwp[[i-1]][7])==TRUE & is.na(lofwp[[i-1]][6])==TRUE & is.na(lofwp[[i-1]][5])==TRUE & is.na(lofwp[[i-1]][4])==TRUE & is.na(lofwp[[i-1]][3])==FALSE) {bb<-lofwp[[i-1]][3]}
else {bb<-lofwp[[i-1]][2]}
if (is.na(bb)==FALSE & is.na(be)==FALSE) {return=log(bb)-log(be)} else {return<-NA}
returns=append(returns,return)}
remove(return,bb,be)
remove(obs,nofw,i,lofwp,df)
cf[[k]]<-returns
remove(returns)
}
else if (k>logdif & k<=lastaverage) {
lenlof=length(lofwp)
averages<-0
for (d in 1:lenlof) {
average<-0
sum_prices<-0
not_NA<-0
for (s in 1:7) {
'lofwp<-as.numeric(lofwp[[d]])'
if (is.na(lofwp[[d]][s])==FALSE) {not_NA=not_NA+1;sum_prices=sum_prices+(as.numeric(lofwp[[d]][s]))}}
remove(s)
if (not_NA==0) {averages=append(averages,NA)} else {average=sum_prices/not_NA;averages=append(averages,average)}}
remove(d)
averages<-averages[-1]
remove(average,lenlof,not_NA,sum_prices,lofwp,lenlof)
cf[[k]]<-averages
remove(averages)
}
else if (k>lastaverage & k<=lastcompound) {
lenlof=length(lofwp)
lofwp_no_NA<-list(0)
for (d in 1:lenlof) {
not_NA_rates<-0
lofwp[[d]]<-as.numeric(lofwp[[d]])
for (s in 1:7) {
if (is.na(lofwp[[d]][s])==FALSE) {not_NA_rates=append(not_NA_rates,as.numeric(lofwp[[d]][s]))} }
remove(s)
not_NA_rates<-not_NA_rates[-1]
lofwp_no_NA[[d]]<-not_NA_rates
}
remove(d,not_NA_rates)
permnogrates<-0
compounding_rates<-0
compounding_rate<-0
for (h in 1:lenlof) {
len_of_week<-length(lofwp_no_NA[[h]])
if (len_of_week==7) {permnogrates=(1+lofwp_no_NA[[h]][1])*(1+lofwp_no_NA[[h]][2])*(1+lofwp_no_NA[[h]][3])*(1+lofwp_no_NA[[h]][4])*(1+lofwp_no_NA[[h]][5])*(1+lofwp_no_NA[[h]][6])*(1+lofwp_no_NA[[h]][7]);compounding_rate=permnogrates-1;compounding_rates=append(compounding_rates,compounding_rate)}
else if (len_of_week==6) {permnogrates=(1+lofwp_no_NA[[h]][1])*(1+lofwp_no_NA[[h]][2])*(1+lofwp_no_NA[[h]][3])*(1+lofwp_no_NA[[h]][4])*(1+lofwp_no_NA[[h]][5])*(1+lofwp_no_NA[[h]][6]);compounding_rate=permnogrates-1;compounding_rates=append(compounding_rates,compounding_rate)}
else if (len_of_week==5) {permnogrates=(1+lofwp_no_NA[[h]][1])*(1+lofwp_no_NA[[h]][2])*(1+lofwp_no_NA[[h]][3])*(1+lofwp_no_NA[[h]][4])*(1+lofwp_no_NA[[h]][5]);compounding_rate=permnogrates-1;compounding_rates=append(compounding_rates,compounding_rate)}
else if (len_of_week==4) {permnogrates=(1+lofwp_no_NA[[h]][1])*(1+lofwp_no_NA[[h]][2])*(1+lofwp_no_NA[[h]][3])*(1+lofwp_no_NA[[h]][4]);compounding_rate=permnogrates-1;compounding_rates=append(compounding_rates,compounding_rate)}
else if (len_of_week==3) {permnogrates=(1+lofwp_no_NA[[h]][1])*(1+lofwp_no_NA[[h]][2])*(1+lofwp_no_NA[[h]][3]);compounding_rate=permnogrates-1;compounding_rates=append(compounding_rates,compounding_rate)}
else if (len_of_week==2) {permnogrates=(1+lofwp_no_NA[[h]][1])*(1+lofwp_no_NA[[h]][2]);compounding_rate=permnogrates-1;compounding_rates=append(compounding_rates,compounding_rate)}
else if (len_of_week==1) {permnogrates=(1+lofwp_no_NA[[h]][1]);compounding_rate=permnogrates-1;compounding_rates=append(compounding_rates,compounding_rate)}
else {compounding_rates=append(compounding_rates,NA)}}
remove(h)
compounding_rates<-compounding_rates[-1]
remove(compounding_rate,len_of_week,permnogrates,lofwp_no_NA,lofwp,lenlof)
cf[[k]]<-compounding_rates
remove(compounding_rates)
}
else if (k>lastcompound & k<=lastcumulative) {
lenlof=length(lofwp)
lofwp_no_NA<-list(0)
for (d in 1:lenlof) {
not_NA_rates<-0
lofwp[[d]]<-as.numeric(lofwp[[d]])
for (s in 1:7) {
if (is.na(lofwp[[d]][s])==FALSE) {not_NA_rates=append(not_NA_rates,lofwp[[d]][s])} }
remove(s)
not_NA_rates<-not_NA_rates[-1]
lofwp_no_NA[[d]]<-not_NA_rates
}
remove(d,not_NA_rates)
cumulative_rate<-0
cumulative_rates<-0
for (h in 1:lenlof) {
len_of_week<-length(lofwp_no_NA[[h]])
if (len_of_week==7) {cumulative_rate=(lofwp_no_NA[[h]][1])+(lofwp_no_NA[[h]][2])+(lofwp_no_NA[[h]][3])+(lofwp_no_NA[[h]][4])+(lofwp_no_NA[[h]][5])+(lofwp_no_NA[[h]][6])+(lofwp_no_NA[[h]][7]);cumulative_rates=append(cumulative_rates,cumulative_rate)}
else if (len_of_week==6) {cumulative_rate=(lofwp_no_NA[[h]][1])+(lofwp_no_NA[[h]][2])+(lofwp_no_NA[[h]][3])+(lofwp_no_NA[[h]][4])+(lofwp_no_NA[[h]][5])+(lofwp_no_NA[[h]][6]);cumulative_rates=append(cumulative_rates,cumulative_rate)}
else if (len_of_week==5) {cumulative_rate=(lofwp_no_NA[[h]][1])+(lofwp_no_NA[[h]][2])+(lofwp_no_NA[[h]][3])+(lofwp_no_NA[[h]][4])+(lofwp_no_NA[[h]][5]);cumulative_rates=append(cumulative_rates,cumulative_rate)}
else if (len_of_week==4) {cumulative_rate=(lofwp_no_NA[[h]][1])+(lofwp_no_NA[[h]][2])+(lofwp_no_NA[[h]][3])+(lofwp_no_NA[[h]][4]);cumulative_rates=append(cumulative_rates,cumulative_rate)}
else if (len_of_week==3) {cumulative_rate=(lofwp_no_NA[[h]][1])+(lofwp_no_NA[[h]][2])+(lofwp_no_NA[[h]][3]);cumulative_rates=append(cumulative_rates,cumulative_rate)}
else if (len_of_week==2) {cumulative_rate=(lofwp_no_NA[[h]][1])+(lofwp_no_NA[[h]][2]);cumulative_rates=append(cumulative_rates,cumulative_rate)}
else if (len_of_week==1) {cumulative_rate=(lofwp_no_NA[[h]][1]);cumulative_rates=append(cumulative_rates,cumulative_rate)}
else {cumulative_rates=append(cumulative_rates,cumulative_rate)}}
remove(h)
cumulative_rates<-cumulative_rates[-1]
remove(cumulative_rate,len_of_week,lofwp_no_NA,lofwp,lenlof)
cf[[k]]<-cumulative_rates
remove(cumulative_rates)
}
else if (k>lastcumulative & k<=lastsame) {
lenlof=length(lofwp)
lofwp_no_NA<-list(0)
for (d in 1:lenlof) {
not_NA_rates<-0
lofwp[[d]]<-as.numeric(lofwp[[d]])
for (s in 1:7) {
if (is.na(lofwp[[d]][s])==FALSE) {not_NA_rates=append(not_NA_rates,lofwp[[d]][s])} }
remove(s)
not_NA_rates<-not_NA_rates[-1]
lofwp_no_NA[[d]]<-not_NA_rates
}
remove(d,not_NA_rates)
same_rate<-0
same_rates<-0
for (h in 1:lenlof) {
if (is.na(lofwp_no_NA[[h]][1])==TRUE) {same_rate="NA";same_rates=append(same_rates,same_rate)}
else {same_rate=lofwp_no_NA[[h]][1];same_rates=append(same_rates,same_rate)}}
remove(h)
same_rates<-same_rates[-1]
remove(same_rate,lofwp,lofwp_no_NA,lenlof)
cf[[k]]<-same_rates
remove(same_rates)
}
else {
lenlof<-length(lofwp)
lofwp_no_NA<-list(0)
for (d in 1:lenlof) {
not_NA_rates<-0
lofwp[[d]]<-as.numeric(lofwp[[d]])
for (s in 1:7) {
if (is.na(lofwp[[d]][s])==FALSE) {not_NA_rates=append(not_NA_rates,lofwp[[d]][s])} }
remove(s)
not_NA_rates<-not_NA_rates[-1]
lofwp_no_NA[[d]]<-not_NA_rates }
remove(d,not_NA_rates)
max_rates<-0
max_rate<-0
for (e in 1:lenlof) {
if (is.na(lofwp_no_NA[[e]][1])==FALSE) {max_rate=max(lofwp_no_NA[[e]]);max_rates=append(max_rates,max_rate)}
else {max_rates=append(max_rates,"NA")}
}
max_rates<-max_rates[-1]
remove(e,lenlof,max_rate)
cf[[k]]<-max_rates
remove(max_rates)
}
}
'end of whole cycle'
remove(k)
oddata<-data.frame(cf[[1]])
for (i in 2:nk) {
oddata[i]<-cf[i]}
odcol<-colnames(od)
odcol<-odcol[-1]
colnames(oddata)<-odcol
remove(i,odcol)
number_of_weeks<-length(cf[[2]])
vector_weeks<-(1:number_of_weeks)
final_frame<-data.frame(vector_weeks)
number_of_factors<-nrow(names_f)
for (i in 1:number_of_factors) {
final_frame[,i+1]<-cf[[i+1]]
}
remove(i)
names_f[,1]<-as.character(names_f[,1])
final_column_names<-c("week_number",names_f[,1])
colnames(final_frame)<-final_column_names
install.packages("quantmod")
install.packages("biglasso")
install.packages("Matrix")
install.packages("quantmod")
install.packages("bigmemory")
install.packages("PerformanceAnalytics")
library(quantmod)
library(PerformanceAnalytics)
library(biglasso)
library(bigmemory)
# get data yahoo finance
#rnull <- CalculateReturns(prices = GSPC$GSPC.Adjusted ,method ="log")
getSymbols("SPY", from = "1993-01-01", to = "2018-04-03")
SPYWEEKRETURN <- weeklyReturn(SPY)
PROXYMODUL <- abs(SPYWEEKRETURN)
finalcutNOTBIG <- pretty[161:1475,1:356]
PROXYSQUARED <- SPYWEEKRETURN^2
hminusldaily <- SPY$SPY.High-SPY$SPY.Low
hminusl <- apply.weekly(hminusldaily, mean)
PROXYRB <- 0.361*(hminusl)^2
yABS <- as.matrix(PROXYMODUL)
ySQ <- as.matrix(PROXYSQUARED)
yRB <- as.matrix(PROXYRB)
finalcutNOTBIG <- as.data.frame(finalcutNOTBIG)
finalcut <- as.big.matrix(finalcutNOTBIG)
SPYDAYRETURN <- dailyReturn(SPY)
PROXYVARIANCE <- apply.weekly(SPYDAYRETURN, var) # change number of observations
finalcutNOTBIGVAR <- pretty[162:1473,1:356]
finalcutNOTBIGVAR <- as.data.frame(finalcutNOTBIGVAR)
# for variance to do elastic net
finalcutVAR <- as.big.matrix(finalcutNOTBIGVAR) #
PROXYVARIANCEna <- na.omit(PROXYVARIANCE) #samely
yVARna <- as.matrix(PROXYVARIANCEna) # dep var if variance as proxy
cvfitVAR <- cv.biglasso(finalcutVAR,yVARna, eval.metric = c("default", "MAPE"), alpha = 0.5)
elasticnetVAR <- biglasso(finalcutVAR, yVARna, penalty = c("enet"), alpha = 0.5, lambda = cvfitVAR$lambda.min)
cvfitVARalpha0.1<- cv.biglasso(finalcutVAR, yVARna, alpha = 0.1)
elasticnetVARalpha0.1 <- biglasso(finalcutVAR, yVARna, alpha = 0.1 , lambda = cvfitVARalpha0.1$lambda.min)
cvfitVARalpha0.2<- cv.biglasso(finalcutVAR, yVARna, alpha = 0.2)
elasticnetVARalpha0.2 <- biglasso(finalcutVAR, yVARna, alpha = 0.2 , lambda = cvfitVARalpha0.2$lambda.min)
cvfitVARalpha0.3<-cv.biglasso(finalcutVAR, yVARna, alpha = 0.3)
elasticnetVARalpha0.3 <- biglasso(finalcutVAR, yVARna, alpha = 0.3 , lambda = cvfitVARalpha0.3$lambda.min)
cvfitVARalpha0.4<-cv.biglasso(finalcutVAR, yVARna, alpha = 0.4)
elasticnetVARalpha0.4 <- biglasso(finalcutVAR, yVARna, alpha = 0.4 , lambda = cvfitVARalpha0.4$lambda.min)
cvfitVARalpha0<-cv.biglasso(finalcutVAR, yVARna, alpha = 0)
elasticnetVARalpha0 <- biglasso(finalcutVAR, yVARna, alpha = 0 , lambda = cvfitVARalpha0$lambda.min)
cvfitVARalpha0.6<-cv.biglasso(finalcutVAR, yVARna, alpha = 0.6)
elasticnetVARalpha0.6 <- biglasso(finalcutVAR, yVARna, alpha = 0.6 , lambda = cvfitVARalpha0.6$lambda.min)
cvfitVARalpha0.7<-cv.biglasso(finalcutVAR, yVARna, alpha = 0.7)
elasticnetVARalpha0.7 <- biglasso(finalcutVAR, yVARna, alpha = 0.7 , lambda = cvfitVARalpha0.7$lambda.min)
cvfitVARalpha0.8<-cv.biglasso(finalcutVAR, yVARna, alpha = 0.8)
elasticnetVARalpha0.8 <- biglasso(finalcutVAR, yVARna, alpha = 0.8 , lambda = cvfitVARalpha0.8$lambda.min)
cvfitVARalpha0.9<-cv.biglasso(finalcutVAR, yVARna, alpha = 0.9)
elasticnetVARalpha0.9 <- biglasso(finalcutVAR, yVARna, alpha = 0.9 , lambda = cvfitVARalpha0.9$lambda.min)
cvfitVARalpha1<-cv.biglasso(finalcutVAR, yVARna, alpha = 1)
elasticnetVARalpha1 <- biglasso(finalcutVAR, yVARna, alpha = 1 , lambda = cvfitVARalpha1$lambda.min)
ELASTICNETbetaVAR=matrix(nrow=357, ncol=11)
ELASTICNETbetaVAR[,1] <- elasticnetVARalpha0$beta[,1]
ELASTICNETbetaVAR[,2] <- elasticnetVARalpha0.1$beta[,1]
ELASTICNETbetaVAR[,3]<- elasticnetVARalpha0.2$beta[,1]
ELASTICNETbetaVAR[,4] <- elasticnetVARalpha0.3$beta[,1]
ELASTICNETbetaVAR[,5] <- elasticnetVARalpha0.4$beta[,1]
ELASTICNETbetaVAR[,6] <- elasticnetVAR$beta[,1]
ELASTICNETbetaVAR[,7]<- elasticnetVARalpha0.6$beta[,1]
ELASTICNETbetaVAR[,8] <- elasticnetVARalpha0.7$beta[,1]
ELASTICNETbetaVAR[,9] <- elasticnetVARalpha0.8$beta[,1]
ELASTICNETbetaVAR[,10] <- elasticnetVARalpha0.9$beta[,1]
ELASTICNETbetaVAR[,11] <- elasticnetVARalpha1$beta[,1]
# grid <- seq( from = 0, to = 1, by = 0.1)
# elasticnetABSalphagrid <- biglasso(finalcut, yABS, alpha = grid , lambda = cvfitABSalphagrid$lambda.min)
cvfitABS <- cv.biglasso(finalcut,yABS, eval.metric = c("default", "MAPE"), alpha = 0.5)
elasticnetABS <- biglasso(finalcut, yABS, penalty = c("enet"), alpha = 0.5, lambda = cvfitABS$lambda.min)
#plot(elasticnet)
#plot(cvfit)
#cvfitABS$lambda.min
#elasticnetABS$beta
cvfitABSalpha0.1<-cv.biglasso(finalcut, yABS, alpha = 0.1)
elasticnetABSalpha0.1 <- biglasso(finalcut, yABS, alpha = 0.1 , lambda = cvfitABSalpha0.1$lambda.min)
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