Search is not available for this dataset
sma_50
float64 | sma_200
float64 | sma_ratio
float64 | MACD_12_26_9
float64 | MACDh_12_26_9
float64 | MACDs_12_26_9
float64 | ADX_14
float64 | DMP_14
float64 | DMN_14
float64 | rsi_14
float64 | STOCHk_14_3_3
float64 | STOCHd_14_3_3
float64 | roc_5
float64 | roc_10
float64 | atr_norm
float64 | BBL_20_2.0
float64 | BBM_20_2.0
float64 | BBU_20_2.0
float64 | BBB_20_2.0
float64 | BBP_20_2.0
float64 | bb_width
float64 | bb_pct
float64 | obv
float64 | vol_ratio
float64 | log_ret
float64 | z_score_20
float64 | gap_pct
float64 | month
int32 | day_of_week
int32 | is_month_end
int32 | is_quarter_end
int32 | sharpe_30
float64 | sortino_30
float64 | pivot_p
float64 | pivot_r1
float64 | pivot_s1
float64 | pivot_r2
float64 | pivot_s2
float64 | dist_high_52w
float64 | dist_low_52w
float64 | poc_60
float64 | dist_poc_60
float64 | ts_rank_log_ret_252
float64 | volatility_percentile_252
float64 | bb_width_percentile_252
float64 | trend_persistence_30
float64 | trend_regime_flag
int64 | rel_ret_spy
float64 | alpha_30_spy
float64 | beta_30_spy
float64 | rel_ret_qqq
float64 | alpha_30_qqq
float64 | beta_30_qqq
float64 | Date
timestamp[ns] |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
46.777637
| 40.681915
| 1.149839
| 0.585558
| -0.039651
| 0.62521
| 15.567047
| 20.422447
| 23.0325
| 49.933711
| 69.595787
| 76.038956
| -1.355719
| -1.476788
| 0.026033
| 45.427012
| 48.113645
| 50.800278
| 11.167862
| 0.505124
| 0.111679
| 0.505124
| 38,894,639,000
| 1.103471
| -0.027722
| 0.019978
| -0.005614
| 1
| 1
| 0
| 0
| -0.794729
| -0.719393
| 49.395816
| 50.067775
| 48.822467
| 50.641124
| 48.150507
| -0.047
| 2.433759
| 46.681784
| 0.031263
| 0.123506
| 0.011952
| 0.123506
| 0.5
| 0
| -0.02211
| -0.079429
| 1.828507
| -0.010655
| -0.071518
| 1.671258
| 2024-01-02T00:00:00
|
46.901281
| 40.79111
| 1.149792
| 0.443431
| -0.145423
| 0.588854
| 15.135036
| 19.394514
| 23.475243
| 46.734961
| 45.525828
| 64.971392
| -3.470026
| -5.008279
| 0.025775
| 45.797192
| 48.216738
| 50.636283
| 10.036122
| 0.360672
| 0.100361
| 0.360672
| 38,573,743,000
| 0.874712
| -0.012514
| -0.543202
| -0.014179
| 1
| 2
| 0
| 0
| -1.049602
| -0.944162
| 48.325742
| 49.082985
| 47.383935
| 50.024793
| 46.626692
| -0.058851
| 2.391058
| 46.681784
| 0.018438
| 0.258964
| 0.011952
| 0.079681
| 0.5
| 0
| -0.004313
| -0.078814
| 1.758569
| -0.001876
| -0.069475
| 1.612156
| 2024-01-03T00:00:00
|
47.001761
| 40.901574
| 1.149143
| 0.361227
| -0.182101
| 0.543329
| 14.388105
| 20.124582
| 22.099841
| 49.242829
| 26.04955
| 47.057055
| -2.871465
| -3.237628
| 0.025197
| 45.989705
| 48.288298
| 50.58689
| 9.520288
| 0.431041
| 0.095203
| 0.431041
| 38,880,278,000
| 0.843056
| 0.008978
| -0.268853
| 0.004162
| 1
| 3
| 0
| 0
| -1.478105
| -1.296964
| 47.664446
| 48.035239
| 47.171722
| 48.527963
| 46.800929
| -0.050363
| 2.421641
| 46.681784
| 0.027623
| 0.577689
| 0.007968
| 0.071713
| 0.5
| 0
| 0.012204
| -0.081227
| 1.577333
| 0.014138
| -0.065522
| 1.500822
| 2024-01-04T00:00:00
|
47.110457
| 41.016036
| 1.148586
| 0.380326
| -0.130402
| 0.510728
| 14.044829
| 24.381816
| 20.117758
| 55.077843
| 28.953903
| 33.509761
| -0.858211
| 2.049411
| 0.025127
| 46.545224
| 48.467898
| 50.390571
| 7.933802
| 0.656491
| 0.079338
| 0.656491
| 39,295,317,000
| 1.13609
| 0.022638
| 0.610115
| 0.009667
| 1
| 4
| 0
| 0
| -0.500347
| -0.438098
| 47.975276
| 48.469002
| 47.477553
| 48.966724
| 46.983828
| -0.02862
| 2.499985
| 46.681784
| 0.051152
| 0.784861
| 0.007968
| 0.039841
| 0.533333
| 0
| 0.02127
| -0.052872
| 1.572446
| 0.021453
| -0.040628
| 1.514638
| 2024-01-05T00:00:00
|
47.319894
| 41.144925
| 1.150078
| 0.642577
| 0.105479
| 0.537098
| 15.512123
| 34.546351
| 16.790502
| 66.859992
| 59.472969
| 38.158807
| 5.514723
| 6.660546
| 0.026267
| 46.410041
| 48.75059
| 51.09114
| 9.602138
| 1.241988
| 0.096021
| 1.241988
| 39,937,827,000
| 1.691232
| 0.062299
| 2.8928
| 0.008453
| 1
| 0
| 0
| 0
| 1.788715
| 1.842977
| 48.956057
| 49.633014
| 48.392704
| 50.196367
| 47.715747
| -0.000421
| 2.724967
| 47.851809
| 0.091367
| 0.976096
| 0.027888
| 0.079681
| 0.566667
| 0
| 0.048124
| 0.024001
| 2.152595
| 0.041842
| 0.030194
| 1.877233
| 2024-01-08T00:00:00
|
47.576102
| 41.274635
| 1.152672
| 0.911439
| 0.299473
| 0.611966
| 17.72906
| 40.111883
| 14.62997
| 69.297302
| 79.907538
| 56.11147
| 10.322212
| 8.826553
| 0.027525
| 46.092813
| 49.032133
| 51.971454
| 11.989365
| 1.193745
| 0.119894
| 1.193745
| 40,710,927,000
| 1.929854
| 0.016833
| 2.704717
| 0.002832
| 1
| 1
| 0
| 0
| 2.748682
| 2.788486
| 51.307086
| 53.162719
| 50.368275
| 54.101531
| 48.512642
| -0.021813
| 2.511233
| 48.413262
| 0.097022
| 0.713147
| 0.035857
| 0.215139
| 0.6
| 0
| 0.018351
| 0.062451
| 2.076302
| 0.014859
| 0.063126
| 1.856507
| 2024-01-09T00:00:00
|
47.853019
| 41.41245
| 1.155523
| 1.20817
| 0.476963
| 0.731207
| 19.885911
| 38.594743
| 13.586766
| 72.291106
| 93.068456
| 77.482988
| 14.255076
| 10.290396
| 0.026909
| 45.889112
| 49.418068
| 52.947024
| 14.282047
| 1.194493
| 0.14282
| 1.194493
| 41,244,723,000
| 1.328499
| 0.022515
| 2.707631
| 0.008957
| 1
| 2
| 0
| 0
| 3.040074
| 3.123856
| 53.022129
| 54.383038
| 51.749503
| 55.655664
| 50.388594
| -0.004579
| 2.514356
| 48.244519
| 0.125926
| 0.784861
| 0.035857
| 0.302789
| 0.6
| 0
| 0.016875
| 0.067817
| 2.158062
| 0.01576
| 0.068306
| 1.893351
| 2024-01-10T00:00:00
|
48.126159
| 41.553862
| 1.158163
| 1.464514
| 0.586646
| 0.877868
| 22.148835
| 38.867357
| 12.420056
| 73.381473
| 91.040207
| 88.005401
| 14.217245
| 10.937537
| 0.027099
| 45.643767
| 49.776118
| 53.908469
| 16.60375
| 1.10684
| 0.166037
| 1.10684
| 41,841,482,000
| 1.444859
| 0.008647
| 2.365899
| 0.011941
| 1
| 3
| 0
| 0
| 3.50495
| 3.442757
| 54.116183
| 54.773151
| 53.662769
| 55.226565
| 53.005802
| -0.009468
| 2.5403
| 48.511836
| 0.129445
| 0.569721
| 0.039841
| 0.434263
| 0.633333
| 0
| 0.009088
| 0.086659
| 2.132248
| 0.006568
| 0.086257
| 1.900986
| 2024-01-11T00:00:00
|
48.404676
| 41.69532
| 1.160914
| 1.639735
| 0.609494
| 1.030242
| 24.250121
| 37.620673
| 12.021678
| 72.650957
| 94.037646
| 92.715436
| 11.432487
| 10.476161
| 0.02605
| 45.539886
| 50.107034
| 54.674183
| 18.229569
| 1.000587
| 0.182296
| 1.000587
| 41,488,488,000
| 0.864583
| -0.002045
| 1.951647
| -0.003685
| 1
| 4
| 0
| 0
| 3.277208
| 3.379584
| 54.545612
| 55.561045
| 53.77604
| 56.330617
| 52.760607
| -0.011491
| 2.533067
| 48.511836
| 0.127138
| 0.40239
| 0.027888
| 0.541833
| 0.6
| 0
| -0.002737
| 0.076569
| 2.153102
| -0.002558
| 0.076076
| 1.91348
| 2024-01-12T00:00:00
|
48.685734
| 41.842265
| 1.163554
| 1.891634
| 0.689114
| 1.20252
| 26.784537
| 42.780046
| 10.784751
| 76.424367
| 93.59537
| 92.891074
| 7.901932
| 13.852425
| 0.026164
| 45.276359
| 50.508411
| 55.740463
| 20.717547
| 1.058308
| 0.207175
| 1.058308
| 41,938,068,000
| 1.093337
| 0.030103
| 2.176686
| 0.00563
| 1
| 1
| 0
| 0
| 4.896114
| 5.225178
| 54.639566
| 54.979376
| 54.339733
| 55.27921
| 53.999923
| -0.00797
| 2.489453
| 48.325304
| 0.166068
| 0.876494
| 0.031873
| 0.669323
| 0.633333
| 1
| 0.033781
| 0.143152
| 2.060952
| 0.030201
| 0.132631
| 1.829606
| 2024-01-16T00:00:00
|
48.936611
| 41.985573
| 1.165558
| 2.041204
| 0.670947
| 1.370257
| 28.962943
| 39.238331
| 10.657111
| 74.253428
| 93.032125
| 93.555047
| 5.481751
| 16.369801
| 0.026644
| 45.174288
| 50.866362
| 56.558436
| 22.380504
| 0.952861
| 0.223805
| 0.952861
| 41,463,674,000
| 1.154462
| -0.005852
| 1.765576
| -0.000621
| 1
| 2
| 0
| 0
| 4.724839
| 5.040637
| 56.007796
| 57.146161
| 55.212241
| 57.941716
| 54.073876
| -0.013759
| 2.351735
| 48.325304
| 0.159264
| 0.346614
| 0.043825
| 0.74502
| 0.633333
| 1
| -0.000278
| 0.148879
| 2.114257
| -0.000195
| 0.135393
| 1.82938
| 2024-01-17T00:00:00
|
49.178595
| 42.132179
| 1.167245
| 2.21916
| 0.679122
| 1.540038
| 31.30424
| 41.728451
| 9.87062
| 76.551509
| 94.074947
| 93.567481
| 5.07268
| 20.050871
| 0.026219
| 44.934163
| 51.217666
| 57.501169
| 24.536468
| 0.966104
| 0.245365
| 0.966104
| 41,955,324,000
| 1.185055
| 0.018629
| 1.81721
| 0.021533
| 1
| 3
| 0
| 0
| 6.188742
| 6.716824
| 55.723626
| 56.737727
| 55.007692
| 57.453661
| 53.993591
| -0.008559
| 2.414759
| 48.687603
| 0.172274
| 0.741036
| 0.035857
| 0.796813
| 0.666667
| 1
| 0.009775
| 0.180594
| 1.967472
| 0.004535
| 0.157804
| 1.692476
| 2024-01-18T00:00:00
|
49.453322
| 42.289759
| 1.169392
| 2.523365
| 0.786662
| 1.736703
| 33.913032
| 45.852556
| 8.789981
| 80.739184
| 95.637285
| 94.248119
| 8.516662
| 23.944742
| 0.026244
| 44.532088
| 51.711741
| 58.891395
| 27.767982
| 1.039451
| 0.27768
| 1.039451
| 42,498,825,000
| 1.297671
| 0.040898
| 2.103166
| 0.015445
| 1
| 4
| 0
| 0
| 6.427432
| 7.245448
| 56.906297
| 57.736834
| 56.244666
| 58.398466
| 55.414128
| -0.000151
| 2.557313
| 48.601749
| 0.223369
| 0.932271
| 0.039841
| 0.824701
| 0.666667
| 1
| 0.028509
| 0.18588
| 2.103378
| 0.021261
| 0.158547
| 1.723765
| 2024-01-19T00:00:00
|
49.72723
| 42.450712
| 1.171411
| 2.745941
| 0.807391
| 1.938551
| 36.495669
| 47.025227
| 8.275814
| 80.989171
| 96.642364
| 95.451532
| 9.036729
| 21.502339
| 0.025813
| 44.536453
| 52.288569
| 60.040686
| 29.651285
| 0.972917
| 0.296513
| 0.972917
| 42,951,780,000
| 1.074419
| 0.002736
| 1.84377
| 0.00938
| 1
| 0
| 0
| 0
| 7.416637
| 8.365353
| 58.705962
| 60.218788
| 57.945053
| 60.979697
| 56.432228
| -0.011221
| 2.54713
| 48.672342
| 0.224942
| 0.474104
| 0.023904
| 0.840637
| 0.7
| 1
| 0.000624
| 0.205559
| 2.005974
| 0.001431
| 0.17727
| 1.661339
| 2024-01-22T00:00:00
|
49.993144
| 42.615617
| 1.173118
| 2.906492
| 0.774353
| 2.132139
| 38.383948
| 44.105802
| 10.034475
| 81.339612
| 97.067571
| 96.449074
| 6.191698
| 14.582894
| 0.025462
| 44.579915
| 52.832417
| 61.084918
| 31.240296
| 0.924553
| 0.312403
| 0.924553
| 43,246,434,000
| 0.699405
| 0.003664
| 1.655212
| -0.001408
| 1
| 1
| 0
| 0
| 6.93156
| 7.745265
| 59.651768
| 60.266426
| 59.006127
| 60.912068
| 58.391469
| -0.007591
| 2.361745
| 48.76719
| 0.227048
| 0.49004
| 0.01992
| 0.860558
| 0.7
| 1
| 0.000752
| 0.190176
| 1.982179
| -0.000476
| 0.166932
| 1.67332
| 2024-01-23T00:00:00
|
50.281306
| 42.787184
| 1.175149
| 3.117872
| 0.788586
| 2.329286
| 40.706662
| 51.240992
| 8.724381
| 83.558734
| 93.861206
| 95.857047
| 9.471389
| 15.472338
| 0.026534
| 44.642666
| 53.458668
| 62.27467
| 32.982499
| 0.9463
| 0.329825
| 0.9463
| 43,806,705,000
| 1.283022
| 0.024565
| 1.739998
| 0.007199
| 1
| 2
| 0
| 0
| 7.02944
| 7.906642
| 59.422896
| 60.293412
| 58.969148
| 60.747159
| 58.098633
| -0.02366
| 2.304049
| 48.120336
| 0.274468
| 0.836653
| 0.059761
| 0.868526
| 0.7
| 1
| 0.023473
| 0.198597
| 1.955922
| 0.019031
| 0.171069
| 1.681815
| 2024-01-24T00:00:00
|
50.546883
| 42.957317
| 1.176677
| 3.268282
| 0.751197
| 2.517085
| 42.863467
| 47.083439
| 8.016509
| 83.911587
| 92.771819
| 94.566865
| 7.897448
| 13.37074
| 0.026703
| 44.809087
| 54.075224
| 63.341362
| 34.271288
| 0.905102
| 0.342713
| 0.905102
| 44,289,482,000
| 1.076163
| 0.004147
| 1.579379
| 0.016101
| 1
| 3
| 0
| 0
| 7.93323
| 8.730327
| 61.348823
| 62.793018
| 59.88364
| 64.258202
| 58.439445
| -0.019603
| 2.317779
| 48.390998
| 0.272606
| 0.498008
| 0.067729
| 0.880478
| 0.733333
| 1
| -0.001277
| 0.219878
| 1.973759
| 0.002927
| 0.201177
| 1.786299
| 2024-01-25T00:00:00
|
50.79505
| 43.126569
| 1.177813
| 3.302158
| 0.628059
| 2.6741
| 44.5859
| 44.56257
| 8.812958
| 79.67947
| 89.412635
| 92.01522
| 2.588614
| 11.32574
| 0.02645
| 45.184331
| 54.655601
| 64.126871
| 34.658003
| 0.834771
| 0.34658
| 0.834771
| 43,899,173,000
| 0.855111
| -0.009556
| 1.305177
| -0.010663
| 1
| 4
| 0
| 0
| 6.982343
| 8.098639
| 61.694292
| 62.572471
| 60.704508
| 63.562254
| 59.826329
| -0.028927
| 2.222062
| 48.390998
| 0.260503
| 0.278884
| 0.055777
| 0.884462
| 0.7
| 1
| -0.008285
| 0.1943
| 1.988534
| -0.00358
| 0.18368
| 1.791578
| 2024-01-26T00:00:00
|
51.051175
| 43.306356
| 1.178838
| 3.405399
| 0.585039
| 2.820359
| 46.325159
| 44.567108
| 8.195162
| 82.063498
| 91.496575
| 91.22701
| 4.712177
| 14.174733
| 0.025806
| 45.566221
| 55.302391
| 65.038561
| 35.210666
| 0.866049
| 0.352107
| 0.866049
| 44,247,906,000
| 0.755569
| 0.023225
| 1.427122
| 0.003293
| 1
| 0
| 0
| 0
| 7.306386
| 8.564273
| 61.094961
| 61.65065
| 60.441324
| 62.304286
| 59.885635
| -0.00611
| 2.297769
| 48.337469
| 0.291549
| 0.804781
| 0.027888
| 0.89243
| 0.7
| 1
| 0.015336
| 0.21433
| 2.269206
| 0.013036
| 0.20035
| 1.884995
| 2024-01-29T00:00:00
|
51.328826
| 43.487846
| 1.180303
| 3.472112
| 0.521402
| 2.95071
| 48.124898
| 46.615382
| 7.739762
| 82.538864
| 91.924681
| 90.94463
| 4.845241
| 11.336942
| 0.025248
| 46.097856
| 55.964622
| 65.831388
| 35.260726
| 0.843295
| 0.352607
| 0.843295
| 44,658,641,000
| 0.887841
| 0.004934
| 1.33841
| 0.006964
| 1
| 1
| 0
| 0
| 7.29121
| 8.54793
| 61.919173
| 62.965255
| 61.384139
| 63.500289
| 60.338057
| -0.011324
| 2.314082
| 49.256275
| 0.273727
| 0.517928
| 0.015936
| 0.896414
| 0.7
| 1
| 0.005708
| 0.217809
| 2.277608
| 0.011613
| 0.205662
| 1.837887
| 2024-01-30T00:00:00
|
51.569719
| 43.66163
| 1.181122
| 3.385392
| 0.347746
| 3.037646
| 48.29815
| 42.352142
| 13.910927
| 74.013648
| 89.859705
| 91.093654
| 0.268892
| 9.765748
| 0.026327
| 47.174864
| 56.6322
| 66.089535
| 33.399146
| 0.756972
| 0.333991
| 0.756972
| 44,204,846,000
| 0.97643
| -0.020065
| 1.001861
| -0.021251
| 1
| 2
| 1
| 0
| 6.190268
| 7.310675
| 62.807336
| 63.389346
| 62.157031
| 64.039651
| 61.575021
| -0.030964
| 2.248248
| 49.120699
| 0.25187
| 0.159363
| 0.063745
| 0.87251
| 0.666667
| 1
| -0.003613
| 0.201441
| 2.142295
| -0.000284
| 0.199094
| 1.754543
| 2024-01-31T00:00:00
|
🚀 QuantAlpha NASDAQ-100 Feature-Engineered Sample
This dataset provides a representative sample of the full QuantAlpha NASDAQ-100 dataset. It allows researchers and quantitative traders to explore the schema and feature richness of the NVDA dataset before accessing the full NASDAQ-100 universe.
📁 Dataset Contents
The sample consists of one Parquet file containing a randomly selected month of data from 2024 for NVIDIA (NVDA):
| Ticker | Filename | Rows | Date Range |
|---|---|---|---|
| NVDA | NVDA_2024_month01.parquet |
~21 | January 2024 |
⚠️ Note: This is a limited sample. The full dataset includes all NASDAQ-100 constituents and multi-year historical coverage.
📊 Feature Overview
Each record contains 53 machine-learning-ready features, including:
- Trend Indicators: SMA ratios, MACD, ADX, Trend Persistence
- Momentum & Volatility: RSI, Stochastic Oscillator, ROC, Normalized ATR, Bollinger Band metrics
- Volume Metrics: On-Balance Volume (OBV), Volume Ratios
- Performance Metrics: Log Returns, 30-day Sharpe Ratio, 30-day Sortino Ratio
- Benchmark Analysis: Relative returns, Alpha, Beta vs. SPY and QQQ
- Market Microstructure: Price over Control (POC), Gap percentages, Z-scores
All features are cleaned, normalized, and free of look-ahead bias, making them ready for ML pipelines with XGBoost, LightGBM, or neural networks.
🛠 Usage
You can load the sample file directly into a Pandas DataFrame using fastparquet or pyarrow:
import pandas as pd
# Load the sample file
df = pd.read_parquet("NVDA_2024_month01.parquet")
# Inspect the data
print(df.info())
display(df.head())
📜 License
This sample is provided under the Creative Commons Attribution Non-Commercial 4.0 (CC BY-NC 4.0) license. For commercial licensing of the full NASDAQ-100 universe, please visit our Gumroad storefront.
📬 Contact & Support
If you have any questions about this dataset, licensing, or access to the full version, feel free to reach out:
📧 Email: quantalpha.global@gmail.com
Please note that this email is intended for dataset-related inquiries only.
We aim to respond within 1–2 business days.
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