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[Feature Request] Quotes API

I would to see the DarwinInfoAPI \quote API expanded to allow the return of daily Open, High, Low, Close Darwin prices and a volume proxy. This volume proxy could be a historical daily timeseries of Investor Capital.

Or perhaps implement it as a new API: \OHLCV

4 Likes

Hi @ManFromGlad,

Thank you for your suggestion!

I understand you would like a mix of the candle chart and the investor capital progress (already available on the website, not yet through the API), right?

Darwin candle chart:

Capital & investors evolution:

2 Likes

Yes, a JSON array of datetimestamp, open, high, low, close, investor capital, # of investors would be of interest for technical analysis.

3 Likes

I would also like to second this. I was also wondering if darwinex holds finer quote data? I know that they exist for recent periods, but what about the full past? Right now, there is a single quote per day in the retrieved data

The response is a list of points (one point per timestamp), oldest first.
Each period-item contains.
item[0] -> (long) Timestamp
item[1] -> (double) Quote

I looked at this, and the difference between timestamps are a full day (barring weekends and other anomalies). If we could get hourly ohlc quote data, that would be lovely.

2 Likes

Hi @yhlasx,

We are analyzing internally how to offer minute resolution data for the whole history of a Darwin. We do have the info, but the problem is offering it through the API without compromising the performance of our system.

We will inform you all informed as soon as we make any progress.

Cheers

4 Likes

Hi

I just now got access to the API ! I think it is fantastic to have this tool !!

my interest in the API is to use Python do do ML to backtest a porfolio selection model based on historical features at the time.

so I looked at the DarwinInfoAPI - 1.3 the “/products/{productName}/history/”

I am not sure if it is possible to add more historical data, please find below a couple of suggestions:

-historical D-score (I think now it is only current D score that is available)
-historical num of investors and capital , reason I believe it could be a contrarian indicator for forward performance
-historical traders equity and Var, reason is to see skin in the game, assumption is that the more the trader invests in the darwin the more reliable
-historical Monthly divergence & Latency : negative divergence reduces realized returns

and maybe current value for these, since I guess these don’t change much over time:
-assets & timeframes: , the number of assets the darwin trades, I think it is important to know, assumption is that : more assets, more diversified , more robust
-% profitable trades, to see what type of EA it is : scalper vs trend or breakout

Also I noticed by reading some of the darwins descriptions like (https://www.darwinex.com/darwin/LVS.4.20/) that some of the best darwins are portfolios of multiple strategies like a combination of a breakout and trender and a mean reversion EA, it would be good to have this info in a numeric field like “number of strategies in darwin”. Again more strategies make the darwin more robust, that is my assumption

Many thanks

4 Likes

Thanks, rickinvestor!
Good suggestions. I cannot guarantee we will provide these features but certainly we will take them into consideration :slight_smile:

2 Likes

I hope there will be more than just cosideration! :slight_smile:

The features suggested by @rickinvestor are something that could turn a programming exercise into something really useful to build a profitable portfolio.

3 Likes

Hi @rickinvestor,

Great to have you here :slight_smile: Let us know if you need any assistance on the Python front as regards API usage.

You can indeed get historical D-Score (including all the other attributes) by calling ‘/history/badges’:

In [6]: _info = DWX_DarwinInfo_API() 

# Send GET request to "/products/PLF.4.1/history/badges"
In [7]: PLF_scores = _info._Get_Scores_('PLF.4.1')

In [8]: PLF_scores
Out[8]: 
                      Dp         Ex        Mc         Rs         Ra         Os         Cs        Rp        Rm        Dc        La        Pf        Cp         Ds
1414184400000   0.000000   0.000000  0.000000  10.000000  10.000000  10.000000  10.000000  0.000000  0.000000  0.000000  0.000000  7.823545  0.000000   0.000000
1414443600000   0.055556   0.046296  0.000000  10.000000   1.301432   9.940361  10.000000  0.000000  0.000000  0.000000  0.000000  6.528328  0.839300   0.247381
1414530000000   0.108111   0.090093  0.000000  10.000000   0.514035   8.863636   8.563433  0.000000  0.000000  0.000000  0.000000  3.388206  0.839300   0.362124
1414616400000   0.200000   0.166667  0.000000  10.000000   0.514035   8.863636   8.579545  0.000000  0.000000  0.000000  0.000000  3.926517  3.140790   0.815315
1414702800000   0.227222   0.189352  0.000000  10.000000   2.066800   8.080556   8.288889  0.000000  0.000000  0.000000  0.000000  4.207620  2.856062   0.930220
1414789200000   0.309566   0.257971  0.000000  10.000000   2.589524   8.562500   8.562500  0.000000  0.000000  0.000000  0.000000  5.221156  1.543766   1.398663
1415052000000   0.335150   0.279292  0.000000  10.000000   2.640262   7.863131   8.823190  0.000000  0.000000  0.000000  0.000000  5.262936  1.920985   1.498529
1415138400000   0.357749   0.298124  0.000000  10.000000   2.797340   7.822222   8.512931  0.000000  0.000000  0.000000  0.000000  5.483451  1.920985   1.612309
1415224800000   0.369476   0.307897  0.000000  10.000000   3.261605   7.886508   8.512931  0.000000  0.000000  0.000000  0.000000  2.580120  0.929472   1.145996
1415311200000   0.394760   0.328967  0.000000  10.000000   3.348826   7.886508   8.124603  0.000000  0.000000  0.000000  0.000000  3.106680  1.077168   1.332609
1415397600000   0.400542   0.333785  0.000000  10.000000   3.655977   8.511376   8.466667  0.000000  0.000000  0.000000  0.000000  3.515375  1.138513   1.448684
1415656800000   0.414305   0.345254  0.000000  10.000000   3.655977   8.511376   8.761099  0.000000  0.000000  0.000000  0.000000  4.159927  1.278253   1.644149
1415743200000   0.415383   0.346153  0.000000  10.000000   3.723455   8.629808   8.761099  0.000000  0.000000  0.000000  0.000000  4.159027  1.278253   1.651671
1415829600000   0.417733   0.348111  0.000000  10.000000   4.190982   8.664861   8.974458  0.000000  0.000000  0.000000  0.000000  4.320135  1.089133   1.609450
1415916000000   0.442778   0.368981  0.000000  10.000000   4.190982   8.664861   8.974458  0.000000  0.000000  0.000000  0.000000  4.346522  1.259810   1.783496
1416002400000   0.442778   0.368981  0.000000  10.000000   4.473587   8.881195   9.046875  0.000000  0.000000  0.000000  0.000000  4.833321  1.302250   1.877533
1416261600000   0.453098   0.377581  0.000000  10.000000   4.938991   8.845109   8.505435  0.000000  0.000000  0.000000  0.000000  3.617874  1.333226   1.746875
1416348000000   0.475730   0.396442  0.000000  10.000000   4.978649   8.750000   8.416667  0.000000  0.000000  0.000000  0.000000  3.804592  1.333226   1.853228
1416434400000   0.477769   0.398141  0.000000  10.000000   4.978649   8.750000   8.416667  0.000000  0.000000  0.000000  0.000000  3.844151  1.183945   1.797219
1416520800000   0.477769   0.398141  0.000000  10.000000   5.057756   8.646002   8.130198  0.000000  0.000000  0.000000  0.000000  3.894284  1.079043   1.744700
1416607200000   0.480731   0.400609  0.000000  10.000000   5.057756   8.646002   8.130198  0.000000  0.000000  0.000000  0.000000  3.926621  1.088449   1.764369
1416866400000   0.480731   0.400609  0.000000  10.000000   5.373594   8.553030   8.302258  0.000000  0.000000  0.000000  0.000000  3.715377  1.197490   1.785766
1416952800000   0.508350   0.423625  9.998011  10.000000   5.373594   8.553030   8.302258  8.831602  8.503004  8.892336  1.354903  3.748609  1.197490   3.733731
1417039200000   0.508350   0.423625  9.998011  10.000000   5.373594   8.553030   8.302258  8.831602  8.503004  8.892336  1.354903  3.760142  1.211444   3.731457
1417125600000   0.508350   0.423625  9.834055  10.000000   5.477239   8.467262   8.527015  8.880603  8.503004  8.857832  1.354903  3.789622  1.264220   3.705197
1417212000000   0.517806   0.431505  9.917355   9.701396   5.642343   8.383317   8.527015  8.880603  8.503004  8.857832  1.354903  3.536451  1.282538   3.679933
1417471200000   0.528013   0.440011  9.876541   9.638850   6.270122   8.367820   8.815512  8.114385  8.503004  8.761010  1.970581  4.595272  1.370657   3.996319
1417557600000   0.591466   0.492888  9.923966   9.608360   6.397680   8.367820   9.022857  8.162609  8.525662  8.718544  1.970581  5.000000  1.370657   4.594071
1417644000000   0.631197   0.525998  9.953626   9.590061   6.527965   8.228022   9.035714  8.102607  8.525662  8.711685  2.171543  5.777179  1.479632   5.096235
1417730400000   0.655339   0.546116  9.959224   9.590061   6.527965   8.228022   9.035714  8.102607  8.525662  8.711685  2.171543  5.761572  1.355891   5.326950
...                  ...        ...       ...        ...        ...        ...        ...       ...       ...       ...       ...       ...       ...        ...
1545084000000  28.482674  10.000000  9.991166   8.766299   9.877594   9.645433   8.830721  8.530259  7.313556  8.394697  6.153679  6.957483  1.215596  74.468952
1545170400000  28.500592  10.000000  9.989656   8.768926   9.879655   9.640593   8.874419  8.379766  7.326218  8.381287  5.949035  7.233770  1.205401  75.667508
1545256800000  28.549585  10.000000  9.989663   8.768926   9.879655   9.638223   8.880359  8.380999  7.318649  8.390064  5.664756  6.956693  1.194270  74.353436
1545343200000  28.549585  10.000000  9.989077   8.777463   9.884826   9.644536   8.839999  8.396101  7.318649  8.382512  5.308633  6.992396  1.194270  74.134172
1545429600000  28.602988  10.000000  9.988022   8.781112   9.869635   9.657126   8.851449  8.645972  7.322963  8.355021  5.325709  7.305001  1.175885  75.048721
1545688800000  28.647821  10.000000  9.987769   8.781112   9.869635   9.653374   8.846256  8.649782  7.322963  8.355484  5.325709  7.131898  1.143709  74.407433
1545861600000  28.647821  10.000000  9.987741   8.781112   9.869635   9.653374   8.846256  8.649782  7.322963  8.355484  5.325709  7.151627  1.143709  74.481267
1545948000000  28.647821  10.000000  9.988889   8.778292   9.870337   9.646208   8.854028  8.652954  7.284744  8.344501  4.893006  6.884434  1.129796  73.062472
1546034400000  28.686720  10.000000  9.988751   8.774255   9.868038   9.642726   8.812404  8.696824  7.261490  8.303321  4.498935  6.872647  1.109624  72.632708
1546293600000  28.691652  10.000000  9.988775   8.774255   9.868038   9.642726   8.812404  8.696824  7.261490  8.303321  4.498935  6.675181  1.105806  71.896535
1546466400000  28.691652  10.000000  9.987873   8.764151   9.872340   9.641127   8.839804  8.720674  7.261490  8.277692  4.864689  7.207962  1.105806  74.218265
1546552800000  28.740321  10.000000  9.987964   8.761728   9.873461   9.637931   8.851946  8.731918  7.238435  8.270220  4.737119  7.249616  1.107428  74.616718
1546639200000  28.754417  10.000000  9.987927   8.761728   9.873461   9.637931   8.851946  8.731918  7.238435  8.270220  4.737119  7.230999  1.060899  74.567358
1546898400000  28.754417  10.000000  9.987955   8.761728   9.873461   9.637931   8.851946  8.731918  7.238435  8.270220  4.737119  7.228367  1.060899  74.557598
1546984800000  28.754417  10.000000  9.987347   8.747036   9.877768   9.635808   8.901898  8.737468  7.205481  8.255392  4.359498  7.075805  1.060899  73.654758
1547071200000  28.797416  10.000000  9.987357   8.747036   9.877768   9.634048   8.902622  8.737468  7.205481  8.255392  4.359498  7.073417  1.056434  73.648142
1547157600000  28.797416  10.000000  9.987072   8.737362   9.879020   9.635384   8.906720  8.740911  7.205481  8.246140  4.441983  7.228561  1.056434  74.288404
1547244000000  28.810493  10.000000  9.986913   8.719830   9.880208   9.635384   8.906720  8.741077  7.205481  8.242276  4.451924  7.225934  1.049807  74.268606
1547503200000  28.823013  10.000000  9.986565   8.711387   9.880208   9.636261   8.903493  8.744631  7.216009  8.226541  4.847633  7.334491  1.025260  75.002628
1547589600000  28.823150  10.000000  9.988890   8.701009   9.878953   9.627682   8.831737  8.742763  7.209168  8.190512  3.742210  6.604509  1.023620  71.277945
1547676000000  28.864424  10.000000  9.989386   8.699296   9.880722   9.628491   8.819952  8.751650  7.204518  8.154607  3.627226  6.728314  1.017836  71.630406
1547762400000  28.882239  10.000000  9.989356   8.693839   9.879946   9.625127   8.815640  8.752302  7.204518  8.148867  3.760123  6.697105  1.027306  71.595667
1547848800000  28.886945  10.000000  9.989805   8.686343   9.880995   9.621698   8.801809  8.752574  7.204518  8.141668  3.752671  6.807770  1.036427  71.971510
1548108000000  28.897013  10.000000  9.990120   8.687093   9.881084   9.620927   8.782250  8.752574  7.216206  8.128274  3.755979  6.763184  1.036312  71.796469
1548194400000  28.902930  10.000000  9.990021   8.687203   9.881909   9.620927   8.782250  8.734720  7.216206  8.128274  3.755995  6.744454  1.031293  71.722857
1548280800000  28.913985  10.000000  9.989565   8.688059   9.882643   9.620927   8.803658  8.730781  7.216206  8.121655  3.759859  6.764941  1.031152  71.811794
1548367200000  28.929349  10.000000  9.989071   8.688599   9.884706   9.620018   8.820977  8.727546  7.216206  8.115871  3.762323  6.771192  1.025619  71.849986
1548453600000  28.964233  10.000000  9.989303   8.691628   9.885361   9.613499   8.882521  8.750485  7.216206  8.100873  3.623291  6.809733  1.023316  71.929884
1548712800000  28.976388  10.000000  9.988661   8.690352   9.883621   9.608258   8.886167  8.750485  7.216206  8.100873  3.627235  6.714409  1.018413  71.575888
1548799200000  28.985254  10.000000  9.988563   8.688608   9.884127   9.607201   8.868630  8.429244  7.212497  8.103588  3.621674  6.634292  1.012285  71.085409

[1105 rows x 14 columns]
3 Likes

Style and timeframe can be acheived from LA and CP scores.

2 Likes