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Tag Archives: Historical

Dukascopy Jforex historical tester is full of strange bugs

Dukascopy Jforex historical tester is full of strange bugs

 

This historical tester in Dukascopy JForex is pretty weird. I get this event error when trying to run my strategy:

2018-01-03 00:00:00 Exception java.lang.IllegalArgumentException: The chart cannot be opened for AUD/JPY, select AUD/JPY before testing @ jforex.strategies.sdk.QLNStratFXVol3d.setupChart(QLNStratFXVol3d.java:680)

I do leave the AUD/JPY open before trying this.

I can run it no problem in my demo account so I have no idea what is causing it. Nor do I care as I can just run this thing in regular test mode against all my 40 + subscribed currency pair instruments. I am sure this is caused by something stupid but it looks like sloppy internal programming to cause this. Not only that, you would think the idiot architecture person would have come up with better messaging. I have so much confidence that Dukascopy support is so useless it will get ignored or take a year for a fix. This is just one more reason why I believe ‘rolling your solution’ can work in your favor.

 

Link for instructions: https://www.dukascopy.com/wiki/en/forex-cfds/jforex/historical-tester

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ALL CRYPTO CURRENCY EXCHANGES – HISTORICAL ORDER BOOKS DATA

ALL EXCHANGES – HISTORICAL 10% ORDER BOOKS

This is ain’t cheap for folk but thanks to someone on my Telegram chat group

All Exchanges – Historical 10% Order Books

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Does Dukascopy limit amount of historical forex data to download

Does Dukascopy limit amount of historical forex data to download

This is a set of strange random exceptions thrown by getting to ‘greedy’ with a Dukascopy demo account. Does this happen when you have a live trading account? At this point, I will go back to using my old IQFeed Python script for unlimited forex data.

Note that this forces me to stay on Windows for the download script for my Forex data from IQFeed. I can confirm that IQFeed still does not work properly on Mac OS as of Oct 6/2017.

Exception is:

 

2017-10-05 16:11:31.144 INFO ProtocolVersionClientNegotiatorFilter – Server: DDS2 Standalone Transport Client responded with version: 4
2017-10-05 16:11:31.144 INFO ClientConnector – Child session opened for [d-ja-usa-e-97-4-b.dukascopy.com/107.21.41.150:10443], sending [<ChildSocketAuthAcceptorMessage(parentSessionId=a7ec129c-1038-48d3-bb4d-134700a1491c,timestamp=1507234289627)>], successful consequent attempt [1]
Strategy “HistoryBarsFilter1Week” Strategy ID: 5EB1734D2C5AAC6EAE735A634E65CCB1 is started at 2017-10-05 20:11:32.573 GMT on the local computer with no parameters
com.dukascopy.charts.data.datacache.DataCacheException: Failed to load in-progress candle data in timeout period [NZD/CHF, Monthly, Bid] @ com.dukascopy.charts.data.datacache.IntraperiodCandlesGenerator.getInProgressCandleBlocking(IntraperiodCandlesGenerator.java:1284)
com.dukascopy.charts.data.datacache.DataCacheException: Failed to load in-progress candle data in timeout period [NZD/CHF, Monthly, Bid]: com.dukascopy.api.JFException: com.dukascopy.charts.data.datacache.DataCacheException: Failed to load in-progress candle data in timeout period [NZD/CHF, Monthly, Bid]
at com.dukascopy.api.impl.History.getBar(History.java:208)

 

 

 

 

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Tutorial on fix to download Yahoo Finance historical data in Python

Tutorial on fix to download Yahoo Finance historical data in Python

 

 

Date manipulation for:

https://stackoverflow.com/questions/5158160/python-get-datetime-for-3-years-ago-today

https://www.cyberciti.biz/faq/howto-get-current-date-time-in-python/

https://stackoverflow.com/questions/10624937/convert-datetime-object-to-a-string-of-date-only-in-python

Fix tutorial from

Fix now for Yahoo Finance with Python Historical Datareader

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Fix now for Yahoo Finance with Python Historical Datareader

Fix now for Yahoo Finance with Python Historical Datareader

Note future changes as well

Visit https://github.com/ranaroussi/fix-yahoo-finance

Note requirements but run in your in console:

pip3 install pandas –upgrade

pip3 install numpy –upgrade

pip3 install requests –upgrade

pip3 install multitasking –upgrade

pip3 install fix_yahoo_finance –upgrade –no-cache-dir

Run the supplied example which appears to work ok:

python3

Python 3.6.1 (default, Apr 4 2017, 09:40:21)

[GCC 4.2.1 Compatible Apple LLVM 8.1.0 (clang-802.0.38)] on darwin

Type “help”, “copyright”, “credits” or “license” for more information.

>>> import fix_yahoo_finance as yf

/usr/local/lib/python3.6/site-packages/fix_yahoo_finance/__init__.py:43: DeprecationWarning:

Auto-overriding of pandas_datareader’s get_data_yahoo() is deprecated and will be removed in future versions.

Use pdr_override() to explicitly override it.

DeprecationWarning)

>>> data = yf.download(“SPY”, start=”2017-01-01″, end=”2017-04-30″)

[*********************100%***********************] 1 of 1 downloaded>>>

>>> data

Open High Low Close Adj Close \

Date

2017-01-03 225.039993 225.830002 223.880005 225.240005 223.176010

2017-01-04 225.619995 226.750000 225.610001 226.580002 224.503738

2017-01-05 226.270004 226.580002 225.479996 226.399994 224.325378

2017-01-06 226.529999 227.750000 225.899994 227.210007 225.127960

2017-01-09 226.910004 227.070007 226.419998 226.460007 224.384842

2017-01-10 226.479996 227.449997 226.009995 226.460007 224.384842

2017-01-11 226.360001 227.100006 225.589996 227.100006 225.018967

2017-01-12 226.500000 226.750000 224.960007 226.529999 224.454193

2017-01-13 226.729996 227.399994 226.690002 227.050003 224.969421

2017-01-17 226.309998 226.779999 225.800003 226.250000 224.176743

2017-01-18 226.539993 226.800003 225.899994 226.750000 224.672165

2017-01-19 226.839996 227.000000 225.410004 225.910004 223.839874

2017-01-20 226.699997 227.309998 225.970001 226.740005 224.662262

2017-01-23 226.740005 226.809998 225.270004 226.149994 224.077667

2017-01-24 226.399994 228.080002 226.270004 227.600006 225.514389

2017-01-25 228.699997 229.570007 228.509995 229.570007 227.466339

2017-01-26 229.399994 229.710007 229.009995 229.330002 227.228531

2017-01-27 229.419998 229.589996 228.759995 228.970001 226.871826

2017-01-30 228.169998 228.199997 226.410004 227.550003 225.464844

2017-01-31 226.979996 227.600006 226.320007 227.529999 225.445023

2017-02-01 227.529999 228.589996 226.940002 227.619995 225.534195

2017-02-02 227.619995 228.100006 226.820007 227.770004 225.682831

2017-02-03 228.820007 229.550003 228.460007 229.339996 227.238434

2017-02-06 228.869995 229.330002 228.539993 228.929993 226.832184

2017-02-07 229.380005 229.660004 228.720001 228.940002 226.842117

2017-02-08 228.940002 229.389999 228.309998 229.240005 227.139359

2017-02-09 229.240005 230.949997 229.240005 230.600006 228.486893

2017-02-10 231.000000 231.770004 230.619995 231.509995 229.388550

2017-02-13 232.080002 233.070007 232.050003 232.770004 230.637009

2017-02-14 232.559998 233.710007 232.160004 233.699997 231.558472

… … … … … …

2017-03-17 237.750000 237.970001 237.029999 237.029999 235.879700

2017-03-20 237.029999 237.360001 236.320007 236.770004 235.620972

2017-03-21 237.470001 237.610001 233.580002 233.729996 232.595718

2017-03-22 233.770004 234.610001 233.050003 234.279999 233.143051

2017-03-23 234.279999 235.339996 233.600006 234.029999 232.894257

2017-03-24 234.380005 235.039993 232.960007 233.860001 232.725082

2017-03-27 231.929993 233.919998 231.610001 233.619995 232.486252

2017-03-28 233.270004 235.809998 233.139999 235.320007 234.178009

2017-03-29 234.990005 235.809998 234.729996 235.539993 234.396927

2017-03-30 235.470001 236.520004 235.270004 236.289993 235.143295

2017-03-31 235.899994 236.509995 235.679993 235.740005 234.595978

2017-04-03 235.800003 236.029999 233.910004 235.330002 234.187958

2017-04-04 235.000000 235.580002 234.559998 235.479996 234.337219

2017-04-05 236.259995 237.389999 234.539993 234.779999 233.640625

2017-04-06 234.940002 236.039993 234.429993 235.440002 234.297424

2017-04-07 235.149994 236.000000 234.639999 235.199997 234.058578

2017-04-10 235.360001 236.259995 234.729996 235.339996 234.197906

2017-04-11 234.899994 235.179993 233.339996 235.059998 233.919266

2017-04-12 234.740005 234.960007 233.770004 234.029999 232.894257

2017-04-13 233.639999 234.490005 232.509995 232.509995 231.381638

2017-04-17 233.110001 234.570007 232.880005 234.570007 233.431656

2017-04-18 233.720001 234.490005 233.080002 233.869995 232.735031

2017-04-19 234.520004 234.949997 233.179993 233.440002 232.307129

2017-04-20 234.149994 235.850006 233.779999 235.339996 234.197906

2017-04-21 235.250000 235.309998 234.130005 234.589996 233.451538

2017-04-24 237.179993 237.410004 234.559998 237.169998 236.019028

2017-04-25 237.910004 238.949997 237.809998 238.550003 237.392334

2017-04-26 238.509995 239.529999 238.350006 238.399994 237.243057

2017-04-27 238.770004 238.949997 237.979996 238.600006 237.442093

2017-04-28 238.899994 238.929993 237.929993 238.080002 236.924606

Volume

Date

2017-01-03 91366500

2017-01-04 78744400

2017-01-05 78379000

2017-01-06 71559900

2017-01-09 46939700

2017-01-10 63771900

2017-01-11 74650000

2017-01-12 72113200

2017-01-13 62717900

2017-01-17 61240800

2017-01-18 54793300

2017-01-19 66608800

2017-01-20 129168600

2017-01-23 75061600

2017-01-24 95555300

2017-01-25 84437700

2017-01-26 59970700

2017-01-27 59711100

2017-01-30 79737300

2017-01-31 75880800

2017-02-01 79117700

2017-02-02 69657600

2017-02-03 80563200

2017-02-06 57790100

2017-02-07 57931200

2017-02-08 51566200

2017-02-09 65955200

2017-02-10 66015900

2017-02-13 55182100

2017-02-14 71109000

… …

2017-03-17 89002100

2017-03-20 52537000

2017-03-21 131809300

2017-03-22 97569200

2017-03-23 100410300

2017-03-24 112504900

2017-03-27 87454500

2017-03-28 93483900

2017-03-29 61950400

2017-03-30 56737900

2017-03-31 73733100

2017-04-03 85546500

2017-04-04 56466200

2017-04-05 108800600

2017-04-06 69135800

2017-04-07 74412300

2017-04-10 67615300

2017-04-11 88045300

2017-04-12 81864400

2017-04-13 92880400

2017-04-17 68405400

2017-04-18 83225800

2017-04-19 68699900

2017-04-20 92572200

2017-04-21 110389800

2017-04-24 119209900

2017-04-25 76698300

2017-04-26 84702500

2017-04-27 57410300

2017-04-28 63532800

[81 rows x 6 columns]

>>>

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Build a historical database with Google or Yahoo Finance

How to Build a historical database with Google or Yahoo Finance

Forget these old school databases. Times have changed since these with legacy data feed sources as well. I just focus on Redis NOSQL which answers a lot of my current data repository problems.

Here is the old story of what was posted:

http://quantlabs.net/blog/2014/04/how-to-build-a-historical-database-with-google-or-yahoo-finance/

Here is my latest Redis searches on the blog of the latest interesting info you should know about:

http://quantlabs.net/blog/?s=redis

Just a reminder that the new Quant Analytics service is now fully underway with daily video trading calls based on my human workflow. The new benefit starting this Monday will be the private event on May 22 at 8PM EDT.

>> JOIN HERE <<


Read the full benefits here

Thanks for reading

Bryan

P.S. Don’t forget as this is important to remember:

We are coming down to the wire over the next weeks where this  newsletter will be retired. To continue with the conversation, you will need to be doing the following:

Get my 2 ebooks to opt in for the automated newsletter found on my new server driven by Infusionsoft.

Go here

All future online events can be found here which points to my Facebook Page events page

NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!

Historical quant learning lesson for my BEST moment ever

Historical quant learning lesson for my greatest moment ever

Historical quant learning lesson for my greatest moment ever

Hey…thanks for being part of journey. Now let’s make some real $

As usual, I made a 15 minute on this topic.

Here it is

Also (I know I keep harping on this but it is pivotal you sign for this!)

I have also announced I will be moving this ‘newsletter’ to another server from Infusionsoft. You can also get my free 2 PDFs on (in case you never got them):

Trade Like a Boss

Tecbnical Secrets in Algo Trading

You can also be part of this new newsletter on this server. I am thinking of actually discontinuing this current one you are reading from. It has been highly recommended to manually opt in yourself into this new server.

Sign up for the above FREE PDFs and join the new server here

Thanks Bryan

NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!

Historical quant learning lesson for my greatest moment ever

Historical quant learning lesson for my greatest moment ever

Hey…thanks for being part of journey. Now let’s make some real $

https://www.quantcast.com/quantlabs.net?qcLocale=en_US#trafficCard

https://www.facebook.com/groups/quantlabsnet/

 

 

NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!

Dukascopy historical forex trading data downloader

Dukascopy historical forex trading data downloader

An open source project using Python 3.5 . I use 2.7 but will eventually need to upgrade

https://github.com/giuse88/duka

Thanks to someone my Facebook for sharing this

Join my FREE newsletter to learn more about Python scripts to help in your Dukascopy automated trading

NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!

C++ Status at the end of 2016 with entire historical timeline

C++ Status at the end of 2016 with entire historical timeline

This is the best C++ historical timeline I have seen ever

http://www.bfilipek.com/2016/12/c-status-at-end-of-2016.html

Join my FREE newsletter to learn about how C++ will enhance your algo trading

NOTE I now post my TRADING ALERTS into my personal FACEBOOK ACCOUNT and TWITTER. Don't worry as I don't post stupid cat videos or what I eat!
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