Download script forex - LiteForex

Releasing a Decade of Forex Tick Data I Crawled and Converted

Releasing a Decade of Forex Tick Data I Crawled and Converted

Intro:

In my exploration of the world of big data and I became curious about tick data. Unfortunately, market data is almost always behind a paywall or de-sampled to the point of uselessness. After discovering the Dukascopy API, I knew I wanted to make this data available for all in a more accessible format. Over the course of a few months, I downloaded, cleaned, parsed, and compressed over a decade of Forex tick data on 37 currency pairs and commodities. Today I am happy to finally release the final result of my work to the DataHoarder community!

Download Links:

Warning: I have rented a seedbox for the next 3 months from seedbox.io but I have been having some issues. If you have any issues with the torrent please leave a comment. Also, PLEASE SEED when you are done. This is quite a large data set and I can only push so much data on my own.
Torrent File: https://drive.google.com/file/d/18ymZWeFLJK7FggK_iiWZ-TxgWIVdJVvv/view?usp=sharingCompanion Blog Post: https://www.driftinginrecursion.com/post/dukascopy_opensource_data/

Stats Overview:

Totals Quantities
Total Files 463
Total Line Count 8,495,770,706
Total Data Points 33,983,082,824
Total Decompressed Size 501 GB
Total Compressed Size 61 GB

About the Data:

The data was collected from https://www.dukascopy.com/ via a public API that allows for the download of tick data on the hour level. These files come in the form of a .bi5 file. The data starts as early as 2004 all the way to 2019.
These files were decompressed, then merged into yearly CSV’s named in the following convention. “AUDCHF_tick_UTC+0_00_2011.csv” or ‘Pair_Resolution_Timezone_Year.csv’
These CSV’s are split into 3 categories “Majors”, “Crosses”, “Commodities”.
Majors, Crosses, and Commodities have had their timestamps modified so that they are in the official UTC ISO standard. This was originally done for a Postgresql database that quickly became obsolesced. Any files that have been modified are appended with a “-Parse”. These timestamps have been modified in the following format.
Millisecond timestamps to UTC +00:00 time [2017.01.01 22:37:08.014] -- [2017-01-01T22:37:08.014+00:00]
https://preview.redd.it/x6g277skfiu51.png?width=1399&format=png&auto=webp&s=35cd6735c1826424580919ac3377612377a3107c

User Resources:

For those looking to use this data in a live context or update it frequently, I have included a number of tools for both Windows and Linux that will be useful.

Windows

The ~/dukascopy/resources/windows folder contains a third party tool written in java that can download and convert Dukascopy’s .bi5 files. I have also included the latest zstd binaries from Zstandard Github page.

Linux

Linux is my daily driver in 99% of cases, so I have developed all my scraping tools using Linux only tools. In the ~/dukascopy/resources/linux folder you will find a number of shell script and pyhton3 files that I used to collect this data. There are quite a few files in this directory but I will cover the core ones below.

download-day.py:

This file is used to download a single symbol for a single day and then convert and merge all 24 .bi5 files into a single CSV.

download-year.py

This file is used to download a single symbol for a full year and then convert and merge all .bi5 files into a single CSV.

dukascopy.py

This file contains all the core logic for downloading and converting data from dukascopy.

utc-timestamp-convert.py

This tad slow but works well enough. It requires the pandas project and parses timestamps into the UTC ISO standard. This is useful for those looking to maintain the format of new files with the those in this repo, or those looking to use this in a SQL database.
submitted by jtimperio to DataHoarder [link] [comments]

Universal Bypass - Changelog

Universal Bypass

Changelog

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submitted by Hakorr to UniversalBypass [link] [comments]

How to optimise the speed of my Pandas code?

Hi learnpython,
My first attempt at writing my own project. Prior to this I had never used classes or Pandas so it's been a difficult learning curve. I was hoping to get some feedback on the overall structure - does everything look sensible? Are there better ways of writing some bits?
I also wanted to specifically check how I can increase the execution speed. I currently iterate rows which Pandas did say will be slow, but I couldn't see a workaround. The fact it is quite slow makes me think there is a better solution that I'm missing.
To run the code yourself download a .csv of Forex data and store in same folder as script - I used Yahoo finance GBP USD.
"""This program simulates a Double SMA (single moving average) trading strategy. The user provides a .csv file containing trade history and two different window sizes for simple moving averages (smallest number first). The .csv must contain date and close columns - trialled on Yahoo FX data). The program will generate a 'buy' signal when the short SMA is greater than the long SMA, and vice versa. The results of each trade are stored and can be output to a .csv file.""" import pandas as pd class DoubleSMA(): """Generates a Double SMA trading system.""" def __init__(self, name, sma_a, sma_b): """Don't know what goes here.""" self.name = name self.sma_a = sma_a self.sma_b = sma_b self.index = 0 self.order = 'Start' self.signal = '' def gen_sma(self, dataset, sma): """Calculates SMA and adds as column to dataset.""" col_title = 'sma' + str(sma) dataset[col_title] = dataset['Close'].rolling(sma).mean() return dataset def gen_signal(self, row, dataset): """Generates trade signal based on comparison of SMAs.""" if row[0] == (dataset.shape[0] - 1): #Reached final line of dataset; close current trade. self.order = 'Finish' elif row[3] > row[4]: self.signal = 'Buy' elif row[3] < row[4]: self.signal = 'Sell' def append_result(row, result, order): """Adds 'entry' details to results dataframe (i.e. opens trade).""" result = result.append({"Entry date": row[1], "Pair": "GBPUSD", "Order": order, "Entry price": row[2]}, ignore_index=True) return result def trade(row, order, signal, index, result): """Executes a buy or sell routine depending on signal. Flips between 'buy' and 'sell' on each trade.""" if order == 'Start': order = signal result = append_result(row, result, order) elif order == 'Finish': result.iloc[index, 1] = row[1] result.iloc[index, 5] = row[2] elif order != signal: #Close current trade result.iloc[index, 1] = row[1] result.iloc[index, 5] = row[2] index += 1 order = signal result = append_result(row, result, order) return order, index, result def result_df(): """Creates a dataframe to store the results of each trade.""" result = pd.DataFrame({"Entry date": [], "Exit date": [], "Pair": [], "Order": [], "Entry price": [], "Exit price": [], "P/L": []}) return result def dataset_df(): """Opens and cleans up the data to be analysed.""" dataset = pd.read_csv('GBPUSD 2003-2020 Yahoo.csv', usecols=['Date', 'Close']) dataset.dropna(inplace=True) dataset['Close'] = dataset['Close'].round(4) return dataset def store_result(result): """Outputs results table to .csv.""" result.to_csv('example.csv') def calc_pl(result): """Calculates the profil/loss of each row of result dataframe.""" pass #Complete later dataset = dataset_df() result = result_df() sma_2_3 = DoubleSMA('sma_2_3', 2, 3) dataset = sma_2_3.gen_sma(dataset, sma_2_3.sma_a) dataset = sma_2_3.gen_sma(dataset, sma_2_3.sma_b) dataset.dropna(inplace=True) dataset.reset_index(inplace=True, drop=True) for row in dataset.itertuples(): sma_2_3.gen_signal(row, dataset) sma_2_3.order, sma_2_3. index, result = trade(row, sma_2_3.order, sma_2_3.signal, sma_2_3.index, result) calc_pl(result) print(result) store_result(result) 
submitted by tbYuQfzB to learnpython [link] [comments]

MAME 0.214

MAME 0.214

With the end of September almost here, it’s time to see what goodies MAME 0.214 delivers. This month, we’ve got support for five more Nintendo Game & Watch titles (Fire, Flagman, Helmet, Judge and Vermin), four Chinese computers from the 1980s, and three Motorola CPU evaluation kits. Cassette support has been added or fixed for a number of systems, the Dragon Speech Synthesis module has been emulated, and the Dragon Sound Extension module has been fixed. Acorn Archimedes video, sound and joystick support has been greatly improved.
On the arcade side, remaining issues in Capcom CPS-3 video emulation have been resolved and CD images have been upgraded to CHD version 5, Sega versus cabinet billboard support has been added to relevant games, and long-standing issues with music tempo in Data East games have been worked around.
Of course, you can get the source and Windows binary packages from the download page.

MAMETesters Bugs Fixed

New working machines

New working clones

Machines promoted to working

Clones promoted to working

New machines marked as NOT_WORKING

New clones marked as NOT_WORKING

New working software list additions

Software list items promoted to working

New NOT_WORKING software list additions

Source Changes

submitted by cuavas to emulation [link] [comments]

MAME 0.214

MAME 0.214

With the end of September almost here, it’s time to see what goodies MAME 0.214 delivers. This month, we’ve got support for five more Nintendo Game & Watch titles (Fire, Flagman, Helmet, Judge and Vermin), four Chinese computers from the 1980s, and three Motorola CPU evaluation kits. Cassette support has been added or fixed for a number of systems, the Dragon Speech Synthesis module has been emulated, and the Dragon Sound Extension module has been fixed. Acorn Archimedes video, sound and joystick support has been greatly improved.
On the arcade side, remaining issues in Capcom CPS-3 video emulation have been resolved and CD images have been upgraded to CHD version 5, Sega versus cabinet billboard support has been added to relevant games, and long-standing issues with music tempo in Data East games have been worked around.
Of course, you can get the source and Windows binary packages from the download page.

MAMETesters Bugs Fixed

New working machines

New working clones

Machines promoted to working

Clones promoted to working

New machines marked as NOT_WORKING

New clones marked as NOT_WORKING

New working software list additions

Software list items promoted to working

New NOT_WORKING software list additions

Source Changes

submitted by cuavas to MAME [link] [comments]

MAME 0.214

MAME 0.214

With the end of September almost here, it’s time to see what goodies MAME 0.214 delivers. This month, we’ve got support for five more Nintendo Game & Watch titles (Fire, Flagman, Helmet, Judge and Vermin), four Chinese computers from the 1980s, and three Motorola CPU evaluation kits. Cassette support has been added or fixed for a number of systems, the Dragon Speech Synthesis module has been emulated, and the Dragon Sound Extension module has been fixed. Acorn Archimedes video, sound and joystick support has been greatly improved.
On the arcade side, remaining issues in Capcom CPS-3 video emulation have been resolved and CD images have been upgraded to CHD version 5, Sega versus cabinet billboard support has been added to relevant games, and long-standing issues with music tempo in Data East games have been worked around.
Of course, you can get the source and Windows binary packages from the download page.

MAMETesters Bugs Fixed

New working machines

New working clones

Machines promoted to working

Clones promoted to working

New machines marked as NOT_WORKING

New clones marked as NOT_WORKING

New working software list additions

Software list items promoted to working

New NOT_WORKING software list additions

Source Changes

submitted by cuavas to cade [link] [comments]

Looking back 18 months.

I was going through old emails today and came across this one I sent out to family on January 4, 2018. It was a reflection on the 2017 crypto bull market and where I saw it heading, as well as some general advice on crypto, investment, and being safe about how you handle yourself in cryptoland.
I feel that we are on the cusp of a new bull market right now, so I thought that I would put this out for at least a few people to see *before* the next bull run, not after. While the details have changed, I don't see a thing in this email that I fundamentally wouldn't say again, although I'd also probably insist that people get a Yubikey and use that for all 2FA where it is supported.
Happy reading, and sorry for some of the formatting weirdness -- I cleaned it up pretty well from the original email formatting, but I love lists and indents and Reddit has limitations... :-/
Also, don't laught at my token picks from January 2018! It was a long time ago and (luckliy) I took my own advice about moving a bunch into USD shortly after I sent this. I didn't hit the top, and I came back in too early in the summer of 2018, but I got lucky in many respects.
----------------------------------------------------------------------- Jan-4, 2018
Hey all!
I woke up this morning to ETH at a solid $1000 and decided to put some thoughts together on what I think crypto has done and what I think it will do. *******, if you could share this to your kids I’d appreciate it -- I don’t have e-mail addresses, and it’s a bit unwieldy for FB Messenger… Hopefully they’ll at least find it thought-provoking. If not, they can use it as further evidence that I’m a nutjob. 😉
Some history before I head into the future.
I first mined some BTC in 2011 or 2012 (Can’t remember exactly, but it was around the Christmas holidays when I started because I had time off from work to get it set up and running.) I kept it up through the start of summer in 2012, but stopped because it made my PC run hot and as it was no longer winter, ********** didn’t appreciate the sound of the fans blowing that hot air into the room any more. I’ve always said that the first BTC I mined was at $1, but looking back at it now, that’s not true – It was around $2. Here’s a link to BTC price history.
In the summer of 2013 I got a new PC and moved my programs and files over before scrapping the old one. I hadn’t touched my BTC mining folder for a year then, and I didn’t even think about salvaging those wallet files. They are now gone forever, including the 9-10BTC that were in them. While I can intellectually justify the loss, it was sloppy and underlines a key thing about cryptocurrency that I believe will limit its widespread adoption by the general public until it is addressed and solved: In cryptoland, you are your own bank, and if you lose your password or account number, there is no person or organization that can help you reset it so that you can get access back. Your money is gone forever.
On April 12, 2014 I bought my first BTC through Coinbase. BTC had spiked to $1000 and been in the news, at least in Japan. This made me remember my old wallet and freak out for a couple of months trying to find it and reclaim the coins. I then FOMO’d (Fear Of Missing Out”) and bought $100 worth of BTC. I was actually very lucky in my timing and bought at around $430. Even so, except for a brief 50% swing up almost immediately afterwards that made me check prices 5 times a day, BTC fell below my purchase price by the end of September and I didn’t get back to even until the end of 2015.
In May 2015 I bought my first ETH at around $1. I sent some guy on bitcointalk ~$100 worth of BTC and he sent me 100 ETH – all on trust because the amounts were small and this was a small group of people. BTC was down in the $250 range at that point, so I had lost 30-40% of my initial investment. This was of the $100 invested, so not that much in real terms, but huge in percentages. It also meant that I had to buy another $100 of BTC on Coinbase to send to this guy. A few months after I purchased my ETH, BTC had doubled and ETH had gone down to $0.50, halving the value of my ETH holdings. I was even on the first BTC purchase finally, but was now down 50% on the ETH I had bought.
The good news was that this made me start to look at things more seriously. Where I had skimmed white papers and gotten a superficial understanding of the technology before FOMO’ing, I started to act as an investor, not a speculator. Let me define how I see those two different types of activity:
So what has been my experience as an investor? After sitting out the rest of 2015 because I needed to understand the market better, I bought into ETH quite heavily, with my initial big purchases being in March-April of 2016. Those purchases were in the $11-$14 range. ETH, of course, dropped immediately to under $10, then came back and bounced around my purchase range for a while until December of 2016, when I purchased a lot more at around $8.
I also purchased my first ICO in August of 2016, HEAT. I bought 25ETH worth. Those tokens are now worth about half of their ICO price, so about 12.5ETH or $12500 instead of the $25000 they would be worth if I had just kept ETH. There are some other things with HEAT that mean I’ve done quite a bit better than those numbers would suggest, but the fact is that the single best thing I could have done is to hold ETH and not spend the effort/time/cost of working with HEAT. That holds true for about every top-25 token on the market when compared to ETH. It certainly holds true for the many, many tokens I tried to trade in Q1-Q2 of 2017. In almost every single case I would have done better and slept better had I just held ETH instead of trying to be smarter than Mr. Market.
But, I made money on all of them except one because the crypto market went up more in USD terms than any individual coin went down in ETH or BTC terms. This underlines something that I read somewhere and that I take to heart: A rising market makes everyone seem like a genius. A monkey throwing darts at a list of the top 100 cryptocurrencies last year would have doubled his money. Here’s a chart from September that shows 2017 year-to-date returns for the top 10 cryptocurrencies, and all of them went up a *lot* more between then and December. A monkey throwing darts at this list there would have quintupled his money.
When evaluating performance, then, you have to beat the monkey, and preferably you should try to beat a Wall Street monkey. I couldn’t, so I stopped trying around July 2017. My benchmark was the BLX, a DAA (Digital Asset Array – think fund like a Fidelity fund) created by ICONOMI. I wasn’t even close to beating the BLX returns, so I did several things.
  1. I went from holding about 25 different tokens to holding 10 now. More on that in a bit.
  2. I used those funds to buy ETH and BLX. ETH has done crazy-good since then and BLX has beaten BTC handily, although it hasn’t done as well as ETH.
  3. I used some of those funds to set up an arbitrage operation.
The arbitrage operation is why I kept the 11 tokens that I have now. All but a couple are used in an ETH/token pair for arbitrage, and each one of them except for one special case is part of BLX. Why did I do that? I did that because ICONOMI did a better job of picking long-term holds than I did, and in arbitrage the only speculative thing you must do is pick the pairs to trade. My pairs are (No particular order):
I also hold PLU, PLBT, and ART. These two are multi-year holds for me. I have not purchased BTC once since my initial $200, except for a few cases where BTC was the only way to go to/from an altcoin that didn’t trade against ETH yet. Right now I hold about the same 0.3BTC that I held after my first $100 purchase, so I don’t really count it.
Looking forward to this year, I am positioning myself as follows:
Looking at my notes, I have two other things that I wanted to work into this email that I didn’t get to, so here they are:
  1. Just like with free apps and other software, if you are getting something of value and you didn’t pay anything for it, you need to ask why this is. With apps, the phrase is “If you didn’t pay for the product, you are the product”, and this works for things such as pump groups, tips, and even technical analysis. Here’s how I see it.
    1. People don’t give tips on stocks or crypto that they don’t already own that stock or token. Why would they, since if they convince anyone to buy it, the price only goes up as a result, making it more expensive for them to buy in? Sure, you will have friends and family that may do this, but people in a crypto club, your local cryptocurrency meetup, or online are generally not your friends. They are there to make money, and if they can get you to help them make money, they will do it. Pump groups are the worst of these, and no matter how enticing it may look, stay as far away as possible from these scams. I even go so far as to report them when I see them advertise on FB or Twitter, because they are violating the terms of use.
    2. Technical analysis (TA) is something that has been argued about for longer than I’ve been alive, but I think that it falls into the same boat. In short, TA argues that there are patterns in trading that can be read and acted upon to signal when one must buy or sell. It has been used forever in the stock and foreign exchange markets, and people use it in crypto as well. Let’s break down these assumptions a bit.
i. First, if crypto were like the stock or forex markets we’d all be happy with 5-7% gains per year rather than easily seeing that in a day. For TA to work the same way in crypto as it does in stocks and foreign exchange, the signals would have to be *much* stronger and faster-reacting than they work in the traditional market, but people use them in exactly the same way.
ii. Another area where crypto is very different than the stock and forex markets centers around market efficiency theory. This theory says that markets are efficient and that the price reflects all the available information at any given time. This is why gold in New York is similar in price to gold in London or Shanghai, and why arbitrage margins are easily <0.1% in those markets compared to cryptoland where I can easily get 10x that. Crypto simply has too much speculation and not enough professional traders in it yet to operate as an efficient market. That fundamentally changes the way that the market behaves and should make any TA patterns from traditional markets irrelevant in crypto.
iii. There are services, both free and paid that claim to put out signals based on TA for when one should buy and sell. If you think for even a second that they are not front-running (Placing orders ahead of yours to profit.) you and the other people using the service, you’re naïve.
iv. Likewise, if you don’t think that there are people that have but together computerized systems to get ahead of people doing manual TA, you’re naïve. The guys that I have programming my arbitrage bots have offered to build me a TA bot and set up a service to sell signals once our position is taken. I said no, but I am sure that they will do it themselves or sell that to someone else. Basically they look at TA as a tip machine where when a certain pattern is seen, people act on that “tip”. They use software to see that “tip” faster and take a position on it so that when slower participants come in they either have to sell lower or buy higher than the TA bot did. Remember, if you are getting a tip for free, you’re the product. In TA I see a system when people are all acting on free preset “tips” and getting played by the more sophisticated market participants. Again, you have to beat that Wall Street monkey.
  1. If you still don’t agree that TA is bogus, think about it this way: If TA was real, Wall Street would have figured it out decades ago and we would have TA funds that would be beating the market. We don’t.
  2. If you still don’t agree that TA is bogus and that its real and well, proven, then you must think that all smart traders use them. Now follow that logic forward and think about what would happen if every smart trader pushing big money followed TA. The signals would only last for a split second and would then be overwhelmed by people acting on them, making them impossible to leverage. This is essentially what the efficient market theory postulates for all information, including TA.
OK, the one last item. Read this weekly newsletter – You can sign up at the bottom. It is free, so they’re selling something, right? 😉 From what I can tell, though, Evan is a straight-up guy who posts links and almost zero editorial comments.
Happy 2018.
submitted by uetani to CryptoCurrency [link] [comments]

How to install a Forex Robot in MetaTrader4 - YouTube EARLY BIRD FOREX TRADING SCRIPT 2019 FREE DOWNLOAD MT4 Script Editing Free MT4 Forex session indicator. Download the Forex ... EARLY BIRD FOREX SIGNAL SCRIPT 2019 FREE DOWNLOAD - YouTube MT4 Forex Scripts - YouTube

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How to install a Forex Robot in MetaTrader4 - YouTube

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