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Using Python and Pandas to explore trader sentiment data

FXCM’s Speculative Sentiment Index (SSI) focuses on buyers and sellers, comparing how many are active in the market and producing a ratio to indicate how traders are behaving in relation to a particular currency pair. A positive SSI ratio indicates more buyers are in the market than sellers, while a negative SSI ratio indicates that more sellers are in the market. FXCM’s sentiment data was designed around this index, providing 12 sentiment measurements per minute (click here for an overview of each measurement.)
The sample data is stored in a GNU compressed zip file on FXCM’s GitHub as https://sampledata.fxcorporate.com/sentiment/{instrument}.csv.gz. To download the file, we’ll use this URL, but change {instrument} to the instrument of our choice. For this example we’ll use EUUSD price.
import datetime import pandas as pd url = 'https://sampledata.fxcorporate.com/sentiment/EURUSD.csv.gz' data = pd.read_csv(url, compression='gzip', index_col='DateTime', parse_dates=True) """Convert data into GMT to match the price data we will download later""" import pytz data = data.tz_localize(pytz.timezone('US/Eastern')) data = data.tz_convert(pytz.timezone('GMT')) """Use pivot method to pivot Name rows into columns""" sentiment_pvt = data.tz_localize(None).pivot(columns='Name', values='Value') 
Now that we have downloaded sentiment data, it would be helpful to have the price data for the same instrument over the same period for analysis. Note the sentiment data is in 1-minute increments, so I will need to pull 1-minute EURUSD candles. We could pull this data into a DataFrame quickly and easily using fxcmpy, however the limit of the number of candles we can pull using fxcmpy is 10,000, which is fewer than the number of 1-minute candles in January 2018. Instead, we can download the candles in 1-week packages from FXCM’s GitHub and create a loop to compile them into a DataFrame. This sounds like a lot of work, but really it’s only a few lines of code. Similarly to the sentiment data, historical candle data is stored in GNU zip files which can be called by their URL.
url = 'https://candledata.fxcorporate.com/' periodicity='m1' ##periodicity, can be m1, H1, D1 url_suffix = '.csv.gz' symbol = 'EURUSD' start_dt = datetime.date(2018,1,2)##select start date end_dt = datetime.date(2018,2,1)##select end date start_wk = start_dt.isocalendar()[1] end_wk = end_dt.isocalendar()[1] year = str(start_dt.isocalendar()[0]) data=pd.DataFrame() for i in range(start_wk, end_wk+1): url_data = url + periodicity + '/' + symbol + '/' + year + '/' + str(i) + url_suffix print(url_data) tempdata = pd.read_csv(url_data, compression='gzip', index_col='DateTime', parse_dates=True) data=pd.concat([data, tempdata]) """Combine price and sentiment data""" frames = data['AskClose'], sentiment_pvt.tz_localize(None) combineddf = pd.concat(frames, axis=1, join_axes=[sentiment_pvt.tz_localize(None).index], ignore_index=False).dropna() combineddf 
At this point you can begin your exploratory data analysis. We started by viewing the descriptive statistics of the data, creating a heatmap of the correlation matrix, and plotting a histogram of the data to view its distribution. View this articleto see our sample code and the results.
submitted by JasonRogers to AlgoTradingFXCM [link] [comments]

Exclusive arrangement | ASIC supervises 63 brokerage firms'full list. Before the end of April, pay attention to the entry and exit of these platforms.

Australian regulators have asked their brokers to violate Chinese and EU laws in providing OTC derivatives to overseas retail traders.
At present, there are 63 Australian brokers in China. This week, the platforms that have cancelled ASIC regulatory licences are UTRADE, ESA ASIA and Baofu International.
Yesterday, the suspension of Chinese customers'cash inflows was announced by OANDA and Lotte Securities.
It should also be noted that only ASIC license platforms, if there is no good plan before the end of April, then customers in China will be affected. Investors should pay attention to the situation of April's income and expenditure. These platforms include (ranked indiscriminately):
Amdforex
Cardiff
IFGM
Advanced Markets
Best Leader
Charterprime
Rubix FX
PGWG
EightCap
GS Deep Ocean
Global Prime
Millennium,
Wiston FX
INVAST
OGFX
Mickens MARKETS
DV Markets (IFS Markets)
JB Alpha
City index
ILQ
Trend
FOREX CT
VT Markets
ETO Markets
TradeMax
GO Markets
AUGS Markets
Hantec Markets
GMT Markets
USGFX
SuperTrader
BCR
ACY
Capstone
Anzo Capital
TBC
With ASIC licences, there are also platforms with other licences. Although customer access to ASIC is monitored under Australian supervision, diversified licences still have advantages for customer ownership arrangements. These platforms include (ranked indiscriminately):
AVATrade
Eddie McAdral markets
KVB
Think Markets
XM
Profit securities
IC Markets
AETOS
MahiFX (Saled Retail Business)
FXOpen
Vantage FX
Xforex
FP Markets
European market
Velocity
Royal
MEX Group
Pepperstone
AxiTrader
Easy Markets
CMC Markets
Gain capital
FXCM
IG Markets
Before the end of April, ASIC brokers requested a written reply to ASIC detailing the measures taken to comply with regulatory requirements for overseas customers.
Before May 7, ASIC brokers need to e-mail the number of customers in each jurisdiction.
In the meantime, investors can choose platforms with a wide range of licences and high ratings through the official website of foreign exchange agents www.fxmitan.com.
submitted by Zebrahelps to u/Zebrahelps [link] [comments]

Oanda's spreads are HUGE Part 2

In my first post I compared Oanda's spreads to other legitimate brokers. I received criticism (see below) because I compared spreads on the weekend and brokers with different business models (Market Makers vs ECN).
In this post I used the same mechanics to compare brokers, except I used average spreads, not current, from 30/11/16 20:07 GMT+3 to 6/12/16 20:07 GMT+3, and included comissions into the spreads.
Oanda: 1.50
FXCM: 1.16
Forex.com: 1.96
Pepperstone: 0.90
Darwinex: 0.94
IC Markets: 0.85
Exness: 1.14
RoboForex: 1.01
Although Oanda's spreads have reduced and are smaller in comparison to other brokers, broker spreads ranking hasn't changed. Oanda has the second highest spreads after Forex.com. IC Markets has nearly half the spreads of Oanda's, even after including commissions. I am leaning towards opening an account with Pepperstone or IC Markets more than ever before.
Although spreads are a major factor in choosing a broker, they do not represent execution quality, slippage, or any other fees of a broker.
While this is true, why open an account with Oanda over Pepperstone, for example?
Hall of Criticism
NormanConquest:
You're doing it wrong. Never in 3 years as an Oanda client have I seen eurusd with an 8 pip spread. When we're you looking, Sunday night? Eurusd is usually around 1.2 pips, sometimes less than 1. However you're finding them, it's not reporting them right.
KidUnidentifiable:
You can't just compare spreads with brokers using different business models. http://prntscr.com/d3tjme If you look at the spreads of ICMarkets (I use) and Oanda, they don't differ by much really. That's because you need to integrate the commission ICMarkets charge and integrate it into the spread. Once you do, they don't differ by much.
submitted by JacobM00re to Forex [link] [comments]

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