About FOREX Data
The FOREX Data by OANDA serves 71 foreign exchange (FOREX) pairs, starts on various dates from January 2007, and is delivered on any frequency from tick to daily. This dataset is created by QuantConnect processing raw tick data from OANDA.
About OANDA
OANDA was co-founded by Dr. Stumm, a computer scientist and Dr. Olsen, an economist, in 1997. The company was born out of the belief that the Internet and technology would open up the markets for both currency data and trading. OANDA uses innovative computer and financial technology to provide Internet-based forex trading and currency information services to everyone, from individuals to large corporations, from portfolio managers to financial institutions. OANDA is a market maker and a trusted source for currency data. It has access to one of the world's largest historical, high-frequency, filtered currency databases.
About QuantConnect
QuantConnect was founded in 2012 to serve quants everywhere with the best possible algorithmic trading technology. Seeking to disrupt a notoriously closed-source industry, QuantConnect takes a radically open-source approach to algorithmic trading. Through the QuantConnect web platform, more than 50,000 quants are served every month.
Algorithm Example
from AlgorithmImports import *
from QuantConnect.DataSource import *
class ForexCarryTradeAlgorithm(QCAlgorithm):
def initialize(self) -> None:
self.set_start_date(2008, 1, 1)
self.set_cash(25000)
# We will use hard-coded interest rates
self.rates = {
"USDAUD": 1.5, # Australia
"USDCAD": 0.5, # Canada
"USDCNY": 4.35, # China
"USDEUR": 0.0, # Euro Area
"USDINR": 6.5, # India
"USDJPY": -0.1, # Japan
"USDMXN": 4.25, # Mexico
"USDTRY": 7.5, # Turkey
"USDZAR": 7.0 # South Africa
}
for ticker in self.rates:
self.add_forex(ticker, Resolution.DAILY, Market.OANDA)
self.month = -1
def on_data(self, slice: Slice) -> None:
if self.month == self.time.month:
return
self.month = self.time.month
sorted_rates = sorted(self.rates.items(), key = lambda x: x[1])
self.set_holdings(sorted_rates[0][0], -0.5)
self.set_holdings(sorted_rates[-1][0], 0.5)
Example Applications
The FOREX price data enables you to trade currency pairs in the global mark. Examples include the following strategies:
- Exploring the impact that daily worldwide news cycles has on international currencies
- Carry Trade: borrow from a lower interest currency pair to fund the purchase of a currency pair with a higher interest rate
Pricing
Cloud Access
Freely harness gigabytes of FOREX data in the QuantConnect Cloud for your backtesting and live trading purposes.
Second Download
FOREX Second resolution archives in LEAN format for on premise backtesting and research. One file per ticker/day.
Minute Download
FOREX Minute resolution archives in LEAN format for on premise backtesting and research. One file per ticker/day.
Hour Download
FOREX Hour resolution archives in LEAN format for on premise backtesting and research. One file per ticker.
Daily Download
FOREX Daily resolution archives in LEAN format for on premise backtesting and research. One file per ticker.
Bulk Second Updates
Bulk download second data
Bulk Minute Updates
Bulk download minute data
Bulk Hour Updates
Bulk download hour data
Bulk Daily Updates
Bulk download daily data
Bulk Second Download
Bulk download second data
Bulk Minute Download
Bulk download minute data
Bulk Hour Download
Bulk download hour data
Bulk Daily Download
Bulk download daily data
Explore Other Datasets
Wikipedia Page Views
Dataset by Quiver Quantitative
Insider Trading
Dataset by Quiver Quantitative
US Equity Options
Dataset by AlgoSeek