OANDA
FOREX Data
Introduction
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.
For more information about the FOREX Data dataset, including CLI commands and pricing, see the dataset listing.
About the Provider
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.
Data Summary
The following table describes the dataset properties:
| Property | Value |
|---|---|
| Start Date | January 2007 |
| Asset Coverage | 71 Currency pairs |
| Data Density | Dense |
| Resolution | Tick, Second, Minute, Hour, & Daily |
| Timezone | UTC |
| Market Hours | Always Open, except from Friday 5 PM EST to Sunday 5 PM EST |
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
For more example algorithms, see Examples.
Requesting Data
To add FOREX data to your algorithm, call the AddForexadd_forex method. Save a reference to the Forex Symbol so you can access the data later in your algorithm.
class ForexAlgorithm (QCAlgorithm):
def initialize(self) -> None:
self.set_start_date(2019, 2, 20)
self.set_end_date(2019, 2, 21)
self.set_cash(100000)
self.eurusd = self.add_forex('EURUSD', Resolution.MINUTE, Market.OANDA).symbol
self.set_benchmark(self.eurusd)
namespace QuantConnect.Algorithm.CSharp
{
public class ForexAlgorithm : QCAlgorithm
{
private Symbol _symbol;
public override void Initialize()
{
SetStartDate(2019, 2, 20);
SetEndDate(2019, 2, 21);
SetCash(100000);
_symbol = AddForex("EURUSD", Resolution.Minute, Market.Oanda).Symbol;
SetBenchmark(_symbol);
}
}
}
For more information about creating Forex subscriptions, see Requesting Data.
Accessing Data
To get the current Forex data, index the QuoteBarsquote_bars, or Ticksticks properties of the current Slice with the Forex Symbol. Slice objects deliver unique events to your algorithm as they happen, but the Slice may not contain data for your security at every time step. To avoid issues, check if the Slice contains the data you want before you index it.
def on_data(self, slice: Slice) -> None:
if self.eurusd in slice.quote_bars:
quote_bar = slice.quote_bars[self.eurusd]
self.log(f"{self.eurusd} bid at {slice.time}: {quote_bar.bid.close}")
if self.eurusd in slice.ticks:
ticks = slice.ticks[self.eurusd]
for tick in ticks:
self.log(f"{self.eurusd} price at {slice.time}: {tick.price}") public override void OnData(Slice slice)
{
if (slice.QuoteBars.ContainsKey(_symbol))
{
var quoteBar = slice.QuoteBars[_symbol];
Log($"{_symbol} bid at {slice.Time}: {quoteBar.Bid.Close}");
}
if (slice.Ticks.ContainsKey(_symbol))
{
var ticks = slice.Ticks[_symbol];
foreach (var tick in ticks)
{
Log($"{_symbol} price at {slice.Time}: {tick.Price}");
}
}
}
You can also iterate through all of the data objects in the current Slice.
def on_data(self, slice: Slice) -> None:
for symbol, quote_bar in slice.quote_bars.items():
self.log(f"{symbol} bid at {slice.time}: {quote_bar.bid.close}")
for symbol, ticks in slice.ticks.items():
for tick in ticks:
self.log(f"{symbol} price at {slice.time}: {tick.price}") public override void OnData(Slice slice)
{
foreach (var kvp in slice.QuoteBars)
{
var symbol = kvp.Key;
var quoteBar = kvp.Value;
Log($"{symbol} bid at {slice.Time}: {quoteBar.Bid.Close}");
}
foreach (var kvp in slice.Ticks)
{
var symbol = kvp.Key;
var ticks = kvp.Value;
foreach (var tick in ticks)
{
Log($"{symbol} price at {slice.Time}: {tick.Price}");
}
}
}
For more information about accessing Forex data, see Handling Data.
Historical Data
To get historical Forex data, call the Historyhistory method with the Forex Symbol. If there is no data in the period you request, the history result is empty.
# DataFrame history_df = self.history(self.eurusd, 100, Resolution.MINUTE) # QuoteBar objects history_quote_bars = self.history[QuoteBar](self.eurusd, 100, Resolution.MINUTE) # Tick objects history_ticks = self.history[Tick](self.eurusd, timedelta(seconds=10), Resolution.TICK)
// QuoteBar objects var historyQuoteBars = History<QuoteBar>(_symbol, 100, Resolution.Minute); // Tick objects var historyTicks = History<Tick>(_symbol, TimeSpan.FromSeconds(10), Resolution.Tick);
For more information about historical data, see History Requests.
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
For more example algorithms, see Examples.
You can also see our Videos. You can also get in touch with us via Discord.
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