Datasets
Forex
Create Subscriptions
Follow these steps to subscribe to a Forex security:
- Load the assembly files and data types in their own cell.
- Import the data types.
- Create a
QuantBook
. - (Optional) Set the time zone to the data time zone.
- Call the
AddForex
add_forex
method with a ticker and then save a reference to the ForexSymbol
.
#load "../Initialize.csx"
#load "../QuantConnect.csx" #r "../Microsoft.Data.Analysis.dll" using QuantConnect; using QuantConnect.Data; using QuantConnect.Algorithm; using QuantConnect.Research; using QuantConnect.Indicators; using QuantConnect.Securities.Forex; using Microsoft.Data.Analysis;
var qb = new QuantBook();
qb = QuantBook()
qb.set_time_zone(TimeZones.UTC);
qb.set_time_zone(TimeZones.UTC)
var eurusd = qb.AddForex("EURUSD").Symbol; var gbpusd = qb.AddForex("GBPUSD").Symbol;
eurusd = qb.add_forex("EURUSD").symbol gbpusd = qb.add_forex("GBPUSD").symbol
To view all of the available Forex pairs, see Supported Assets.
Get Historical Data
You need a subscription before you can request historical data for a security. On the time dimension, you can request an amount of historical data based on a trailing number of bars, a trailing period of time, or a defined period of time. On the security dimension, you can request historical data for a single Forex pair, a subset of the pairs you created subscriptions for in your notebook, or all of the pairs in your notebook.
Trailing Number of Bars
To get historical data for a number of trailing bars, call the History
history
method with the Symbol
object(s) and an integer.
// Slice objects var singleHistorySlice = qb.History(eurusd, 10); var subsetHistorySlice = qb.History(new[] {eurusd, gbpusd}, 10); var allHistorySlice = qb.History(10); // QuoteBar objects var singleHistoryQuoteBars = qb.History<QuoteBar>(eurusd, 10); var subsetHistoryQuoteBars = qb.History<QuoteBar>(new[] {eurusd, gbpusd}, 10); var allHistoryQuoteBars = qb.History<QuoteBar>(qb.Securities.Keys, 10);
# DataFrame single_history_df = qb.history(eurusd, 10) subset_history_df = qb.history([eurusd, gbpusd], 10) all_history_df = qb.history(qb.securities.keys(), 10) # Slice objects all_history_slice = qb.history(10) # QuoteBar objects single_history_quote_bars = qb.history[QuoteBar](eurusd, 10) subset_history_quote_bars = qb.history[QuoteBar]([eurusd, gbpusd], 10) all_history_quote_bars = qb.history[QuoteBar](qb.securities.keys(), 10)
The preceding calls return the most recent bars, excluding periods of time when the exchange was closed.
Trailing Period of Time
To get historical data for a trailing period of time, call the History
history
method with the Symbol
object(s) and a TimeSpan
timedelta
.
// Slice objects var singleHistorySlice = qb.History(eurusd, TimeSpan.FromDays(3)); var subsetHistorySlice = qb.History(new[] {eurusd, gbpusd}, TimeSpan.FromDays(3)); var allHistorySlice = qb.History(10); // QuoteBar objects var singleHistoryQuoteBars = qb.History<QuoteBar>(eurusd, TimeSpan.FromDays(3), Resolution.Minute); var subsetHistoryQuoteBars = qb.History<QuoteBar>(new[] {eurusd, gbpusd}, TimeSpan.FromDays(3), Resolution.Minute); var allHistoryQuoteBars = qb.History<QuoteBar>(qb.Securities.Keys, TimeSpan.FromDays(3), Resolution.Minute); // Tick objects var singleHistoryTicks = qb.History<Tick>(eurusd, TimeSpan.FromDays(3), Resolution.Tick); var subsetHistoryTicks = qb.History<Tick>(new[] {eurusd, gbpusd}, TimeSpan.FromDays(3), Resolution.Tick);
var allHistoryTicks = qb.History<Tick>(qb.Securities.Keys, TimeSpan.FromDays(3), Resolution.Tick);
# DataFrame of quote data (Forex data doesn't have trade data) single_history_df = qb.history(eurusd, timedelta(days=3)) subset_history_df = qb.history([eurusd, gbpusd], timedelta(days=3)) all_history_df = qb.history(qb.securities.keys(), timedelta(days=3)) # DataFrame of tick data single_history_tick_df = qb.history(eurusd, timedelta(days=3), Resolution.TICK) subset_history_tick_df = qb.history([eurusd, gbpusd], timedelta(days=3), Resolution.TICK) all_history_tick_df = qb.history(qb.securities.keys(), timedelta(days=3), Resolution.TICK) # Slice objects all_history_slice = qb.history(timedelta(days=3)) # QuoteBar objects single_history_quote_bars = qb.history[QuoteBar](eurusd, timedelta(days=3), Resolution.MINUTE) subset_history_quote_bars = qb.history[QuoteBar]([eurusd, gbpusd], timedelta(days=3), Resolution.MINUTE) all_history_quote_bars = qb.history[QuoteBar](qb.securities.keys(), timedelta(days=3), Resolution.MINUTE) # Tick objects single_history_ticks = qb.history[Tick](eurusd, timedelta(days=3), Resolution.TICK) subset_history_ticks = qb.history[Tick]([eurusd, gbpusd], timedelta(days=3), Resolution.TICK) all_history_ticks = qb.history[Tick](qb.securities.keys(), timedelta(days=3), Resolution.TICK)
The preceding calls return the most recent bars or ticks, excluding periods of time when the exchange was closed.
Defined Period of Time
To get historical data for a specific period of time, call the History
history
method with the Symbol
object(s), a start DateTime
datetime
, and an end DateTime
datetime
. The start and end times you provide are based in the notebook time zone.
var startTime = new DateTime(2021, 1, 1); var endTime = new DateTime(2021, 2, 1); // Slice objects var singleHistorySlice = qb.History(eurusd, startTime, endTime); var subsetHistorySlice = qb.History(new[] {eurusd, gbpusd}, startTime, endTime); var allHistorySlice = qb.History(qb.Securities.Keys, startTime, endTime); // QuoteBar objects var singleHistoryQuoteBars = qb.History<QuoteBar>(eurusd, startTime, endTime, Resolution.Minute); var subsetHistoryQuoteBars = qb.History<QuoteBar>(new[] {eurusd, gbpusd}, startTime, endTime, Resolution.Minute); var allHistoryQuoteBars = qb.History<QuoteBar>(qb.Securities.Keys, startTime, endTime, Resolution.Minute); // Tick objects var singleHistoryTicks = qb.History<Tick>(eurusd, startTime, endTime, Resolution.Tick); var subsetHistoryTicks = qb.History<Tick>(new[] {eurusd, gbpusd}, startTime, endTime, Resolution.Tick); var allHistoryTicks = qb.History<Tick>(qb.Securities.Keys, startTime, endTime, Resolution.Tick);
start_time = datetime(2021, 1, 1) end_time = datetime(2021, 2, 1) # DataFrame of quote data (Forex data doesn't have trade data) single_history_df = qb.history(eurusd, start_time, end_time) subset_history_df = qb.history([eurusd, gbpusd], start_time, end_time) all_history_df = qb.history(qb.securities.keys(), start_time, end_time) # DataFrame of tick data single_history_tick_df = qb.history(eurusd, start_time, end_time, Resolution.TICK) subset_history_tick_df = qb.history([eurusd, gbpusd], start_time, end_time, Resolution.TICK) all_history_tick_df = qb.history(qb.securities.keys(), start_time, end_time, Resolution.TICK) # QuoteBar objects single_history_quote_bars = qb.history[QuoteBar](eurusd, start_time, end_time, Resolution.MINUTE) subset_history_quote_bars = qb.history[QuoteBar]([eurusd, gbpusd], start_time, end_time, Resolution.MINUTE) all_history_quote_bars = qb.history[QuoteBar](qb.securities.keys(), start_time, end_time, Resolution.MINUTE) # Tick objects single_history_ticks = qb.history[Tick](eurusd, start_time, end_time, Resolution.TICK) subset_history_ticks = qb.history[Tick]([eurusd, gbpusd], start_time, end_time, Resolution.TICK) all_history_ticks = qb.history[Tick](qb.securities.keys(), start_time, end_time, Resolution.TICK)
The preceding calls return the bars or ticks that have a timestamp within the defined period of time.
Wrangle Data
You need some historical data to perform wrangling operations. The process to manipulate the historical data depends on its data type. To display pandas
objects, run a cell in a notebook with the pandas
object as the last line. To display other data formats, call the print
method.
You need some historical data to perform wrangling operations. Use LINQ to wrangle the data and then call the Console.WriteLine
method in a Jupyter Notebook to display the data. The process to manipulate the historical data depends on its data type.
DataFrame Objects
If the History
history
method returns a DataFrame
, the first level of the DataFrame
index is the encoded Forex Symbol and the second level is the EndTime
end_time
of the data sample. The columns of the DataFrame
are the data properties.
To select the historical data of a single Forex, index the loc
property of the DataFrame
with the Forex Symbol
.
all_history_df.loc[eurusd] # or all_history_df.loc['EURUSD']
To select a column of the DataFrame
, index it with the column name.
all_history_df.loc[eurusd]['close']
If you request historical data for multiple Forex pairs, you can transform the DataFrame
so that it's a time series of close values for all of the Forex pairs. To transform the DataFrame
, select the column you want to display for each Forex pair and then call the unstack method.
all_history_df['close'].unstack(level=0)
The DataFrame
is transformed so that the column indices are the Symbol
of each Forex pair and each row contains the close value.
The historical data methods don't return DataFrame objects, but you can create one for efficient vectorized data wrangling.
using Microsoft.Data.Analysis; var columns = new DataFrameColumn[] { new PrimitiveDataFrameColumn("Time", history.Select(x => x[eurusd].EndTime)), new DecimalDataFrameColumn("EURUSD Open", history.Select(x => x[eurusd].Open)), new DecimalDataFrameColumn("EURUSD High", history.Select(x => x[eurusd].High)), new DecimalDataFrameColumn("EURUSD Low", history.Select(x => x[eurusd].Low)), new DecimalDataFrameColumn("EURUSD Close", history.Select(x => x[eurusd].Close)) }; var df = new DataFrame(columns); df
To select a particular column of the DataFrame, index it with the column name.
df["EURUSD close"]
Slice Objects
If the History
history
method returns Slice
objects, iterate through the Slice
objects to get each one. The Slice
objects may not have data for all of your Forex subscriptions. To avoid issues, check if the Slice
contains data for your Forex pair before you index it with the Forex Symbol
.
foreach (var slice in allHistorySlice) { if (slice.QuoteBars.ContainsKey(eurusd)) { var quoteBar = slice.QuoteBars[eurusd]; } }
for slice in all_history_slice: if slice.quote_bars.contains_key(eurusd): quote_bar = slice.quote_bars[eurusd]
You can also iterate through each QuoteBar
in the Slice
.
foreach (var slice in allHistorySlice) { foreach (var kvp in slice.QuoteBars) { var symbol = kvp.Key; var quoteBar = kvp.Value; } }
for slice in all_history_slice: for kvp in slice.quote_bars: symbol = kvp.key quote_bar = kvp.value
You can also use LINQ to select each QuoteBar
in the Slice
for a given Symbol
.
var quoteBars = allHistorySlice.Where(slice => slice.QuoteBars.ContainsKey(eurusd)).Select(slice => slice.QuoteBars[eurusd]);
QuoteBar Objects
If the History
history
method returns QuoteBar
objects, iterate through the QuoteBar
objects to get each one.
foreach (var quoteBar in singleHistoryQuoteBars) { Console.WriteLine(quoteBar); }
for quote_bar in single_history_quote_bars: print(quote_bar)
If the History
history
method returns QuoteBars
, iterate through the QuoteBars
to get the QuoteBar
of each Forex pair. The QuoteBars
may not have data for all of your Forex subscriptions. To avoid issues, check if the QuoteBars
object contains data for your security before you index it with the Forex Symbol
.
foreach (var quoteBars in allHistoryQuoteBars) { if (quoteBars.ContainsKey(eurusd)) { var quoteBar = quoteBars[eurusd]; } }
for quote_bars in all_history_quote_bars: if quote_bars.contains_key(eurusd): quote_bar = quote_bars[eurusd]
You can also iterate through each of the QuoteBars
.
foreach (var quoteBars in allHistoryQuoteBars) { foreach (var kvp in quoteBars) { var symbol = kvp.Key; var quoteBar = kvp.Value; } }
for quote_bars in all_history_quote_bars: for kvp in quote_bars: symbol = kvp.key quote_bar = kvp.value
Tick Objects
If the History
history
method returns Tick
TICK
objects, iterate through the Tick
TICK
objects to get each one.
foreach (var tick in singleHistoryTicks) { Console.WriteLine(tick); }
for tick in single_history_ticks: print(tick)
If the History
history
method returns Ticks
, iterate through the Ticks
to get the Tick
TICK
of each Forex pair. The Ticks
may not have data for all of your Forex subscriptions. To avoid issues, check if the Ticks
object contains data for your security before you index it with the Forex Symbol
.
foreach (var ticks in allHistoryTicks) { if (ticks.ContainsKey(eurusd)) { var tick = ticks[eurusd]; } }
for ticks in all_history_ticks: if ticks.contains_key(eurusd): ticks = ticks[eurusd]
You can also iterate through each of the Ticks
.
foreach (var ticks in allHistoryTicks) { foreach (var kvp in ticks) { var symbol = kvp.Key; var tick = kvp.Value; } }
for ticks in all_history_ticks: for kvp in ticks: symbol = kvp.key tick = kvp.value
The Ticks
objects only contain the last tick of each security for that particular timeslice
Plot Data
You need some historical Forex data to produce plots. You can use many of the supported plotting librariesPlot.NET package to visualize data in various formats. For example, you can plot candlestick and line charts.
Candlestick Chart
Follow these steps to plot candlestick charts:
- Get some historical data.
- Import the
plotly
Plot.NET
library. - Create a
Candlestick
. - Create a
Layout
. - Create the
Figure
. - Assign the
Layout
to the chart. - Show the
Figure
.
history = qb.history(eurusd, datetime(2021, 11, 26), datetime(2021, 12, 8), Resolution.DAILY).loc[eurusd]
var history = qb.History<QuoteBar>(eurusd, new DateTime(2021, 11, 26), new DateTime(2021, 12, 8), Resolution.Daily);
import plotly.graph_objects as go
#r "../Plotly.NET.dll" using Plotly.NET; using Plotly.NET.LayoutObjects;
candlestick = go.Candlestick(x=history.index, open=history['open'], high=history['high'], low=history['low'], close=history['close'])
var chart = Chart2D.Chart.Candlestick<decimal, decimal, decimal, decimal, DateTime, string>( history.Select(x => x.Open), history.Select(x => x.High), history.Select(x => x.Low), history.Select(x => x.Close), history.Select(x => x.EndTime) );
layout = go.Layout(title=go.layout.Title(text='EURUSD OHLC'), xaxis_title='Date', yaxis_title='Price', xaxis_rangeslider_visible=False)
LinearAxis xAxis = new LinearAxis(); xAxis.SetValue("title", "Time"); LinearAxis yAxis = new LinearAxis(); yAxis.SetValue("title", "Price ($)"); Title title = Title.init($"{eurusd} OHLC"); Layout layout = new Layout(); layout.SetValue("xaxis", xAxis); layout.SetValue("yaxis", yAxis); layout.SetValue("title", title);
fig = go.Figure(data=[candlestick], layout=layout)
chart.WithLayout(layout);
fig.show()
HTML(GenericChart.toChartHTML(chart))
Candlestick charts display the open, high, low, and close prices of the security.
Line Chart
Follow these steps to plot line charts using built-in methodsPlotly.NET
package:
- Get some historical data.
- Select the data to plot.
- Call the
plot
method on thepandas
object. - Create
Line
charts. - Create a
Layout
. - Combine the charts and assign the
Layout
to the chart. - Show the plot.
history = qb.history([eurusd, gbpusd], datetime(2021, 11, 26), datetime(2021, 12, 8), Resolution.DAILY)
var history = qb.History<QuoteBar>(new [] {eurusd, gbpusd}, new DateTime(2021, 11, 26), new DateTime(2021, 12, 8), Resolution.Daily);
pct_change = history['close'].unstack(0).pct_change().dropna()
pct_change.plot(title="Close Price %Change", figsize=(15, 10))
var chart1 = Chart2D.Chart.Line<DateTime, decimal, string>( history.Select(x => x[eurusd].EndTime), history.Select(x => x[eurusd].Close), Name: "EURUSD" ); var chart2 = Chart2D.Chart.Line<DateTime, decimal, string>( history.Select(x => x[gbpusd].EndTime), history.Select(x => x[gbpusd].Close), Name: "GBPUSD" );
LinearAxis xAxis = new LinearAxis(); xAxis.SetValue("title", "Time"); LinearAxis yAxis = new LinearAxis(); yAxis.SetValue("title", "Price ($)"); Title title = Title.init("EURUSD & GBPUSD Close Price"); Layout layout = new Layout(); layout.SetValue("xaxis", xAxis); layout.SetValue("yaxis", yAxis); layout.SetValue("title", title);
var chart = Plotly.NET.Chart.Combine(new []{chart1, chart2}); chart.WithLayout(layout);
plt.show()
HTML(GenericChart.toChartHTML(chart))
Line charts display the value of the property you selected in a time series.