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/*
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using QuantConnect.Data;
using QuantConnect.Data.UniverseSelection;
using QuantConnect.Interfaces;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// In this algortihm we show how you can easily use the universe selection feature to fetch symbols
/// to be traded using the AddUniverse method. This method accepts a function that will return the
/// desired current set of symbols. Return Universe.Unchanged if no universe changes should be made
/// </summary>
/// <meta name="tag" content="using data" />
/// <meta name="tag" content="universes" />
/// <meta name="tag" content="custom universes" />
public class DropboxUniverseSelectionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
// the changes from the previous universe selection
private SecurityChanges _changes = SecurityChanges.None;
// only used in backtest for caching the file results
private readonly Dictionary<DateTime, List<string>> _backtestSymbolsPerDay = new Dictionary<DateTime, List<string>>();
/// <summary>
/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
/// </summary>
/// <seealso cref="QCAlgorithm.SetStartDate(System.DateTime)"/>
/// <seealso cref="QCAlgorithm.SetEndDate(System.DateTime)"/>
/// <seealso cref="QCAlgorithm.SetCash(decimal)"/>
public override void Initialize()
{
// this sets the resolution for data subscriptions added by our universe
UniverseSettings.Resolution = Resolution.Daily;
// set our start and end for backtest mode
SetStartDate(2013, 01, 01);
SetEndDate(2013, 12, 31);
// define a new custom universe that will trigger each day at midnight
AddUniverse("my-dropbox-universe", Resolution.Daily, dateTime =>
{
// handle live mode file format
if (LiveMode)
{
// fetch the file from dropbox
var file = Download(@"https://www.dropbox.com/s/2az14r5xbx4w5j6/daily-stock-picker-live.csv?dl=1");
// if we have a file for today, break apart by commas and return symbols
if (file.Length > 0) return file.ToCsv();
// no symbol today, leave universe unchanged
return Universe.Unchanged;
}
// backtest - first cache the entire file
if (_backtestSymbolsPerDay.Count == 0)
{
// No need for headers for authorization with dropbox, these two lines are for example purposes
var byteKey = Encoding.ASCII.GetBytes($"UserName:Password");
// The headers must be passed to the Download method as list of key/value pair.
var headers = new List<KeyValuePair<string, string>>
{
new KeyValuePair<string, string>("Authorization", $"Basic ({Convert.ToBase64String(byteKey)})")
};
var file = Download(@"https://www.dropbox.com/s/rmiiktz0ntpff3a/daily-stock-picker-backtest.csv?dl=1", headers);
// split the file into lines and add to our cache
foreach (var line in file.Split(new[] { '\n', '\r' }, StringSplitOptions.RemoveEmptyEntries))
{
var csv = line.ToCsv();
var date = DateTime.ParseExact(csv[0], "yyyyMMdd", null);
var symbols = csv.Skip(1).ToList();
_backtestSymbolsPerDay[date] = symbols;
}
}
// if we have symbols for this date return them, else specify Universe.Unchanged
List<string> result;
if (_backtestSymbolsPerDay.TryGetValue(dateTime.Date, out result))
{
return result;
}
return Universe.Unchanged;
});
}
/// <summary>
/// Event - v3.0 DATA EVENT HANDLER: (Pattern) Basic template for user to override for receiving all subscription data in a single event
/// </summary>
/// <code>
/// TradeBars bars = slice.Bars;
/// Ticks ticks = slice.Ticks;
/// TradeBar spy = slice["SPY"];
/// List{Tick} aaplTicks = slice["AAPL"]
/// Quandl oil = slice["OIL"]
/// dynamic anySymbol = slice[symbol];
/// DataDictionary{Quandl} allQuandlData = slice.Get{Quand}
/// Quandl oil = slice.Get{Quandl}("OIL")
/// </code>
/// <param name="slice">The current slice of data keyed by symbol string</param>
public override void OnData(Slice slice)
{
if (slice.Bars.Count == 0) return;
if (_changes == SecurityChanges.None) return;
// start fresh
Liquidate();
var percentage = 1m/slice.Bars.Count;
foreach (var tradeBar in slice.Bars.Values)
{
SetHoldings(tradeBar.Symbol, percentage);
}
// reset changes
_changes = SecurityChanges.None;
}
/// <summary>
/// Event fired each time the we add/remove securities from the data feed
/// </summary>
/// <param name="changes"></param>
public override void OnSecuritiesChanged(SecurityChanges changes)
{
// each time our securities change we'll be notified here
_changes = changes;
}
/// <summary>
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
/// </summary>
public bool CanRunLocally { get; } = true;
/// <summary>
/// This is used by the regression test system to indicate which languages this algorithm is written in.
/// </summary>
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
/// <summary>
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
/// </summary>
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Trades", "66"},
{"Average Win", "1.06%"},
{"Average Loss", "-0.50%"},
{"Compounding Annual Return", "18.511%"},
{"Drawdown", "7.100%"},
{"Expectancy", "0.810"},
{"Net Profit", "18.511%"},
{"Sharpe Ratio", "1.439"},
{"Loss Rate", "42%"},
{"Win Rate", "58%"},
{"Profit-Loss Ratio", "2.12"},
{"Alpha", "0.308"},
{"Beta", "-10.065"},
{"Annual Standard Deviation", "0.1"},
{"Annual Variance", "0.01"},
{"Information Ratio", "1.275"},
{"Tracking Error", "0.1"},
{"Treynor Ratio", "-0.014"},
{"Total Fees", "$193.75"}
};
}
}
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