| Overall Statistics |
|
Total Trades 0 Average Win 0% Average Loss 0% Compounding Annual Return 0% Drawdown 0% Expectancy 0 Net Profit 0% Sharpe Ratio 0 Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha 0 Beta 0 Annual Standard Deviation 0 Annual Variance 0 Information Ratio 0 Tracking Error 0 Treynor Ratio 0 Total Fees $0.00 |
using System.Collections.Generic;
using System.Linq;
using QuantConnect.Data.Fundamental;
using QuantConnect.Data.Market;
using QuantConnect.Data.UniverseSelection;
using QuantConnect.Data;
using QuantConnect.Data.Market;
using QuantConnect.Orders;
using QuantConnect.Securities.Option;
using System.Collections.Generic;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// In this algorithm we demonstrate how to define a universe
/// as a combination of use the coarse fundamental data and fine fundamental data
/// </summary>
public class CoarseFineFundamentalComboAlgorithm : QCAlgorithm
{
private const int NumberOfSymbolsCoarse = 5;
private const int NumberOfSymbolsFine = 2;
// initialize our changes to nothing
private SecurityChanges _changes = SecurityChanges.None;
public override void Initialize()
{
UniverseSettings.Resolution = Resolution.Daily;
SetStartDate(2016, 03, 01);
SetEndDate(2016, 03, 10);
SetCash(10000);
// this add universe method accepts two parameters:
// - coarse selection function: accepts an IEnumerable<CoarseFundamental> and returns an IEnumerable<Symbol>
// - fine selection function: accepts an IEnumerable<FineFundamental> and returns an IEnumerable<Symbol>
AddUniverse(CoarseSelectionFunction, FineSelectionFunction);
}
// sort the data by daily dollar volume and take the top 'NumberOfSymbolsCoarse'
public IEnumerable<Symbol> CoarseSelectionFunction(IEnumerable<CoarseFundamental> coarse)
{
// select only symbols with fundamental data and sort descending by daily dollar volume
var sortedByDollarVolume = coarse
.Where(x => x.HasFundamentalData)
.OrderByDescending(x => x.DollarVolume);
// take the top entries from our sorted collection
var top5 = sortedByDollarVolume.Take(15);
// we need to return only the symbol objects
return top5.Select(x => x.Symbol);
}
// sort the data by P/E ratio and take the top 'NumberOfSymbolsFine'
public IEnumerable<Symbol> FineSelectionFunction(IEnumerable<FineFundamental> fine)
{
return fine.Where(x =>
// More than 7 days after earnings report
Time >= x.EarningReports.FileDate.AddDays(-7) &&
Time >= x.EarningReports.FileDate.AddDays(0) &&
// Invalid FileDate
x.EarningReports.FileDate != new DateTime())
.Take(5)
.Select(x => x.Symbol);
}
//Data Event Handler: New data arrives here. "TradeBars" type is a dictionary of strings so you can access it by symbol.
public override void OnData(Slice data) {
foreach (var kvp in data.OptionChains) {
var symbol = kvp.Key;
var chain = kvp.Value;
var atmStraddle = chain
.OrderBy(x => Math.Abs(chain.Underlying.Price - x.Strike))
.ThenByDescending(x => x.Expiry)
.FirstOrDefault();
if (atmStraddle != null && !Portfolio.Invested)
{
Buy(OptionStrategies.Straddle(symbol, atmStraddle.Strike, atmStraddle.Expiry), 1);
Log("Bought Straddle: " + symbol);
}
}
_changes = SecurityChanges.None;
}
// this event fires whenever we have changes to our universe
public override void OnSecuritiesChanged(SecurityChanges changes)
{
_changes = changes;
if (changes.AddedSecurities.Count > 0)
{
Debug("Securities added: " + string.Join(",", changes.AddedSecurities.Select(x => x.Symbol.Value)));
}
if (changes.RemovedSecurities.Count > 0)
{
Debug("Securities removed: " + string.Join(",", changes.RemovedSecurities.Select(x => x.Symbol.Value)));
}
foreach (var security in changes.RemovedSecurities)
{
if (security.Invested)
{
Liquidate(security.Symbol);
}
}
}
}
}