Overall Statistics |
Total Trades 496 Average Win 2.66% Average Loss -2.69% Compounding Annual Return 9.783% Drawdown 40.400% Expectancy 0.100 Net Profit 66.407% Sharpe Ratio 0.492 Loss Rate 45% Win Rate 55% Profit-Loss Ratio 0.99 Alpha 0.006 Beta 0.907 Annual Standard Deviation 0.256 Annual Variance 0.065 Information Ratio -0.03 Tracking Error 0.215 Treynor Ratio 0.139 Total Fees $0.00 |
/* * 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 QuantConnect.Data.Market; using QuantConnect.Indicators; using QuantConnect.Orders; using QuantConnect.Data.Market; namespace QuantConnect.Algorithm.Examples { /// <summary> /// Basic template algorithm simply initializes the date range and cash /// </summary> public class TueThruThurs : QCAlgorithm { string Symbol = null; string LevSymbol = null; decimal leverage = 1.0m; TradeBar entryBar = null; TradeBar firstBar = null; /// <summary> /// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized. /// </summary> public override void Initialize() { SetStartDate(2010, 11, 30); //Set Start Date SetEndDate(2016, 5, 13); SetCash(50000); //Set Strategy Cash SetBrokerageModel(BrokerageName.InteractiveBrokersBrokerage, AccountType.Margin); //SetBrokerageModel(BrokerageName.TradierBrokerage, AccountType.Margin); UniverseSettings.MinimumTimeInUniverse = TimeSpan.FromDays(2190); UniverseSettings.FillForward = true; Symbol = "SPY"; LevSymbol = "SPXL"; // Find more symbols here: http://quantconnect.com/data AddSecurity(SecurityType.Equity, Symbol, Resolution.Minute); AddSecurity(SecurityType.Equity, LevSymbol, Resolution.Minute); } /// <summary> /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here. /// </summary> /// <param name="data">TradeBars IDictionary object with your stock data</param> public void OnData(TradeBars data) { try { bool IsLong = true; TradeBar b = data[Symbol]; decimal price = 0; if ( IsFirstTradingMin(b) == true ) firstBar = b; if ( IsExit(b, out price) == true) { Liquidate(); entryBar = null; Log(">>Close>> " + b.Time.ToString() + " " + Symbol + " @" + price); } else { if ( IsEntry(b, out price, out IsLong ) == true) { entryBar = b; TradeBar c = data[LevSymbol]; price = c.High; decimal qnt = leverage; if ( IsLong == false) qnt = -leverage; SetHoldings(LevSymbol, qnt); //SetHoldings(Symbol, 1.0); Log(">>BUY/sell>> " + b.Time.ToString() + " " + qnt + " " + Symbol + " @" + price); } // if } } catch (Exception ex) { Error("OnData: " + ex.Message + "\r\n\r\n" + ex.StackTrace); } } // OnData bool IsLastTradingMin(TradeBar b) { if ( b.Time.Hour==15 && b.Time.Minute == 59) return true; else return false; } bool IsFirstTradingMin(TradeBar b) { if ( b.Time.Hour==9 && b.Time.Minute == 31) return true; else return false; } /// <summary> /// checks if this bar is good for entry /// </summary> /// <param name="b"></param> /// <returns></returns> bool IsEntry( TradeBar b, out decimal entryPrice, out bool IsLong) { entryPrice = 0; IsLong = true; bool rtn = false; // check for Long entry VXX if ( Portfolio.Invested == false && ( b.Time.Date.DayOfWeek == DayOfWeek.Tuesday || b.Time.Date.DayOfWeek == DayOfWeek.Wednesday || b.Time.Date.DayOfWeek == DayOfWeek.Thursday ) && IsFirstTradingMin(b) ) { // enter entryPrice = b.Close; IsLong = true; rtn = true; } // if // check for Short entry VXX // if ( Portfolio.Invested == false // && ( // b.Time.Date.DayOfWeek == DayOfWeek.Monday // ||b.Time.Date.DayOfWeek == DayOfWeek.Friday // ) // && (b.Time.Hour==14 || b.Time.Hour==15 && b.Time.Minute<=30 ) // short after 2pm // ) // { // // enter short // entryPrice = b.Close; // IsLong = false; // rtn = true; // } // if return rtn; } // IsEntry bool IsExit( TradeBar b, out decimal exit ) { exit = 0; bool rtn = false; if ( Portfolio.Invested == true && Portfolio[LevSymbol] != null ) { if ( // for Long exit Portfolio[LevSymbol].IsLong==true && b.Time.Hour==15 && b.Time.Minute==59 //|| // for short exit //Portfolio[LevSymbol].IsShort==true //&& ( b.Time.Hour==15 && b.Time.Minute==59 // converts to MarketOnOpen for next day // || GettPercentGain(b, LevSymbol) <= -3 // ) ) { rtn = true; exit = b.Close; } } return rtn; } // IsExit decimal GettPercentGain( TradeBar b, string ticker) { decimal rtn = 0; if ( Portfolio[ticker] != null ) { rtn = (Portfolio[ticker].Price - Portfolio[ticker].AveragePrice) / Portfolio[ticker].AveragePrice*100; if (Portfolio[ticker].IsShort==true) rtn = -rtn; } return rtn; } // GettPercentGain } }
namespace QuantConnect.Algorithm.Examples { // // Make sure to change "BasicTemplateAlgorithm" to your algorithm class name, and that all // files use "public partial class" if you want to split up your algorithm namespace into multiple files. // //public partial class BasicTemplateAlgorithm : QCAlgorithm, IAlgorithm //{ // Extension functions can go here...(ones that need access to QCAlgorithm functions e.g. Debug, Log etc.) //} //public class Indicator //{ // ...or you can define whole new classes independent of the QuantConnect Context //} public class RollingWin<T> : IReadOnlyWindow<T> { // the backing list object used to hold the data public List<T> _list; // read-write lock used for controlling access to the underlying list data structure //private readonly ReaderWriterLockSlim _listLock = new ReaderWriterLockSlim(LockRecursionPolicy.SupportsRecursion); // the most recently removed item from the window (fell off the back) private T _mostRecentlyRemoved; // the total number of samples taken by this indicator private decimal _samples; // used to locate the last item in the window as an indexer into the _list private int _tail; /// <summary> /// Initializes a new instance of the RollwingWindow class with the specified window size. /// </summary> /// <param name="size">The number of items to hold in the window</param> public RollingWin(int size) { if (size < 1) { throw new ArgumentException("RollingWindow must have size of at least 1.", "size"); } _list = new List<T>(size); } /// <summary> /// Gets the size of this window /// </summary> public int Size { get { return _list.Capacity; } } /// <summary> /// Gets the current number of elements in this window /// </summary> public int Count { get { return _list.Count; } } /// <summary> /// Gets the number of samples that have been added to this window over its lifetime /// </summary> public decimal Samples { get { return _samples; } } /// <summary> /// Gets the most recently removed item from the window. This is the /// piece of data that just 'fell off' as a result of the most recent /// add. If no items have been removed, this will throw an exception. /// </summary> public T MostRecentlyRemoved { get { if (!IsReady) { throw new InvalidOperationException("No items have been removed yet!"); } return _mostRecentlyRemoved; } } /// <summary> /// Indexes into this window, where index 0 is the most recently /// entered value /// </summary> /// <param name="i">the index, i</param> /// <returns>the ith most recent entry</returns> public T this [int i] { get { //_listLock.EnterReadLock(); if (i >= Count) { throw new ArgumentOutOfRangeException("i", i, string.Format("Must be between 0 and Count {0}", Count)); } return _list[(Count + _tail - i - 1) % Count]; } set { if (i >= Count) { throw new ArgumentOutOfRangeException("i", i, string.Format("Must be between 0 and Count {0}", Count)); } _list[(Count + _tail - i - 1) % Count] = value; } } /// <summary> /// Gets a value indicating whether or not this window is ready, i.e, /// it has been filled to its capacity and one has fallen off the back /// </summary> public bool IsReady { get { return Samples > Size; } } /// <summary> /// Returns an enumerator that iterates through the collection. /// </summary> /// <returns> /// A <see cref="T:System.Collections.Generic.IEnumerator`1" /> that can be used to iterate through the collection. /// </returns> /// <filterpriority>1</filterpriority> public IEnumerator<T> GetEnumerator() { // we make a copy on purpose so the enumerator isn't tied // to a mutable object, well it is still mutable but out of scope var temp = new List<T>(Count); for (int i = 0; i < Count; i++) { temp.Add(this[i]); } return temp.GetEnumerator(); } /// <summary> /// Returns an enumerator that iterates through a collection. /// </summary> /// <returns> /// An <see cref="T:System.Collections.IEnumerator" /> object that can be used to iterate through the collection. /// </returns> /// <filterpriority>2</filterpriority> IEnumerator IEnumerable.GetEnumerator() { return GetEnumerator(); } /// <summary> /// Adds an item to this window and shifts all other elements /// </summary> /// <param name="item">The item to be added</param> public void Add(T item) { _samples++; if (Size == Count) { // keep track of what's the last element // so we can reindex on this[ int ] _mostRecentlyRemoved = _list[_tail]; _list[_tail] = item; _tail = (_tail + 1) % Size; } else { _list.Add(item); } } /// <summary> /// Clears this window of all data /// </summary> public void Reset() { _samples = 0; _list.Clear(); } } }