| Overall Statistics |
|
Total Trades 8 Average Win 0.47% Average Loss 0% Compounding Annual Return -33.408% Drawdown 4.100% Expectancy 0 Net Profit -1.724% Sharpe Ratio -2.724 Loss Rate 0% Win Rate 100% Profit-Loss Ratio 0 Alpha -0.332 Beta 0.282 Annual Standard Deviation 0.121 Annual Variance 0.015 Information Ratio -2.661 Tracking Error 0.126 Treynor Ratio -1.171 Total Fees $8.00 |
//Copyright HardingSoftware.com 2019, granted to the public domain.
//Use at your own risk. Do not remove this copyright notice.
namespace QuantConnect.Algorithm.CSharp
{
public class TMA2Algo : QCAlgorithm
{
//Symbol symbol = QuantConnect.Symbol.Create("Y", SecurityType.Equity, Market.USA);
int period = 10;
decimal LimitRatio = 0.5m;
Resolution resolution = Resolution.Minute;
TimeSpan orderExpiryTime = new TimeSpan(0,0,0,59);
int priceDecimals = 2;
List<TradeBar> history = new List<TradeBar>();
decimal startCash = 5000;
public override void Initialize()
{
SetStartDate(2018, 8, 26);
SetEndDate(2019, 8, 26);
SetCash(startCash);
//AddEquity(symbol, resolution);
AddUniverse(CoarseSelectionFilter);
UniverseSettings.Resolution = Resolution.Minute;
UniverseSettings.Leverage = 2;
AddRiskManagement(new MaximumDrawdownPercentPerSecurity());
}
public override void OnSecuritiesChanged(SecurityChanges changes)
{
Log($"OnSecuritiesChanged({UtcTime}):: {changes}");
/* foreach (var security in changes.RemovedSecurities)
{
if (security.Invested)
{
Liquidate(security.Symbol);
}
}
*/
//2. Now that we have more leverage, set the allocation to set the allocation to 18% each instead of 10%
foreach (var security in changes.AddedSecurities)
{
SetHoldings(security.Symbol, 0.18m);
}
}
public IEnumerable<Symbol> CoarseSelectionFilter(IEnumerable<CoarseFundamental> coarse)
{
var sortedByDollarVolume = coarse.OrderByDescending(x => x.DollarVolume);
var filteredByPrice = sortedByDollarVolume.Where(x => x.Price > 10).Select(x => x.Symbol);
filteredByPrice = filteredByPrice.Take(10);
return filteredByPrice;
}
public override void OnData(Slice data)
{
CancelExpiredOrders();
foreach(var kvp in Securities)
{
var symbol = kvp.Key;
if (data.Bars.ContainsKey(symbol) && data.Bars[symbol] != null)
{
history.Add(data.Bars[symbol]);
if (history.Count > period)
{
history.RemoveAt(0);
}
else
{
return;
}
decimal tma = TMA2.TriangularCandleAverage(history);
decimal range = TMA2.FullRange(history);
decimal buyPrice = tma - LimitRatio * range;
decimal sellPrice = tma + LimitRatio * range;
if (Portfolio[symbol].Quantity == 0)
{
buyPrice = Math.Round(buyPrice, priceDecimals);
if (buyPrice > 0)
{
decimal quantity = startCash / buyPrice;
if (OrderIsPlaced(symbol, quantity) == false)
{
Transactions.CancelOpenOrders();
LimitOrder(symbol, quantity, buyPrice);
}
}
}
else if (Portfolio[symbol].Quantity > 0)
{
sellPrice = Math.Round(sellPrice, priceDecimals);
if (sellPrice > 0)
{
decimal quantity = -Portfolio[symbol].Quantity;
if (OrderIsPlaced(symbol, quantity) == false)
{
Transactions.CancelOpenOrders();
LimitOrder(symbol, quantity, sellPrice);
}
}
}
}
}
}
public bool OrderIsPlaced(Symbol symbol, decimal quantity)
{
List<Order> orders = Transactions.GetOpenOrders(symbol);
foreach (Order order in orders)
{
if (order.Symbol == symbol)
{
if (Math.Sign(quantity) == Math.Sign(order.Quantity))
{
return true;
}
}
}
return false;
}
public void CancelExpiredOrders()
{
List<Order> orders = Transactions.GetOpenOrders();
foreach (Order order in orders)
{
if (Time > order.Time + orderExpiryTime)
{
Transactions.CancelOrder(order.Id);
}
}
}
public class TMA2
{
//Copyright HardingSoftware.com 2019, granted to the public domain.
//Use at your own risk. Do not remove this copyright notice.
public static decimal TriangularCandleAverage(List<TradeBar> candles)
{
return TriangularMovingAverage(CandleAverages(candles));
}
public static decimal[] CandleAverages(List<TradeBar> candles)
{
return candles.Select(x => CandleAverage(x)).ToArray();
}
public static decimal CandleAverage(TradeBar candle)
{
return (candle.Open + candle.High + candle.Low + candle.Close) / 4;
}
public static decimal[] TriangularWeightsDecimal(int length)
{
int[] intWeights = Enumerable.Range(1, length).ToArray();
return intWeights.Select(x => Convert.ToDecimal(x)).ToArray();
}
public static decimal TriangularMovingAverage(decimal[] values)
{
return WeightedAverage(values, TriangularWeightsDecimal(values.Length));
}
public static decimal FullRange(List<TradeBar> candles)
{
return candles.Select(x => x.High).Max() - candles.Select(x => x.Low).Min();
}
public static decimal WeightedAverage(decimal[] values, decimal[] weights)
{
return values.Zip(weights, (x, y) => x * y).Sum() / weights.Sum();
}
}
}
}/*
* 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 QuantConnect.Algorithm.Framework.Portfolio;
namespace QuantConnect.Algorithm.Framework.Risk
{
/// <summary>
/// Provides an implementation of <see cref="IRiskManagementModel"/> that limits the drawdown
/// per holding to the specified percentage
/// </summary>
public class MaximumDrawdownPercentPerSecurity : RiskManagementModel
{
private readonly decimal _maximumDrawdownPercent;
/// <summary>
/// Initializes a new instance of the <see cref="MaximumDrawdownPercentPerSecurity"/> class
/// </summary>
/// <param name="maximumDrawdownPercent">The maximum percentage drawdown allowed for any single security holding,
/// defaults to 5% drawdown per security</param>
public MaximumDrawdownPercentPerSecurity(
decimal maximumDrawdownPercent = 0.05m
)
{
_maximumDrawdownPercent = -Math.Abs(maximumDrawdownPercent);
}
/// <summary>
/// Manages the algorithm's risk at each time step
/// </summary>
/// <param name="algorithm">The algorithm instance</param>
/// <param name="targets">The current portfolio targets to be assessed for risk</param>
public override IEnumerable<IPortfolioTarget> ManageRisk(QCAlgorithm algorithm, IPortfolioTarget[] targets)
{
foreach (var kvp in algorithm.Securities)
{
var security = kvp.Value;
if (!security.Invested)
{
continue;
}
var pnl = security.Holdings.UnrealizedProfitPercent;
if (pnl > (-_maximumDrawdownPercent)-0.02m)
{
// liquidate
yield return new PortfolioTarget(security.Symbol, 0);
}
}
}
}
}