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BasicTemplateIndiaAlgorithm.cs
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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 QuantConnect.Data;
using System.Collections.Generic;
using QuantConnect.Interfaces;
using QuantConnect.Orders;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Basic template India algorithm simply initializes the date range and cash. This is a skeleton
/// framework you can use for designing an algorithm.
/// </summary>
/// <meta name="tag" content="using data" />
/// <meta name="tag" content="using quantconnect" />
/// <meta name="tag" content="trading and orders" />
public class BasicTemplateIndiaAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
/// <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()
{
SetAccountCurrency("INR"); //Set Account Currency
SetStartDate(2019, 1, 23); //Set Start Date
SetEndDate(2019, 10, 31); //Set End Date
SetCash(100000); //Set Strategy Cash
// Find more symbols here: http://quantconnect.com/data
// Equities Resolutions: Tick, Second, Minute, Hour, Daily.
AddEquity("YESBANK", Resolution.Minute, Market.India);
//Set Order Properties as per the requirements for order placement
DefaultOrderProperties = new IndiaOrderProperties(exchange: Exchange.NSE);
//override default productType value set in config.json if needed - order specific productType value
//DefaultOrderProperties = new IndiaOrderProperties(exchange: Exchange.NSE, IndiaOrderProperties.IndiaProductType.CNC);
// General Debug statement for acknowledgement
Debug("Initialization Done");
}
/// <summary>
/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
/// </summary>
/// <param name="data">Slice object keyed by symbol containing the stock data</param>
public override void OnData(Slice slice)
{
if (!Portfolio.Invested)
{
var marketTicket = MarketOrder("YESBANK", 1);
}
}
public override void OnOrderEvent(OrderEvent orderEvent)
{
if (orderEvent.Status.IsFill())
{
Debug($"Purchased Complete: {orderEvent.Symbol}");
}
}
/// <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 List<Language> Languages { get; } = new() { Language.CSharp, Language.Python };
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 29524;
/// <summary>
/// Data Points count of the algorithm history
/// </summary>
public int AlgorithmHistoryDataPoints => 0;
/// <summary>
/// Final status of the algorithm
/// </summary>
public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
/// <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 Orders", "1"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "-0.010%"},
{"Drawdown", "0.000%"},
{"Expectancy", "0"},
{"Start Equity", "100000"},
{"End Equity", "99992.45"},
{"Net Profit", "-0.008%"},
{"Sharpe Ratio", "-497.389"},
{"Sortino Ratio", "-73.22"},
{"Probabilistic Sharpe Ratio", "0.001%"},
{"Loss Rate", "0%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "0"},
{"Beta", "0"},
{"Annual Standard Deviation", "0"},
{"Annual Variance", "0"},
{"Information Ratio", "-1.183"},
{"Tracking Error", "0"},
{"Treynor Ratio", "0"},
{"Total Fees", "₹6.00"},
{"Estimated Strategy Capacity", "₹61000000000.00"},
{"Lowest Capacity Asset", "YESBANK UL"},
{"Portfolio Turnover", "0.00%"},
{"Drawdown Recovery", "0"},
{"OrderListHash", "06f782c83dd633dac6f228b91273ba26"}
};
}
}