/* * 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 NUnit.Framework; using QuantConnect.Indicators; namespace QuantConnect.Tests.Indicators { [TestFixture] public class LogReturnTests : CommonIndicatorTests { protected override IndicatorBase CreateIndicator() { return new LogReturn(14); } protected override string TestFileName => "spy_logr14.txt"; protected override string TestColumnName => "LOGR14"; [Test] public void LOGRComputesCorrectly() { var period = 4; var logr = new LogReturn(period); var data = new[] { 1, 10, 100, 1000, 10000, 1234, 56789 }; var seen = new List(); var time = DateTime.Now; for (var i = 0; i < data.Length; i++) { var datum = data[i]; var value0 = 0.0; if (seen.Count >= 0 && seen.Count < period) { value0 = data[0]; } else if (seen.Count >= period) { value0 = data[i - period]; } var expected = (decimal)Math.Log(datum / value0); seen.Add(datum); logr.Update(time.AddSeconds(i), datum); Assert.AreEqual(expected, logr.Current.Value); } } } }