wehub-resource-sync
109 lines
4.3 KiB
C#
109 lines
4.3 KiB
C#
/*
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* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*
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*/
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using QuantConnect.Optimizer.Parameters;
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using System.Collections.Generic;
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using System.Globalization;
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using System.Linq;
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namespace QuantConnect.Optimizer.Analysis
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{
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/// <summary>
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/// Detects local maxima of the Sharpe surface; backtests strictly greater than every face-neighbor on the parameter grid.
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/// </summary>
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internal static class OptimizationModes
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{
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public static IReadOnlyList<Mode> Find(
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IReadOnlyList<OptimizationBacktestMetrics> backtests,
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IReadOnlyCollection<OptimizationParameter> parameters)
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{
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var modes = new List<Mode>();
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if (backtests == null || parameters == null) return modes;
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if (parameters.Count == 0 || backtests.Count == 0) return modes;
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var paramNames = parameters.Select(p => p.Name).ToArray();
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// Sorted distinct values per parameter define the grid axes.
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var axisValues = new Dictionary<string, List<decimal>>();
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foreach (var name in paramNames)
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{
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axisValues[name] = backtests
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.Where(b => b.Parameters.ContainsKey(name))
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.Select(b => b.Parameters[name])
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.Distinct()
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.OrderBy(v => v)
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.ToList();
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}
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// Map each backtest to its grid position.
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var indexed = new List<(OptimizationBacktestMetrics Backtest, int[] Indices)>();
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foreach (var b in backtests)
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{
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if (!paramNames.All(b.Parameters.ContainsKey)) continue;
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var idx = new int[paramNames.Length];
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var ok = true;
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for (var d = 0; d < paramNames.Length; d++)
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{
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idx[d] = axisValues[paramNames[d]].IndexOf(b.Parameters[paramNames[d]]);
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if (idx[d] < 0) { ok = false; break; }
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}
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if (ok) indexed.Add((b, idx));
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}
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var byTuple = indexed.ToDictionary(p => TupleKey(p.Indices), p => p.Backtest);
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foreach (var (backtest, idx) in indexed)
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{
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var totalNeighbors = 0;
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var dominatesAll = true;
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for (var d = 0; d < paramNames.Length && dominatesAll; d++)
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{
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var axisLen = axisValues[paramNames[d]].Count;
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foreach (var delta in new[] { -1, 1 })
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{
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var ni = idx[d] + delta;
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if (ni < 0 || ni >= axisLen) continue;
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var neighborIdx = (int[])idx.Clone();
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neighborIdx[d] = ni;
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if (!byTuple.TryGetValue(TupleKey(neighborIdx), out var neighbor)) continue;
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totalNeighbors++;
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if (neighbor.SharpeRatio >= backtest.SharpeRatio) { dominatesAll = false; break; }
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}
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}
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if (dominatesAll && totalNeighbors > 0)
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{
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modes.Add(new Mode
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{
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BacktestId = backtest.BacktestId,
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Parameters = new Dictionary<string, decimal>(backtest.Parameters),
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SharpeRatio = backtest.SharpeRatio,
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NeighborCount = totalNeighbors
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});
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}
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}
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return modes.OrderByDescending(m => m.SharpeRatio).ToList();
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}
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private static string TupleKey(int[] indices)
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=> string.Join(",", indices.Select(i => i.ToString(CultureInfo.InvariantCulture)));
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}
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}
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