public static void Generate(FileInfo dataDir) { IMarketLoader loader = new YahooFinanceLoader(); var market = new MarketMLDataSet(loader, Config.INPUT_WINDOW, Config.PREDICT_WINDOW); var desc = new MarketDataDescription( Config.TICKER, MarketDataType.AdjustedClose, true, true); market.AddDescription(desc); var end = DateTime.Now; // end today var begin = new DateTime(end.Ticks); // begin 30 days ago // Gather training data for the last 2 years, stopping 60 days short of today. // The 60 days will be used to evaluate prediction. begin = begin.AddDays(-60); end = end.AddDays(-60); begin = begin.AddYears(-2); market.Load(begin, end); market.Generate(); EncogUtility.SaveEGB(FileUtil.CombinePath(dataDir, Config.TRAINING_FILE), market); // create a network BasicNetwork network = EncogUtility.SimpleFeedForward( market.InputSize, Config.HIDDEN1_COUNT, Config.HIDDEN2_COUNT, market.IdealSize, true); // save the network and the training EncogDirectoryPersistence.SaveObject(FileUtil.CombinePath(dataDir, Config.NETWORK_FILE), network); }
public void Loader() { IMarketLoader loader = new YahooFinanceLoader(); var from = new DateTime(2008, 8, 4); var to = new DateTime(2008, 8, 5); ICollection<LoadedMarketData> list = loader.Load(new TickerSymbol("aapl"), null, from, to); IEnumerator<LoadedMarketData> itr = list.GetEnumerator(); itr.MoveNext(); LoadedMarketData data = itr.Current; Assert.AreEqual(160, (int) data.GetData(MarketDataType.Close)); itr.MoveNext(); data = itr.Current; Assert.AreEqual(153, (int) data.GetData(MarketDataType.Close)); }
public static MarketMLDataSet GrabData() { IMarketLoader loader = new YahooFinanceLoader(); var result = new MarketMLDataSet(loader, Config.INPUT_WINDOW, Config.PREDICT_WINDOW); var desc = new MarketDataDescription(Config.TICKER, MarketDataType.AdjustedClose, true, true); result.AddDescription(desc); var end = DateTime.Now; // end today var begin = new DateTime(end.Ticks); // begin 30 days ago begin = begin.AddDays(-60); result.Load(begin, end); result.Generate(); return result; }
public void MarketData() { IMarketLoader loader = new YahooFinanceLoader(); var tickerAAPL = new TickerSymbol("AAPL", null); var tickerMSFT = new TickerSymbol("MSFT", null); var marketData = new MarketMLDataSet(loader, 5, 1); marketData.AddDescription(new MarketDataDescription(tickerAAPL, MarketDataType.Close, true, true)); marketData.AddDescription(new MarketDataDescription(tickerMSFT, MarketDataType.Close, true, false)); marketData.AddDescription(new MarketDataDescription(tickerAAPL, MarketDataType.Volume, true, false)); marketData.AddDescription(new MarketDataDescription(tickerMSFT, MarketDataType.Volume, true, false)); var begin = new DateTime(2008, 7, 1); var end = new DateTime(2008, 7, 31); marketData.Load(begin, end); marketData.Generate(); Assert.AreEqual(22, marketData.Points.Count); // first test the points IEnumerator<TemporalPoint> itr = marketData.Points.GetEnumerator(); itr.MoveNext(); TemporalPoint point = itr.Current; Assert.AreEqual(0, point.Sequence); Assert.AreEqual(4, point.Data.Length); Assert.AreEqual(174.68, point[0]); Assert.AreEqual(26.87, point[1]); Assert.AreEqual(39, (int) (point[2]/1000000)); Assert.AreEqual(100, (int) (point[3]/1000000)); itr.MoveNext(); point = itr.Current; Assert.AreEqual(1, point.Sequence); Assert.AreEqual(4, point.Data.Length); Assert.AreEqual(168.18, point[0]); Assert.AreEqual(25.88, point[1]); Assert.AreEqual(29, (int) (point[2]/1000000)); Assert.AreEqual(84, (int) (point[3]/1000000)); itr.MoveNext(); point = itr.Current; Assert.AreEqual(2, point.Sequence); Assert.AreEqual(4, point.Data.Length); Assert.AreEqual(170.12, point[0]); Assert.AreEqual(25.98, point[1]); Assert.AreEqual(18, (int) (point[2]/1000000)); Assert.AreEqual(37, (int) (point[3]/1000000)); // now check the actual data Assert.AreEqual(16, marketData.Data.Count); Assert.AreEqual(20, marketData.InputNeuronCount); Assert.AreEqual(1, marketData.OutputNeuronCount); IEnumerator<IMLDataPair> itr2 = marketData.Data.GetEnumerator(); itr2.MoveNext(); IMLDataPair pair = itr2.Current; Assert.AreEqual(20, pair.Input.Count); Assert.AreEqual(1, pair.Ideal.Count); Assert.AreEqual(-0.037, Math.Round(pair.Input[0]*1000.0)/1000.0); Assert.AreEqual(-0.037, Math.Round(pair.Input[1]*1000.0)/1000.0); Assert.AreEqual(-0.246, Math.Round(pair.Input[2]*1000.0)/1000.0); Assert.AreEqual(-0.156, Math.Round(pair.Input[3]*1000.0)/1000.0); Assert.AreEqual(0.012, Math.Round(pair.Input[4]*1000.0)/1000.0); Assert.AreEqual(0.0040, Math.Round(pair.Input[5]*1000.0)/1000.0); Assert.AreEqual(-0.375, Math.Round(pair.Input[6]*1000.0)/1000.0); Assert.AreEqual(-0.562, Math.Round(pair.Input[7]*1000.0)/1000.0); Assert.AreEqual(0.03, Math.Round(pair.Input[8]*1000.0)/1000.0); Assert.AreEqual(0.0020, Math.Round(pair.Input[9]*1000.0)/1000.0); Assert.AreEqual(0.57, Math.Round(pair.Input[10]*100.0)/100.0); Assert.AreEqual(0.929, Math.Round(pair.Input[11]*1000.0)/1000.0); Assert.AreEqual(0.025, Math.Round(pair.Input[12]*1000.0)/1000.0); Assert.AreEqual(-0.0070, Math.Round(pair.Input[13]*1000.0)/1000.0); // for some reason, Yahoo likes to vary the volume numbers slightly, sometimes! Assert.AreEqual(0.1, Math.Round(pair.Input[14]*10.0)/10.0); Assert.AreEqual(-0.084, Math.Round(pair.Input[15]*1000.0)/1000.0); Assert.AreEqual(-0.03, Math.Round(pair.Input[16]*1000.0)/1000.0); Assert.AreEqual(-0.024, Math.Round(pair.Input[17]*1000.0)/1000.0); Assert.AreEqual(0.008, Math.Round(pair.Input[18]*1000.0)/1000.0); Assert.AreEqual(-0.172, Math.Round(pair.Input[19]*1000.0)/1000.0); itr2.MoveNext(); pair = itr2.Current; Assert.AreEqual(20, pair.Input.Count); Assert.AreEqual(1, pair.Ideal.Count); Assert.AreEqual(0.012, Math.Round(pair.Input[0]*1000.0)/1000.0); Assert.AreEqual(0.0040, Math.Round(pair.Input[1]*1000.0)/1000.0); Assert.AreEqual(-0.375, Math.Round(pair.Input[2]*1000.0)/1000.0); Assert.AreEqual(-0.562, Math.Round(pair.Input[3]*1000.0)/1000.0); Assert.AreEqual(0.03, Math.Round(pair.Input[4]*1000.0)/1000.0); Assert.AreEqual(0.0020, Math.Round(pair.Input[5]*1000.0)/1000.0); Assert.AreEqual(0.6, Math.Round(pair.Input[6]*10.0)/10.0); Assert.AreEqual(0.929, Math.Round(pair.Input[7]*1000.0)/1000.0); Assert.AreEqual(0.025, Math.Round(pair.Input[8]*1000.0)/1000.0); Assert.AreEqual(-0.0070, Math.Round(pair.Input[9]*1000.0)/1000.0); Assert.AreEqual(0.1, Math.Round(pair.Input[10]*10.0)/10.0); Assert.AreEqual(-0.084, Math.Round(pair.Input[11]*1000.0)/1000.0); Assert.AreEqual(-0.03, Math.Round(pair.Input[12]*1000.0)/1000.0); Assert.AreEqual(-0.024, Math.Round(pair.Input[13]*1000.0)/1000.0); Assert.AreEqual(0.0080, Math.Round(pair.Input[14]*1000.0)/1000.0); Assert.AreEqual(-0.172, Math.Round(pair.Input[15]*1000.0)/1000.0); Assert.AreEqual(0.014, Math.Round(pair.Input[16]*1000.0)/1000.0); Assert.AreEqual(0.0090, Math.Round(pair.Input[17]*1000.0)/1000.0); Assert.AreEqual(-0.1, Math.Round(pair.Input[18]*10.0)/10.0); Assert.AreEqual(0.066, Math.Round(pair.Input[19]*1000.0)/1000.0); }
/// <summary> /// Called to load training data for a company. This is how the training data is actually created. /// To prepare input data for recognition use the CreateData method. The training set will be /// added to. This allows the network to learn from multiple companies if this method is called /// multiple times. /// </summary> /// <param name="symbol">The ticker symbol.</param> /// <param name="training">The training set to add to.</param> /// <param name="from">Beginning date</param> /// <param name="to">Ending date</param> public void LoadCompany(String symbol, BasicMLDataSet training, DateTime from, DateTime to) { IMarketLoader loader = new YahooFinanceLoader(); TickerSymbol ticker = new TickerSymbol(symbol); IList<MarketDataType> dataNeeded = new List<MarketDataType>(); dataNeeded.Add(MarketDataType.AdjustedClose); dataNeeded.Add(MarketDataType.Close); dataNeeded.Add(MarketDataType.Open); dataNeeded.Add(MarketDataType.High); dataNeeded.Add(MarketDataType.Low); List<LoadedMarketData> results = (List<LoadedMarketData>)loader.Load(ticker, dataNeeded, from, to); results.Sort(); for (int index = PredictWindow; index < results.Count - EvalWindow; index++) { LoadedMarketData data = results[index]; // determine bull or bear position, or neither bool bullish = false; bool bearish = false; for (int search = 1; search <= EvalWindow; search++) { LoadedMarketData data2 = results[index + search]; double priceBase = data.GetData(MarketDataType.AdjustedClose); double priceCompare = data2.GetData(MarketDataType.AdjustedClose); double diff = priceCompare - priceBase; double percent = diff / priceBase; if (percent > BullPercent) { bullish = true; } else if (percent < BearPercent) { bearish = true; } } IMLDataPair pair = null; if (bullish) { pair = CreateData(results, index, true); } else if (bearish) { pair = CreateData(results, index, false); } if (pair != null) { training.Add(pair); } } }
/// <summary> /// Load the market data. /// </summary> /// <returns>True if the data was loaded.</returns> private bool LoadMarketData() { try { IMarketLoader loader = new YahooFinanceLoader(); TickerSymbol ticker = new TickerSymbol(this.Company.Text); IList<MarketDataType> needed = new List<MarketDataType>(); needed.Add(MarketDataType.AdjustedClose); needed.Add(MarketDataType.Close); needed.Add(MarketDataType.Open); needed.Add(MarketDataType.High); needed.Add(MarketDataType.Low); DateTime from = this.starting -TimeSpan.FromDays(365); DateTime to = this.starting + TimeSpan.FromDays(365*2); this.marketData = (List<LoadedMarketData>)loader.Load(ticker, needed, from, to); this.marketData.Sort(); this.numberOfDays = (int)((ActualWidth - FIRST_DAY_OFFSET) / DAY_WIDTH); this.numberOfDays = Math.Min(numberOfDays, this.marketData.Count); return true; } catch (Exception e) { MessageBox.Show("Ticker symbol likely invalid.\n"+e.Message, "Error Loading Data"); return false; } }