/// <summary> /// Load the market data. /// </summary> /// <returns> True if the data was loaded. </returns> private bool LoadMarketData() { try { IMarketLoader loader = new YahooFinanceLoader(); var ticker = new TickerSymbol(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 = starting - TimeSpan.FromDays(365); DateTime to = starting + TimeSpan.FromDays(365 * 2); marketData = (List <LoadedMarketData>)loader.Load(ticker, needed, from, to); marketData.Sort(); numberOfDays = (int)((ActualWidth - FirstDayOffset) / DayWidth); numberOfDays = Math.Min(numberOfDays, marketData.Count); return(true); } catch (Exception e) { MessageBox.Show("Ticker symbol likely invalid.\n" + e.Message, "Error Loading Data"); return(false); } }
/// <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(); var 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); var results = (List <LoadedMarketData>)loader.Load(ticker, dataNeeded, from, to); results.Sort(); for (var index = PredictWindow; index < results.Count - EvalWindow; index++) { var data = results[index]; // determine bull or bear position, or neither var bullish = false; var bearish = false; for (int search = 1; search <= EvalWindow; search++) { var data2 = results[index + search]; var priceBase = data.GetData(MarketDataType.AdjustedClose); var priceCompare = data2.GetData(MarketDataType.AdjustedClose); var diff = priceCompare - priceBase; var 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); } } }
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)); }