public void SetStats(LoadedMarketData data)
{
this.open = data.GetData(MarketDataType.Open);
this.close = data.GetData(MarketDataType.Close);
this.high = data.GetData(MarketDataType.High);
this.low = data.GetData(MarketDataType.Low);
this.bodyTop = Math.Max(this.open, this.close);
this.bodyBottom = Math.Min(this.open, this.close);
}
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));
}
/// <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);
}
}
}
public void SetStats(LoadedMarketData data)
{
this.open = data.GetData(MarketDataType.Open);
this.close = data.GetData(MarketDataType.Close);
this.high = data.GetData(MarketDataType.High);
this.low = data.GetData(MarketDataType.Low);
this.bodyTop = Math.Max(this.open, this.close);
this.bodyBottom = Math.Min(this.open, this.close);
}
