/// <summary>
/// Creates a market recommendation using a fully sequential operation
/// </summary>
/// <returns>A market recommendation</returns>
public MarketRecommendation DoAnalysisSequential()
{
StockDataCollection nyseData =
LoadNyseData();
StockDataCollection nasdaqData =
LoadNasdaqData();
StockDataCollection mergedMarketData =
MergeMarketData(new[] { nyseData, nasdaqData });
StockDataCollection normalizedMarketData =
NormalizeData(mergedMarketData);
StockDataCollection fedHistoricalData =
LoadFedHistoricalData();
StockDataCollection normalizedHistoricalData =
NormalizeData(fedHistoricalData);
StockAnalysisCollection analyzedStockData =
AnalyzeData(normalizedMarketData);
MarketModel modeledMarketData =
RunModel(analyzedStockData);
StockAnalysisCollection analyzedHistoricalData =
AnalyzeData(normalizedHistoricalData);
MarketModel modeledHistoricalData =
RunModel(analyzedHistoricalData);
MarketRecommendation recommendation =
CompareModels(new[] { modeledMarketData,
modeledHistoricalData });
return(recommendation);
}
MarketModel RunModel(StockAnalysisCollection data)
{
SampleUtilities.DoCpuIntensiveOperation(2.0 * speedFactor, cts.Token);
if (cts.Token.IsCancellationRequested)
{
return(null);
}
else
{
return(MarketModeler.Run(data));
}
}
public static MarketModel Run(StockAnalysisCollection data)
{
return new MarketModel();
}
MarketModel RunModel(StockAnalysisCollection data)
{
SampleUtilities.DoCpuIntensiveOperation(2.0 * speedFactor, cts.Token);
if (cts.Token.IsCancellationRequested)
return null;
else
return MarketModeler.Run(data);
}
