/// <summary>
/// 用BPNN预测股票
/// </summary>
public void BPNNForecastStock(DateTime date)
{
try
{
var net = JsonHelper.DeserializeJsonToObject <BPNN>(File.ReadAllText(DataHelper.GetConfig("networkPath")));
var todayStr = date.ToString("yyyy-MM-dd");
proc.deleteStockForeCast(todayStr);
StockPointCompute spc = new StockPointCompute();
DataTable stockIndexCode = proc.getStockIndexCode(todayStr);
foreach (DataRow dr in stockIndexCode.Rows)
{
string stockCode = dr[0].ToString();
DataTable res = proc.getStockMatchedIndex(todayStr, stockCode);
List <double> features = new List <double>();
foreach (DataRow row in res.Rows)
{
features.Add(Convert.ToDouble(row[1]));
}
double result = net.forecast(ref net, features.ToArray())[0];
proc.insertStockForeCast(stockCode, todayStr, result);
}
}
catch (Exception ex)
{
LogHelper.WriteLog("预测股票失败", ex);
}
}
/// <summary>
/// 计算股票指标
/// </summary>
/// <param name="startDate">开始时间</param>
/// <param name="endDate">结束时间ps:日期跨度要满足指标分析算法需求</param>
/// <param name="stockCode">股票代码</param>
/// <returns></returns>
private List <StockMatchedIndex> GetStockIndex(string startDate, string endDate, string stockCode)
{
List <StockMatchedIndex> result = new List <StockMatchedIndex>();
DataTable dt = proc.getStockHistoryData(startDate, endDate, stockCode);
List <StockHistoryData> data = Utility.XHelper.FillListByDataTable <StockHistoryData>(dt);
#region 检测数据
if (data == null || data.Count == 0 || data.Count < 45 || Convert.ToDateTime(data[0].StockHistoryDate) != Convert.ToDateTime(endDate))
{
return(result);
}
int suspended = 0;
foreach (var item in data)
{
// 成交量为零，停牌超过10个交易日
if (item.SVolume == 0)
{
suspended++;
if (suspended > 5)
{
result.Add(new StockMatchedIndex()
{
Date = Convert.ToDateTime(endDate), StockCode = stockCode, StockIndexID = SpacialShape.Suspended, StockMatchedIndexID = Guid.NewGuid()
});
return(result);
}
}
// 涨跌超过10%，事件
else if (Math.Abs((item.SClose - item.SOpen) / item.SOpen) > 0.11M)
{
result.Add(new StockMatchedIndex()
{
Date = Convert.ToDateTime(endDate), StockCode = stockCode, StockIndexID = SpacialShape.Event, StockMatchedIndexID = Guid.NewGuid()
});
return(result);
}
}
#endregion
data = data.Where(w => w.SVolume > 0).ToList();
if (data.Count < 45)
{
return(result);
}
#region 计算指标
try
{
StockPointCompute spc = new StockPointCompute();
result.AddRange(getStockMatchedIndex(endDate, stockCode, spc.Index_KDJ(data)));
result.AddRange(getStockMatchedIndex(endDate, stockCode, spc.Index_LineEqual(data)));
result.AddRange(getStockMatchedIndex(endDate, stockCode, spc.Index_LineK(data)));
result.AddRange(getStockMatchedIndex(endDate, stockCode, spc.Index_PSY(data)));
result.AddRange(getStockMatchedIndex(endDate, stockCode, spc.Index_VR(data)));
result.AddRange(getStockMatchedIndex(endDate, stockCode, spc.Index_W_R(data)));
}
catch (Exception ex)
{
LogHelper.WriteLog(string.Format("计算指标失败 startDate：{0}，endDate：{1}，stockCode：{2}", startDate, endDate, stockCode), ex);
}
#endregion
return(result.Where(w => w.StockIndexID % 100 != 0).ToList());
}
/// <summary>
///
/// </summary>
/// <param name="date"></param>
/// <param name="takeN"></param>
/// <param name="closeWeight"></param>
/// <param name="upperShadowWeight"></param>
/// <param name="lowerShadowWeight"></param>
/// <param name="entityWeight"></param>
/// <param name="topN"></param>
/// <returns></returns>
public List <String> getSimilarPlate(DateTime date, int takeN, double closeWeight, double upperShadowWeight, double lowerShadowWeight, double entityWeight, int topN)
{
WangYiStockApi wysa = new WangYiStockApi();
StockPointCompute spc = new StockPointCompute();
var ssPlate = wysa.getDataFromWangYi("000001.ss", date.AddYears(-5), date).Where(w => w.SVolume > 0).OrderBy(o => o.StockHistoryDate);
var szPlate = wysa.getDataFromWangYi("399001.sz", date.AddYears(-5), date).Where(w => w.SVolume > 0).OrderBy(o => o.StockHistoryDate);
if (Convert.ToDateTime(ssPlate.ToList()[ssPlate.Count() - 1].StockHistoryDate) != date)
{
return(null);
}
Dictionary <string, decimal> meanClose = new Dictionary <string, decimal>();
Dictionary <string, decimal> meanOpen = new Dictionary <string, decimal>();
Dictionary <string, decimal> meanHigh = new Dictionary <string, decimal>();
Dictionary <string, decimal> meanLow = new Dictionary <string, decimal>();
foreach (var i in ssPlate)
{
foreach (var j in szPlate)
{
if (i.StockHistoryDate == j.StockHistoryDate)
{
meanClose.Add(i.StockHistoryDate, i.SClose + j.SClose);
meanOpen.Add(i.StockHistoryDate, i.SOpen + j.SOpen);
meanHigh.Add(i.StockHistoryDate, i.SHigh + j.SHigh);
meanLow.Add(i.StockHistoryDate, i.SLow + j.SLow);
break;
}
}
}
var meanCloseRise = spc.GetIncrease(meanClose.Values.ToList());
List <double> upperShadow = new List <double>();
List <double> lowerShadow = new List <double>();
List <double> entity = new List <double>();
for (int i = 1; i < meanClose.Count; i++)
{
var low = meanLow.Values.ToList()[i];
var high = meanHigh.Values.ToList()[i];
var open = meanOpen.Values.ToList()[i];
var close = meanClose.Values.ToList()[i];
upperShadow.Add((double)(high - (open > close ? open : close)) / (double)(high - low));
entity.Add((double)Math.Abs(close - open) / (double)(high - low));
lowerShadow.Add((double)((open < close ? open : close) - low) / (double)(high - low));
}
var closeRise = meanCloseRise.Skip(meanCloseRise.Count - takeN).ToList();
var upperSw = upperShadow.Skip(upperShadow.Count - takeN).ToList();
var lowerSw = lowerShadow.Skip(lowerShadow.Count - takeN).ToList();
var ey = entity.Skip(entity.Count - takeN).ToList();
var closeRiseArray = spc.spiltArray(meanCloseRise, takeN);
var upperShadowArray = spc.spiltArray(upperShadow, takeN);
var lowerShadowArray = spc.spiltArray(lowerShadow, takeN);
var entityArray = spc.spiltArray(entity, takeN);
Dictionary <string, double> resultDic = new Dictionary <string, double>();
for (int i = 1; i < meanClose.Count - 6; i++)
{
double distanceClose = DataHelper.ListDistance(closeRise, closeRiseArray[i]);
double distanceUpperSw = DataHelper.ListDistance(upperSw, upperShadowArray[i]);
double distanceLowerSw = DataHelper.ListDistance(lowerSw, lowerShadowArray[i]);
double distanceEntity = DataHelper.ListDistance(ey, entityArray[i]);
resultDic.Add(meanClose.Keys.ToList()[i], distanceClose * closeWeight + distanceEntity * entityWeight + distanceLowerSw * lowerShadowWeight + distanceUpperSw * upperShadowWeight);
}
return(resultDic.OrderBy(o => o.Value).Take(topN).Select(s => s.Key).ToList());
}
