我正在尝试计算金融工具的相对强弱指数 RSI 。当我将计算与商业软件的计算进行比较时，它们看起来并不相同。我无法弄清楚我做错了什么。有人可以帮忙吗？
RSI formula：
{100} - （100 /（1 + RS））。其中RS是AvgGain（N个周期）/ AvgLoss（N个周期）
public DataTable RSI(string instrument, int period, string oper, int entryVal)
{
DataTable dtRSI = new DataTable(); //table to return
dtRSI.Columns.Add("Date");
dtRSI.Columns.Add("Instrument");
dtRSI.Columns.Add("Close");
dtRSI.Columns.Add("RSI");
//Load Datatable from database
DataTable dt = new DataTable();
dt = conn.ExtractDataFromDb(instrument);
int column = 1; //Close price
//variables to RSI formula
Queue<float> avgUp = new Queue<float>();
Queue<float> avgDown = new Queue<float>();
float close1, close2, rsi, rs;
float avgUp1, avgUp2, newAvgUp, avgDown1, avgDown2, newAvgDown;
string[] dateCloseRsi = new string[3]; //row of data to insert into new table
string date; //date of calculation
string[] splitDate = new string[2];
//get first close
close1 = float.Parse(dt.Rows[0][column].ToString());
dt.Rows.RemoveAt(0);
//get close for number of periods into the que-list
for (int i = 1; i <= period; i++)
{
close2 = float.Parse(dt.Rows[0][column].ToString());
//are todays close higher then yesterday?
if (close2 > close1)
{
avgUp.Enqueue(close2 - close1);
avgDown.Enqueue(0);
}
else if (close2<close1)
{
avgUp.Enqueue(0);
avgDown.Enqueue(close1 - close2);
}
else
{
avgUp.Enqueue(0);
avgDown.Enqueue(0);
}
close1 = close2;
dt.Rows.RemoveAt(0);
}
//iterate datatable and calculate RSI
foreach (DataRow rows in dt.Rows)
{
avgUp1 = float.Parse(avgUp.Average().ToString("n2")); //calculate yesterdays avg difference on up days
avgDown1 = float.Parse(avgDown.Average().ToString("n2")); //calculate yesterdays avg difference on down days
avgUp.Dequeue();
avgDown.Dequeue();
close2 = float.Parse(rows[column].ToString()); //todays close
//close today higher then yesterday?
if (close2 > close1)
{
avgUp.Enqueue(close2 - close1);
avgDown.Enqueue(0);
}
else if (close2 < close1)
{
avgDown.Enqueue(close1 - close2);
avgUp.Enqueue(0);
}
else
{
avgUp.Enqueue(0);
avgDown.Enqueue(0);
}
avgUp2 = float.Parse(avgUp.Average().ToString("n2")); //todays avg difference on up days
avgDown2 = float.Parse(avgDown.Average().ToString("n2")); //todays avg difference on down days
newAvgUp = ((avgUp1 * (period - 1)) + avgUp2) / period; //yesterdays and todays avg diff value on up days
newAvgDown = ((avgDown1 * (period - 1)) + avgDown2) / period; //yesterdays and todays avg diff value on down days
newAvgUp = float.Parse(newAvgUp.ToString("n2")); //round to 2 decimals
newAvgDown = float.Parse(newAvgDown.ToString("n2")); //round to 2 decimals
rs = newAvgUp / newAvgDown; //calc Relative Strength
rs = float.Parse(rs.ToString("n2")); //round to 2 decimals
rsi = 100 - (100 / (1 + rs)); //Calc RSI
rsi = float.Parse(rsi.ToString("n2")); //round to 2 decimals
close1 = close2; //todays close become yesterdays close for tomorrow
//remove time from date
date = rows[0].ToString();
splitDate = date.Split(' ');
date = splitDate[0];
//add data to dtRSI
DataRow rsiRow = dtRSI.NewRow();
rsiRow["Date"] = date;
rsiRow["Instrument"] = instrument;
rsiRow["Close"] = rows[column];
rsiRow["RSI"] = rsi;
dtRSI.Rows.Add(rsiRow);
}
return dtRSI; //returns a table with Date, Instrument, Close Price and RSI
}
答案 0 :(得分：0)
您好，这是一个经过测试和验证的 C# 类，它以 100% 的准确度生成 RSI 值：
using System;
using System.Data;
using System.Globalization;
namespace YourNameSpace
{
class PriceEngine
{
public static DataTable data;
public static double[] positiveChanges;
public static double[] negativeChanges;
public static double[] averageGain;
public static double[] averageLoss;
public static double[] rsi;
public static double CalculateDifference(double current_price, double previous_price)
{
return current_price - previous_price;
}
public static double CalculatePositiveChange(double difference)
{
return difference > 0 ? difference : 0;
}
public static double CalculateNegativeChange(double difference)
{
return difference < 0 ? difference * -1 : 0;
}
public static void CalculateRSI(int rsi_period, int price_index = 5)
{
for(int i = 0; i < PriceEngine.data.Rows.Count; i++)
{
double current_difference = 0.0;
if (i > 0)
{
double previous_close = Convert.ToDouble(PriceEngine.data.Rows[i-1].Field<string>(price_index));
double current_close = Convert.ToDouble(PriceEngine.data.Rows[i].Field<string>(price_index));
current_difference = CalculateDifference(current_close, previous_close);
}
PriceEngine.positiveChanges[i] = CalculatePositiveChange(current_difference);
PriceEngine.negativeChanges[i] = CalculateNegativeChange(current_difference);
if(i == Math.Max(1,rsi_period))
{
double gain_sum = 0.0;
double loss_sum = 0.0;
for(int x = Math.Max(1,rsi_period); x > 0; x--)
{
gain_sum += PriceEngine.positiveChanges[x];
loss_sum += PriceEngine.negativeChanges[x];
}
PriceEngine.averageGain[i] = gain_sum / Math.Max(1,rsi_period);
PriceEngine.averageLoss[i] = loss_sum / Math.Max(1,rsi_period);
}else if (i > Math.Max(1,rsi_period))
{
PriceEngine.averageGain[i] = ( PriceEngine.averageGain[i-1]*(rsi_period-1) + PriceEngine.positiveChanges[i]) / Math.Max(1, rsi_period);
PriceEngine.averageLoss[i] = ( PriceEngine.averageLoss[i-1]*(rsi_period-1) + PriceEngine.negativeChanges[i]) / Math.Max(1, rsi_period);
PriceEngine.rsi[i] = PriceEngine.averageLoss[i] == 0 ? 100 : PriceEngine.averageGain[i] == 0 ? 0 : Math.Round(100 - (100 / (1 + PriceEngine.averageGain[i] / PriceEngine.averageLoss[i])), 5);
}
}
}
public static void Launch()
{
PriceEngine.data = new DataTable();
//load {date, time, open, high, low, close} values in PriceEngine.data (6th column (index #5) = close price) here
positiveChanges = new double[PriceEngine.data.Rows.Count];
negativeChanges = new double[PriceEngine.data.Rows.Count];
averageGain = new double[PriceEngine.data.Rows.Count];
averageLoss = new double[PriceEngine.data.Rows.Count];
rsi = new double[PriceEngine.data.Rows.Count];
CalculateRSI(14);
}
}
}
关于详细的分步说明，我写了一篇很长的文章，你可以在这里查看： https://turmanauli.medium.com/a-step-by-step-guide-for-calculating-reliable-rsi-values-programmatically-a6a604a06b77
附言您需要全局变量来存储先前的值，这不适用于 RSI 等指标，简单函数仅适用于简单移动平均线等简单指标。所有平滑/加权指标都需要缓冲区/全局数组来存储数据。