MarketPersistence

StockSharp.Algo.Candles

Whether moves tend to continue or to come back.

构造函数

public MarketPersistence(decimal Autocorrelation1, decimal Autocorrelation5, decimal VarianceRatio5, decimal VarianceRatio20, decimal DirectionalDaySharePercent)

marketPersistence = MarketPersistence(Autocorrelation1, Autocorrelation5, VarianceRatio5, VarianceRatio20, DirectionalDaySharePercent)

Whether moves tend to continue or to come back.

Autocorrelation1: Correlation between a candle's return and the next one's.
Autocorrelation5: Correlation between a candle's return and the one five candles later.
VarianceRatio5: Variance of five-candle returns against five times the one-candle variance.
VarianceRatio20: Variance of twenty-candle returns against twenty times the one-candle variance.
DirectionalDaySharePercent: Share of days that closed near an extreme of their range rather than mid-range, in percent.

属性

Autocorrelation1

public decimal Autocorrelation1 { get; set; }

value = marketPersistence.Autocorrelation1
marketPersistence.Autocorrelation1 = value

Correlation between a candle's return and the next one's.

Autocorrelation5

public decimal Autocorrelation5 { get; set; }

value = marketPersistence.Autocorrelation5
marketPersistence.Autocorrelation5 = value

Correlation between a candle's return and the one five candles later.

DirectionalDaySharePercent

public decimal DirectionalDaySharePercent { get; set; }

value = marketPersistence.DirectionalDaySharePercent
marketPersistence.DirectionalDaySharePercent = value

Share of days that closed near an extreme of their range rather than mid-range, in percent.

VarianceRatio20

public decimal VarianceRatio20 { get; set; }

value = marketPersistence.VarianceRatio20
marketPersistence.VarianceRatio20 = value

Variance of twenty-candle returns against twenty times the one-candle variance.

VarianceRatio5

public decimal VarianceRatio5 { get; set; }

value = marketPersistence.VarianceRatio5
marketPersistence.VarianceRatio5 = value

Variance of five-candle returns against five times the one-candle variance.