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Toh4iem9
278 lines
10 KiB
Plaintext
278 lines
10 KiB
Plaintext
//+------------------------------------------------------------------+
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//| Stochastic_Adaptive_Calculator.mqh |
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//| Engine for Frank Key's Variable-Length Stochastic. |
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//| Copyright 2025, xxxxxxxx |
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//+------------------------------------------------------------------+
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#property copyright "Copyright 2025, xxxxxxxx"
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#include <MyIncludes\MovingAverage_Engine.mqh> // For ENUM_MA_TYPE
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#include <MyIncludes\HeikinAshi_Tools.mqh>
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//+==================================================================+
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class CStochasticAdaptiveCalculator
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{
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protected:
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int m_er_period, m_min_period, m_max_period, m_slowing_period, m_d_period;
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ENUM_MA_TYPE m_d_ma_type;
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double m_price[];
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virtual bool PreparePriceSeries(int rates_total, ENUM_APPLIED_PRICE price_type, const double &open[], const double &high[], const double &low[], const double &close[]);
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void CalculateMA(const double &source_array[], double &dest_array[], int period, ENUM_MA_TYPE method, int start_pos);
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public:
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CStochasticAdaptiveCalculator(void) {};
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virtual ~CStochasticAdaptiveCalculator(void) {};
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bool Init(int er_p, int min_p, int max_p, int slow_p, int d_p, ENUM_MA_TYPE d_ma);
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void Calculate(int rates_total, const double &open[], const double &high[], const double &low[], const double &close[], ENUM_APPLIED_PRICE price_type,
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double &k_buffer[], double &d_buffer[]);
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};
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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class CStochasticAdaptiveCalculator_HA : public CStochasticAdaptiveCalculator
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{
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private:
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CHeikinAshi_Calculator m_ha_calculator;
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protected:
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virtual bool PreparePriceSeries(int rates_total, ENUM_APPLIED_PRICE price_type, const double &open[], const double &high[], const double &low[], const double &close[]) override;
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};
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//+==================================================================+
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//| METHOD IMPLEMENTATIONS |
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//+==================================================================+
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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bool CStochasticAdaptiveCalculator::Init(int er_p, int min_p, int max_p, int slow_p, int d_p, ENUM_MA_TYPE d_ma)
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{
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m_er_period = (er_p < 1) ? 1 : er_p;
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m_min_period = (min_p < 1) ? 1 : min_p;
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m_max_period = (max_p <= m_min_period) ? m_min_period + 1 : max_p;
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m_slowing_period = (slow_p < 1) ? 1 : slow_p;
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m_d_period = (d_p < 1) ? 1 : d_p;
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m_d_ma_type = d_ma;
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return true;
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}
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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void CStochasticAdaptiveCalculator::Calculate(int rates_total, const double &open[], const double &high[], const double &low[], const double &close[], ENUM_APPLIED_PRICE price_type,
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double &k_buffer[], double &d_buffer[])
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{
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if(rates_total <= m_er_period + m_max_period)
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return;
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if(!PreparePriceSeries(rates_total, price_type, open, high, low, close))
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return;
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double er_buffer[], nsp_buffer[], raw_k[];
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ArrayResize(er_buffer, rates_total);
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ArrayResize(nsp_buffer, rates_total);
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ArrayResize(raw_k, rates_total);
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for(int i = m_er_period; i < rates_total; i++)
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{
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double direction = MathAbs(m_price[i] - m_price[i - m_er_period]);
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double volatility = 0;
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for(int j = 0; j < m_er_period; j++)
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volatility += MathAbs(m_price[i - j] - m_price[i - j - 1]);
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er_buffer[i] = (volatility > 0.000001) ? direction / volatility : 0;
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}
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for(int i = m_er_period; i < rates_total; i++)
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{
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nsp_buffer[i] = (int)(er_buffer[i] * (m_max_period - m_min_period) + m_min_period);
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if(nsp_buffer[i] < 1)
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nsp_buffer[i] = 1;
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}
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for(int i = m_er_period + m_max_period - 1; i < rates_total; i++)
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{
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int current_nsp = (int)nsp_buffer[i];
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double highest = m_price[i], lowest = m_price[i];
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for(int j = 1; j < current_nsp; j++)
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{
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if(i-j < 0)
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break;
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highest = MathMax(highest, m_price[i-j]);
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lowest = MathMin(lowest, m_price[i-j]);
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}
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double range = highest - lowest;
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if(range > 0.000001)
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raw_k[i] = (m_price[i] - lowest) / range * 100.0;
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else
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raw_k[i] = (i > 0) ? raw_k[i-1] : 50.0;
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}
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int k_slow_start = m_er_period + m_max_period + m_slowing_period - 2;
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CalculateMA(raw_k, k_buffer, m_slowing_period, SMA, k_slow_start);
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int d_start = k_slow_start + m_d_period - 1;
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CalculateMA(k_buffer, d_buffer, m_d_period, m_d_ma_type, d_start);
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}
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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void CStochasticAdaptiveCalculator::CalculateMA(const double &source_array[], double &dest_array[], int period, ENUM_MA_TYPE method, int start_pos)
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{
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for(int i = start_pos; i < ArraySize(source_array); i++)
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{
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switch(method)
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{
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case EMA:
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case SMMA:
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if(i == start_pos)
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{
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double sum=0;
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int count=0;
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for(int j=0; j<period; j++)
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{
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if(source_array[i-j] != EMPTY_VALUE)
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{
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sum+=source_array[i-j];
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count++;
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}
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}
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if(count > 0)
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dest_array[i]=sum/count;
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}
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else
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{
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if(method==EMA)
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{
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double pr=2.0/(period+1.0);
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dest_array[i]=source_array[i]*pr+dest_array[i-1]*(1.0-pr);
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}
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else
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dest_array[i]=(dest_array[i-1]*(period-1)+source_array[i])/period;
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}
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break;
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case LWMA:
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{
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double sum=0, w_sum=0;
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for(int j=0; j<period; j++)
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{
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if(source_array[i-j] == EMPTY_VALUE)
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continue;
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int w=period-j;
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sum+=source_array[i-j]*w;
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w_sum+=w;
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}
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if(w_sum>0)
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dest_array[i]=sum/w_sum;
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}
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break;
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default: // SMA
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{
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double sum=0;
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int count=0;
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for(int j=0; j<period; j++)
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{
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if(source_array[i-j] != EMPTY_VALUE)
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{
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sum+=source_array[i-j];
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count++;
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}
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}
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if(count > 0)
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dest_array[i]=sum/count;
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}
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break;
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}
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}
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}
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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bool CStochasticAdaptiveCalculator::PreparePriceSeries(int rates_total, ENUM_APPLIED_PRICE price_type, const double &open[], const double &high[], const double &low[], const double &close[])
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{
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if(ArraySize(m_price) != rates_total)
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if(ArrayResize(m_price, rates_total) != rates_total)
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return false;
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switch(price_type)
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{
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case PRICE_CLOSE:
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ArrayCopy(m_price, close, 0, 0, rates_total);
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break;
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case PRICE_OPEN:
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ArrayCopy(m_price, open, 0, 0, rates_total);
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break;
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case PRICE_HIGH:
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ArrayCopy(m_price, high, 0, 0, rates_total);
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break;
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case PRICE_LOW:
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ArrayCopy(m_price, low, 0, 0, rates_total);
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break;
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case PRICE_MEDIAN:
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for(int i=0; i<rates_total; i++)
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m_price[i] = (high[i]+low[i])/2.0;
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break;
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case PRICE_TYPICAL:
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for(int i=0; i<rates_total; i++)
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m_price[i] = (high[i]+low[i]+close[i])/3.0;
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break;
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case PRICE_WEIGHTED:
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for(int i=0; i<rates_total; i++)
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m_price[i] = (high[i]+low[i]+close[i]+close[i])/4.0;
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break;
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default:
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return false;
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}
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return true;
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}
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//+------------------------------------------------------------------+
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//| |
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//+------------------------------------------------------------------+
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bool CStochasticAdaptiveCalculator_HA::PreparePriceSeries(int rates_total, ENUM_APPLIED_PRICE price_type, const double &open[], const double &high[], const double &low[], const double &close[])
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{
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double ha_open[], ha_high[], ha_low[], ha_close[];
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ArrayResize(ha_open, rates_total);
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ArrayResize(ha_high, rates_total);
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ArrayResize(ha_low, rates_total);
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ArrayResize(ha_close, rates_total);
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m_ha_calculator.Calculate(rates_total, open, high, low, close, ha_open, ha_high, ha_low, ha_close);
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if(ArraySize(m_price) != rates_total)
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if(ArrayResize(m_price, rates_total) != rates_total)
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return false;
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switch(price_type)
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{
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case PRICE_CLOSE:
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ArrayCopy(m_price, ha_close, 0, 0, rates_total);
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break;
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case PRICE_OPEN:
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ArrayCopy(m_price, ha_open, 0, 0, rates_total);
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break;
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case PRICE_HIGH:
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ArrayCopy(m_price, ha_high, 0, 0, rates_total);
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break;
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case PRICE_LOW:
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ArrayCopy(m_price, ha_low, 0, 0, rates_total);
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break;
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case PRICE_MEDIAN:
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for(int i=0; i<rates_total; i++)
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m_price[i] = (ha_high[i]+ha_low[i])/2.0;
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break;
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case PRICE_TYPICAL:
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for(int i=0; i<rates_total; i++)
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m_price[i] = (ha_high[i]+ha_low[i]+ha_close[i])/3.0;
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break;
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case PRICE_WEIGHTED:
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for(int i=0; i<rates_total; i++)
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m_price[i] = (ha_high[i]+ha_low[i]+ha_close[i]+ha_close[i])/4.0;
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break;
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default:
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return false;
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}
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return true;
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}
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//+------------------------------------------------------------------+
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//+------------------------------------------------------------------+
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