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// Kaufman Adaptive Ma
//
// kaufman_adaptive_ma
//
// Kaufman Adaptive Moving Average
//
// AMA based on efficiency ratio
//
// Inputs: 1
// Outputs: 1
// Constants: 1
#include <math.h>
#include "ts.h"
typedef struct {
uint_t k;
} ts_kaufman_adaptive_ma_params_t;
ts_parameter_t const ts_kaufman_adaptive_ma_p = { .n_inputs = 1, .n_outputs = 1, .n_constants = 1, .params_size = sizeof(ts_kaufman_adaptive_ma_params_t) };
uint_t ts_kaufman_adaptive_ma_offset( ts_constant_t const *c )
{
( void )c;
return ( c ? ((ts_kaufman_adaptive_ma_params_t *)c)->k : 0 );
}
int ts_kaufman_adaptive_ma(
fp_t * const *y, uint_t y_n,
fp_t const * const *x, uint_t x_n,
uint_t n, ts_constant_t const *c
)
{
TS_PROLOGUE( ts_kaufman_adaptive_ma_p );
if ( !c ) return -1;
uint_t k = ((ts_kaufman_adaptive_ma_params_t *)c)->k;
if (k == 0 || n < k) return -1;
fp_t ama = x[0][0];
fp_t sm = 2.0 / ((fp_t)k + 1.0);
fp_t sn = 2.0 / (sqrt((fp_t)k) + 1.0);
for (uint_t i = k; i < n; ++i)
{
fp_t price_change = fabs(x[0][i] - x[0][i - k]);
fp_t noise = 0;
for (uint_t j = i - k + 1; j <= i; ++j)
noise += fabs(x[0][j] - x[0][j - 1]);
fp_t er = noise != 0 ? price_change / noise : 0;
fp_t er_sq = er * er;
fp_t sc = er_sq * (sn - sm) + sm;
sc = sc * sc;
ama = ama + sc * (x[0][i] - ama);
y[0][i] = ama;
}
return 0;
}
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