summaryrefslogtreecommitdiffstats
path: root/lib/kaufman_adaptive_ma.c
diff options
context:
space:
mode:
authorEthan Werner <mail@ethanwerner.com>2026-07-01 09:42:39 +0400
committerEthan Werner <mail@ethanwerner.com>2026-07-01 09:42:39 +0400
commit07e18043145f3d91c8ea7ec3ad41b3c905585277 (patch)
tree2bdeae46973f4bdfce263679a4008ac768011f28 /lib/kaufman_adaptive_ma.c
initial commit: ts time series analysis library v0.1.0
- 354 financial and mathematical time-series indicators - Uniform C11 API with consistent function signatures - 349 passing tests with -Werror - Static and shared library builds - pkg-config integration - Python bindings - Fuzzing and sanitizer support - Security hardening flags
Diffstat (limited to 'lib/kaufman_adaptive_ma.c')
-rw-r--r--lib/kaufman_adaptive_ma.c61
1 files changed, 61 insertions, 0 deletions
diff --git a/lib/kaufman_adaptive_ma.c b/lib/kaufman_adaptive_ma.c
new file mode 100644
index 0000000..f56c6a1
--- /dev/null
+++ b/lib/kaufman_adaptive_ma.c
@@ -0,0 +1,61 @@
+// 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;
+}
+