add statistical functions

chungg · Jul 16, 2024 · 9385139 · 9385139
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commit 9385139
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diff --git a/README.md b/README.md
@@ -16,7 +16,7 @@ that you can beat the market.
 
 ## types of indicators
 
-100+ indicators available across 5 categories. Even across categories, indicators often
+130+ indicators available across multiple categories. Even across categories, indicators often
 behave quite similarly depending on window size. The classfication/api may change
 (if egregiously wrong).
 
@@ -43,6 +43,9 @@ the indicator, it may be a momentum indicator or trend indicator.
 Provides moving average functions. Often used to track trend, levels of support, breakouts, etc...
 The results are in the same scale as input data and are often used as a signal line for input data.
 
+### correlation
+Signals that compare two or more variables and their relationship to one another.
+
 ## installation
 1. (optional) https://rustup.rs/
 2. (optional) cargo new <lib name>
@@ -64,7 +67,7 @@ encouraged.
 - cargo test
 - cargo bench
 - cargo run --example file_json
--
+
 ## todo
 - handle div by zero scenarios
 - allow other numeric types rather than just f64
diff --git a/benches/traquer.rs b/benches/traquer.rs
@@ -514,6 +514,7 @@ fn criterion_benchmark(c: &mut Criterion) {
     c.bench_function("sig-volatility-cc_hv", |b| {
         b.iter(|| black_box(volatility::cc_hv(&stats.close, 16).collect::<Vec<_>>()))
     });
+
     c.bench_function("ma-ewma", |b| {
         b.iter(|| black_box(smooth::ewma(&stats.close, 16).collect::<Vec<f64>>()))
     });
@@ -580,6 +581,88 @@ fn criterion_benchmark(c: &mut Criterion) {
     c.bench_function("ma-t3", |b| {
         b.iter(|| black_box(smooth::t3(&stats.close, 6, None).collect::<Vec<f64>>()))
     });
+
+    c.bench_function("correlation-pcc", |b| {
+        b.iter(|| black_box(correlation::pcc(&stats.close, &stats.close, 16).collect::<Vec<_>>()))
+    });
+    c.bench_function("correlation-rsq", |b| {
+        b.iter(|| black_box(correlation::rsq(&stats.close, &stats.close, 16).collect::<Vec<_>>()))
+    });
+    c.bench_function("correlation-beta", |b| {
+        b.iter(|| black_box(correlation::beta(&stats.close, &stats.close, 16).collect::<Vec<_>>()))
+    });
+    c.bench_function("correlation-rsc", |b| {
+        b.iter(|| black_box(correlation::rsc(&stats.close, &stats.close).collect::<Vec<_>>()))
+    });
+    c.bench_function("correlation-perf", |b| {
+        b.iter(|| black_box(correlation::perf(&stats.close, &stats.close, 16).collect::<Vec<_>>()))
+    });
+
+    c.bench_function("stats-dist-variance", |b| {
+        b.iter(|| {
+            black_box(statistic::distribution::variance(&stats.close, 16).collect::<Vec<_>>())
+        })
+    });
+    c.bench_function("stats-dist-std_dev", |b| {
+        b.iter(|| black_box(statistic::distribution::std_dev(&stats.close, 16).collect::<Vec<_>>()))
+    });
+    c.bench_function("stats-dist-zscore", |b| {
+        b.iter(|| black_box(statistic::distribution::zscore(&stats.close, 16).collect::<Vec<_>>()))
+    });
+
+    c.bench_function("stats-dist-mad", |b| {
+        b.iter(|| black_box(statistic::distribution::mad(&stats.close, 16).collect::<Vec<_>>()))
+    });
+    c.bench_function("stats-dist-cv", |b| {
+        b.iter(|| black_box(statistic::distribution::cv(&stats.close, 16).collect::<Vec<_>>()))
+    });
+    c.bench_function("stats-dist-kurtosis", |b| {
+        b.iter(|| {
+            black_box(statistic::distribution::kurtosis(&stats.close, 16).collect::<Vec<_>>())
+        })
+    });
+    c.bench_function("stats-dist-skew", |b| {
+        b.iter(|| black_box(statistic::distribution::skew(&stats.close, 16).collect::<Vec<_>>()))
+    });
+    c.bench_function("stats-dist-median", |b| {
+        b.iter(|| black_box(statistic::distribution::median(&stats.close, 16).collect::<Vec<_>>()))
+    });
+    c.bench_function("stats-dist-quantile", |b| {
+        b.iter(|| {
+            black_box(statistic::distribution::quantile(&stats.close, 16, 90.0).collect::<Vec<_>>())
+        })
+    });
+
+    c.bench_function("stats-regress-mse", |b| {
+        b.iter(|| {
+            black_box(statistic::regression::mse(&stats.close, &stats.open).collect::<Vec<_>>())
+        })
+    });
+    c.bench_function("stats-regress-rmse", |b| {
+        b.iter(|| {
+            black_box(statistic::regression::rmse(&stats.close, &stats.open).collect::<Vec<_>>())
+        })
+    });
+    c.bench_function("stats-regress-mae", |b| {
+        b.iter(|| {
+            black_box(statistic::regression::mae(&stats.close, &stats.open).collect::<Vec<_>>())
+        })
+    });
+    c.bench_function("stats-regress-mape", |b| {
+        b.iter(|| {
+            black_box(statistic::regression::mape(&stats.close, &stats.open).collect::<Vec<_>>())
+        })
+    });
+    c.bench_function("stats-regress-smape", |b| {
+        b.iter(|| {
+            black_box(statistic::regression::smape(&stats.close, &stats.open).collect::<Vec<_>>())
+        })
+    });
+    c.bench_function("stats-regress-mda", |b| {
+        b.iter(|| {
+            black_box(statistic::regression::mda(&stats.close, &stats.open).collect::<Vec<_>>())
+        })
+    });
 }
 
 criterion_group!(benches, criterion_benchmark);

diff --git a/src/lib.rs b/src/lib.rs
@@ -3,6 +3,7 @@
 pub mod correlation;
 pub mod momentum;
 pub mod smooth;
+pub mod statistic;
 pub mod trend;
 pub mod volatility;
 pub mod volume;
diff --git a/src/smooth.rs b/src/smooth.rs
@@ -9,6 +9,8 @@ use std::collections::VecDeque;
 use std::f64::consts::PI;
 use std::iter;
 
+use crate::statistic::distribution::_std_dev;
+
 /// Moving average types
 pub enum MaMode {
     SMA,
@@ -278,13 +280,6 @@ pub fn hull(data: &[f64], window: usize) -> impl Iterator<Item = f64> + '_ {
     .into_iter()
 }
 
-pub(crate) fn std_dev(data: &[f64], window: usize) -> impl Iterator<Item = f64> + '_ {
-    data.windows(window).map(move |w| {
-        let mean = w.iter().sum::<f64>() / window as f64;
-        (w.iter().map(|x| (x - mean).powi(2)).sum::<f64>() / window as f64).sqrt()
-    })
-}
-
 /// Volatility Index Dynamic Average (VIDYA)
 ///
 /// A type of moving average that uses a combination of short-term and long-term
@@ -301,7 +296,7 @@ pub(crate) fn std_dev(data: &[f64], window: usize) -> impl Iterator<Item = f64>
 /// ```
 pub fn vidya(data: &[f64], window: usize) -> impl Iterator<Item = f64> + '_ {
     let alpha = 2.0 / (window + 1) as f64;
-    let std5 = std_dev(data, 5).collect::<Vec<f64>>();
+    let std5 = _std_dev(data, 5).collect::<Vec<f64>>();
     let std20 = sma(&std5, 20).collect::<Vec<f64>>();
     let offset = (5 - 1) + (20 - 1);
     iter::repeat(f64::NAN).take(offset).chain(