diff --git a/Cargo.lock b/Cargo.lock
index 9f80713..676577c 100644
--- a/Cargo.lock
+++ b/Cargo.lock
@@ -183,6 +183,17 @@ dependencies = [
  "wasm-bindgen",
 ]
 
+[[package]]
+name = "console_log"
+version = "1.0.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "be8aed40e4edbf4d3b4431ab260b63fdc40f5780a4766824329ea0f1eefe3c0f"
+dependencies = [
+ "log",
+ "wasm-bindgen",
+ "web-sys",
+]
+
 [[package]]
 name = "crossbeam-deque"
 version = "0.8.6"
@@ -258,6 +269,7 @@ dependencies = [
  "pyo3",
  "rayon",
  "statrs",
+ "wasm-bindgen",
 ]
 
 [[package]]
@@ -274,7 +286,9 @@ name = "finlib-wasm"
 version = "0.0.1"
 dependencies = [
  "console_error_panic_hook",
+ "console_log",
  "finlib",
+ "log",
  "wasm-bindgen",
  "wasm-bindgen-test",
 ]
diff --git a/Cargo.toml b/Cargo.toml
index 162eedf..0867f5b 100644
--- a/Cargo.toml
+++ b/Cargo.toml
@@ -30,6 +30,7 @@ ndarray-stats = "0.6.0"
 nalgebra = "0.33.2"
 statrs = "0.18.0"
 log = "0.4.25"
+wasm-bindgen = "0.2.100"
 pyo3 = { version = "0.23.4", features = ["extension-module", "abi3-py38"] }
 pyo3-log = "0.12.1"
 
diff --git a/finlib-ffi/Cargo.toml b/finlib-ffi/Cargo.toml
index a371f5c..46c3636 100644
--- a/finlib-ffi/Cargo.toml
+++ b/finlib-ffi/Cargo.toml
@@ -13,7 +13,7 @@ readme.workspace = true
 crate-type = ["cdylib"]
 
 [dependencies]
-finlib = { path = "../finlib" }
+finlib = { path = "../finlib", features = ["ffi"] }
 
 [build-dependencies]
 cbindgen = "0.28.0"
diff --git a/finlib-wasm/Cargo.toml b/finlib-wasm/Cargo.toml
index b368953..e9f9e90 100644
--- a/finlib-wasm/Cargo.toml
+++ b/finlib-wasm/Cargo.toml
@@ -16,8 +16,10 @@ crate-type = ["cdylib", "rlib"]
 default = ["console_error_panic_hook"]
 
 [dependencies]
-wasm-bindgen = "0.2.100"
+wasm-bindgen = { workspace = true }
 finlib = { path = "../finlib", features = ["wasm"] }
+log = { workspace = true }
+console_log = { version = "1.0.0", features = ["color"] }
 
 # The `console_error_panic_hook` crate provides better debugging of panics by
 # logging them with `console.error`. This is great for development, but requires
diff --git a/finlib-wasm/src/lib.rs b/finlib-wasm/src/lib.rs
index e7f8af4..d6489d8 100644
--- a/finlib-wasm/src/lib.rs
+++ b/finlib-wasm/src/lib.rs
@@ -1,4 +1,13 @@
 use wasm_bindgen::prelude::wasm_bindgen;
+use console_log;
+use log::Level;
+
+#[wasm_bindgen(start)]
+fn start() {
+    if let Err(_) = console_log::init_with_level(Level::Debug) {
+
+    }
+}
 
 #[wasm_bindgen]
 pub struct Interest { }
diff --git a/finlib/Cargo.toml b/finlib/Cargo.toml
index cf65cbd..3fc91b6 100644
--- a/finlib/Cargo.toml
+++ b/finlib/Cargo.toml
@@ -11,6 +11,7 @@ documentation.workspace = true
 readme.workspace = true
 
 [dependencies]
+wasm-bindgen = { workspace = true, optional = true }
 pyo3 = { workspace = true, optional = true }
 rayon = { workspace = true, optional = true }
 ndarray = { workspace = true }
@@ -22,5 +23,6 @@ getrandom = "*"
 
 [features]
 py = ["dep:pyo3"]
-wasm = ["getrandom/js"]
-parallel = ["dep:rayon"]
\ No newline at end of file
+wasm = ["getrandom/js", "dep:wasm-bindgen"]
+parallel = ["dep:rayon"]
+ffi = []
\ No newline at end of file
diff --git a/finlib/src/lib.rs b/finlib/src/lib.rs
index 71f9f98..29a08cf 100644
--- a/finlib/src/lib.rs
+++ b/finlib/src/lib.rs
@@ -1,4 +1,6 @@
 pub mod interest;
 pub mod stats;
 pub mod util;
-pub mod risk;
\ No newline at end of file
+pub mod risk;
+#[cfg(feature = "py")]
+pub mod py;
\ No newline at end of file
diff --git a/finlib/src/py/mod.rs b/finlib/src/py/mod.rs
new file mode 100644
index 0000000..3d5ddb6
--- /dev/null
+++ b/finlib/src/py/mod.rs
@@ -0,0 +1,30 @@
+use pyo3::prelude::*;
+use crate::risk::portfolio::{Portfolio, PortfolioAsset};
+
+#[pymethods]
+impl Portfolio {
+
+    #[new]
+    pub fn init(assets: Vec<PortfolioAsset>) -> Self {
+        Portfolio::from(assets)
+    }
+
+    #[pyo3(name = "is_valid")]
+    pub fn is_valid_py(&self) -> bool {
+        self.is_valid()
+    }
+
+    #[pyo3(name = "value_at_risk")]
+    pub fn value_at_risk_py(&mut self, confidence: f64) -> PyResult<Option<f64>> {
+        Ok(self.value_at_risk(confidence))
+    }
+}
+
+#[pymethods]
+impl PortfolioAsset {
+
+    #[new]
+    pub fn init(portfolio_weight: f64, name: String, values: Vec<f64>) -> Self {
+        PortfolioAsset::new(portfolio_weight, name, values)
+    }
+}
\ No newline at end of file
diff --git a/finlib/src/risk/mod.rs b/finlib/src/risk/mod.rs
index cd03cb3..bc8efc9 100644
--- a/finlib/src/risk/mod.rs
+++ b/finlib/src/risk/mod.rs
@@ -1 +1,2 @@
-pub mod var;
\ No newline at end of file
+pub mod var;
+pub mod portfolio;
diff --git a/finlib/src/risk/portfolio.rs b/finlib/src/risk/portfolio.rs
new file mode 100644
index 0000000..0340a39
--- /dev/null
+++ b/finlib/src/risk/portfolio.rs
@@ -0,0 +1,201 @@
+use ndarray::prelude::*;
+use ndarray_stats::CorrelationExt;
+#[cfg(feature = "wasm")]
+use wasm_bindgen::prelude::*;
+#[cfg(feature = "py")]
+use pyo3::prelude::*;
+use crate::risk::var::varcovar::portfolio_value_at_risk;
+use crate::stats;
+use crate::util::roc::rates_of_change;
+
+#[cfg_attr(feature = "wasm", wasm_bindgen)]
+#[cfg_attr(feature = "py", pyclass)]
+#[cfg_attr(feature = "ffi", repr(C))]
+#[derive(Clone)]
+pub struct Portfolio {
+    assets: Vec<PortfolioAsset>
+}
+
+#[cfg_attr(feature = "wasm", wasm_bindgen)]
+#[cfg_attr(feature = "py", pyclass)]
+#[repr(u8)]
+#[derive(Clone, Copy, Debug, Eq, PartialEq, Ord, PartialOrd)]
+pub enum ValueType {
+    Absolute,
+    RateOfChange
+}
+
+#[cfg_attr(feature = "wasm", wasm_bindgen)]
+#[cfg_attr(feature = "py", pyclass)]
+#[cfg_attr(feature = "ffi", repr(C))]
+#[derive(Clone)]
+pub struct PortfolioAsset {
+    portfolio_weight: f64,
+    name: String,
+    values: Vec<f64>,
+    value_type: ValueType
+}
+
+impl PortfolioAsset {
+    pub fn new(portfolio_weight: f64, name: String, values: Vec<f64>) -> PortfolioAsset {
+        PortfolioAsset {
+            portfolio_weight, name, values, value_type: ValueType::Absolute
+        }
+    }
+
+    pub fn apply_rates_of_change(&mut self) {
+        match self.value_type {
+            ValueType::Absolute => {
+                self.values = rates_of_change(&self.values).collect();
+                self.value_type = ValueType::RateOfChange;
+            }
+            _ => {}
+        }
+    }
+
+    pub fn get_mean_and_std(&self) -> Option<(f64, f64)> {
+        match self.value_type {
+            ValueType::Absolute => {
+                let roc = rates_of_change(&self.values).collect::<Vec<f64>>();
+                Some((stats::mean(&roc), stats::sample_std_dev(&roc)))
+            }
+            ValueType::RateOfChange => {
+                Some((stats::mean(&self.values), stats::sample_std_dev(&self.values)))
+            }
+        }
+    }
+}
+
+impl Portfolio {
+    pub fn from(assets: Vec<PortfolioAsset>) -> Portfolio {
+        Portfolio {
+            assets
+        }
+    }
+
+    pub fn get_asset_weight(&self) -> impl Iterator<Item=f64> + use<'_> {
+        self.assets
+            .iter()
+            .map(|x| x.portfolio_weight)
+    }
+
+    pub fn apply_rates_of_change(&mut self) {
+        for asset in self.assets.iter_mut() {
+            asset.apply_rates_of_change();
+        }
+    }
+
+    pub fn valid_sizes(&self) -> bool {
+        let mut last_value_length: Option<usize> = None;
+
+        for asset in &self.assets {
+            match last_value_length {
+                None => {
+                    last_value_length = Some(asset.values.len());
+                }
+                Some(l) => {
+                    if l != asset.values.len() {
+                        return false;
+                    }
+                    last_value_length = Some(asset.values.len());
+                }
+            }
+        }
+
+        true
+    }
+
+    pub fn valid_weights(&self) -> bool {
+        let mut weight = 1 as f64;
+
+        for asset in &self.assets {
+            weight -= asset.portfolio_weight;
+        }
+
+        f64::abs(weight) < 0.01
+    }
+
+    pub fn is_valid(&self) -> bool {
+        self.valid_sizes() && self.valid_weights()
+    }
+
+    pub fn get_matrix(&self) -> Option<Array2<f64>> {
+        if self.assets.is_empty() || !self.valid_sizes() {
+            return None;
+        }
+
+        let column_count = self.assets.len();
+        let row_count = self.assets[0].values.len();
+
+        let matrix = Array2::from_shape_vec((column_count, row_count),
+            self.assets
+                .iter()
+                .map(|a| a.values.clone())
+                .flatten()
+                .collect::<Vec<f64>>()
+        ).unwrap();
+
+        Some(matrix.into_owned())
+    }
+
+    pub fn get_mean_and_std(&mut self) -> Option<(f64, f64)> {
+        if !self.valid_sizes() {
+            return None;
+        }
+
+        self.apply_rates_of_change();
+        let m = self.get_matrix();
+        if m.is_none() {
+            return None;
+        }
+        let m = m.unwrap();
+
+        let cov = m.cov(1.);
+        if cov.is_err() {
+            return None;
+        }
+        let cov = cov.unwrap();
+        let mean_return = m.mean_axis(Axis(1));
+        if mean_return.is_none() {
+            return None;
+        }
+        let mean_return = mean_return.unwrap();
+        let asset_weights = Array::from_vec(
+            self.get_asset_weight().collect::<Vec<f64>>()
+        ).to_owned();
+
+        let porfolio_mean_return = mean_return.dot(&asset_weights);
+        let portfolio_stddev = f64::sqrt(asset_weights.t().dot(&cov).dot(&asset_weights));
+
+        Some((porfolio_mean_return, portfolio_stddev))
+    }
+
+    pub fn value_at_risk(&mut self, confidence: f64) -> Option<f64> {
+        portfolio_value_at_risk(self, confidence)
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn var_test() {
+        let assets = vec![
+            PortfolioAsset::new(0.3, "awdad".to_string(), vec![2f64, 3f64, 4f64]),
+            PortfolioAsset::new(0.7, "awdad".to_string(), vec![1f64, 6f64, 8f64]),
+        ];
+
+        let m = Portfolio::from(assets).get_matrix().unwrap();
+        println!("matrix 0; {:?}", m);
+
+        let col = m.row(0);
+        println!("column 0; {:?}", col);
+        let cov = m.cov(1.);
+
+        println!("cov 0; {:?}", cov);
+
+
+        col.len();
+    }
+}
\ No newline at end of file
diff --git a/finlib/src/risk/var/mod.rs b/finlib/src/risk/var/mod.rs
index 6c298bf..36a75d8 100644
--- a/finlib/src/risk/var/mod.rs
+++ b/finlib/src/risk/var/mod.rs
@@ -1,2 +1,2 @@
 pub mod historical;
-pub mod varcovar;
\ No newline at end of file
+pub mod varcovar;
diff --git a/finlib/src/risk/var/varcovar.rs b/finlib/src/risk/var/varcovar.rs
index 870811c..06b0f08 100644
--- a/finlib/src/risk/var/varcovar.rs
+++ b/finlib/src/risk/var/varcovar.rs
@@ -1,10 +1,11 @@
-use crate::util::roc::rates_of_change;
 use crate::stats;
+use crate::util::roc::rates_of_change;
+use ndarray_stats::CorrelationExt;
 
+use crate::risk::portfolio::Portfolio;
 #[cfg(feature = "parallel")]
 use rayon::prelude::*;
 use statrs::distribution::{ContinuousCDF, Normal};
-
 // https://medium.com/@serdarilarslan/value-at-risk-var-and-its-implementation-in-python-5c9150f73b0e
 
 pub fn value_at_risk(values: &[f64], confidence: f64) -> f64 {
@@ -16,4 +17,44 @@ pub fn value_at_risk(values: &[f64], confidence: f64) -> f64 {
     let n = Normal::new(0.0, 1.0).unwrap();
 
     mean + std_dev * n.inverse_cdf(confidence)
+}
+
+pub fn portfolio_value_at_risk(portfolio: &mut Portfolio, confidence: f64) -> Option<f64> {
+    match portfolio.get_mean_and_std() {
+        None => None,
+        Some((mean, std_dev)) => {
+            let n = Normal::new(0.0, 1.0).unwrap();
+            Some(mean + std_dev * n.inverse_cdf(confidence))
+        }
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::risk::portfolio::PortfolioAsset;
+
+    #[test]
+    fn var_test() {
+        let assets = vec![
+            PortfolioAsset::new(0.3, "awdad".to_string(), vec![2f64, 3f64, 4f64]),
+            PortfolioAsset::new(0.7, "awdad".to_string(), vec![1f64, 6f64, 8f64]),
+        ];
+
+        let mut portfolio = Portfolio::from(assets);
+
+        portfolio_value_at_risk(&mut portfolio, 0.1);
+
+    }
+
+    #[test]
+    fn var_test_one_asset() {
+        let assets = vec![
+            PortfolioAsset::new(0.3, "awdad".to_string(), vec![2f64, 3f64, 4f64])
+        ];
+
+        let mut portfolio = Portfolio::from(assets);
+
+        portfolio_value_at_risk(&mut portfolio, 0.1);
+    }
 }
\ No newline at end of file
diff --git a/notebooks/varcovar_var_portfolio.ipynb b/notebooks/varcovar_var_portfolio.ipynb
new file mode 100644
index 0000000..425bf13
--- /dev/null
+++ b/notebooks/varcovar_var_portfolio.ipynb
@@ -0,0 +1,417 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "id": "initial_id",
+   "metadata": {
+    "collapsed": true,
+    "ExecuteTime": {
+     "end_time": "2025-02-15T20:07:39.398175Z",
+     "start_time": "2025-02-15T20:07:34.126281Z"
+    }
+   },
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "from openbb import obb\n",
+    "import pyfinlib\n"
+   ],
+   "outputs": [],
+   "execution_count": 1
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-02-15T20:07:39.862808Z",
+     "start_time": "2025-02-15T20:07:39.401473Z"
+    }
+   },
+   "cell_type": "code",
+   "source": "aapl = obb.equity.price.historical(symbol='AAPL', provider='yfinance')",
+   "id": "e5573366e39b2962",
+   "outputs": [],
+   "execution_count": 2
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-02-15T20:07:39.992579Z",
+     "start_time": "2025-02-15T20:07:39.984673Z"
+    }
+   },
+   "cell_type": "code",
+   "source": "aapl.results",
+   "id": "ba361e8697a2e425",
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[YFinanceEquityHistoricalData(date=2024-02-15, open=183.5500030517578, high=184.49000549316406, low=181.35000610351562, close=183.86000061035156, volume=65434500, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-02-16, open=183.4199981689453, high=184.85000610351562, low=181.6699981689453, close=182.30999755859375, volume=49701400, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-02-20, open=181.7899932861328, high=182.42999267578125, low=180.0, close=181.55999755859375, volume=53665600, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-02-21, open=181.94000244140625, high=182.88999938964844, low=180.66000366210938, close=182.32000732421875, volume=41529700, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-02-22, open=183.47999572753906, high=184.9600067138672, low=182.4600067138672, close=184.3699951171875, volume=52292200, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-02-23, open=185.00999450683594, high=185.0399932861328, low=182.22999572753906, close=182.52000427246094, volume=45119700, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-02-26, open=182.24000549316406, high=182.75999450683594, low=180.64999389648438, close=181.16000366210938, volume=40867400, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-02-27, open=181.10000610351562, high=183.9199981689453, low=179.55999755859375, close=182.6300048828125, volume=54318900, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-02-28, open=182.50999450683594, high=183.1199951171875, low=180.1300048828125, close=181.4199981689453, volume=48953900, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-02-29, open=181.27000427246094, high=182.57000732421875, low=179.52999877929688, close=180.75, volume=136682600, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-03-01, open=179.5500030517578, high=180.52999877929688, low=177.3800048828125, close=179.66000366210938, volume=73488000, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-03-04, open=176.14999389648438, high=176.89999389648438, low=173.7899932861328, close=175.10000610351562, volume=81510100, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-03-05, open=170.75999450683594, high=172.0399932861328, low=169.6199951171875, close=170.1199951171875, volume=95132400, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-03-06, open=171.05999755859375, high=171.24000549316406, low=168.67999267578125, close=169.1199951171875, volume=68587700, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-03-07, open=169.14999389648438, high=170.72999572753906, low=168.49000549316406, close=169.0, volume=71765100, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-03-08, open=169.0, high=173.6999969482422, low=168.94000244140625, close=170.72999572753906, volume=76114600, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-03-11, open=172.94000244140625, high=174.3800048828125, low=172.0500030517578, close=172.75, volume=60139500, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-03-12, open=173.14999389648438, high=174.02999877929688, low=171.00999450683594, close=173.22999572753906, volume=59825400, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-03-13, open=172.77000427246094, high=173.19000244140625, low=170.75999450683594, close=171.1300048828125, volume=52488700, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-03-14, open=172.91000366210938, high=174.30999755859375, low=172.0500030517578, close=173.0, volume=72913500, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-03-15, open=171.1699981689453, high=172.6199951171875, low=170.2899932861328, close=172.6199951171875, volume=121664700, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-03-18, open=175.57000732421875, high=177.7100067138672, low=173.52000427246094, close=173.72000122070312, volume=75604200, vwap=None, split_ratio=None, dividend=0.0),\n",
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+       " YFinanceEquityHistoricalData(date=2024-11-29, open=234.80999755859375, high=237.80999755859375, low=233.97000122070312, close=237.3300018310547, volume=28481400, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-12-02, open=237.27000427246094, high=240.7899932861328, low=237.16000366210938, close=239.58999633789062, volume=48137100, vwap=None, split_ratio=None, dividend=0.0),\n",
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+       " YFinanceEquityHistoricalData(date=2024-12-04, open=242.8699951171875, high=244.11000061035156, low=241.25, close=243.00999450683594, volume=44383900, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-12-05, open=243.99000549316406, high=244.5399932861328, low=242.1300048828125, close=243.0399932861328, volume=40033900, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-12-06, open=242.91000366210938, high=244.6300048828125, low=242.0800018310547, close=242.83999633789062, volume=36870600, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-12-09, open=241.8300018310547, high=247.24000549316406, low=241.75, close=246.75, volume=44649200, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-12-10, open=246.88999938964844, high=248.2100067138672, low=245.33999633789062, close=247.77000427246094, volume=36914800, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-12-11, open=247.9600067138672, high=250.8000030517578, low=246.25999450683594, close=246.49000549316406, volume=45205800, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-12-12, open=246.88999938964844, high=248.74000549316406, low=245.67999267578125, close=247.9600067138672, volume=32777500, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-12-13, open=247.82000732421875, high=249.2899932861328, low=246.24000549316406, close=248.1300048828125, volume=33155300, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-12-16, open=247.99000549316406, high=251.3800048828125, low=247.64999389648438, close=251.0399932861328, volume=51694800, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-12-17, open=250.0800018310547, high=253.8300018310547, low=249.77999877929688, close=253.47999572753906, volume=51356400, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-12-18, open=252.16000366210938, high=254.27999877929688, low=247.74000549316406, close=248.0500030517578, volume=56774100, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-12-19, open=247.5, high=252.0, low=247.08999633789062, close=249.7899932861328, volume=60882300, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-12-20, open=248.0399932861328, high=255.0, low=245.69000244140625, close=254.49000549316406, volume=147495300, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-12-23, open=254.77000427246094, high=255.64999389648438, low=253.4499969482422, close=255.27000427246094, volume=40858800, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-12-24, open=255.49000549316406, high=258.2099914550781, low=255.2899932861328, close=258.20001220703125, volume=23234700, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-12-26, open=258.19000244140625, high=260.1000061035156, low=257.6300048828125, close=259.0199890136719, volume=27237100, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-12-27, open=257.8299865722656, high=258.70001220703125, low=253.05999755859375, close=255.58999633789062, volume=42355300, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-12-30, open=252.22999572753906, high=253.5, low=250.75, close=252.1999969482422, volume=35557500, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2024-12-31, open=252.44000244140625, high=253.27999877929688, low=249.42999267578125, close=250.4199981689453, volume=39480700, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-01-02, open=248.92999267578125, high=249.10000610351562, low=241.82000732421875, close=243.85000610351562, volume=55740700, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-01-03, open=243.36000061035156, high=244.17999267578125, low=241.88999938964844, close=243.36000061035156, volume=40244100, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-01-06, open=244.30999755859375, high=247.3300018310547, low=243.1999969482422, close=245.0, volume=45045600, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-01-07, open=242.97999572753906, high=245.5500030517578, low=241.35000610351562, close=242.2100067138672, volume=40856000, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-01-08, open=241.9199981689453, high=243.7100067138672, low=240.0500030517578, close=242.6999969482422, volume=37628900, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-01-10, open=240.00999450683594, high=240.16000366210938, low=233.0, close=236.85000610351562, volume=61710900, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-01-13, open=233.52999877929688, high=234.6699981689453, low=229.72000122070312, close=234.39999389648438, volume=49630700, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-01-14, open=234.75, high=236.1199951171875, low=232.47000122070312, close=233.27999877929688, volume=39435300, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-01-15, open=234.63999938964844, high=238.9600067138672, low=234.42999267578125, close=237.8699951171875, volume=39832000, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-01-16, open=237.35000610351562, high=238.00999450683594, low=228.02999877929688, close=228.25999450683594, volume=71759100, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-01-17, open=232.1199951171875, high=232.2899932861328, low=228.47999572753906, close=229.97999572753906, volume=68488300, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-01-21, open=224.0, high=224.4199981689453, low=219.3800048828125, close=222.63999938964844, volume=98070400, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-01-22, open=219.7899932861328, high=224.1199951171875, low=219.7899932861328, close=223.8300018310547, volume=64126500, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-01-23, open=224.74000549316406, high=227.02999877929688, low=222.3000030517578, close=223.66000366210938, volume=60234800, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-01-24, open=224.77999877929688, high=225.6300048828125, low=221.41000366210938, close=222.77999877929688, volume=54697900, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-01-27, open=224.02000427246094, high=232.14999389648438, low=223.97999572753906, close=229.86000061035156, volume=94863400, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-01-28, open=230.85000610351562, high=240.19000244140625, low=230.80999755859375, close=238.25999450683594, volume=75707600, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-01-29, open=234.1199951171875, high=239.86000061035156, low=234.00999450683594, close=239.36000061035156, volume=45486100, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-01-30, open=238.6699981689453, high=240.7899932861328, low=237.2100067138672, close=237.58999633789062, volume=55658300, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-01-31, open=247.19000244140625, high=247.19000244140625, low=233.44000244140625, close=236.0, volume=101075100, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-02-03, open=229.99000549316406, high=231.8300018310547, low=225.6999969482422, close=228.00999450683594, volume=73063300, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-02-04, open=227.25, high=233.1300048828125, low=226.64999389648438, close=232.8000030517578, volume=45067300, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-02-05, open=228.52999877929688, high=232.6699981689453, low=228.27000427246094, close=232.47000122070312, volume=39620300, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-02-06, open=231.2899932861328, high=233.8000030517578, low=230.42999267578125, close=233.22000122070312, volume=29925300, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-02-07, open=232.60000610351562, high=234.0, low=227.25999450683594, close=227.6300048828125, volume=39707200, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-02-10, open=229.57000732421875, high=230.58999633789062, low=227.1999969482422, close=227.64999389648438, volume=33115600, vwap=None, split_ratio=None, dividend=0.25),\n",
+       " YFinanceEquityHistoricalData(date=2025-02-11, open=228.1999969482422, high=235.22999572753906, low=228.1300048828125, close=232.6199951171875, volume=53718400, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-02-12, open=231.1999969482422, high=236.9600067138672, low=230.67999267578125, close=236.8699951171875, volume=45243300, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-02-13, open=236.91000366210938, high=242.33999633789062, low=235.57000732421875, close=241.52999877929688, volume=53614100, vwap=None, split_ratio=None, dividend=0.0),\n",
+       " YFinanceEquityHistoricalData(date=2025-02-14, open=241.25, high=245.5500030517578, low=240.99000549316406, close=244.60000610351562, volume=40838100, vwap=None, split_ratio=None, dividend=0.0)]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "execution_count": 3
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-02-15T20:07:40.016044Z",
+     "start_time": "2025-02-15T20:07:40.014035Z"
+    }
+   },
+   "cell_type": "code",
+   "source": "data = [i.open for i in aapl.results]",
+   "id": "481bc5b5742518f7",
+   "outputs": [],
+   "execution_count": 4
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-02-15T20:07:40.041952Z",
+     "start_time": "2025-02-15T20:07:40.038215Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "returns = pyfinlib.util.rates_of_change(data)\n",
+    "portfolio = pyfinlib.Portfolio([pyfinlib.PortfolioAsset(1, \"AAPL\", data)])\n",
+    "\n",
+    "VaR_historical = portfolio.value_at_risk(0.05)\n",
+    "VaR_historical_10 = portfolio.value_at_risk(0.1)\n",
+    "VaR_historical, VaR_historical_10"
+   ],
+   "id": "28a68dea99911874",
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(-0.026022532720986438, -0.020002956044025813)"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "execution_count": 5
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-02-15T20:07:40.167970Z",
+     "start_time": "2025-02-15T20:07:40.061711Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "# Plot the historical returns and VaR threshold\n",
+    "plt.figure(figsize=(10, 6))\n",
+    "plt.hist(returns, bins=50, alpha=0.75, color='blue', edgecolor='black')\n",
+    "plt.axvline(VaR_historical, color='red', linestyle='--', label=f'VaR (95%): {VaR_historical:.2%}')\n",
+    "plt.axvline(VaR_historical_10, color='orange', linestyle='--', label=f'VaR (90%): {VaR_historical_10:.2%}')\n",
+    "plt.title('Historical Returns of AAPL')\n",
+    "plt.xlabel('Returns')\n",
+    "plt.ylabel('Frequency')\n",
+    "plt.legend()\n",
+    "plt.show()"
+   ],
+   "id": "5ab5e055a23f28ed",
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 1000x600 with 1 Axes>"
+      ],
+      "image/png": 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"
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "execution_count": 6
+  },
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "outputs": [],
+   "execution_count": null,
+   "source": "",
+   "id": "ddeb6ada3ab526b5"
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/pyfinlib/src/lib.rs b/pyfinlib/src/lib.rs
index 17ccebb..9f9f586 100644
--- a/pyfinlib/src/lib.rs
+++ b/pyfinlib/src/lib.rs
@@ -4,6 +4,11 @@ use pyo3::prelude::*;
 mod pyfinlib {
     use super::*;
 
+    #[pymodule_export]
+    use finlib::risk::portfolio::Portfolio;
+    #[pymodule_export]
+    use finlib::risk::portfolio::PortfolioAsset;
+
     #[pymodule_init]
     fn init(m: &Bound<'_, PyModule>) -> PyResult<()> {
         pyo3_log::init();