diff --git a/crates/ferro_ta_core/src/alerts.rs b/crates/ferro_ta_core/src/alerts.rs
index ac933f4..62d3475 100644
--- a/crates/ferro_ta_core/src/alerts.rs
+++ b/crates/ferro_ta_core/src/alerts.rs
@@ -22,14 +22,10 @@ pub fn check_threshold(series: &[f64], level: f64, direction: i32) -> Vec<i8> {
         if prev.is_nan() || curr.is_nan() {
             continue;
         }
-        if direction == 1 {
-            if prev <= level && curr > level {
-                out[i] = 1;
-            }
-        } else if direction == -1 {
-            if prev >= level && curr < level {
-                out[i] = 1;
-            }
+        if (direction == 1 && prev <= level && curr > level)
+            || (direction == -1 && prev >= level && curr < level)
+        {
+            out[i] = 1;
         }
     }
     out
diff --git a/crates/ferro_ta_core/src/backtest.rs b/crates/ferro_ta_core/src/backtest.rs
index 5d99b55..7b9c33f 100644
--- a/crates/ferro_ta_core/src/backtest.rs
+++ b/crates/ferro_ta_core/src/backtest.rs
@@ -1565,6 +1565,7 @@ pub struct MultiAssetBacktestResult {
 /// `weights_2d`: row-major (n_assets, n_bars)
 ///
 /// Callers must transpose from (n_bars, n_assets) if needed.
+#[allow(clippy::too_many_arguments)]
 pub fn backtest_multi_asset_core(
     close_2d: &[Vec<f64>],
     weights_2d: &[Vec<f64>],
@@ -1585,6 +1586,7 @@ pub fn backtest_multi_asset_core(
 
     // Apply portfolio constraints per bar
     let mut constrained: Vec<Vec<f64>> = weights_2d.to_vec();
+    #[allow(clippy::needless_range_loop)]
     if max_asset_weight != 1.0 || max_gross_exposure > 0.0 || max_net_exposure > 0.0 {
         for i in 0..n_bars {
             // 1. Clamp per-asset weight
@@ -1635,6 +1637,7 @@ pub fn backtest_multi_asset_core(
 
     // Portfolio return = sum of per-asset strategy returns
     let mut portfolio_returns = vec![0.0_f64; n_bars];
+    #[allow(clippy::needless_range_loop)]
     for i in 0..n_bars {
         let mut s = 0.0_f64;
         for j in 0..n_assets {
diff --git a/crates/ferro_ta_core/src/batch.rs b/crates/ferro_ta_core/src/batch.rs
index 353647b..24f55c5 100644
--- a/crates/ferro_ta_core/src/batch.rs
+++ b/crates/ferro_ta_core/src/batch.rs
@@ -272,6 +272,7 @@ pub fn batch_atr(
 
 /// Apply Stochastic to each set of (high, low, close) columns.
 /// Returns `(slowk_columns, slowd_columns)`.
+#[allow(clippy::type_complexity)]
 pub fn batch_stoch(
     high: &[Vec<f64>],
     low: &[Vec<f64>],
diff --git a/crates/ferro_ta_core/src/extended.rs b/crates/ferro_ta_core/src/extended.rs
index 44a47c4..5706800 100644
--- a/crates/ferro_ta_core/src/extended.rs
+++ b/crates/ferro_ta_core/src/extended.rs
@@ -231,13 +231,7 @@ pub fn supertrend(
         // Direction and output only from index timeperiod (warmup = 0, NaN)
         if i >= timeperiod {
             let prev_dir = direction[i - 1];
-            direction[i] = if prev_dir == 0 {
-                if close[i] > upper_band[i] {
-                    1
-                } else {
-                    -1
-                }
-            } else if prev_dir == -1 {
+            direction[i] = if prev_dir == 0 || prev_dir == -1 {
                 if close[i] > upper_band[i] {
                     1
                 } else {
@@ -464,6 +458,7 @@ pub fn chandelier_exit(
 ///
 /// # Returns
 /// `(tenkan, kijun, senkou_a, senkou_b, chikou)` arrays.
+#[allow(clippy::type_complexity)]
 pub fn ichimoku(
     high: &[f64],
     low: &[f64],
@@ -534,6 +529,7 @@ pub fn ichimoku(
 ///
 /// # Returns
 /// `(pivot, r1, s1, r2, s2)` arrays. Index 0 is always `NaN` (no previous bar).
+#[allow(clippy::type_complexity)]
 pub fn pivot_points(
     high: &[f64],
     low: &[f64],
diff --git a/crates/ferro_ta_core/src/portfolio.rs b/crates/ferro_ta_core/src/portfolio.rs
index 610511e..83b7671 100644
--- a/crates/ferro_ta_core/src/portfolio.rs
+++ b/crates/ferro_ta_core/src/portfolio.rs
@@ -165,6 +165,7 @@ pub fn correlation_matrix(data: &[Vec<f64>]) -> Vec<Vec<f64>> {
     assert!(n_assets > 0, "data must contain at least one asset column");
     let n_bars = data[0].len();
     assert!(n_bars >= 2, "data must have at least 2 rows (bars)");
+    #[allow(clippy::needless_range_loop)]
     for j in 1..n_assets {
         assert!(
             data[j].len() == n_bars,
@@ -190,6 +191,7 @@ pub fn correlation_matrix(data: &[Vec<f64>]) -> Vec<Vec<f64>> {
 
     // Build correlation matrix (exploit symmetry: compute each pair once)
     let mut result = vec![vec![0.0_f64; n_assets]; n_assets];
+    #[allow(clippy::needless_range_loop)]
     for j1 in 0..n_assets {
         result[j1][j1] = 1.0;
         for j2 in (j1 + 1)..n_assets {
@@ -332,6 +334,7 @@ pub fn compose_weighted(data: &[Vec<f64>], weights: &[f64]) -> Vec<f64> {
         return vec![];
     }
     let n_bars = data[0].len();
+    #[allow(clippy::needless_range_loop)]
     for j in 1..n_sigs {
         assert!(
             data[j].len() == n_bars,
diff --git a/src/backtest/mod.rs b/src/backtest/mod.rs
index 09013ce..5d4997a 100644
--- a/src/backtest/mod.rs
+++ b/src/backtest/mod.rs
@@ -147,8 +147,7 @@ pub fn sma_crossover_signals<'py>(
     validation::validate_timeperiod(fast, "fast", 1)?;
     validation::validate_timeperiod(slow, "slow", 1)?;
     let prices = close.as_slice()?;
-    let out =
-        core_bt::sma_crossover_signals(prices, fast, slow).map_err(|e| PyValueError::new_err(e))?;
+    let out = core_bt::sma_crossover_signals(prices, fast, slow).map_err(PyValueError::new_err)?;
     Ok(out.into_pyarray(py))
 }
 
@@ -166,7 +165,7 @@ pub fn macd_crossover_signals<'py>(
     validation::validate_timeperiod(signalperiod, "signalperiod", 1)?;
     let prices = close.as_slice()?;
     let out = core_bt::macd_crossover_signals(prices, fastperiod, slowperiod, signalperiod)
-        .map_err(|e| PyValueError::new_err(e))?;
+        .map_err(PyValueError::new_err)?;
     Ok(out.into_pyarray(py))
 }
 
@@ -210,7 +209,7 @@ pub fn backtest_core<'py>(
         initial_capital,
         commission_per_trade,
     )
-    .map_err(|e| PyValueError::new_err(e))?;
+    .map_err(PyValueError::new_err)?;
 
     Ok((
         result.positions.into_pyarray(py),
@@ -314,7 +313,7 @@ pub fn backtest_ohlcv_core<'py>(
     let lp_opt: Option<&[f64]> = limit_prices.as_ref().and_then(|lp| lp.as_slice().ok());
 
     let result = core_bt::backtest_ohlcv_core(o, h, l, c, s, &config, lp_opt)
-        .map_err(|e| PyValueError::new_err(e))?;
+        .map_err(PyValueError::new_err)?;
 
     Ok((
         result.positions.into_pyarray(py),
@@ -344,7 +343,7 @@ pub fn compute_performance_metrics<'py>(
     let br = benchmark_returns.as_ref().and_then(|b| b.as_slice().ok());
 
     let metrics = core_bt::compute_performance_metrics(r, eq, periods_per_year, risk_free_rate, br)
-        .map_err(|e| PyValueError::new_err(e))?;
+        .map_err(PyValueError::new_err)?;
 
     let dict = PyDict::new(py);
     dict.set_item("total_return", metrics.total_return)?;
@@ -441,8 +440,7 @@ pub fn extract_trades_ohlcv<'py>(
         (l.len(), "low"),
     ])?;
 
-    let trades =
-        core_bt::extract_trades_ohlcv(pos, fp, h, l).map_err(|e| PyValueError::new_err(e))?;
+    let trades = core_bt::extract_trades_ohlcv(pos, fp, h, l).map_err(PyValueError::new_err)?;
 
     let mut entry_bars: Vec<i64> = Vec::with_capacity(trades.len());
     let mut exit_bars: Vec<i64> = Vec::with_capacity(trades.len());
@@ -535,6 +533,7 @@ pub fn backtest_multi_asset_core<'py>(
     // Apply portfolio constraints first via the core function's logic.
 
     // Apply constraints
+    #[allow(clippy::needless_range_loop)]
     if max_asset_weight != 1.0 || max_gross_exposure > 0.0 || max_net_exposure > 0.0 {
         for i in 0..n_bars {
             if max_asset_weight < f64::INFINITY && max_asset_weight > 0.0 {
@@ -703,7 +702,7 @@ pub fn walk_forward_indices<'py>(
     step_bars: usize,
 ) -> PyResult<Bound<'py, PyArray2<i64>>> {
     let folds = core_bt::walk_forward_indices(n_bars, train_bars, test_bars, anchored, step_bars)
-        .map_err(|e| PyValueError::new_err(e))?;
+        .map_err(PyValueError::new_err)?;
 
     let n_folds = folds.len();
     let mut arr = Array2::<i64>::zeros((n_folds, 4));
@@ -722,12 +721,12 @@ pub fn walk_forward_indices<'py>(
 
 #[pyfunction]
 pub fn kelly_fraction(win_rate: f64, avg_win: f64, avg_loss: f64) -> PyResult<f64> {
-    core_bt::kelly_fraction(win_rate, avg_win, avg_loss).map_err(|e| PyValueError::new_err(e))
+    core_bt::kelly_fraction(win_rate, avg_win, avg_loss).map_err(PyValueError::new_err)
 }
 
 #[pyfunction]
 pub fn half_kelly_fraction(win_rate: f64, avg_win: f64, avg_loss: f64) -> PyResult<f64> {
-    core_bt::half_kelly_fraction(win_rate, avg_win, avg_loss).map_err(|e| PyValueError::new_err(e))
+    core_bt::half_kelly_fraction(win_rate, avg_win, avg_loss).map_err(PyValueError::new_err)
 }
 
 // ---------------------------------------------------------------------------
diff --git a/src/streaming/mod.rs b/src/streaming/mod.rs
index 3e3959e..a0b3ab5 100644
--- a/src/streaming/mod.rs
+++ b/src/streaming/mod.rs
@@ -298,13 +298,19 @@ pub struct StreamingVWAP {
     inner: core::StreamingVWAP,
 }
 
+impl Default for StreamingVWAP {
+    fn default() -> Self {
+        Self {
+            inner: core::StreamingVWAP::new(),
+        }
+    }
+}
+
 #[pymethods]
 impl StreamingVWAP {
     #[new]
     pub fn new() -> Self {
-        Self {
-            inner: core::StreamingVWAP::new(),
-        }
+        Self::default()
     }
 
     /// Add a new bar (high, low, close, volume) and return cumulative VWAP.