feat: update version to 0.2.1 and add rolling min/max indicators (#6)

* feat: add session tracking and multi-leg spread backtesting

Add SessionTracker for trading session management:                             - Market hours detection (pre-open, trading, squareoff, post-close)
 - Session boundary tracking with configurable timezone    - Squareoff time support for intraday strategies                                   - Session high/low/open price tracking

Add SpreadBacktest for multi-leg options strategies:                                  - Support for straddles, strangles, vertical spreads, iron condors                                      - Coordinated entry/exit across all legs                                             - Net premium P&L calculation with max loss/target profit exits                                            - Helper functions for common spread configurations

Extend StreamingMetrics for backtest integration:                                - Add equity and drawdown tracking (update_equity, current_drawdown_pct)           - Add trade recording (record_trade, record_fees)                              - Add finalize() method to produce BacktestMetrics                        - Add with_initial_capital() constructor

Bump version to 0.2.0.

* chore: bump up version to 0.2.0

* feat: update version to 0.2.1 and add rolling min/max indicators

* fix: formatting

Cargo.lock

@@ -502,7 +502,7 @@ dependencies = [
 
 [[package]]
 name = "raptorbt"
-version = "0.1.0"
+version = "0.2.1"
 dependencies = [
  "approx",
  "criterion",

Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "raptorbt"
-version = "0.1.0"
+version = "0.2.1"
 edition = "2021"
 description = "High-performance Rust backtesting engine with Python bindings. Drop-in VectorBT replacement with up insanely faster performance at fractional memory footprint."
 authors = ["Alphabench <contact@alphabench.in>"]

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "maturin"
 
 [project]
 name = "raptorbt"
-version = "0.1.0"
+version = "0.2.1"
 description = "High-performance Rust backtesting engine with Python bindings. Drop-in VectorBT replacement with up insanely faster performance at fractional memory footprint."
 readme = "README.md"
 requires-python = ">=3.10"

python/raptorbt/__init__.py

@@ -37,7 +37,7 @@ from raptorbt._raptorbt import (
     supertrend,
 )
 
-__version__ = "0.1.0"
+__version__ = "0.2.1"
 
 __all__ = [
     # Config classes

src/core/mod.rs

@@ -1,9 +1,11 @@
 //! Core types and utilities for RaptorBT.
 
 pub mod error;
+pub mod session;
 pub mod timeseries;
 pub mod types;
 
 pub use error::{RaptorError, Result};
+pub use session::{SessionConfig, SessionTracker};
 pub use timeseries::TimeSeries;
 pub use types::*;

src/core/session.rs

@@ -0,0 +1,397 @@
+//! Session tracking for intraday strategies.
+//!
+//! Handles:
+//! - Session boundary detection (market open/close)
+//! - Squareoff time enforcement
+//! - Session high/low tracking for ORB and session-based indicators
+//! - Timezone handling for IST (India Standard Time)
+
+use serde::{Deserialize, Serialize};
+
+/// Session configuration for trading hours.
+#[derive(Debug, Clone, Serialize, Deserialize)]
+pub struct SessionConfig {
+    /// Market open hour (24-hour format).
+    pub market_open_hour: u32,
+    /// Market open minute.
+    pub market_open_minute: u32,
+    /// Market close hour (24-hour format).
+    pub market_close_hour: u32,
+    /// Market close minute.
+    pub market_close_minute: u32,
+    /// Squareoff minutes before market close.
+    pub squareoff_minutes_before_close: u32,
+    /// Timezone offset in hours from UTC (5 for IST = UTC+5:30).
+    pub timezone_offset_hours: i32,
+    /// Timezone offset minutes (30 for IST).
+    pub timezone_offset_minutes: i32,
+}
+
+impl Default for SessionConfig {
+    fn default() -> Self {
+        // Default: NSE equity session (9:15 - 15:30 IST, squareoff at 15:25)
+        Self {
+            market_open_hour: 9,
+            market_open_minute: 15,
+            market_close_hour: 15,
+            market_close_minute: 30,
+            squareoff_minutes_before_close: 5,
+            timezone_offset_hours: 5,
+            timezone_offset_minutes: 30,
+        }
+    }
+}
+
+impl SessionConfig {
+    /// Create NSE equity session config (9:15 - 15:30).
+    pub fn nse_equity() -> Self {
+        Self::default()
+    }
+
+    /// Create MCX commodity session config (9:00 - 23:30).
+    pub fn mcx_commodity() -> Self {
+        Self {
+            market_open_hour: 9,
+            market_open_minute: 0,
+            market_close_hour: 23,
+            market_close_minute: 30,
+            squareoff_minutes_before_close: 5,
+            timezone_offset_hours: 5,
+            timezone_offset_minutes: 30,
+        }
+    }
+
+    /// Create CDS currency session config (9:00 - 17:00).
+    pub fn cds_currency() -> Self {
+        Self {
+            market_open_hour: 9,
+            market_open_minute: 0,
+            market_close_hour: 17,
+            market_close_minute: 0,
+            squareoff_minutes_before_close: 5,
+            timezone_offset_hours: 5,
+            timezone_offset_minutes: 30,
+        }
+    }
+
+    /// Get market open time in minutes from midnight.
+    pub fn market_open_minutes(&self) -> u32 {
+        self.market_open_hour * 60 + self.market_open_minute
+    }
+
+    /// Get market close time in minutes from midnight.
+    pub fn market_close_minutes(&self) -> u32 {
+        self.market_close_hour * 60 + self.market_close_minute
+    }
+
+    /// Get squareoff time in minutes from midnight.
+    pub fn squareoff_minutes(&self) -> u32 {
+        self.market_close_minutes().saturating_sub(self.squareoff_minutes_before_close)
+    }
+
+    /// Get timezone offset in seconds.
+    pub fn timezone_offset_seconds(&self) -> i64 {
+        (self.timezone_offset_hours as i64 * 3600) + (self.timezone_offset_minutes as i64 * 60)
+    }
+}
+
+/// Session tracker for managing intraday session state.
+#[derive(Debug, Clone)]
+pub struct SessionTracker {
+    config: SessionConfig,
+    /// Current session date (days since epoch in local timezone).
+    current_session_date: i64,
+    /// Session high price.
+    session_high: f64,
+    /// Session low price.
+    session_low: f64,
+    /// Session open price.
+    session_open: f64,
+    /// Bar index at session start.
+    session_start_idx: usize,
+    /// Whether we're currently in a trading session.
+    in_session: bool,
+    /// Whether squareoff has been triggered today.
+    squareoff_triggered: bool,
+}
+
+impl SessionTracker {
+    /// Create a new session tracker.
+    pub fn new(config: SessionConfig) -> Self {
+        Self {
+            config,
+            current_session_date: -1,
+            session_high: f64::NEG_INFINITY,
+            session_low: f64::INFINITY,
+            session_open: 0.0,
+            session_start_idx: 0,
+            in_session: false,
+            squareoff_triggered: false,
+        }
+    }
+
+    /// Convert nanosecond timestamp to local time components.
+    fn timestamp_to_local(&self, timestamp_ns: i64) -> (i64, u32, u32, u32) {
+        // Convert to seconds
+        let timestamp_s = timestamp_ns / 1_000_000_000;
+
+        // Apply timezone offset
+        let local_s = timestamp_s + self.config.timezone_offset_seconds();
+
+        // Calculate date (days since epoch)
+        let days = local_s / 86400;
+
+        // Calculate time within day
+        let time_in_day = (local_s % 86400) as u32;
+        let hours = time_in_day / 3600;
+        let minutes = (time_in_day % 3600) / 60;
+        let seconds = time_in_day % 60;
+
+        (days, hours, minutes, seconds)
+    }
+
+    /// Get minutes from midnight for a timestamp.
+    fn get_minutes_from_midnight(&self, timestamp_ns: i64) -> u32 {
+        let (_, hours, minutes, _) = self.timestamp_to_local(timestamp_ns);
+        hours * 60 + minutes
+    }
+
+    /// Check if timestamp is within trading hours.
+    pub fn is_within_trading_hours(&self, timestamp_ns: i64) -> bool {
+        let minutes = self.get_minutes_from_midnight(timestamp_ns);
+        minutes >= self.config.market_open_minutes() && minutes < self.config.market_close_minutes()
+    }
+
+    /// Check if it's squareoff time.
+    pub fn is_squareoff_time(&self, timestamp_ns: i64) -> bool {
+        let minutes = self.get_minutes_from_midnight(timestamp_ns);
+        minutes >= self.config.squareoff_minutes()
+    }
+
+    /// Check if this bar starts a new session.
+    pub fn is_session_start(&self, prev_ts_ns: i64, curr_ts_ns: i64) -> bool {
+        let (prev_date, prev_h, prev_m, _) = self.timestamp_to_local(prev_ts_ns);
+        let (curr_date, curr_h, curr_m, _) = self.timestamp_to_local(curr_ts_ns);
+
+        // New day
+        if curr_date != prev_date {
+            let curr_minutes = curr_h * 60 + curr_m;
+            return curr_minutes >= self.config.market_open_minutes();
+        }
+
+        // Same day, but crossed market open
+        let prev_minutes = prev_h * 60 + prev_m;
+        let curr_minutes = curr_h * 60 + curr_m;
+
+        prev_minutes < self.config.market_open_minutes()
+            && curr_minutes >= self.config.market_open_minutes()
+    }
+
+    /// Check if this bar ends the session.
+    pub fn is_session_end(&self, curr_ts_ns: i64, next_ts_ns: Option<i64>) -> bool {
+        let (curr_date, curr_h, curr_m, _) = self.timestamp_to_local(curr_ts_ns);
+        let curr_minutes = curr_h * 60 + curr_m;
+
+        // At or past market close
+        if curr_minutes >= self.config.market_close_minutes() {
+            return true;
+        }
+
+        // Check if next bar is in a new session
+        if let Some(next_ts) = next_ts_ns {
+            let (next_date, _, _, _) = self.timestamp_to_local(next_ts);
+            if next_date != curr_date {
+                return true;
+            }
+        }
+
+        false
+    }
+
+    /// Update session state for a new bar.
+    ///
+    /// Returns tuple of (is_new_session, is_squareoff_time, is_session_end).
+    pub fn update(
+        &mut self,
+        idx: usize,
+        timestamp_ns: i64,
+        open: f64,
+        high: f64,
+        low: f64,
+        _close: f64,
+        prev_timestamp_ns: Option<i64>,
+        next_timestamp_ns: Option<i64>,
+    ) -> (bool, bool, bool) {
+        let (date, hours, minutes, _) = self.timestamp_to_local(timestamp_ns);
+        let time_minutes = hours * 60 + minutes;
+
+        // Check for new session
+        let is_new_session = if self.current_session_date != date {
+            // New date - check if within trading hours
+            if time_minutes >= self.config.market_open_minutes()
+                && time_minutes < self.config.market_close_minutes()
+            {
+                self.reset_session(idx, date, open);
+                true
+            } else {
+                false
+            }
+        } else if let Some(prev_ts) = prev_timestamp_ns {
+            if self.is_session_start(prev_ts, timestamp_ns) {
+                self.reset_session(idx, date, open);
+                true
+            } else {
+                false
+            }
+        } else {
+            // First bar - start session if within hours
+            if time_minutes >= self.config.market_open_minutes()
+                && time_minutes < self.config.market_close_minutes()
+            {
+                self.reset_session(idx, date, open);
+                true
+            } else {
+                false
+            }
+        };
+
+        // Update session high/low
+        if self.in_session {
+            if high > self.session_high {
+                self.session_high = high;
+            }
+            if low < self.session_low {
+                self.session_low = low;
+            }
+        }
+
+        // Check squareoff time
+        let is_squareoff =
+            if time_minutes >= self.config.squareoff_minutes() && !self.squareoff_triggered {
+                self.squareoff_triggered = true;
+                self.in_session
+            } else {
+                false
+            };
+
+        // Check session end
+        let is_session_end = self.is_session_end(timestamp_ns, next_timestamp_ns);
+        if is_session_end {
+            self.in_session = false;
+        }
+
+        (is_new_session, is_squareoff, is_session_end)
+    }
+
+    /// Reset session state for a new trading day.
+    fn reset_session(&mut self, idx: usize, date: i64, open_price: f64) {
+        self.current_session_date = date;
+        self.session_start_idx = idx;
+        self.session_open = open_price;
+        self.session_high = open_price;
+        self.session_low = open_price;
+        self.in_session = true;
+        self.squareoff_triggered = false;
+    }
+
+    /// Get current session high.
+    pub fn session_high(&self) -> f64 {
+        self.session_high
+    }
+
+    /// Get current session low.
+    pub fn session_low(&self) -> f64 {
+        self.session_low
+    }
+
+    /// Get current session open.
+    pub fn session_open(&self) -> f64 {
+        self.session_open
+    }
+
+    /// Get session start index.
+    pub fn session_start_idx(&self) -> usize {
+        self.session_start_idx
+    }
+
+    /// Check if currently in a trading session.
+    pub fn in_session(&self) -> bool {
+        self.in_session
+    }
+
+    /// Get opening range (high - low) for the session.
+    pub fn opening_range(&self) -> f64 {
+        self.session_high - self.session_low
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    fn make_timestamp(year: i32, month: u32, day: u32, hour: u32, minute: u32) -> i64 {
+        // Simplified: calculate seconds from 1970-01-01 and convert to nanoseconds
+        // This is approximate for testing
+        let days_since_epoch = (year - 1970) as i64 * 365 + (month - 1) as i64 * 30 + day as i64;
+        let seconds = days_since_epoch * 86400 + hour as i64 * 3600 + minute as i64 * 60;
+        // Subtract IST offset to get UTC
+        let utc_seconds = seconds - (5 * 3600 + 30 * 60);
+        utc_seconds * 1_000_000_000
+    }
+
+    #[test]
+    fn test_session_config_defaults() {
+        let config = SessionConfig::default();
+        assert_eq!(config.market_open_hour, 9);
+        assert_eq!(config.market_open_minute, 15);
+        assert_eq!(config.market_close_hour, 15);
+        assert_eq!(config.market_close_minute, 30);
+        assert_eq!(config.squareoff_minutes_before_close, 5);
+    }
+
+    #[test]
+    fn test_squareoff_minutes() {
+        let config = SessionConfig::default();
+        // 15:30 - 5 minutes = 15:25 = 925 minutes
+        assert_eq!(config.squareoff_minutes(), 925);
+    }
+
+    #[test]
+    fn test_mcx_session() {
+        let config = SessionConfig::mcx_commodity();
+        assert_eq!(config.market_open_hour, 9);
+        assert_eq!(config.market_close_hour, 23);
+        assert_eq!(config.market_close_minute, 30);
+    }
+
+    #[test]
+    fn test_session_tracker_new_session() {
+        let config = SessionConfig::default();
+        let mut tracker = SessionTracker::new(config);
+
+        // Simulate market open at 9:15 IST
+        let ts = make_timestamp(2024, 1, 15, 9, 15);
+        let (is_new, _, _) = tracker.update(0, ts, 100.0, 101.0, 99.0, 100.5, None, None);
+
+        assert!(is_new);
+        assert!(tracker.in_session());
+        assert_eq!(tracker.session_open(), 100.0);
+    }
+
+    #[test]
+    fn test_session_high_low() {
+        let config = SessionConfig::default();
+        let mut tracker = SessionTracker::new(config);
+
+        // First bar
+        let ts1 = make_timestamp(2024, 1, 15, 9, 15);
+        tracker.update(0, ts1, 100.0, 105.0, 95.0, 102.0, None, None);
+
+        // Second bar
+        let ts2 = make_timestamp(2024, 1, 15, 9, 30);
+        tracker.update(1, ts2, 102.0, 110.0, 100.0, 108.0, Some(ts1), None);
+
+        assert_eq!(tracker.session_high(), 110.0);
+        assert_eq!(tracker.session_low(), 95.0);
+    }
+}

src/indicators/mod.rs

@@ -4,12 +4,14 @@
 //! and return Vec outputs. NaN values are used for the warmup period.
 
 pub mod momentum;
+pub mod rolling;
 pub mod strength;
 pub mod trend;
 pub mod volatility;
 pub mod volume;
 
 pub use momentum::{macd, rsi, stochastic, MacdResult, StochasticResult};
+pub use rolling::{rolling_max, rolling_min};
 pub use strength::adx;
 pub use trend::{ema, sma, supertrend, SupertrendResult};
 pub use volatility::{atr, bollinger_bands, BollingerBandsResult};

src/indicators/rolling.rs

@@ -0,0 +1,106 @@
+//! Rolling min/max indicators for LLV/HHV support.
+//!
+//! Provides rolling minimum and maximum calculations for Lowest Low Value (LLV)
+//! and Highest High Value (HHV) expressions.
+
+use crate::core::error::RaptorError;
+
+/// Calculate rolling minimum (Lowest Low Value) over a period.
+///
+/// Returns NaN for the first (period - 1) values where insufficient data exists.
+///
+/// # Arguments
+/// * `data` - Input data slice
+/// * `period` - Lookback period
+///
+/// # Returns
+/// Vec of rolling minimum values
+pub fn rolling_min(data: &[f64], period: usize) -> Result<Vec<f64>, RaptorError> {
+    if period == 0 {
+        return Err(RaptorError::invalid_parameter("period must be at least 1"));
+    }
+
+    let n = data.len();
+    let mut result = vec![f64::NAN; n];
+
+    for i in (period - 1)..n {
+        let start = i + 1 - period;
+        let min_val =
+            data[start..=i]
+                .iter()
+                .fold(f64::INFINITY, |a, &b| if b.is_nan() { a } else { a.min(b) });
+        result[i] = if min_val == f64::INFINITY { f64::NAN } else { min_val };
+    }
+
+    Ok(result)
+}
+
+/// Calculate rolling maximum (Highest High Value) over a period.
+///
+/// Returns NaN for the first (period - 1) values where insufficient data exists.
+///
+/// # Arguments
+/// * `data` - Input data slice
+/// * `period` - Lookback period
+///
+/// # Returns
+/// Vec of rolling maximum values
+pub fn rolling_max(data: &[f64], period: usize) -> Result<Vec<f64>, RaptorError> {
+    if period == 0 {
+        return Err(RaptorError::invalid_parameter("period must be at least 1"));
+    }
+
+    let n = data.len();
+    let mut result = vec![f64::NAN; n];
+
+    for i in (period - 1)..n {
+        let start = i + 1 - period;
+        let max_val =
+            data[start..=i]
+                .iter()
+                .fold(f64::NEG_INFINITY, |a, &b| if b.is_nan() { a } else { a.max(b) });
+        result[i] = if max_val == f64::NEG_INFINITY { f64::NAN } else { max_val };
+    }
+
+    Ok(result)
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn test_rolling_min() {
+        let data = vec![5.0, 3.0, 8.0, 2.0, 7.0, 1.0, 9.0];
+        let result = rolling_min(&data, 3).unwrap();
+
+        assert!(result[0].is_nan());
+        assert!(result[1].is_nan());
+        assert!((result[2] - 3.0).abs() < f64::EPSILON); // min(5, 3, 8)
+        assert!((result[3] - 2.0).abs() < f64::EPSILON); // min(3, 8, 2)
+        assert!((result[4] - 2.0).abs() < f64::EPSILON); // min(8, 2, 7)
+        assert!((result[5] - 1.0).abs() < f64::EPSILON); // min(2, 7, 1)
+        assert!((result[6] - 1.0).abs() < f64::EPSILON); // min(7, 1, 9)
+    }
+
+    #[test]
+    fn test_rolling_max() {
+        let data = vec![5.0, 3.0, 8.0, 2.0, 7.0, 1.0, 9.0];
+        let result = rolling_max(&data, 3).unwrap();
+
+        assert!(result[0].is_nan());
+        assert!(result[1].is_nan());
+        assert!((result[2] - 8.0).abs() < f64::EPSILON); // max(5, 3, 8)
+        assert!((result[3] - 8.0).abs() < f64::EPSILON); // max(3, 8, 2)
+        assert!((result[4] - 8.0).abs() < f64::EPSILON); // max(8, 2, 7)
+        assert!((result[5] - 7.0).abs() < f64::EPSILON); // max(2, 7, 1)
+        assert!((result[6] - 9.0).abs() < f64::EPSILON); // max(7, 1, 9)
+    }
+
+    #[test]
+    fn test_invalid_period() {
+        let data = vec![1.0, 2.0, 3.0];
+        assert!(rolling_min(&data, 0).is_err());
+        assert!(rolling_max(&data, 0).is_err());
+    }
+}

src/lib.rs

@@ -41,6 +41,7 @@ fn _raptorbt(_py: Python<'_>, m: &PyModule) -> PyResult<()> {
     m.add_function(wrap_pyfunction!(python::bindings::run_options_backtest, m)?)?;
     m.add_function(wrap_pyfunction!(python::bindings::run_pairs_backtest, m)?)?;
     m.add_function(wrap_pyfunction!(python::bindings::run_multi_backtest, m)?)?;
+    m.add_function(wrap_pyfunction!(python::bindings::run_spread_backtest, m)?)?;
 
     // Register indicator functions
     m.add_function(wrap_pyfunction!(python::bindings::sma, m)?)?;
@@ -53,6 +54,8 @@ fn _raptorbt(_py: Python<'_>, m: &PyModule) -> PyResult<()> {
     m.add_function(wrap_pyfunction!(python::bindings::adx, m)?)?;
     m.add_function(wrap_pyfunction!(python::bindings::vwap, m)?)?;
     m.add_function(wrap_pyfunction!(python::bindings::supertrend, m)?)?;
+    m.add_function(wrap_pyfunction!(python::bindings::rolling_min, m)?)?;
+    m.add_function(wrap_pyfunction!(python::bindings::rolling_max, m)?)?;
 
     Ok(())
 }

src/metrics/streaming.rs

@@ -2,9 +2,12 @@
 //!
 //! Enables single-pass calculation of mean, variance, Sharpe ratio, and Sortino ratio.
 
+use crate::core::types::BacktestMetrics;
+
 /// Streaming metrics calculator using Welford's algorithm.
 ///
 /// Allows incremental calculation of statistics without storing all values.
+/// Also tracks equity and drawdown for backtesting.
 #[derive(Debug, Clone)]
 pub struct StreamingMetrics {
     /// Number of observations.
@@ -27,6 +30,59 @@ pub struct StreamingMetrics {
     count_positive: usize,
     /// Count of negative returns.
     count_negative: usize,
+
+    // === Equity and drawdown tracking ===
+    /// Initial capital.
+    #[allow(dead_code)]
+    initial_capital: f64,
+    /// Peak equity value (for drawdown calculation).
+    peak_equity: f64,
+    /// Current equity value.
+    current_equity: f64,
+    /// Maximum drawdown percentage.
+    max_drawdown_pct: f64,
+    /// Current drawdown percentage.
+    current_drawdown: f64,
+    /// Bars since peak (for max drawdown duration).
+    bars_since_peak: usize,
+    /// Maximum drawdown duration in bars.
+    max_drawdown_duration: usize,
+
+    // === Trade tracking ===
+    /// Number of trades.
+    trade_count: usize,
+    /// Number of winning trades.
+    winning_trades: usize,
+    /// Number of losing trades.
+    losing_trades: usize,
+    /// Sum of winning trade P&L.
+    sum_wins: f64,
+    /// Sum of losing trade P&L.
+    sum_losses: f64,
+    /// Sum of trade return percentages.
+    sum_trade_returns: f64,
+    /// Sum of squared trade return percentages (for SQN).
+    sum_trade_returns_sq: f64,
+    /// Best trade return percentage.
+    best_trade_pct: f64,
+    /// Worst trade return percentage.
+    worst_trade_pct: f64,
+    /// Sum of winning trade durations.
+    sum_winning_duration: usize,
+    /// Sum of losing trade durations.
+    sum_losing_duration: usize,
+    /// Current consecutive wins.
+    current_consecutive_wins: usize,
+    /// Current consecutive losses.
+    current_consecutive_losses: usize,
+    /// Maximum consecutive wins.
+    max_consecutive_wins: usize,
+    /// Maximum consecutive losses.
+    max_consecutive_losses: usize,
+    /// Total holding period (bars).
+    total_holding_period: usize,
+    /// Total fees paid.
+    total_fees: f64,
 }
 
 impl Default for StreamingMetrics {
@@ -38,6 +94,11 @@ impl Default for StreamingMetrics {
 impl StreamingMetrics {
     /// Create a new streaming metrics calculator.
     pub fn new() -> Self {
+        Self::with_initial_capital(0.0)
+    }
+
+    /// Create a new streaming metrics calculator with initial capital.
+    pub fn with_initial_capital(initial_capital: f64) -> Self {
         Self {
             count: 0,
             mean: 0.0,
@@ -49,6 +110,32 @@ impl StreamingMetrics {
             sum_negative: 0.0,
             count_positive: 0,
             count_negative: 0,
+            // Equity tracking
+            initial_capital,
+            peak_equity: initial_capital,
+            current_equity: initial_capital,
+            max_drawdown_pct: 0.0,
+            current_drawdown: 0.0,
+            bars_since_peak: 0,
+            max_drawdown_duration: 0,
+            // Trade tracking
+            trade_count: 0,
+            winning_trades: 0,
+            losing_trades: 0,
+            sum_wins: 0.0,
+            sum_losses: 0.0,
+            sum_trade_returns: 0.0,
+            sum_trade_returns_sq: 0.0,
+            best_trade_pct: f64::NEG_INFINITY,
+            worst_trade_pct: f64::INFINITY,
+            sum_winning_duration: 0,
+            sum_losing_duration: 0,
+            current_consecutive_wins: 0,
+            current_consecutive_losses: 0,
+            max_consecutive_wins: 0,
+            max_consecutive_losses: 0,
+            total_holding_period: 0,
+            total_fees: 0.0,
         }
     }
 
@@ -218,6 +305,249 @@ impl StreamingMetrics {
         self.profit_factor()
     }
 
+    // === Equity tracking methods ===
+
+    /// Update equity and calculate drawdown.
+    pub fn update_equity(&mut self, equity: f64) {
+        self.current_equity = equity;
+
+        if equity > self.peak_equity {
+            self.peak_equity = equity;
+            self.bars_since_peak = 0;
+        } else {
+            self.bars_since_peak += 1;
+            if self.bars_since_peak > self.max_drawdown_duration {
+                self.max_drawdown_duration = self.bars_since_peak;
+            }
+        }
+
+        // Calculate current drawdown percentage
+        if self.peak_equity > 0.0 {
+            self.current_drawdown = (self.peak_equity - equity) / self.peak_equity * 100.0;
+            if self.current_drawdown > self.max_drawdown_pct {
+                self.max_drawdown_pct = self.current_drawdown;
+            }
+        }
+    }
+
+    /// Get current drawdown percentage.
+    #[inline]
+    pub fn current_drawdown_pct(&self) -> f64 {
+        self.current_drawdown
+    }
+
+    /// Get maximum drawdown percentage.
+    #[inline]
+    pub fn max_drawdown_pct(&self) -> f64 {
+        self.max_drawdown_pct
+    }
+
+    // === Trade tracking methods ===
+
+    /// Record a completed trade.
+    ///
+    /// # Arguments
+    /// * `pnl` - Trade profit/loss
+    /// * `return_pct` - Trade return percentage
+    /// * `duration` - Trade duration in bars
+    pub fn record_trade(&mut self, pnl: f64, return_pct: f64, duration: usize) {
+        self.trade_count += 1;
+        self.sum_trade_returns += return_pct;
+        self.sum_trade_returns_sq += return_pct * return_pct;
+        self.total_holding_period += duration;
+
+        // Track best/worst trades
+        if return_pct > self.best_trade_pct {
+            self.best_trade_pct = return_pct;
+        }
+        if return_pct < self.worst_trade_pct {
+            self.worst_trade_pct = return_pct;
+        }
+
+        if pnl > 0.0 {
+            self.winning_trades += 1;
+            self.sum_wins += pnl;
+            self.sum_winning_duration += duration;
+            self.current_consecutive_wins += 1;
+            self.current_consecutive_losses = 0;
+            if self.current_consecutive_wins > self.max_consecutive_wins {
+                self.max_consecutive_wins = self.current_consecutive_wins;
+            }
+        } else if pnl < 0.0 {
+            self.losing_trades += 1;
+            self.sum_losses += pnl.abs();
+            self.sum_losing_duration += duration;
+            self.current_consecutive_losses += 1;
+            self.current_consecutive_wins = 0;
+            if self.current_consecutive_losses > self.max_consecutive_losses {
+                self.max_consecutive_losses = self.current_consecutive_losses;
+            }
+        }
+    }
+
+    /// Record fees paid.
+    pub fn record_fees(&mut self, fees: f64) {
+        self.total_fees += fees;
+    }
+
+    /// Finalize metrics and produce BacktestMetrics.
+    ///
+    /// # Arguments
+    /// * `initial_capital` - Starting capital
+    /// * `final_value` - Ending portfolio value
+    /// * `returns` - Array of period returns for ratio calculations
+    pub fn finalize(
+        &self,
+        initial_capital: f64,
+        final_value: f64,
+        returns: &[f64],
+    ) -> BacktestMetrics {
+        // Calculate return metrics from the returns array
+        let mut return_metrics = StreamingMetrics::new();
+        for &r in returns {
+            if !r.is_nan() {
+                return_metrics.update(r);
+            }
+        }
+
+        let total_return_pct = if initial_capital > 0.0 {
+            (final_value - initial_capital) / initial_capital * 100.0
+        } else {
+            0.0
+        };
+
+        // Calculate trade-based metrics
+        let win_rate_pct = if self.trade_count > 0 {
+            self.winning_trades as f64 / self.trade_count as f64 * 100.0
+        } else {
+            0.0
+        };
+
+        let profit_factor = if self.sum_losses > 0.0 {
+            self.sum_wins / self.sum_losses
+        } else if self.sum_wins > 0.0 {
+            f64::INFINITY
+        } else {
+            0.0
+        };
+
+        let avg_trade_return_pct = if self.trade_count > 0 {
+            self.sum_trade_returns / self.trade_count as f64
+        } else {
+            0.0
+        };
+
+        let avg_win_pct = if self.winning_trades > 0 {
+            self.sum_wins / self.winning_trades as f64 / initial_capital * 100.0
+        } else {
+            0.0
+        };
+
+        let avg_loss_pct = if self.losing_trades > 0 {
+            -(self.sum_losses / self.losing_trades as f64 / initial_capital * 100.0)
+        } else {
+            0.0
+        };
+
+        let avg_winning_duration = if self.winning_trades > 0 {
+            self.sum_winning_duration as f64 / self.winning_trades as f64
+        } else {
+            0.0
+        };
+
+        let avg_losing_duration = if self.losing_trades > 0 {
+            self.sum_losing_duration as f64 / self.losing_trades as f64
+        } else {
+            0.0
+        };
+
+        let avg_holding_period = if self.trade_count > 0 {
+            self.total_holding_period as f64 / self.trade_count as f64
+        } else {
+            0.0
+        };
+
+        // Expectancy: average profit per trade
+        let expectancy = if self.trade_count > 0 {
+            (self.sum_wins - self.sum_losses) / self.trade_count as f64
+        } else {
+            0.0
+        };
+
+        // SQN (System Quality Number)
+        let sqn = if self.trade_count > 1 {
+            let mean_return = self.sum_trade_returns / self.trade_count as f64;
+            let variance =
+                (self.sum_trade_returns_sq / self.trade_count as f64) - (mean_return * mean_return);
+            let std_dev = variance.max(0.0).sqrt();
+            if std_dev > 0.0 {
+                (mean_return / std_dev) * (self.trade_count as f64).sqrt()
+            } else {
+                0.0
+            }
+        } else {
+            0.0
+        };
+
+        // Sharpe ratio (annualized, assuming 252 trading days)
+        let sharpe_ratio = return_metrics.sharpe_ratio(252.0);
+
+        // Sortino ratio (annualized)
+        let sortino_ratio = return_metrics.sortino_ratio(252.0);
+
+        // Calmar ratio (annualized return / max drawdown)
+        let calmar_ratio = if self.max_drawdown_pct > 0.0 {
+            total_return_pct / self.max_drawdown_pct
+        } else if total_return_pct > 0.0 {
+            f64::INFINITY
+        } else {
+            0.0
+        };
+
+        // Omega ratio
+        let omega_ratio = return_metrics.omega_ratio();
+
+        // Best/worst trade handling (handle edge cases)
+        let best_trade_pct =
+            if self.best_trade_pct == f64::NEG_INFINITY { 0.0 } else { self.best_trade_pct };
+        let worst_trade_pct =
+            if self.worst_trade_pct == f64::INFINITY { 0.0 } else { self.worst_trade_pct };
+
+        BacktestMetrics {
+            total_return_pct,
+            sharpe_ratio,
+            sortino_ratio,
+            calmar_ratio,
+            omega_ratio,
+            max_drawdown_pct: self.max_drawdown_pct,
+            max_drawdown_duration: self.max_drawdown_duration,
+            win_rate_pct,
+            profit_factor,
+            expectancy,
+            sqn,
+            total_trades: self.trade_count,
+            total_closed_trades: self.trade_count,
+            total_open_trades: 0,
+            open_trade_pnl: 0.0,
+            winning_trades: self.winning_trades,
+            losing_trades: self.losing_trades,
+            start_value: initial_capital,
+            end_value: final_value,
+            total_fees_paid: self.total_fees,
+            best_trade_pct,
+            worst_trade_pct,
+            avg_trade_return_pct,
+            avg_win_pct,
+            avg_loss_pct,
+            avg_winning_duration,
+            avg_losing_duration,
+            max_consecutive_wins: self.max_consecutive_wins,
+            max_consecutive_losses: self.max_consecutive_losses,
+            avg_holding_period,
+            exposure_pct: 0.0, // TODO: calculate based on time in market
+        }
+    }
+
     /// Reset all metrics.
     pub fn reset(&mut self) {
         *self = Self::new();

src/python/bindings.rs

@@ -15,6 +15,9 @@ use crate::strategies::options::{
 };
 use crate::strategies::pairs::{PairsBacktest, PairsConfig};
 use crate::strategies::single::SingleBacktest;
+use crate::strategies::spreads::{
+    LegConfig, OptionType as SpreadOptionType, SpreadBacktest, SpreadConfig, SpreadType,
+};
 
 use super::numpy_bridge::*;
 
@@ -673,6 +676,68 @@ pub fn run_pairs_backtest<'py>(
     Ok(convert_result(result))
 }
 
+/// Run spread backtest (multi-leg options).
+#[pyfunction]
+#[pyo3(signature = (timestamps, underlying_close, legs_premiums, leg_configs, entries, exits, config=None, spread_type="custom", max_loss=None, target_profit=None))]
+pub fn run_spread_backtest<'py>(
+    _py: Python<'py>,
+    timestamps: PyReadonlyArray1<i64>,
+    underlying_close: PyReadonlyArray1<f64>,
+    legs_premiums: Vec<PyReadonlyArray1<f64>>,
+    leg_configs: Vec<(String, f64, i32, usize)>, // (option_type, strike, quantity, lot_size)
+    entries: PyReadonlyArray1<bool>,
+    exits: PyReadonlyArray1<bool>,
+    config: Option<&PyBacktestConfig>,
+    spread_type: &str,
+    max_loss: Option<f64>,
+    target_profit: Option<f64>,
+) -> PyResult<PyBacktestResult> {
+    let ts = numpy_to_vec_i64(timestamps);
+    let underlying = numpy_to_vec_f64(underlying_close);
+    let premiums: Vec<Vec<f64>> = legs_premiums.into_iter().map(numpy_to_vec_f64).collect();
+    let entry_signals = numpy_to_vec_bool(entries);
+    let exit_signals = numpy_to_vec_bool(exits);
+
+    // Convert leg configs
+    let rust_leg_configs: Vec<LegConfig> = leg_configs
+        .into_iter()
+        .map(|(opt_type, strike, quantity, lot_size)| {
+            let option_type =
+                SpreadOptionType::from_str(&opt_type).unwrap_or(SpreadOptionType::Call);
+            LegConfig::new(option_type, strike, quantity, lot_size)
+        })
+        .collect();
+
+    // Parse spread type
+    let spread_type_enum = match spread_type.to_lowercase().as_str() {
+        "straddle" => SpreadType::Straddle,
+        "strangle" => SpreadType::Strangle,
+        "vertical_call" | "verticalcall" => SpreadType::VerticalCall,
+        "vertical_put" | "verticalput" => SpreadType::VerticalPut,
+        "iron_condor" | "ironcondor" => SpreadType::IronCondor,
+        "iron_butterfly" | "ironbutterfly" => SpreadType::IronButterfly,
+        "butterfly_call" | "butterflycall" => SpreadType::ButterflyCall,
+        "butterfly_put" | "butterflyput" => SpreadType::ButterflyPut,
+        "calendar" => SpreadType::Calendar,
+        "diagonal" => SpreadType::Diagonal,
+        _ => SpreadType::Custom,
+    };
+
+    let spread_config = SpreadConfig {
+        base: config.map(|c| BacktestConfig::from(c)).unwrap_or_default(),
+        spread_type: spread_type_enum,
+        leg_configs: rust_leg_configs,
+        max_loss,
+        target_profit,
+        close_at_eod: false,
+    };
+
+    let backtest = SpreadBacktest::new(spread_config);
+    let result = backtest.run(&ts, &underlying, &premiums, &entry_signals, &exit_signals);
+
+    Ok(convert_result(result))
+}
+
 /// Run multi-strategy backtest.
 #[pyfunction]
 #[pyo3(signature = (timestamps, open, high, low, close, volume, strategies, config=None, combine_mode="any"))]
@@ -903,6 +968,32 @@ pub fn supertrend<'py>(
     Ok((vec_to_numpy_f64(py, result.supertrend), direction_array))
 }
 
+/// Rolling minimum (Lowest Low Value).
+#[pyfunction]
+pub fn rolling_min<'py>(
+    py: Python<'py>,
+    data: PyReadonlyArray1<f64>,
+    period: usize,
+) -> PyResult<&'py PyArray1<f64>> {
+    let vec = numpy_to_vec_f64(data);
+    let result = indicators::rolling::rolling_min(&vec, period)
+        .map_err(|e| pyo3::exceptions::PyValueError::new_err(e.to_string()))?;
+    Ok(vec_to_numpy_f64(py, result))
+}
+
+/// Rolling maximum (Highest High Value).
+#[pyfunction]
+pub fn rolling_max<'py>(
+    py: Python<'py>,
+    data: PyReadonlyArray1<f64>,
+    period: usize,
+) -> PyResult<&'py PyArray1<f64>> {
+    let vec = numpy_to_vec_f64(data);
+    let result = indicators::rolling::rolling_max(&vec, period)
+        .map_err(|e| pyo3::exceptions::PyValueError::new_err(e.to_string()))?;
+    Ok(vec_to_numpy_f64(py, result))
+}
+
 // ============================================================================
 // Helper Functions
 // ============================================================================

src/strategies/mod.rs

@@ -5,9 +5,13 @@ pub mod multi;
 pub mod options;
 pub mod pairs;
 pub mod single;
+pub mod spreads;
 
 pub use basket::BasketBacktest;
 pub use multi::MultiStrategyBacktest;
 pub use options::OptionsBacktest;
 pub use pairs::PairsBacktest;
 pub use single::SingleBacktest;
+pub use spreads::{
+    LegConfig, OptionType as SpreadOptionType, SpreadBacktest, SpreadConfig, SpreadType,
+};

src/strategies/spreads.rs

@@ -0,0 +1,585 @@
+//! Multi-leg options spread backtesting implementation.
+//!
+//! Provides high-performance spread backtesting for:
+//! - Straddles and Strangles
+//! - Vertical spreads (bull/bear call/put)
+//! - Iron Condors and Iron Butterflies
+//! - Calendar and Diagonal spreads
+//!
+//! Key features:
+//! - Single-pass O(n) algorithm
+//! - Coordinated entry/exit across all legs
+//! - Net premium P&L calculation
+//! - Combined Greeks tracking
+
+use crate::core::types::{
+    BacktestConfig, BacktestMetrics, BacktestResult, Direction, ExitReason, Trade,
+};
+use crate::metrics::streaming::StreamingMetrics;
+use serde::{Deserialize, Serialize};
+
+/// Spread type enumeration.
+#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
+pub enum SpreadType {
+    Straddle,
+    Strangle,
+    VerticalCall,
+    VerticalPut,
+    IronCondor,
+    IronButterfly,
+    ButterflyCall,
+    ButterflyPut,
+    Calendar,
+    Diagonal,
+    Custom,
+}
+
+/// Option type for a leg.
+#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
+pub enum OptionType {
+    Call,
+    Put,
+}
+
+impl OptionType {
+    pub fn from_str(s: &str) -> Option<Self> {
+        match s.to_uppercase().as_str() {
+            "CE" | "CALL" | "C" => Some(OptionType::Call),
+            "PE" | "PUT" | "P" => Some(OptionType::Put),
+            _ => None,
+        }
+    }
+}
+
+/// Configuration for a single leg of a spread.
+#[derive(Debug, Clone, Serialize, Deserialize)]
+pub struct LegConfig {
+    /// Option type (Call or Put).
+    pub option_type: OptionType,
+    /// Strike price.
+    pub strike: f64,
+    /// Position quantity (+1 long, -1 short).
+    pub quantity: i32,
+    /// Lot size for the option.
+    pub lot_size: usize,
+}
+
+impl LegConfig {
+    pub fn new(option_type: OptionType, strike: f64, quantity: i32, lot_size: usize) -> Self {
+        Self { option_type, strike, quantity, lot_size }
+    }
+
+    /// Check if this is a long position.
+    pub fn is_long(&self) -> bool {
+        self.quantity > 0
+    }
+
+    /// Check if this is a short position.
+    pub fn is_short(&self) -> bool {
+        self.quantity < 0
+    }
+}
+
+/// Configuration for spread backtest.
+#[derive(Debug, Clone, Serialize, Deserialize)]
+pub struct SpreadConfig {
+    /// Base backtest configuration.
+    pub base: BacktestConfig,
+    /// Spread type.
+    pub spread_type: SpreadType,
+    /// Leg configurations.
+    pub leg_configs: Vec<LegConfig>,
+    /// Maximum loss threshold (optional, for early exit).
+    pub max_loss: Option<f64>,
+    /// Target profit threshold (optional, for early exit).
+    pub target_profit: Option<f64>,
+    /// Whether to close at end of day.
+    pub close_at_eod: bool,
+}
+
+impl Default for SpreadConfig {
+    fn default() -> Self {
+        Self {
+            base: BacktestConfig::default(),
+            spread_type: SpreadType::Custom,
+            leg_configs: Vec::new(),
+            max_loss: None,
+            target_profit: None,
+            close_at_eod: false,
+        }
+    }
+}
+
+/// State for a single leg position.
+#[derive(Debug, Clone)]
+struct LegPosition {
+    /// Entry premium price.
+    pub entry_premium: f64,
+    /// Entry index.
+    #[allow(dead_code)]
+    pub entry_idx: usize,
+    /// Current premium price.
+    pub current_premium: f64,
+    /// Leg configuration.
+    pub config: LegConfig,
+}
+
+impl LegPosition {
+    fn new(config: LegConfig, entry_premium: f64, entry_idx: usize) -> Self {
+        Self { entry_premium, entry_idx, current_premium: entry_premium, config }
+    }
+
+    /// Calculate unrealized P&L for this leg.
+    fn unrealized_pnl(&self) -> f64 {
+        // For short positions: profit when premium decreases
+        // For long positions: profit when premium increases
+        let premium_change = self.current_premium - self.entry_premium;
+        let quantity = self.config.quantity as f64;
+        let lot_size = self.config.lot_size as f64;
+        -quantity * premium_change * lot_size
+    }
+}
+
+/// Spread position state.
+#[derive(Debug, Clone)]
+struct SpreadPosition {
+    /// Individual leg positions.
+    pub legs: Vec<LegPosition>,
+    /// Entry bar index.
+    pub entry_idx: usize,
+    /// Entry net premium (positive = credit, negative = debit).
+    pub entry_net_premium: f64,
+    /// Entry timestamp.
+    pub entry_time: i64,
+    /// Whether position is open.
+    pub is_open: bool,
+}
+
+impl SpreadPosition {
+    fn new(legs: Vec<LegPosition>, entry_idx: usize, entry_time: i64) -> Self {
+        let entry_net_premium: f64 = legs
+            .iter()
+            .map(|leg| leg.entry_premium * leg.config.quantity as f64 * leg.config.lot_size as f64)
+            .sum();
+
+        Self { legs, entry_idx, entry_net_premium, entry_time, is_open: true }
+    }
+
+    /// Calculate total unrealized P&L across all legs.
+    fn total_unrealized_pnl(&self) -> f64 {
+        self.legs.iter().map(|leg| leg.unrealized_pnl()).sum()
+    }
+
+    /// Update leg premiums.
+    fn update_premiums(&mut self, leg_premiums: &[f64]) {
+        for (leg, &premium) in self.legs.iter_mut().zip(leg_premiums.iter()) {
+            leg.current_premium = premium;
+        }
+    }
+
+    /// Close the position and return P&L.
+    fn close(&mut self) -> f64 {
+        self.is_open = false;
+        self.total_unrealized_pnl()
+    }
+}
+
+/// Spread backtest runner.
+pub struct SpreadBacktest {
+    config: SpreadConfig,
+}
+
+impl SpreadBacktest {
+    /// Create a new spread backtest.
+    pub fn new(config: SpreadConfig) -> Self {
+        Self { config }
+    }
+
+    /// Run the spread backtest.
+    ///
+    /// # Arguments
+    /// * `timestamps` - Timestamp array
+    /// * `underlying_close` - Underlying close prices
+    /// * `legs_premiums` - Premium series for each leg (Vec of Vec)
+    /// * `entries` - Entry signals
+    /// * `exits` - Exit signals
+    ///
+    /// # Returns
+    /// Backtest result with metrics, trades, and equity curve
+    pub fn run(
+        &self,
+        timestamps: &[i64],
+        _underlying_close: &[f64],
+        legs_premiums: &[Vec<f64>],
+        entries: &[bool],
+        exits: &[bool],
+    ) -> BacktestResult {
+        let n = timestamps.len();
+
+        // Validate inputs
+        if legs_premiums.len() != self.config.leg_configs.len() {
+            return self.empty_result(n);
+        }
+
+        for premiums in legs_premiums {
+            if premiums.len() != n {
+                return self.empty_result(n);
+            }
+        }
+
+        let mut metrics = StreamingMetrics::with_initial_capital(self.config.base.initial_capital);
+        let mut equity_curve = Vec::with_capacity(n);
+        let mut drawdown_curve = Vec::with_capacity(n);
+        let mut returns = Vec::with_capacity(n);
+        let mut trades: Vec<Trade> = Vec::new();
+        let mut trade_id: u64 = 0;
+
+        let mut cash = self.config.base.initial_capital;
+        let mut position: Option<SpreadPosition> = None;
+        let mut prev_equity = cash;
+
+        // Single-pass O(n) algorithm
+        for i in 0..n {
+            // Get current leg premiums
+            let current_premiums: Vec<f64> = legs_premiums.iter().map(|p| p[i]).collect();
+
+            // Update position premiums if open
+            if let Some(ref mut pos) = position {
+                pos.update_premiums(&current_premiums);
+            }
+
+            // Calculate unrealized P&L for exit checks
+            let unrealized_pnl = position.as_ref().map(|p| p.total_unrealized_pnl()).unwrap_or(0.0);
+
+            // Check for exit signals or conditions
+            let should_exit = position.is_some()
+                && (exits[i]
+                    || self.check_max_loss(&position, unrealized_pnl)
+                    || self.check_target_profit(&position, unrealized_pnl));
+
+            if should_exit {
+                if let Some(mut pos) = position.take() {
+                    let pnl = pos.close();
+                    let fees = self.calculate_fees(&pos);
+                    let net_pnl = pnl - fees;
+
+                    cash += net_pnl;
+
+                    // Record trade
+                    trade_id += 1;
+                    let exit_reason = if exits[i] {
+                        ExitReason::Signal
+                    } else if self.check_max_loss(&Some(pos.clone()), pnl) {
+                        ExitReason::StopLoss
+                    } else {
+                        ExitReason::TakeProfit
+                    };
+
+                    let entry_premium = pos.entry_net_premium;
+                    let exit_premium: f64 = current_premiums
+                        .iter()
+                        .zip(self.config.leg_configs.iter())
+                        .map(|(&p, cfg)| p * cfg.quantity as f64 * cfg.lot_size as f64)
+                        .sum();
+
+                    trades.push(Trade {
+                        id: trade_id,
+                        symbol: "SPREAD".to_string(),
+                        entry_idx: pos.entry_idx,
+                        exit_idx: i,
+                        entry_price: entry_premium,
+                        exit_price: exit_premium,
+                        size: 1.0,
+                        direction: Direction::Long, // Spreads are treated as "long spread"
+                        pnl: net_pnl,
+                        return_pct: if entry_premium.abs() > 0.0 {
+                            net_pnl / entry_premium.abs() * 100.0
+                        } else {
+                            0.0
+                        },
+                        entry_time: pos.entry_time,
+                        exit_time: timestamps[i],
+                        fees,
+                        exit_reason,
+                    });
+
+                    metrics.record_trade(
+                        net_pnl,
+                        net_pnl / entry_premium.abs() * 100.0,
+                        i - pos.entry_idx,
+                    );
+                }
+            }
+
+            // Check for entry signals
+            if position.is_none() && entries[i] {
+                let legs: Vec<LegPosition> = self
+                    .config
+                    .leg_configs
+                    .iter()
+                    .zip(current_premiums.iter())
+                    .map(|(cfg, &premium)| LegPosition::new(cfg.clone(), premium, i))
+                    .collect();
+
+                let new_position = SpreadPosition::new(legs, i, timestamps[i]);
+
+                // Calculate entry fees
+                let entry_fees = self.calculate_entry_fees(&new_position);
+                cash -= entry_fees;
+
+                position = Some(new_position);
+            }
+
+            // Update equity tracking
+            let equity = cash + position.as_ref().map(|p| p.total_unrealized_pnl()).unwrap_or(0.0);
+            equity_curve.push(equity);
+
+            let daily_return =
+                if prev_equity > 0.0 { (equity - prev_equity) / prev_equity } else { 0.0 };
+            returns.push(daily_return);
+            prev_equity = equity;
+
+            // Update drawdown
+            metrics.update_equity(equity);
+            drawdown_curve.push(metrics.current_drawdown_pct());
+        }
+
+        // Close any remaining open position at end
+        if let Some(mut pos) = position.take() {
+            let pnl = pos.close();
+            let fees = self.calculate_fees(&pos);
+            cash += pnl - fees;
+        }
+
+        // Finalize metrics
+        let final_metrics = metrics.finalize(self.config.base.initial_capital, cash, &returns);
+
+        BacktestResult { metrics: final_metrics, equity_curve, drawdown_curve, trades, returns }
+    }
+
+    /// Check if max loss threshold is hit.
+    fn check_max_loss(&self, _position: &Option<SpreadPosition>, unrealized_pnl: f64) -> bool {
+        if let Some(max_loss) = self.config.max_loss {
+            if unrealized_pnl < -max_loss {
+                return true;
+            }
+        }
+        false
+    }
+
+    /// Check if target profit threshold is hit.
+    fn check_target_profit(&self, _position: &Option<SpreadPosition>, unrealized_pnl: f64) -> bool {
+        if let Some(target) = self.config.target_profit {
+            if unrealized_pnl > target {
+                return true;
+            }
+        }
+        false
+    }
+
+    /// Calculate entry fees for a position.
+    fn calculate_entry_fees(&self, position: &SpreadPosition) -> f64 {
+        let total_premium: f64 = position
+            .legs
+            .iter()
+            .map(|leg| leg.entry_premium.abs() * leg.config.lot_size as f64)
+            .sum();
+        total_premium * self.config.base.fees
+    }
+
+    /// Calculate exit fees for a position.
+    fn calculate_fees(&self, position: &SpreadPosition) -> f64 {
+        let total_premium: f64 = position
+            .legs
+            .iter()
+            .map(|leg| leg.current_premium.abs() * leg.config.lot_size as f64)
+            .sum();
+        total_premium * self.config.base.fees * 2.0 // Entry + Exit
+    }
+
+    /// Create an empty result (used for validation failures).
+    fn empty_result(&self, n: usize) -> BacktestResult {
+        BacktestResult {
+            metrics: BacktestMetrics::default(),
+            equity_curve: vec![self.config.base.initial_capital; n],
+            drawdown_curve: vec![0.0; n],
+            trades: Vec::new(),
+            returns: vec![0.0; n],
+        }
+    }
+}
+
+/// Convenience function to create a straddle spread config.
+pub fn create_straddle_config(
+    base: BacktestConfig,
+    strike: f64,
+    lot_size: usize,
+    short: bool,
+) -> SpreadConfig {
+    let quantity = if short { -1 } else { 1 };
+    SpreadConfig {
+        base,
+        spread_type: SpreadType::Straddle,
+        leg_configs: vec![
+            LegConfig::new(OptionType::Call, strike, quantity, lot_size),
+            LegConfig::new(OptionType::Put, strike, quantity, lot_size),
+        ],
+        ..Default::default()
+    }
+}
+
+/// Convenience function to create a strangle spread config.
+pub fn create_strangle_config(
+    base: BacktestConfig,
+    call_strike: f64,
+    put_strike: f64,
+    lot_size: usize,
+    short: bool,
+) -> SpreadConfig {
+    let quantity = if short { -1 } else { 1 };
+    SpreadConfig {
+        base,
+        spread_type: SpreadType::Strangle,
+        leg_configs: vec![
+            LegConfig::new(OptionType::Call, call_strike, quantity, lot_size),
+            LegConfig::new(OptionType::Put, put_strike, quantity, lot_size),
+        ],
+        ..Default::default()
+    }
+}
+
+/// Convenience function to create an iron condor spread config.
+pub fn create_iron_condor_config(
+    base: BacktestConfig,
+    short_put_strike: f64,
+    long_put_strike: f64,
+    short_call_strike: f64,
+    long_call_strike: f64,
+    lot_size: usize,
+) -> SpreadConfig {
+    SpreadConfig {
+        base,
+        spread_type: SpreadType::IronCondor,
+        leg_configs: vec![
+            LegConfig::new(OptionType::Put, short_put_strike, -1, lot_size),
+            LegConfig::new(OptionType::Put, long_put_strike, 1, lot_size),
+            LegConfig::new(OptionType::Call, short_call_strike, -1, lot_size),
+            LegConfig::new(OptionType::Call, long_call_strike, 1, lot_size),
+        ],
+        ..Default::default()
+    }
+}
+
+/// Convenience function to create a vertical spread config.
+pub fn create_vertical_spread_config(
+    base: BacktestConfig,
+    option_type: OptionType,
+    long_strike: f64,
+    short_strike: f64,
+    lot_size: usize,
+) -> SpreadConfig {
+    let spread_type = match option_type {
+        OptionType::Call => SpreadType::VerticalCall,
+        OptionType::Put => SpreadType::VerticalPut,
+    };
+
+    SpreadConfig {
+        base,
+        spread_type,
+        leg_configs: vec![
+            LegConfig::new(option_type, long_strike, 1, lot_size),
+            LegConfig::new(option_type, short_strike, -1, lot_size),
+        ],
+        ..Default::default()
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+    use crate::core::types::StopConfig;
+    use crate::core::types::TargetConfig;
+
+    fn sample_data() -> (Vec<i64>, Vec<f64>, Vec<Vec<f64>>, Vec<bool>, Vec<bool>) {
+        let n = 20;
+        let timestamps: Vec<i64> = (0..n as i64).collect();
+        let underlying: Vec<f64> = (100..120).map(|x| x as f64).collect();
+
+        // Call and Put premiums
+        let call_premiums: Vec<f64> = (0..n).map(|i| 5.0 + (i as f64 * 0.2)).collect();
+        let put_premiums: Vec<f64> = (0..n).map(|i| 5.0 - (i as f64 * 0.1)).collect();
+
+        let legs_premiums = vec![call_premiums, put_premiums];
+
+        let entries = vec![
+            false, true, false, false, false, false, false, false, false, false, false, false,
+            false, false, false, false, false, false, false, false,
+        ];
+        let exits = vec![
+            false, false, false, false, false, false, false, false, false, true, false, false,
+            false, false, false, false, false, false, false, false,
+        ];
+
+        (timestamps, underlying, legs_premiums, entries, exits)
+    }
+
+    #[test]
+    fn test_straddle_backtest() {
+        let base_config = BacktestConfig {
+            initial_capital: 100_000.0,
+            fees: 0.001,
+            slippage: 0.0,
+            stop: StopConfig::None,
+            target: TargetConfig::None,
+            upon_bar_close: true,
+        };
+
+        let config = create_straddle_config(base_config, 100.0, 50, true);
+        let backtest = SpreadBacktest::new(config);
+
+        let (timestamps, underlying, legs_premiums, entries, exits) = sample_data();
+
+        let result = backtest.run(&timestamps, &underlying, &legs_premiums, &entries, &exits);
+
+        assert_eq!(result.trades.len(), 1);
+        assert!(result.equity_curve.len() == timestamps.len());
+    }
+
+    #[test]
+    fn test_iron_condor_backtest() {
+        let base_config = BacktestConfig::default();
+
+        let config = create_iron_condor_config(
+            base_config,
+            95.0,  // short put
+            90.0,  // long put
+            105.0, // short call
+            110.0, // long call
+            50,
+        );
+
+        let backtest = SpreadBacktest::new(config);
+
+        let n = 20;
+        let timestamps: Vec<i64> = (0..n as i64).collect();
+        let underlying: Vec<f64> = vec![100.0; n];
+
+        // Four legs: short put, long put, short call, long call
+        let legs_premiums = vec![
+            vec![3.0; n], // short put
+            vec![1.5; n], // long put
+            vec![3.0; n], // short call
+            vec![1.5; n], // long call
+        ];
+
+        let mut entries = vec![false; n];
+        entries[1] = true;
+
+        let mut exits = vec![false; n];
+        exits[15] = true;
+
+        let result = backtest.run(&timestamps, &underlying, &legs_premiums, &entries, &exits);
+
+        assert_eq!(result.trades.len(), 1);
+    }
+}

uv.lock

@@ -4,5 +4,5 @@ requires-python = ">=3.10"
 
 [[package]]
 name = "raptorbt"
-version = "0.1.0"
+version = "0.2.0"
 source = { editable = "." }