update

vbt-snippets.md

@@ -1,5 +1,5 @@
 - [DEBUGGING](#debugging)
-- [FETCHING DATA](#fetching-data)
+- [Fetching Data](#fetching-data)
   - [REINDEX to main session](#reindex-to-main-session)
   - [Smart indexing](#smart-indexing)
   - [Data manipulation](#data-manipulation)
@@ -9,7 +9,7 @@
 - [RESAMPLING](#resampling)
   - [config](#config)
 - [REALIGN](#realign)
-  - [REALIGN\_CLOSING accessors](#realign_closing-accessors)
+  - [REALIGN\_CLOSING accessors](#realignclosing-accessors)
 - [SIGNALS](#signals)
   - [Comparing](#comparing)
   - [GENERATE SIGNALS IRERATIVELY (numba)](#generate-signals-ireratively-numba)
@@ -28,11 +28,11 @@
 - [Stoploss/Takeprofit](#stoplosstakeprofit)
   - [SL - ATR based](#sl---atr-based)
   - [EXIT after time](#exit-after-time)
-  - [CALLBACKS -](#callbacks--)
+  - [CALLBACKS -](#callbacks)
     - [MEMORY](#memory)
 - [Portfolio](#portfolio)
   - [from signals](#from-signals)
-  - [CALLBACKS](#callbacks)
+  - [CALLBACKS](#callbacks-1)
     - [Access running total return from sim](#access-running-total-return-from-sim)
     - [Staticization](#staticization)
   - [Grouping](#grouping)
@@ -41,6 +41,15 @@
     - [PnL by hour of the day (BOXPLOT)](#pnl-by-hour-of-the-day-boxplot)
   - [PF resampling](#pf-resampling)
   - [PF Plotting](#pf-plotting)
+  - [Key Portfolio Analysis Methods \& Properties](#key-portfolio-analysis-methods--properties)
+    - [1. **Basic Portfolio Metrics**](#1-basic-portfolio-metrics)
+    - [2. **Comprehensive Stats Method**](#2-comprehensive-stats-method)
+    - [3. **Trade Analysis**](#3-trade-analysis)
+    - [4. **Drawdown Analysis**](#4-drawdown-analysis)
+    - [5. **Order Analysis**](#5-order-analysis)
+    - [6. **Custom Metrics**](#6-custom-metrics)
+    - [7. **Visualization Methods**](#7-visualization-methods)
+    - [8. **Advanced Analysis Examples**](#8-advanced-analysis-examples)
   - [Entries/exits visual analysis](#entriesexits-visual-analysis)
   - [Configuration](#configuration)
 - [Optimalization](#optimalization)
@@ -104,7 +113,7 @@ ollCov.run(ts1, ts2, [2, 3], some_arg="some_value")
 ```
 
 
-# FETCHING DATA  
+# Fetching Data
 ```python
  #fetching from remote db
 from lib.db import Connection
@@ -984,6 +993,150 @@ pf.trades.plot_expanding_mfe_returns().show() #expanding mea/mfe returns
 ```
 [Plot Edge ratio](http://5.161.179.223:8000/static/js/vbt/features/analysis/index.html#edge-ratio) `pf.trades.plot_running_edge_ratio()`
 
+
+I'll research VectorBT PRO's portfolio analysis capabilities for you. Let me search for information about analyzing Portfolio objects, particularly those created by `Portfolio.from_signal`.Let me search for the correct Portfolio creation methods and analysis capabilities:Now let me search specifically for Portfolio analysis methods and attributes:Let me search for more specific information about Portfolio methods and examples:Let me search for specific Portfolio methods that provide analysis capabilities:Now let me find information about the Portfolio.from_signals method:Let me run some code to test the Portfolio analysis capabilities:Let me search for more specific Portfolio analysis examples and metrics:Based on my research of VectorBT PRO's Portfolio analysis capabilities, here's a comprehensive overview of how to analyze Portfolio objects (including those created by `Portfolio.from_signals`):
+
+## Key Portfolio Analysis Methods & Properties
+
+### 1. **Basic Portfolio Metrics**
+The Portfolio object provides numerous built-in properties for analysis:
+
+- **Returns & Performance:**
+  - `pf.returns` - Portfolio returns time series
+  - `pf.total_return` - Total return percentage
+  - `pf.annualized_return` - Annualized return
+  - `pf.cumulative_returns` - Cumulative returns time series
+
+- **Risk Metrics:**
+  - `pf.sharpe_ratio` - Sharpe ratio
+  - `pf.sortino_ratio` - Sortino ratio
+  - `pf.max_drawdown` - Maximum drawdown
+  - `pf.annualized_volatility` - Annualized volatility
+  - `pf.value_at_risk` - Value at Risk
+  - `pf.cond_value_at_risk` - Conditional Value at Risk
+
+- **Portfolio Value & Cash:**
+  - `pf.value` - Portfolio value time series
+  - `pf.final_value` - Final portfolio value
+  - `pf.cash` - Cash holdings over time
+  - `pf.asset_value` - Asset value over time
+
+### 2. **Comprehensive Stats Method**
+The most powerful analysis tool is the `stats()` method:
+
+```python
+# Get default statistics
+pf.stats()
+
+# Get specific metrics
+pf.stats(['total_return', 'sharpe_ratio', 'max_dd', 'total_trades'])
+
+# Get all available metrics
+pf.stats('all')
+```
+
+**Common metric names for `stats()`:**
+- `'total_return'` - Total return percentage
+- `'total_trades'` - Number of trades
+- `'win_rate'` - Winning trade percentage
+- `'sharpe_ratio'` - Sharpe ratio
+- `'sortino_ratio'` - Sortino ratio
+- `'max_dd'` - Maximum drawdown (note: `max_dd`, not `max_drawdown`)
+- `'calmar_ratio'` - Calmar ratio
+- `'omega_ratio'` - Omega ratio
+- `'expectancy'` - Expected value per trade
+- `'profit_factor'` - Profit factor
+- `'best_trade'` - Best trade return
+- `'worst_trade'` - Worst trade return
+- `'avg_winning_trade'` - Average winning trade
+- `'avg_losing_trade'` - Average losing trade
+
+### 3. **Trade Analysis**
+Access detailed trade information through the `trades` property:
+
+```python
+# Trade statistics
+pf.trades.stats()
+pf.trades.count()  # Total number of trades
+pf.trades.win_rate  # Win rate
+pf.trades.profit_factor  # Profit factor
+
+# Direction-specific analysis
+pf.trades.direction_long.count()  # Number of long trades
+pf.trades.direction_short.count()  # Number of short trades
+pf.trades.direction_long.pnl.sum()  # Total long P&L
+pf.trades.direction_short.pnl.sum()  # Total short P&L
+
+# Trade records
+pf.trades.records_readable  # Human-readable trade records
+pf.trade_history  # Detailed trade history DataFrame
+```
+
+### 4. **Drawdown Analysis**
+Analyze drawdowns using the `drawdowns` property:
+
+```python
+pf.drawdowns.stats()  # Drawdown statistics
+pf.drawdowns.max_duration  # Maximum drawdown duration
+pf.drawdown  # Drawdown time series
+```
+
+### 5. **Order Analysis**
+Examine order execution details:
+
+```python
+pf.orders.stats()  # Order statistics
+pf.orders.records_readable  # Human-readable order records
+```
+
+### 6. **Custom Metrics**
+You can add custom metrics to the Portfolio class:
+
+```python
+# Add custom metrics
+vbt.Portfolio.metrics["skew"] = dict(title="Skew", calc_func="returns.skew")
+vbt.Portfolio.metrics["kurtosis"] = dict(title="Kurtosis", calc_func="returns.kurtosis")
+
+# Then use in stats
+pf.stats(['skew', 'kurtosis'])
+```
+
+### 7. **Visualization Methods**
+Portfolio objects have built-in plotting capabilities:
+
+```python
+pf.plot()  # Default portfolio plot
+pf.plot_value()  # Portfolio value over time
+pf.plot_cumulative_returns()  # Cumulative returns
+pf.plot_drawdowns()  # Drawdown plot
+pf.plot_underwater()  # Underwater plot
+pf.trades.plot()  # Trade analysis plots
+```
+
+### 8. **Advanced Analysis Examples**
+
+**Multi-parameter analysis:**
+```python
+# Combine multiple metrics into DataFrame
+metrics = [
+    pf.total_return,
+    pf.trades.win_rate, 
+    pf.sharpe_ratio,
+    pf.max_drawdown,
+    pf.trades.count()
+]
+keys = ['total_return', 'win_rate', 'sharpe_ratio', 'max_drawdown', 'trade_count']
+combined_stats = pd.concat(metrics, axis=1, keys=keys)
+```
+
+**Performance optimization:**
+- Use `save_returns=True` in `Portfolio.from_signals()` to pre-calculate returns and speed up metric calculations
+- Enable caching for repeated analysis
+
+This comprehensive analysis framework allows you to thoroughly evaluate portfolio performance from multiple angles - returns, risk, trade efficiency, and drawdown characteristics.
+
+Would you like me to help you implement any specific analysis workflow, or do you have questions about particular metrics or methods?
+
 ## Entries/exits visual analysis
 
 ```python
@@ -1471,3 +1624,4 @@ nyse = get_calendar('NYSE')
 # Create a CustomBusinessDay object using the NYSE trading calendar
 custom_bd = CustomBusinessDay(holidays=nyse.holidays().holidays, weekmask=nyse.weekmask, calendar=nyse)
 ```
+