feat: add slippage field to Order model and DB

- Add slippage column to domain Order model (init, to_dict, from_dict)
- Add slippage column to SQLOrder infrastructure model (SqliteDecimal)
- Compute and store slippage in backtest_trade_order_evaluator (BUY/SELL)
- Compute and store slippage in vector_backtest_service (all 4 Order sites)
- Serialize slippage to backtest report JSON
- Add Slippage column to orders table in dashboard JS

Author: MDUYN

investing_algorithm_framework/app/reporting/backtest_report.py

@@ -585,6 +585,9 @@ def _build_run_data(self):
                         o_fee_rate = getattr(
                             o, 'order_fee_rate', 0
                         ) or 0
+                        o_slippage = getattr(o, 'slippage', None)
+                        if o_slippage is None:
+                            o_slippage = 0
                         orders_list.append({
                             'sym': getattr(o, 'target_symbol', '')
                             or '',
@@ -611,6 +614,9 @@ def _build_run_data(self):
                             'fee_rate': round(
                                 float(o_fee_rate), 4
                             ),
+                            'slippage': round(
+                                float(o_slippage), 4
+                            ),
                             'created': _fmt_date(o_dt)
                             if o_dt else '',
                             'updated': _fmt_date(u_dt)

investing_algorithm_framework/app/reporting/templates/dashboard.js

@@ -6074,6 +6074,7 @@ var ordersHeaders = [
   {key: 'cost', label: 'Cost', align: 'right'},
   {key: 'fee', label: 'Fee', align: 'right'},
   {key: 'fee_rate', label: 'Fee Rate', align: 'right'},
+  {key: 'slippage', label: 'Slippage', align: 'right'},
   {key: 'created', label: 'Created'},
   {key: 'updated', label: 'Updated'},
 ];

investing_algorithm_framework/domain/models/order/order.py

@@ -40,6 +40,7 @@ def __init__(
         order_fee=None,
         order_fee_currency=None,
         order_fee_rate=None,
+        slippage=None,
         id=None,
         metadata=None,
     ):
@@ -84,6 +85,7 @@ def __init__(
         self.order_fee = order_fee
         self.order_fee_currency = order_fee_currency
         self.order_fee_rate = order_fee_rate
+        self.slippage = slippage
         self.id = id
         self.cost = cost
         self.metadata = metadata if metadata is not None else {}
@@ -260,6 +262,7 @@ def ensure_iso(value):
             "order_fee_currency": self.order_fee_currency,
             "order_fee_rate": self.order_fee_rate,
             "order_fee": self.order_fee,
+            "slippage": self.slippage,
             "metadata": self.metadata if hasattr(self, 'metadata') else {},
         }
 
@@ -301,6 +304,7 @@ def from_dict(data: dict):
             order_fee=data.get("order_fee", None),
             order_fee_currency=data.get("order_fee_currency", None),
             order_fee_rate=data.get("order_fee_rate", None),
+            slippage=data.get("slippage", None),
             metadata=data.get("metadata", {}),
         )
         return order

investing_algorithm_framework/infrastructure/models/order/order.py

@@ -50,6 +50,7 @@ class SQLOrder(Order, SQLBaseModel, SQLAlchemyModelExtension):
     order_fee = Column(SqliteDecimal(), default=None)
     order_fee_currency = Column(String, default=None)
     order_fee_rate = Column(SqliteDecimal(), default=None)
+    slippage = Column(SqliteDecimal(), default=None)
     sell_order_metadata_id = Column(Integer, ForeignKey('orders.id'))
     trade_allocations = relationship(
         'SQLTradeAllocation', back_populates='order'

investing_algorithm_framework/infrastructure/services/backtesting/vector_backtest_service.py

@@ -269,6 +269,7 @@ def _close_trade(sym, sym_data, price, date):
                 order_fee=sell_fee,
                 order_fee_rate=tc.fee_percentage / 100
                 if tc.fee_percentage else None,
+                slippage=price - sell_fill,
             )
             orders.append(sell_order)
             trade_orders = lt.orders
@@ -306,6 +307,7 @@ def _close_trade(sym, sym_data, price, date):
                         order_fee=ot_sell_fee,
                         order_fee_rate=tc.fee_percentage / 100
                         if tc.fee_percentage else None,
+                        slippage=price - sell_fill,
                     )
                     orders.append(sell_o)
                     ot_orders = ot.orders
@@ -363,6 +365,7 @@ def _open_trade(sym, sym_data, price, date, capital):
                 order_fee=buy_fee,
                 order_fee_rate=tc.fee_percentage / 100
                 if tc.fee_percentage else None,
+                slippage=fill_price - price,
             )
             orders.append(buy_order)
             trade = Trade(
@@ -464,6 +467,7 @@ def _partial_close(sym, sym_data, price, date, sell_pct):
                 order_fee=sell_fee,
                 order_fee_rate=tc.fee_percentage / 100
                 if tc.fee_percentage else None,
+                slippage=price - sell_fill,
             )
             orders.append(sell_order)
             trade_orders = lt.orders

investing_algorithm_framework/services/trade_order_evaluator/backtest_trade_oder_evaluator.py

@@ -122,12 +122,14 @@ def _check_has_executed(self, order, ohlcv_df):
             if (ohlcv_data_after_order['Low'] <= order_price).any():
                 fill_price = tc.get_buy_fill_price(order_price)
                 fee = tc.get_fee(fill_price * order.amount)
+                slippage = fill_price - order_price
                 update_data = {
                     'status': OrderStatus.CLOSED.value,
                     'remaining': 0,
                     'filled': order.amount,
                     'price': fill_price,
                     'order_fee': fee,
+                    'slippage': slippage,
                 }
                 if tc.fee_percentage:
                     update_data['order_fee_rate'] = \
@@ -139,12 +141,14 @@ def _check_has_executed(self, order, ohlcv_df):
             if (ohlcv_data_after_order['High'] >= order_price).any():
                 fill_price = tc.get_sell_fill_price(order_price)
                 fee = tc.get_fee(fill_price * order.amount)
+                slippage = order_price - fill_price
                 update_data = {
                     'status': OrderStatus.CLOSED.value,
                     'remaining': 0,
                     'filled': order.amount,
                     'price': fill_price,
                     'order_fee': fee,
+                    'slippage': slippage,
                 }
                 if tc.fee_percentage:
                     update_data['order_fee_rate'] = \

tests/resources/backtest_reports_for_testing/test_algorithm_backtest/runs/backtest_EUR_20231201_20231202/run.json

@@ -1 +1 @@
-{"backtest_start_date": "2023-12-01 00:00:00", "backtest_date_range_name": null, "backtest_end_date": "2023-12-02 00:00:00", "trading_symbol": "EUR", "initial_unallocated": 1000.0, "number_of_runs": 1441, "portfolio_snapshots": [{"metadata": "MetaData()", "portfolio_id": "1", "trading_symbol": "EUR", "pending_value": 0.0, "unallocated": 1000.0, "total_net_gain": 0.0, "total_revenue": 0.0, "total_cost": 0.0, "cash_flow": 0.0, "net_size": 1000.0, "created_at": "2023-12-01T00:00:00+00:00", "total_value": 1000.0}, {"metadata": "MetaData()", "portfolio_id": "1", "trading_symbol": "EUR", "pending_value": 0.0, "unallocated": 1000.0, "total_net_gain": 0.0, "total_revenue": 0.0, "total_cost": 0.0, "cash_flow": 0.0, "net_size": 1000.0, "created_at": "2023-12-02T00:00:00+00:00", "total_value": 1000.0}], "trades": [], "orders": [], "positions": [{"symbol": "EUR", "amount": 1000.0, "cost": 1000.0, "portfolio_id": 1}], "created_at": "2026-04-15 13:13:32", "symbols": [], "number_of_days": 0, "number_of_trades": 0, "number_of_trades_closed": 0, "number_of_trades_open": 0, "number_of_orders": 0, "number_of_positions": 0, "metadata": {}, "signals": {}, "signal_events": []}
+{"backtest_start_date": "2023-12-01 00:00:00", "backtest_date_range_name": null, "backtest_end_date": "2023-12-02 00:00:00", "trading_symbol": "EUR", "initial_unallocated": 1000.0, "number_of_runs": 1441, "portfolio_snapshots": [{"metadata": "MetaData()", "portfolio_id": "1", "trading_symbol": "EUR", "pending_value": 0.0, "unallocated": 1000.0, "total_net_gain": 0.0, "total_revenue": 0.0, "total_cost": 0.0, "cash_flow": 0.0, "net_size": 1000.0, "created_at": "2023-12-01T00:00:00+00:00", "total_value": 1000.0}, {"metadata": "MetaData()", "portfolio_id": "1", "trading_symbol": "EUR", "pending_value": 0.0, "unallocated": 1000.0, "total_net_gain": 0.0, "total_revenue": 0.0, "total_cost": 0.0, "cash_flow": 0.0, "net_size": 1000.0, "created_at": "2023-12-02T00:00:00+00:00", "total_value": 1000.0}], "trades": [], "orders": [], "positions": [{"symbol": "EUR", "amount": 1000.0, "cost": 1000.0, "portfolio_id": 1}], "created_at": "2026-04-15 14:57:33", "symbols": [], "number_of_days": 0, "number_of_trades": 0, "number_of_trades_closed": 0, "number_of_trades_open": 0, "number_of_orders": 0, "number_of_positions": 0, "metadata": {}, "signals": {}, "signal_events": []}

tests/resources/backtest_reports_for_testing/test_algorithm_backtest/runs/backtest_EUR_20231202_20231203/run.json

@@ -1 +1 @@
-{"backtest_start_date": "2023-12-02 00:00:00", "backtest_date_range_name": null, "backtest_end_date": "2023-12-03 00:00:00", "trading_symbol": "EUR", "initial_unallocated": 1000.0, "number_of_runs": 1441, "portfolio_snapshots": [{"metadata": "MetaData()", "portfolio_id": "1", "trading_symbol": "EUR", "pending_value": 0.0, "unallocated": 1000.0, "total_net_gain": 0.0, "total_revenue": 0.0, "total_cost": 0.0, "cash_flow": 0.0, "net_size": 1000.0, "created_at": "2023-12-02T00:00:00+00:00", "total_value": 1000.0}, {"metadata": "MetaData()", "portfolio_id": "1", "trading_symbol": "EUR", "pending_value": 0.0, "unallocated": 1000.0, "total_net_gain": 0.0, "total_revenue": 0.0, "total_cost": 0.0, "cash_flow": 0.0, "net_size": 1000.0, "created_at": "2023-12-03T00:00:00+00:00", "total_value": 1000.0}], "trades": [], "orders": [], "positions": [{"symbol": "EUR", "amount": 1000.0, "cost": 1000.0, "portfolio_id": 1}], "created_at": "2026-04-15 13:13:08", "symbols": [], "number_of_days": 0, "number_of_trades": 0, "number_of_trades_closed": 0, "number_of_trades_open": 0, "number_of_orders": 0, "number_of_positions": 0, "metadata": {}, "signals": {}, "signal_events": []}
+{"backtest_start_date": "2023-12-02 00:00:00", "backtest_date_range_name": null, "backtest_end_date": "2023-12-03 00:00:00", "trading_symbol": "EUR", "initial_unallocated": 1000.0, "number_of_runs": 1441, "portfolio_snapshots": [{"metadata": "MetaData()", "portfolio_id": "1", "trading_symbol": "EUR", "pending_value": 0.0, "unallocated": 1000.0, "total_net_gain": 0.0, "total_revenue": 0.0, "total_cost": 0.0, "cash_flow": 0.0, "net_size": 1000.0, "created_at": "2023-12-02T00:00:00+00:00", "total_value": 1000.0}, {"metadata": "MetaData()", "portfolio_id": "1", "trading_symbol": "EUR", "pending_value": 0.0, "unallocated": 1000.0, "total_net_gain": 0.0, "total_revenue": 0.0, "total_cost": 0.0, "cash_flow": 0.0, "net_size": 1000.0, "created_at": "2023-12-03T00:00:00+00:00", "total_value": 1000.0}], "trades": [], "orders": [], "positions": [{"symbol": "EUR", "amount": 1000.0, "cost": 1000.0, "portfolio_id": 1}], "created_at": "2026-04-15 14:57:08", "symbols": [], "number_of_days": 0, "number_of_trades": 0, "number_of_trades_closed": 0, "number_of_trades_open": 0, "number_of_orders": 0, "number_of_positions": 0, "metadata": {}, "signals": {}, "signal_events": []}