Aave cash management (#1136)

- Create shortcut functions to manage lending based strategies
tradingstrategy-ai · Jan 17, 2025 · 96b4531 · 96b4531
1 parent 98d3c4f
commit 96b4531
Show file tree

Hide file tree

Showing 77 changed files with 912 additions and 259 deletions.
diff --git a/notebooks/momentum/defi-bluechip-momentum.ipynb b/notebooks/momentum/defi-bluechip-momentum.ipynb
@@ -238,7 +238,7 @@
     "    # Calculate how much dollar value we want each individual position to be on this strategy cycle,\n",
     "    # based on our total available equity\n",
     "    portfolio = position_manager.get_current_portfolio()\n",
-    "    portfolio_target_value = portfolio.get_total_equity() * value_allocated_to_positions\n",
+    "    portfolio_target_value = portfolio.calculate_total_equity() * value_allocated_to_positions\n",
     "    alpha_model.calculate_target_positions(position_manager, portfolio_target_value)\n",
     "\n",
     "    # Shift portfolio from current positions to target positions\n",

diff --git a/notebooks/rsi-momentum/matic-eth-usdc/v33-matic-eth-initial.ipynb b/notebooks/rsi-momentum/matic-eth-usdc/v33-matic-eth-initial.ipynb
diff --git a/notebooks/rsi-momentum/v10-grid-search-candle-shift-robustness-check.ipynb b/notebooks/rsi-momentum/v10-grid-search-candle-shift-robustness-check.ipynb
diff --git a/notebooks/rsi-momentum/v11-compare-candle-shift-results.ipynb b/notebooks/rsi-momentum/v11-compare-candle-shift-results.ipynb
diff --git a/notebooks/rsi-momentum/v12-small-timeframe.ipynb b/notebooks/rsi-momentum/v12-small-timeframe.ipynb
diff --git a/notebooks/rsi-momentum/v14-small-timeframe-stop-loss-tests.ipynb b/notebooks/rsi-momentum/v14-small-timeframe-stop-loss-tests.ipynb
diff --git a/notebooks/rsi-momentum/v15-small-timeframe-grid-search-candle-shift-robustness-check.ipynb b/notebooks/rsi-momentum/v15-small-timeframe-grid-search-candle-shift-robustness-check.ipynb
diff --git a/notebooks/rsi-momentum/v16-small-timeframe-grid-shifted.ipynb b/notebooks/rsi-momentum/v16-small-timeframe-grid-shifted.ipynb
diff --git a/notebooks/rsi-momentum/v19-new-style-grid-search.ipynb b/notebooks/rsi-momentum/v19-new-style-grid-search.ipynb
diff --git a/notebooks/rsi-momentum/v20-new-style-backtest-shifted-candles.ipynb b/notebooks/rsi-momentum/v20-new-style-backtest-shifted-candles.ipynb
diff --git a/notebooks/rsi-momentum/v21-shifted-candle-grid-search.ipynb b/notebooks/rsi-momentum/v21-shifted-candle-grid-search.ipynb
diff --git a/notebooks/rsi-momentum/v22-new-style-backtest-shifted-candles-8h-grid.ipynb b/notebooks/rsi-momentum/v22-new-style-backtest-shifted-candles-8h-grid.ipynb
diff --git a/notebooks/rsi-momentum/v23-grid-search-rebalance-criteria.ipynb b/notebooks/rsi-momentum/v23-grid-search-rebalance-criteria.ipynb
diff --git a/notebooks/rsi-momentum/v24-grid-search-stop-loss-rebalanced.ipynb b/notebooks/rsi-momentum/v24-grid-search-stop-loss-rebalanced.ipynb
diff --git a/notebooks/rsi-momentum/v27-momentum-factor-bug-fix.ipynb b/notebooks/rsi-momentum/v27-momentum-factor-bug-fix.ipynb
diff --git a/notebooks/rsi-momentum/v28-grid-search-stop-loss-rebalanced-bug-fix.ipynb b/notebooks/rsi-momentum/v28-grid-search-stop-loss-rebalanced-bug-fix.ipynb
diff --git a/notebooks/rsi-momentum/v29-trading-fee-increased.ipynb b/notebooks/rsi-momentum/v29-trading-fee-increased.ipynb
diff --git a/strategies/base-memex.py b/strategies/base-memex.py
@@ -306,7 +306,7 @@ def decide_trades(
     # Calculate how much dollar value we want each individual position to be on this strategy cycle,
     # based on our total available equity
     portfolio = position_manager.get_current_portfolio()
-    portfolio_target_value = portfolio.get_total_equity() * parameters.allocation
+    portfolio_target_value = portfolio.calculate_total_equity() * parameters.allocation - position_manager.get_pending_redemptions()
 
     # Select max_assets_in_portfolio assets in which we are going to invest
     # Calculate a weight for ecah asset in the portfolio using 1/N method based on the raw signal
@@ -385,7 +385,7 @@ def decide_trades(
         Pairs meeting volatility inclusion criteria: {volatility_included_pair_count}        
         Pairs meeting TVL inclusion criteria: {tvl_included_pair_count}        
         Signals created: {signal_count}
-        Total equity: {portfolio.get_total_equity():,.2f} USD
+        Total equity: {portfolio.calculate_total_equity():,.2f} USD
         Cash: {position_manager.get_current_cash():,.2f} USD
         Redemption queue: {position_manager.get_pending_redemptions():,.2f} USD
         Investable equity: {alpha_model.investable_equity:,.2f} USD

diff --git a/strategies/eth-btc-usdc-credit.py b/strategies/eth-btc-usdc-credit.py
@@ -329,7 +329,7 @@ def decide_trades(
     alpha_model.normalise_weights()
     alpha_model.update_old_weights(state.portfolio, portfolio_pairs=volatile_pairs)
     portfolio = position_manager.get_current_portfolio()
-    portfolio_target_value = portfolio.get_total_equity() * parameters.allocation
+    portfolio_target_value = portfolio.calculate_total_equity() * parameters.allocation
     alpha_model.calculate_target_positions(position_manager, portfolio_target_value)
 
     trades = []
@@ -339,7 +339,7 @@ def decide_trades(
     #
     rebalance_trades = alpha_model.generate_rebalance_trades_and_triggers(
         position_manager,
-        min_trade_threshold=parameters.rebalance_threshold * portfolio.get_total_equity(),
+        min_trade_threshold=parameters.rebalance_threshold * portfolio.calculate_total_equity(),
     )
 
     if len(rebalance_trades) > 0:

diff --git a/strategies/eth-btc-usdc-low-fee.py b/strategies/eth-btc-usdc-low-fee.py
@@ -273,11 +273,11 @@ def decide_trades(
     alpha_model.normalise_weights()
     alpha_model.update_old_weights(state.portfolio)
     portfolio = position_manager.get_current_portfolio()
-    portfolio_target_value = portfolio.get_total_equity() * parameters.allocation
+    portfolio_target_value = portfolio.calculate_total_equity() * parameters.allocation
     alpha_model.calculate_target_positions(position_manager, portfolio_target_value)
     trades = alpha_model.generate_rebalance_trades_and_triggers(
         position_manager,
-        min_trade_threshold=parameters.rebalance_threshold * portfolio.get_total_equity(),
+        min_trade_threshold=parameters.rebalance_threshold * portfolio.calculate_total_equity(),
     )
 
     #

diff --git a/strategies/eth-btc-usdc-size-risk.py b/strategies/eth-btc-usdc-size-risk.py
@@ -273,7 +273,7 @@ def decide_trades(
     # Calculate how much dollar value we want each individual position to be on this strategy cycle,
     # based on our total available equity
     portfolio = position_manager.get_current_portfolio()
-    portfolio_target_value = portfolio.get_total_equity() * parameters.allocation
+    portfolio_target_value = portfolio.calculate_total_equity() * parameters.allocation
 
     #
     # Do 1/N weighting

diff --git a/strategies/eth-btc-usdc.py b/strategies/eth-btc-usdc.py
@@ -334,11 +334,11 @@ def decide_trades(
     alpha_model.normalise_weights()
     alpha_model.update_old_weights(state.portfolio)
     portfolio = position_manager.get_current_portfolio()
-    portfolio_target_value = portfolio.get_total_equity() * parameters.allocation
+    portfolio_target_value = portfolio.calculate_total_equity() * parameters.allocation
     alpha_model.calculate_target_positions(position_manager, portfolio_target_value)
     trades = alpha_model.generate_rebalance_trades_and_triggers(
         position_manager,
-        min_trade_threshold=parameters.rebalance_threshold * portfolio.get_total_equity(),
+        min_trade_threshold=parameters.rebalance_threshold * portfolio.calculate_total_equity(),
     )
 
     #

diff --git a/strategies/matic-eth-usdc.py b/strategies/matic-eth-usdc.py
@@ -266,11 +266,11 @@ def decide_trades(
     alpha_model.normalise_weights()
     alpha_model.update_old_weights(state.portfolio)
     portfolio = position_manager.get_current_portfolio()
-    portfolio_target_value = portfolio.get_total_equity() * parameters.allocation
+    portfolio_target_value = portfolio.calculate_total_equity() * parameters.allocation
     alpha_model.calculate_target_positions(position_manager, portfolio_target_value)
     trades = alpha_model.generate_rebalance_trades_and_triggers(
         position_manager,
-        min_trade_threshold=parameters.rebalance_threshold * portfolio.get_total_equity(),
+        min_trade_threshold=parameters.rebalance_threshold * portfolio.calculate_total_equity(),
     )
 
     #

diff --git a/strategies/pancake-momentum-v2.py b/strategies/pancake-momentum-v2.py
@@ -286,7 +286,7 @@ def decide_trades(
     weights = normalise_weights(weight_by_1_slash_n(alpha_signals))
 
     portfolio = position_manager.get_current_portfolio()
-    portfolio_target_value = portfolio.get_total_equity() * value_allocated_to_positions
+    portfolio_target_value = portfolio.calculate_total_equity() * value_allocated_to_positions
 
     # Shift portfolio from current positions to target positions
     # determined by the alpha signals (momentum)

diff --git a/strategies/spot-and-short-momentum-4.py b/strategies/spot-and-short-momentum-4.py
@@ -158,7 +158,7 @@ def decide_trades(
     # Calculate how much dollar value we want each individual position to be on this strategy cycle,
     # based on our total available equity
     portfolio = position_manager.get_current_portfolio()
-    portfolio_target_value = portfolio.get_total_equity() * value_allocated_to_positions
+    portfolio_target_value = portfolio.calculate_total_equity() * value_allocated_to_positions
     alpha_model.calculate_target_positions(position_manager, portfolio_target_value)
 
     signal_df = format_signals(alpha_model)

diff --git a/strategies/spot-and-short-momentum-grid-3.py b/strategies/spot-and-short-momentum-grid-3.py
@@ -171,7 +171,7 @@ def decide_trades(
         # Calculate how much dollar value we want each individual position to be on this strategy cycle,
         # based on our total available equity
         portfolio = position_manager.get_current_portfolio()
-        portfolio_target_value = portfolio.get_total_equity() * value_allocated_to_positions
+        portfolio_target_value = portfolio.calculate_total_equity() * value_allocated_to_positions
         alpha_model.calculate_target_positions(position_manager, portfolio_target_value)
 
         signal_df = format_signals(alpha_model)

diff --git a/strategies/spot-and-short-momentum-grid.py b/strategies/spot-and-short-momentum-grid.py
@@ -171,7 +171,7 @@ def decide_trades(
         # Calculate how much dollar value we want each individual position to be on this strategy cycle,
         # based on our total available equity
         portfolio = position_manager.get_current_portfolio()
-        portfolio_target_value = portfolio.get_total_equity() * value_allocated_to_positions
+        portfolio_target_value = portfolio.calculate_total_equity() * value_allocated_to_positions
         alpha_model.calculate_target_positions(position_manager, portfolio_target_value)
 
         signal_df = format_signals(alpha_model)

diff --git a/strategies/spot-and-short-momentum-tuned.py b/strategies/spot-and-short-momentum-tuned.py
@@ -157,7 +157,7 @@ def decide_trades(
     # Calculate how much dollar value we want each individual position to be on this strategy cycle,
     # based on our total available equity
     portfolio = position_manager.get_current_portfolio()
-    portfolio_target_value = portfolio.get_total_equity() * value_allocated_to_positions
+    portfolio_target_value = portfolio.calculate_total_equity() * value_allocated_to_positions
     alpha_model.calculate_target_positions(position_manager, portfolio_target_value)
 
     signal_df = format_signals(alpha_model)

diff --git a/strategies/spot-and-short-momentum.py b/strategies/spot-and-short-momentum.py
@@ -157,7 +157,7 @@ def decide_trades(
     # Calculate how much dollar value we want each individual position to be on this strategy cycle,
     # based on our total available equity
     portfolio = position_manager.get_current_portfolio()
-    portfolio_target_value = portfolio.get_total_equity() * value_allocated_to_positions
+    portfolio_target_value = portfolio.calculate_total_equity() * value_allocated_to_positions
     alpha_model.calculate_target_positions(position_manager, portfolio_target_value)
 
     signal_df = format_signals(alpha_model)

diff --git a/strategies/test_only/base-memecoin-index.py b/strategies/test_only/base-memecoin-index.py
@@ -311,7 +311,7 @@ def decide_trades(
     # Calculate how much dollar value we want each individual position to be on this strategy cycle,
     # based on our total available equity
     portfolio = position_manager.get_current_portfolio()
-    portfolio_target_value = portfolio.get_total_equity() * parameters.allocation
+    portfolio_target_value = portfolio.calculate_total_equity() * parameters.allocation
 
     # Select max_assets_in_portfolio assets in which we are going to invest
     # Calculate a weight for ecah asset in the portfolio using 1/N method based on the raw signal
@@ -392,7 +392,7 @@ def decide_trades(
         - meeting volatility inclusion criteria: {volatility_included_pair_count}        
         - meeting TVL inclusion criteria: {tvl_included_pair_count}        
         Signals created: {signal_count}
-        Total equity: {portfolio.get_total_equity():,.2f} USD
+        Total equity: {portfolio.calculate_total_equity():,.2f} USD
         Cash: {position_manager.get_current_cash():,.2f} USD
         Investable equity: {alpha_model.investable_equity:,.2f} USD
         Accepted investable equity: {alpha_model.accepted_investable_equity:,.2f} USD

diff --git a/strategies/test_only/defi-bluechip-momentum-trailing-sl.py b/strategies/test_only/defi-bluechip-momentum-trailing-sl.py
@@ -156,7 +156,7 @@ def decide_trades(
     # Calculate how much dollar value we want each individual position to be on this strategy cycle,
     # based on our total available equity
     portfolio = position_manager.get_current_portfolio()
-    portfolio_target_value = portfolio.get_total_equity() * value_allocated_to_positions
+    portfolio_target_value = portfolio.calculate_total_equity() * value_allocated_to_positions
     alpha_model.calculate_target_positions(position_manager, portfolio_target_value)
 
     # Shift portfolio from current positions to target positions

diff --git a/strategies/test_only/defi-bluechip-momentum.py b/strategies/test_only/defi-bluechip-momentum.py
@@ -160,7 +160,7 @@ def decide_trades(
     # Calculate how much dollar value we want each individual position to be on this strategy cycle,
     # based on our total available equity
     portfolio = position_manager.get_current_portfolio()
-    portfolio_target_value = portfolio.get_total_equity() * value_allocated_to_positions
+    portfolio_target_value = portfolio.calculate_total_equity() * value_allocated_to_positions
     alpha_model.calculate_target_positions(position_manager, portfolio_target_value)
 
     # Added for tests

diff --git a/strategies/test_only/enzyme-polygon-eth-btc-rsi.py b/strategies/test_only/enzyme-polygon-eth-btc-rsi.py
@@ -347,7 +347,7 @@ def decide_trades(
     #
 
     portfolio = position_manager.get_current_portfolio()
-    portfolio_target_value = portfolio.get_total_equity() * parameters.allocation
+    portfolio_target_value = portfolio.calculate_total_equity() * parameters.allocation
 
     # Use alpha model and construct a portfolio of two assets
     alpha_model.select_top_signals(2)
@@ -385,15 +385,15 @@ def decide_trades(
     #
     trades += alpha_model.generate_rebalance_trades_and_triggers(
         position_manager,
-        min_trade_threshold=parameters.rebalance_threshold * portfolio.get_total_equity(),
+        min_trade_threshold=parameters.rebalance_threshold * portfolio.calculate_total_equity(),
     )
 
     if len(trades) == 0 and alpha_model.has_any_signal():
         # Be noisy if our risk parameters are too tight
         # and we starting to lose positions because of it
         position_manager.log(
             f"Generated zero trades even though trade signals: {list(alpha_model.signals.values())}\n" +
-            f"Total equity: {portfolio.get_total_equity()}\n" +
+            f"Total equity: {portfolio.calculate_total_equity()}\n" +
             f"Rebalance threshold: {parameters.rebalance_threshold}\n",
             level=logging.WARNING,
         )

diff --git a/strategies/test_only/ethereum-memecoin-vol-basket.py b/strategies/test_only/ethereum-memecoin-vol-basket.py
@@ -257,7 +257,7 @@ def decide_trades(
     # Calculate how much dollar value we want each individual position to be on this strategy cycle,
     # based on our total available equity
     portfolio = position_manager.get_current_portfolio()
-    portfolio_target_value = portfolio.get_total_equity() * parameters.allocation
+    portfolio_target_value = portfolio.calculate_total_equity() * parameters.allocation
 
     #
     # Do 1/N weighting

diff --git a/strategies/test_only/memecoin_index.py b/strategies/test_only/memecoin_index.py
@@ -292,7 +292,7 @@ def decide_trades(
     # Calculate how much dollar value we want each individual position to be on this strategy cycle,
     # based on our total available equity
     portfolio = position_manager.get_current_portfolio()
-    portfolio_target_value = portfolio.get_total_equity() * parameters.allocation
+    portfolio_target_value = portfolio.calculate_total_equity() * parameters.allocation
 
     # Select max_assets_in_portfolio assets in which we are going to invest
     # Calculate a weight for ecah asset in the portfolio using 1/N method based on the raw signal
@@ -359,7 +359,7 @@ def decide_trades(
         Pairs total: {strategy_universe.data_universe.pairs.get_count()}
         Pairs meeting volume inclusion criteria: {len(volume_inclusion_criteria_pairs)}
         Signals created: {signal_count}
-        Total equity: {portfolio.get_total_equity():,.2f} USD
+        Total equity: {portfolio.calculate_total_equity():,.2f} USD
         Cash: {position_manager.get_current_cash():,.2f} USD
         Investable equity: {alpha_model.investable_equity:,.2f} USD
         Accepted investable equity: {alpha_model.accepted_investable_equity:,.2f} USD

diff --git a/strategies/test_only/pancake-momentum-weekly.py b/strategies/test_only/pancake-momentum-weekly.py
@@ -298,7 +298,7 @@ def decide_trades(
     # Calculate how much dollar value we want each individual position to be on this strategy cycle,
     # based on our total available equity
     portfolio = position_manager.get_current_portfolio()
-    portfolio_target_value = portfolio.get_total_equity() * value_allocated_to_positions
+    portfolio_target_value = portfolio.calculate_total_equity() * value_allocated_to_positions
     alpha_model.calculate_target_positions(position_manager, portfolio_target_value)
 
     # Shift portfolio from current positions to target positions

diff --git a/strategies/test_only/pancakeswap_v2_main_loop.py b/strategies/test_only/pancakeswap_v2_main_loop.py
@@ -186,7 +186,7 @@ def __call__(self, ts: pd.Timestamp, universe: Universe, state: State, debug_det
         # but we also have a minimum liquidity floor related to our portfolio size.
         # With high value portfolio, we will no longer invest in tokens with less liquidity.
         # TODO: Fix QSTrader to pass this information directly.
-        portflio_value = state.portfolio.get_total_equity()
+        portflio_value = state.portfolio.calculate_total_equity()
         liquidity_threshold = max(min_liquidity_threshold, portflio_value * portfolio_base_liquidity_threshold)
 
         # Expose how many candles we evaluated to the testing