test: add test for balance_distribution_over_time
This commit is contained in:
Matthias
@@ -20,6 +20,7 @@ from freqtrade.data.btanalysis import (
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load_trades,
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load_trades_from_db,
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)
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from freqtrade.data.btanalysis.trade_parallelism import balance_distribution_over_time
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from freqtrade.data.history import load_data, load_pair_history
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from freqtrade.data.metrics import (
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calculate_cagr,
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@@ -649,3 +650,189 @@ def test_load_file_from_zip(tmp_path):
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with pytest.raises(ValueError, match=r"File .* not found in zip.*"):
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load_file_from_zip(zip_file, "testfile55.txt")
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@pytest.mark.parametrize("is_short", [False, True])
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def test_balance_distribution_over_time(is_short):
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"""
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Test balance_distribution_over_time for both long and short trades.
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"""
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# Create a minimal trades DataFrame with 4 trades over time
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# Base dates for trades
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start_date = dt_utc(2023, 1, 1)
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base_date = start_date + timedelta(hours=15)
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stake_currency = "USDT"
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start_balance = 1000.0
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fee = 0.001 # 0.1% fee
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# Create trades spanning different time periods
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trades_data = {
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"pair": ["BTC/USDT", "ETH/USDT", "XRP/USDT", "LTC/USDT"],
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"stake_amount": [100.0, 150.0, 80.0, 120.0],
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"open_date": [
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base_date,
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base_date + timedelta(hours=2),
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base_date + timedelta(hours=5),
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base_date + timedelta(hours=8),
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],
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"close_date": [
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base_date + timedelta(hours=3),
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base_date + timedelta(hours=6),
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base_date + timedelta(hours=9),
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base_date + timedelta(hours=12),
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],
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"open_rate": [40000.0, 2000.0, 0.5, 100.0],
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"close_rate": [41000.0, 2100.0, 0.52, 105.0],
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"fee_open": [fee, fee, fee, fee],
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"fee_close": [fee, fee, fee, fee],
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"is_short": [is_short, is_short, is_short, is_short],
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"leverage": [1.0, 1.0, 1.0, 1.0],
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"orders": [
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# Trade 1: BTC/USDT - entry at 40000, exit at 41000
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[
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{
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"amount": 0.0025, # 100 / 40000
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"filled": 0.0025,
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"safe_price": 40000.0,
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"ft_order_side": "sell" if is_short else "buy",
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"order_filled_timestamp": int(base_date.timestamp() * 1000),
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"ft_is_entry": True,
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},
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{
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"amount": 0.0025,
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"filled": 0.0025,
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"safe_price": 41000.0,
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"ft_order_side": "buy" if is_short else "sell",
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"order_filled_timestamp": int(
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(base_date + timedelta(hours=3)).timestamp() * 1000
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),
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"ft_is_entry": False,
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},
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],
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# Trade 2: ETH/USDT - entry at 2000, exit at 2100
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[
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{
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"amount": 0.075, # 150 / 2000
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"filled": 0.075,
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"safe_price": 2000.0,
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"ft_order_side": "sell" if is_short else "buy",
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"order_filled_timestamp": int(
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(base_date + timedelta(hours=2)).timestamp() * 1000
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),
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"ft_is_entry": True,
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},
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{
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"amount": 0.075,
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"filled": 0.075,
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"safe_price": 2100.0,
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"ft_order_side": "buy" if is_short else "sell",
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"order_filled_timestamp": int(
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(base_date + timedelta(hours=6)).timestamp() * 1000
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),
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"ft_is_entry": False,
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},
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],
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# Trade 3: XRP/USDT - entry at 0.5, exit at 0.52
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[
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{
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"amount": 160.0, # 80 / 0.5
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"filled": 160.0,
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"safe_price": 0.5,
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"ft_order_side": "sell" if is_short else "buy",
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"order_filled_timestamp": int(
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(base_date + timedelta(hours=5)).timestamp() * 1000
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),
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"ft_is_entry": True,
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},
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{
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"amount": 160.0,
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"filled": 160.0,
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"safe_price": 0.52,
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"ft_order_side": "buy" if is_short else "sell",
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"order_filled_timestamp": int(
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(base_date + timedelta(hours=9)).timestamp() * 1000
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),
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"ft_is_entry": False,
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},
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],
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# Trade 4: LTC/USDT - entry at 100, exit at 105
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[
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{
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"amount": 1.2, # 120 / 100
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"filled": 1.2,
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"safe_price": 100.0,
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"ft_order_side": "sell" if is_short else "buy",
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"order_filled_timestamp": int(
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(base_date + timedelta(hours=8)).timestamp() * 1000
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),
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"ft_is_entry": True,
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},
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{
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"amount": 1.2,
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"filled": 1.2,
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"safe_price": 105.0,
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"ft_order_side": "buy" if is_short else "sell",
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"order_filled_timestamp": int(
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(base_date + timedelta(hours=12)).timestamp() * 1000
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),
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"ft_is_entry": False,
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},
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],
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],
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}
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trades_df = DataFrame(trades_data)
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pairlist = ["BTC/USDT", "ETH/USDT", "XRP/USDT", "LTC/USDT"]
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min_date = start_date
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max_date = start_date + timedelta(hours=35)
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result = balance_distribution_over_time(
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trades=trades_df,
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min_date=min_date,
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max_date=max_date,
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timeframe="1h",
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stake_currency=stake_currency,
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start_balance=start_balance,
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pairlist=pairlist,
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)
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# Verify basic structure
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assert isinstance(result, DataFrame)
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assert stake_currency in result.columns
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for pair in pairlist:
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assert pair in result.columns
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# Verify the index is a DatetimeIndex
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assert isinstance(result.index, Timestamp.__class__.__bases__[0])
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# Verify we have entries over the full time period (36h)
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assert len(result) == 36
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# First trade opens 15h after the start date
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assert result.iloc[0][stake_currency] == 1000
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expected_first_balance = start_balance - (100.0 + 100.0 * fee)
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assert result.iloc[15][stake_currency] == pytest.approx(expected_first_balance)
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# Check that pair columns have non-zero values during trade periods
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# Trade 1 (BTC/USDT) is open from hour 15 to hour 18
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# At hour 16, BTC/USDT should have position
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btc_during_trade = result.loc[base_date + timedelta(hours=1), "BTC/USDT"]
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assert btc_during_trade > 0, "Trade should have positive position during open period"
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# After Trade 1 closes at hour 3, BTC/USDT position should be 0
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btc_after_close = result.loc[base_date + timedelta(hours=4) :, "BTC/USDT"]
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assert all(btc_after_close == 0), "Position should be 0 after trade closes"
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# Final stake currency should reflect all trades' cash flows minus fees
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# The function tracks cash flow: entries subtract stake, exits add stake
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# Both long and short use the same formula based on order prices
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final_balance = result.iloc[-1][stake_currency]
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# Verify the balance changed (trades had effect)
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assert final_balance != start_balance, "Balance should change after trading"
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# Since all exit prices > entry prices, exits return more cash than entries spent
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# This means final balance > start balance for both long and short trades
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# (the function tracks cash flow, not P&L from long/short perspective)
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assert final_balance > start_balance, "Exit prices > entry prices should increase balance"
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