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feat: add short fields to balance_distribution

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Matthias
2026-01-25 20:17:15 +01:00
parent 803b4cae78
commit e4eee1aa1b
1 changed files with 20 additions and 6 deletions
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freqtrade/data/btanalysis/trade_parallelism.py
+20 -6
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@@ -82,6 +82,8 @@ def balance_distribution_over_time(
- stake_currency: amount of stake currency
- <pair>: amount of base currency in the pair
- <pair>_leverage: leverage used for the pair at the time (NaN if no open trade)
- <pair>_is_short: 1 if the open trade is short, 0 if long (NaN if no open trade)
- <pair>_collateral: amount of stake currency used as collateral for open trades
:param trades: Trades Dataframe - can be loaded from backtest, or created
via trade_list_to_dataframe
:param timeframe: Frequency to use for the resulting dataframe
@@ -98,26 +100,38 @@ def balance_distribution_over_time(
max_date_res = timeframe_to_prev_date(timeframe, max_date)
index = pd.date_range(min_date_res, max_date_res, freq=timeframe_to_resample_freq(timeframe))
pairs_lev = [f"{pair}_leverage" for pair in pairlist]
df = pd.DataFrame(index=index, columns=[stake_currency] + pairlist + pairs_lev, dtype=float)
pairs_is_short = [f"{pair}_is_short" for pair in pairlist]
pairs_collateral = [f"{pair}_collateral" for pair in pairlist]
pairs_lev += pairs_is_short
df = pd.DataFrame(
index=index, columns=[stake_currency] + pairlist + pairs_lev + pairs_collateral, dtype=float
)
# Initialize variables to starting values
df[stake_currency] = float(start_balance)
df[pairlist] = 0.0
df[pairlist + pairs_collateral] = 0.0
df[pairs_lev] = np.nan
for trade in trades.sort_values(by=["open_date"]).itertuples():
pair = trade.pair
end_date = trade.close_date if trade.close_date is not pd.NaT else None
# Exclude open orders - these won't have order_filled_timestamp set.
orders = [o for o in trade.orders if o["order_filled_timestamp"]]
df.loc[trade.open_date : end_date, f"{trade.pair}_leverage"] = trade.leverage
df.loc[trade.open_date : end_date, f"{pair}_leverage"] = trade.leverage
df.loc[trade.open_date : end_date, f"{pair}_is_short"] = 1 if trade.is_short else 0
for order in sorted(orders, key=lambda x: x["order_filled_timestamp"]):
filled_at = pd.Timestamp(dt_from_ts(order["order_filled_timestamp"]))
real_amount = order.get("filled", order["amount"]) / trade.leverage
real_amount = order.get("filled", order["amount"])
stake = order["safe_price"] * real_amount
if order["ft_is_entry"]:
fee = stake * trade.fee_open
df.loc[filled_at:end_date, trade.pair] += real_amount
df.loc[filled_at:end_date, pair] += real_amount
df.loc[filled_at:end_date, f"{pair}_collateral"] += stake / trade.leverage
df.loc[filled_at:, stake_currency] -= stake + fee
else:
fee = stake * trade.fee_close
df.loc[filled_at:end_date, trade.pair] -= real_amount
df.loc[filled_at:end_date, pair] -= real_amount
df.loc[filled_at:end_date, f"{pair}_collateral"] -= stake / trade.leverage
df.loc[filled_at:, stake_currency] += stake - fee
# Round to avoid floating point issues