Handle txn costs in BEP, factor enter/exit blocks and df row assignments B)
Tyler Goodlet
parent
29bab02c64
commit
b6a705852d
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@ -386,12 +386,18 @@ def open_ledger_dfs(
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# allow_reload=True,
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# )
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yield ledger_to_dfs(ledger), ledger
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yield ledger_to_dfs(ledger), ledger
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def ledger_to_dfs(
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ledger: TransactionLedger,
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# include transaction cost in breakeven price
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# and presume the worst case of the same cost
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# to exit this transaction (even though in reality
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# it will be dynamic based on exit stratetgy).
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cost_scalar: float = 1,
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) -> dict[str, pl.DataFrame]:
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txns: dict[str, Transaction] = ledger.to_txns()
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@ -462,12 +468,16 @@ def ledger_to_dfs(
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# the market) to acquire the dst asset, PER txn.
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# when this value is -ve (i.e. a sell operation) then
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# the amount sent is actually "returned".
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(pl.col('price') * pl.col('size')).alias('dst_bot'),
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(
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(pl.col('price') * pl.col('size'))
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+
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pl.col('cost')
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).alias('dst_bot'),
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]).with_columns([
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# rolling balance in src asset units
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(pl.cumsum('dst_bot') * -1).alias('src_balance'),
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(pl.col('dst_bot').cumsum() * -1).alias('src_balance'),
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# "position operation type" in terms of increasing the
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# amount in the dst asset (entering) or decreasing the
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@ -506,7 +516,7 @@ def ledger_to_dfs(
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]).select([
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pl.exclude([
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'tid',
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'dt',
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# 'dt',
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'expiry',
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'bs_mktid',
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'etype',
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@ -518,114 +528,137 @@ def ledger_to_dfs(
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last_cumsize: float = 0
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last_ledger_pnl: float = 0
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last_pos_pnl: float = 0
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last_is_enter: bool = False
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# last_is_enter: bool = False # TODO: drop right?
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# imperatively compute the PPU (price per unit) and BEP
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# (break even price) iteratively over the ledger, oriented
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# to each position state.
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# around each position state: a state of split balances in
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# > 1 asset.
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for i, row in enumerate(df.iter_rows(named=True)):
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cumsize: float = row['cumsize']
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is_enter: bool = row['is_enter']
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price: float = row['price']
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size: float = row['size']
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# ALWAYS reset per-position cum PnL
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if last_cumsize == 0:
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last_pos_pnl: float = 0
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# a "position size INCREASING" transaction which "makes
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# larger", in src asset unit terms, the trade's
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# side-size of the destination asset:
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# the profit is ALWAYS decreased, aka made a "loss"
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# by the constant fee charged by the txn provider!
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# TODO: support exit txn virtual cost which we
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# resolve on exit txns incrementally?
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pnl: float = -1 * row['cost']
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# a "position size INCREASING" or ENTER transaction
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# which "makes larger", in src asset unit terms, the
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# trade's side-size of the destination asset:
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# - "buying" (more) units of the dst asset
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# - "selling" (more short) units of the dst asset
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if is_enter:
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# a cumulative mean of the price-per-unit acquired
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# in the destination asset:
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# https://en.wikipedia.org/wiki/Moving_average#Cumulative_average
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# You could also think of this measure more
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# generally as an exponential mean with `alpha
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# = 1/N` where `N` is the current number of txns
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# included in the "position" defining set:
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# https://en.wikipedia.org/wiki/Exponential_smoothing
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ppu: float = (
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(
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(last_ppu * last_cumsize)
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+
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(row['price'] * row['size'])
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(price * size)
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) /
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cumsize
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)
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pos_bep: float = ppu
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# When we "enter more" dst asset units (increase
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# position state) AFTER having exitted some units
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# the bep needs to be RECOMPUTED based on new ppu
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# such that liquidation of the cumsize at the bep
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# price results in a zero-pnl for the existing
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# position (since the last one).
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if (
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not last_is_enter
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and last_cumsize != 0
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):
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pos_bep: float = (
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(
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(ppu * cumsize)
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-
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last_pos_pnl
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)
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/
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cumsize
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)
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df[i, 'ledger_bep'] = df[i, 'pos_bep'] = pos_bep
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# a "position size DECREASING" transaction which "makes
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# smaller" the trade's side-size of the destination
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# asset:
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# a "position size DECREASING" or EXIT transaction
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# which "makes smaller" the trade's side-size of the
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# destination asset:
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# - selling previously bought units of the dst asset
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# (aka 'closing' a long position).
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# - buying previously borrowed and sold (short) units
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# of the dst asset (aka 'covering'/'closing' a short
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# position).
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else:
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# only changes on position size increasing txns
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ppu: float = last_ppu
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pnl = df[i, 'per_exit_pnl'] = (
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(last_ppu - row['price'])
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*
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row['size']
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# include the per-txn profit or loss given we are
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# "closing" the position with this txn.
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pnl += (last_ppu - price) * size
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# cumulative PnLs per txn
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last_ledger_pnl = (
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last_ledger_pnl + pnl
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)
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last_pos_pnl = df[i, 'cum_pos_pnl'] = (
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last_pos_pnl + pnl
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)
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if cumsize == 0:
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last_ppu = ppu = 0
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# compute the "break even price" that
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# when the remaining cumsize is liquidated at
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# this price the net-pnl on the current position
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# will result in ZERO pnl from open to close B)
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if (
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abs(cumsize) > 0 # non-exit-to-zero position txn
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):
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ledger_bep = pos_bep = ppu
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# TODO: now that this
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# recalc-bep-on-enters-based-on-new-ppu was
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# factored out of the `is_enter` block above we can
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# drop this if condition right?
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#
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# When we "enter more" dst asset units (aka
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# increase position state) AFTER having exited some
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# units (aka decreasing the pos size some) the bep
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# needs to be RECOMPUTED based on new ppu such that
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# liquidation of the cumsize at the bep price
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# results in a zero-pnl for the existing position
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# (since the last one).
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# if (
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# not last_is_enter
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# and last_cumsize != 0
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# ):
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ledger_bep: float = (
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(
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(ppu * cumsize)
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-
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(last_ledger_pnl * copysign(1, cumsize))
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) / cumsize
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)
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last_ledger_pnl = df[i, 'cum_ledger_pnl'] = last_ledger_pnl + pnl
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last_pos_pnl = df[i, 'cum_pos_pnl'] = last_pos_pnl + pnl
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if cumsize == 0:
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ppu: float = 0
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last_ppu: float = 0
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else:
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ppu: float = last_ppu
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if abs(cumsize) > 0:
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# compute the "break even price" that
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# when the remaining cumsize is liquidated at
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# this price the net-pnl on the current position
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# will result in ZERO pnl from open to close B)
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ledger_bep: float = (
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(
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(ppu * cumsize)
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-
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last_ledger_pnl
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) / cumsize
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)
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df[i, 'ledger_bep'] = ledger_bep
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pos_bep: float = (
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(
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(ppu * cumsize)
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-
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last_pos_pnl
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) / cumsize
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)
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df[i, 'pos_bep'] = pos_bep
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# for position lifetime BEP we never can have
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# a valid value once the position is "closed"
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# / full exitted Bo
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pos_bep: float = (
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(
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(ppu * cumsize)
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-
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(last_pos_pnl * copysign(1, cumsize))
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) / cumsize
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)
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# inject DF row with all values
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df[i, 'pos_ppu'] = ppu
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df[i, 'per_exit_pnl'] = pnl
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df[i, 'cum_pos_pnl'] = last_pos_pnl
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df[i, 'pos_bep'] = pos_bep
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df[i, 'cum_ledger_pnl'] = last_ledger_pnl
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df[i, 'ledger_bep'] = ledger_bep
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# keep backrefs to suffice reccurence relation
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last_ppu: float = ppu
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last_cumsize: float = cumsize
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last_is_enter: bool = is_enter
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# last_is_enter: bool = is_enter # TODO: drop right?
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return dfs
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