RealizedSpread

Description

RealizedSpread is the part of the effective spread that the liquidity provider keeps once the price has moved. With the quote-based trade direction (a print above the mid is a buy, below is a sell), D = sign(price - mid),

realized = 2 * D * (price - mid measured `lag` steps later).

It compares a past trade's price to the mid lag steps afterward. What the effective spread does not keep, effective - realized, is the price-impact or adverse-selection component: how far the mid moved in the trade's direction after it printed. The value at each step references a trade lag steps in the past, so it is causal (never a future trade). The first lag samples are NaN (warmup).

Examples

Usage plot

import numpy as np
import plotly.graph_objects as go
from plotly.subplots import make_subplots
from screamer import EffectiveSpread, RealizedSpread

rng = np.random.default_rng(2)
n = 4000
half_spread = 0.10
mid = np.empty(n)
mid[0] = 100.0
price = np.empty(n)
side = rng.choice([-1.0, 1.0], size=n)                 # trade direction
for t in range(n):
    price[t] = mid[t] + side[t] * half_spread          # trade at bid/offer
    step = rng.standard_normal() * 0.01 + side[t] * 0.02   # adverse drift after the trade
    if t + 1 < n:
        mid[t + 1] = mid[t] + step

lag = 20
eff = EffectiveSpread()(price, mid)
real = RealizedSpread(lag=lag)(price, mid)
impact = eff - real                                    # price-impact / adverse selection

fig = go.Figure()
labels = ['effective spread', 'realized spread', 'price impact']
series = [eff, real, impact]
colors = ['crimson', 'seagreen', 'steelblue']
for lab, s, c in zip(labels, series, colors):
    fig.add_trace(go.Bar(x=[lab], y=[np.nanmean(s)], marker_color=c, name=lab))
fig.update_layout(title='Effective = realized + impact (means, lag=20)',
                  yaxis_title='spread', showlegend=False,
                  margin=dict(l=20, r=20, t=60, b=20))
fig.show()