Expected Cost is a live pre-trade market-impact demo: it estimates what an equity order will cost to execute from real-time bid-ask spread, volatility and traded volume, computed on a kdb+/q tick pipeline over the live US consolidated tape — 15 US equities plus BTC/USD, 15-minute delayed by policy. The dashboard requires JavaScript.

Expected cost of your order

NVDA

Es at V = 5,000 $/unit —

Participation rate / sec: —
as-of: —

Order volume V (shares)

5,000

Cost curve — Es(V) right now

instantaneous

Bid–ask spread β $ —

Volatility σ per-sec log-return —

Volume / sec units/s —

Expected cost Es $/unit —

window

Expected cost Es

at fixed V

Bid–ask spread β

Volatility σ

Volume / sec

Volume / sec units/s, day series

—

day

Book updates / sec quotes/s, day series

Cumulative volume units, by time of day

—

todayprevavg5avg20

Cumulative book updates quotes, by time of day

today · prev · avg5 · avg20

todayprevavg5avg20

Mid price $

Ingestion open day, from the RDB

—

symbol	rows	rate	last event
—

engine · query latency

Client round trip —ms mean —

q server compute —µs mean — · max —

Queries served — 0 missing-data

Round trip vs server compute

q compute distribution

—

q compute percentiles

Background: the market impact & optimal execution literature

The expected-cost model served here is a simple parametric impact model (spread + volatility-scaled participation). The canonical research on market impact, execution cost and optimal trading it stands in front of:

Robert Almgren & Neil Chriss, Optimal Execution of Portfolio Transactions, Journal of Risk, 2000.
Albert S. Kyle, Continuous Auctions and Insider Trading, Econometrica, 1985.
Dimitris Bertsimas & Andrew Lo, Optimal Control of Execution Costs, Journal of Financial Markets, 1998.
Fabrizio Lillo, J. Doyne Farmer & Rosario Mantegna, Master Curve for Price-Impact Function, Nature, 2003.
Jean-Philippe Bouchaud, Yuval Gefen, Marc Potters & Matthieu Wyart, Fluctuations and Response in Financial Markets: The Subtle Nature of “Random” Price Changes, Quantitative Finance, 2004.
Jim Gatheral, No-Dynamic-Arbitrage and Market Impact, Quantitative Finance, 2010.
Anna Obizhaeva & Jiang Wang, Optimal Trading Strategy and Supply/Demand Dynamics, Journal of Financial Markets, 2013.
Jean-Philippe Bouchaud, Julius Bonart, Jonathan Donier & Martin Gould, Trades, Quotes and Prices: Financial Markets Under the Microscope, Cambridge University Press, 2018.
Charles-Albert Lehalle & Sophie Laruelle, Market Microstructure in Practice, World Scientific, 2013.

Market impact