418-final

Week 1: Parallel Limit Order Book Simulation

Irene Liu (irenel), Lillian Yu (lyu2)
15-418 – Spring 2026

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Goals

• Implement a correct, baseline LOB
• Set up data generation scripts to create order flows for correctness tests

Deadline: March 31st

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Order Generation as Experimental Design

To create test inputs, since we want to test how syncrhonization strategies behave under realistic contention, our generator should support functionalities that can vary the intensity of such contention variables such as: concentration near the bid-ask spread, burstiness, cancel density, sweeping market orders, and multi-ticker skew. This lines up with the bottlenecks that we want to target in our project: hot spots near bid ask spread, strict price-time dependency enforcement, skewed workloads, and irregular shared-memory updates.

Our two resources may inspire some implementation details:

1. (https://github.com/devmenon23/Limit-Order-Book) Markov-chain market state model plus Pareto-dstributed sizes/prices, explicity creating shifts of buy/sell pressure and heavy-tailed, bursty order flow.
2. (https://github.com/brprojects/Limit-Order-Book) Initial seeded book, requests with prices centered around a moving mid, average active book depth targets, and mixed order types.

Plan for implementation: Generator Ladder

1. Controlled Baseline Generator: This aims to just verify correctness and isolate performance effects. Sampling from identically independent distribution involving
   • fixed tick size
   • one or several tickers
   • seeded initial book with symmetric depth around a reference midprice
   • configurable mix of limit, market, cancel, and modify
   • prices sampled as offsets from current mid price
   • sizes from either a light-tailed or bounded distribution

This gives a first simple baseline for correctness and coarse-grained locking benchmarks.

1. Stateful Market Generator: Markovian process alternating the market to have
   • neutral
   • buy pressure
   • sell pressure
   • high-volatility burst
   • cancellation storm
   • liquidity drought Then, for example, for buy-pressure state we might: - increase buy arrival rate - move buy limit prices closer to or through the ask - increase market buy probability - reduce passive sell replenishment

This will be a good hard scenario to test our fine-grained design on.

1. Generator Event-Based: generate events relative to the current book state i.e. with some probability:
   • place a passive order at level best_bid - k
   • place an aggressive buy at best_ask or above
   • cancel an order currently resting within the top d levels
   • modify an existing order by cancel-and-reinsert
   • send large market order, sweeping across multiple levels

This will really test contention in our LOB to concentrate pressure.