Local Market Simulator
A local interactive market sandbox inspired by your Canva notes on liquidity, order-book imbalance, spoofing, and flash-crash dynamics.
Hover the highlighted terms to see short explanations of the market concepts on the page.
The simulator runs locally in your browser. Use aggressive orders to move price, passive orders to deepen liquidity, spoofing to distort perceived imbalance, and the sell program to stress the market into a flash-crash regime.
Live Market
Offline. Log in to join the shared market room.
In live mode, your orders and spoof actions are sent to a shared Cloudflare-backed market room. Other users connected to the same room see the same tape and leaderboard update in real time.
Manual trade popup
Open Manual Trade beside the market chart when you want to place real orders or paid spoof orders. This keeps the tape visible while you work.
Model note
The live equations are shown in the Model Inspector below.
This version uses a stochastic order-flow process with liquidity feedback and no anchor-price mean reversion.
Colored overlays connect your actions to the tape: green marks buy-side interventions, red marks sell-side interventions, and amber windows show active spoofing periods.
The overview chart keeps the full market path. Drag the highlighted window or use mouse wheel on the main chart to zoom into a specific time range.
Balanced book
Stable quoting
Flat
PnL: 0.00
This view turns the live order book into a simple classroom picture: demand slopes down, supply slopes up, and visible pressure shifts one side left or right. The blue points show the old and new intersection so students can see how bid and ask pressure change both price and quantity.
This simplified lab follows the nonlinear equations from your slide. Adjust only the core parameters and watch how cancellation efficiency, fill probability, and market push change immediately.
Choose one ready-made formula family instead of editing tokens by hand. Some presets are intentionally flawed, so you can compare how the same parameters behave under a better or worse modeling choice.
Exponential: starts gently, then ramps up faster as the spoof order drifts closer to the touch.
Tip: click any bubble already inside a formula to remove it. This keeps the editor visual and avoids typing mistakes.
Decay equation
Closed-form fraction
Readout
Move the sliders to see how the nonlinear fraction changes cancellation efficiency and how much visible pressure is left for the market to react to.
Asks sit above the mid price. Bids sit below it. The closest rows to the middle trade first.
Equation
Equation
Equation
Equation
Equation
What each control changes
Story mode
Read this section like a short slide deck. It starts with a market that looks calm, follows why Navinder Singh Sarao appears in the story, then shows how a screen signal can grow into a market-wide fall.
The key message: a market can look steady on screen and still become fragile very quickly.
Cause chain
If you need one clean explanation, use this chain: a visible signal changes behavior, behavior changes real trading, real trading scares liquidity away, and then price moves much faster.
System stress
If you want to expand the explanation, tell students that the crash was really a system that had already become easy to break. The spoof story matters, but it landed inside a market that was already weak, fast, and too tightly connected.
Volatility was high and liquidity was fragile. That means the market still had prices on the screen, but not much real willingness to absorb a sudden wave of selling.
A very large automated sell program kept selling E-mini futures quickly. It responded to trading volume, but did not adjust carefully enough for how much damage each extra sale was doing to price.
High-frequency firms did not calmly absorb the shock. Many rapidly passed risk among themselves, which made the tape look busy without truly adding stability.
Order-book depth fell sharply. Once visible liquidity disappeared, the same order size started pushing price much farther, so the drop suddenly felt much steeper than before.
The move did not stay inside futures. Cross-market links quickly carried the stress into stocks and ETFs, so what began in one place became a wider market event.
Some algorithms and risk controls canceled orders or cut positions at the same time. Misleading screen signals such as spoofing were believed to have made the selling pressure look even worse.
Teaching takeaway
The cleanest neutral summary is this: the Flash Crash was not caused by one single factor. It was a systemic instability triggered by large sell orders, fragile liquidity, high-speed feedback, misleading signals, and structural weaknesses that all interacted at once.
Complexity
Sarao
Questions
Demo guide
Official source
Useful when you want the formal allegation language, including the description of layering, spoofing, and the claim that the conduct contributed to the Flash Crash.
Open DOJ press releaseOfficial source
Useful when you want the later legal outcome and a more concise summary of what the government said he admitted doing.
Open DOJ guilty plea releaseNews angle
Useful when you want a more reflective discussion: not only what one trader did, but also why the market was so vulnerable to rapid feedback loops.
Open New Yorker discussionLater perspective
Useful if you want to show students that the story did not end with the crash itself. It also helps frame how the event kept being reinterpreted years later.
Open Bloomberg article