Opportunities › High-frequency trading strategy backtesting tools › Proposed app
Tickwake
Replay backtests tick by tick: queue position, latency, fills and raw feed.
- Score
- 29
- confidence 50
- Evidence
- 3
- items on the page
- Rivals
- 1
- named in sources
- First version
- 45 d
- estimate
- Type
- Desktop app
- PWA: runs in the browser, installs on Mac and Windows
- Market since
- 2022
- Emerging market · AI estimate
ScreensConcept
Desktop app: Traders step through backtest events tick by tick, analyze queue positions and latency in detailed technical analysis requiring large displays. Sample screens on a computer, in the proposed brand. Their numbers are sample data.
Replay
Event 48,221 of 1.2M12:04:07.318
- Best bid
About this appAI proposal
Tickwake is a replay console for people who build high-frequency and market-making strategies. Load a backtest run and step through it event by event: the order book, the queue position of each resting order, feed and order latency, fills, and the raw exchange messages behind them.
It is made for quant traders and developers at trading firms and proprietary shops who already have a backtest engine and need to see why a result came out as it did. You can check whether an edge survives realistic latency and queue dynamics before capital goes live.
Tickwake does not replace your engine. It reads the output of your runs and shows the mechanics that a summary profit curve hides. Teams can share a link to an exact moment in a run and discuss it.
- Tagline
- See what your backtest really did, one tick at a time.
- Voice
- PrecisePlainCalm
- Why this name
- A tick is one market event, and a wake is the trail left behind. Tickwake is the trail of events your strategy leaves in a run.
In the first version
Members say which features they would use. It tells PWAS what people want; it changes no score.
Event-by-event replay
Step forward and back through a run, or play it at speed. The book, your orders and the feed stay in sync at every event.
No member yet
Queue position tracking
See where each resting order sits in the queue, how it moves as others trade or cancel, and when it gets filled.
No member yet
Latency lanes
Plot feed latency and order latency over time, and see which fills or misses fall in the slow stretches.
No member yet
Raw feed beside the book
Open the exchange messages behind any book change, so you can check the replay against the source data.
No member yet
Brand identityAI proposal
Check the name against trademark registers before using it.
Palette
#12202BDeep Slate · primary#F3F5F4Paper Fog · surface#14212BInk · text#E8A33DAmber Tick · accent#1F8A7ABid Teal · data: bids#C9503FAsk Coral · data: asks
Typography
Aa
Tickwake
PricingAI proposal
The material gives no competitor prices; the engine named is a free library. These tiers are a starting point to test, scaled by team size and stored runs.
Solo
$49 a month
- 1 user
- Up to 20 stored runs
- Replay, queue and latency views
- Raw feed viewer
Team
$249 a month
- Up to 5 users
- Unlimited stored runs
- Shareable moment links
- Run comparison
- Shared notes
Firm
Contact us
- Unlimited users
- Single sign-on
- Private deployment option
- Priority support
What it could be worthEstimate
What a software business making this much sells for today, from real deals. Pick a monthly revenue.
If it makes
Worth about
$194,000
Sale range $132,000 to $263,000
$120,000 a year in revenue
From 87 software businesses listed and sold on Empire Flippers in the last year, revenue vetted by the broker: they sell for about 19× their monthly revenue, most between 13× and 26×.
Measured on profit, the middle deal is 32× monthly net profit: about 2.7 years of profit.
An estimate, not an offer or financial advice. A real price depends on profit, growth, churn, how much of the work is the owner's, and the buyer.
How it would growAI proposal
How the product would reach new customers through its own use, and how the first ones would be found. A plan to test, not a result.
- Built-in loop
- Shared outputs. Users send teammates and counterparts links to an exact moment in a run, showing book, queue and latency. Viewers open it in the browser with no install, and see the Tickwake name.
- Do they become customers?
- Viewers are often colleagues of a quant, who may sign up or push their firm to buy. A link opened once gives no customer by itself. Test how many viewers create an account.
- First customers
- Small proprietary trading shops and solo quants of 1 to 10 people building market-making strategies on crypto futures, who already run an open-source backtest engine.
- Where to reach them
- GitHub and engine community: Publish a free converter and sample replays for the open-source engine, and answer questions where its users gather.
- Quant forums and Discord: Post short replay clips that explain one fill or one latency miss, with a link to try it on sample data.
- Direct outreach: Message quants who star or fork related repositories and offer a free trial on their own run logs.
- First milestone
- Five paying Solo or Team customers from the crypto market-making niche within 60 days of a public beta.
Why people already pay for this
- VerifiedGitHub repository gained 302 stars in 30 days
- Public claimTraders building high-frequency and market-making strategies need to visualize order book dynamics, latency, queue position, and fills during backtests to validate strategies before live deployment.
- Public claimThe tool runs backtests on real recorded market data (Binance Futures) with low-level latency and execution details visible in a dashboard.
Tech stack
Every proposal builds on the same PWA base, installable from the browser on any phone or computer. Dashed boxes are what this app adds.
- AppNext.js and TypeScript
- PWAManifest and service worker
- UITailwind CSS
- Data and authSupabase Postgres
- PaymentsStripe
- EmailResend
- HostingVercel
- This app · Run storageObject storage for compressed run logsRuns hold millions of events; store them as files and load slices on demand.
- This app · Event renderingCanvas or WebGL charting in the browserStepping through millions of events needs smooth drawing that plain DOM cannot give.
RisksAI inference
- CommercialFirms may build an internal viewer or keep to scripts and notebooks. Evidence shows repository interest, not that firms pay for a console.
- TechnicalLarge runs of millions of events must load and scrub smoothly in a browser, which may need heavy work on data slicing and rendering.
- DataTraders are wary of uploading recorded data and run logs. Exchange data licence terms may limit storage or sharing.
- PlatformDepends on the output format of the underlying open-source engine, which can change. Support for other engines is unproven.
- CommercialThe audience is small and skilled, and may prefer a one-time or self-hosted licence to a hosted subscription.
Everything marked AI proposal or AI inference was written by a model from the evidence on the opportunity page. The proposed name must be checked against trademark registers before it is used.