Options Analytics & DigitalAsset Breakout Alert Platform

Broker API Option chains Greeks Implied volatility ranks/percentiles Yield metrics UIready data structures Digitalasset breakout alerts Python Research dashboards

Marsbridge delivered a Pythonbased options analytics framework to ingest option chains, Greeks, and impliedvolatility measures, compute volatility ranks/percentiles and annualized yield metrics, and prepare clean, UIready data structures for dashboards. We also prototyped a digitalasset breakout alert on a generic marketdata feed with optional volume gating—enabling multiasset research and rapid product experiments on a shared data backbone, without exposing internal trading logic.

Customer

Client Private Quantitative Investor (Switzerland)
Industry Options Analytics & Digital Assets
Region Switzerland (global markets)
Engagement Options analytics (core build) → Digital-asset alert prototype (follow-on)

The brief: (1) create a repeatable options-data pipeline comparable to typical industry dashboards, and (2) test a lightweight breakout-alert concept for digital assets with low operational overhead and clean outputs suitable for a future web/desktop UI—while keeping all trade/strategy logic under the client’s control.

Challenge

Data Completeness and Rapid Prototyping

Solution

Lean Squad Delivery of Data Plane and Alert Prototype

Approach: A lean squad—Tech/Quant Lead, Data Engineer, Frontend–facing Analyst, and QA—built the options data plane first, then iterated on the digitalasset alert prototype using the same packaging conventions.

Options analytics framework

Options analytics framework

API ingestion: Retrieve chains, Greeks, and impliedvolatility fields via a broker API; normalize to tidy data frames with symbol metadata. (No clientspecific screens or symbols disclosed.) Derived fields: Compute volatility rank/percentile and annualized yield metrics, plus listfriendly sort keys for UI watchlists. (Exact formulas and thresholds omitted.) UIready outputs: Emit JSON/CSV with stable keys so a web/desktop frontend can render watchlists, detail panes, and filters without backend rewrites.

Digitalasset breakout alert prototype

Digitalasset breakout alert prototype

Data source: Use a generic marketdata provider for price/volume time series. (Provider names removed.) Signals: Configurable breakout rules on rolling windows with optional volume gating and simple ranking (magnitude/persistence). (Thresholds and ranking coefficients removed.) Artifacts: Lightweight CSV/JSON outputs and alert hooks designed to feed future UI components—no automated trading included.

Collaboration for productization

Collaboration for productization

Provided API/JSON specs, sample pages, and data contracts for frontend collaborators, enabling rapid UI evolution without changing the backend pipeline. (UI details generalized.)

Technologies & tools

Core

Python, broker API ingestion, pandas/NumPy, JSON/CSV for UI contracts

Market Data

Standardized digitalasset price/volume feeds

Storage

Optional relational storage when persistent history is desired

Process

  1. Scope & parity targets: Define required option fields (chains, Greeks, IV) and derived analytics (volatility ranks/percentiles, yields).
  2. Broker integration: Implement ingestion + normalization; validate via spot checks; draft JSON/CSV schemas for UI.
  3. Derived metrics & watchlists: Compute volatility ranks/percentiles and yield-oriented ranks; produce example watchlists. (Exact formulas omitted.)
  4. Digital-asset prototype: Implement breakout detector on generic feeds; add ranking/volume gates; deliver alert outputs. (Provider and thresholds removed.)
  5. Handoff: Docs, data contracts, and example UI stubs for continued product development—no trading rules attached.

Team

User Icon
1
Tech/Quant Lead
User Icon
1
Analyst
User Icon
0.5
Data Engineer
User Icon
1
Frontend–facing Analyst
User Icon
0.5
QA / Ops
Marsbridge team collaborating on options analytics project

Results

Note: Both components are analytics/information systems; they are not trading advice and do not include client strategies or parameters.

Ship Data Products Faster

Need options analytics and a path to UI without months of plumbing? We deliver clean data contracts and researchfirst code—so your team can ship dashboards and alerts quickly across options and digital assets, without exposing proprietary trading details.

Request a Consultation

Drop us a line! We are here to answer your questions within 1 business day.

What happens next?

1

Once we’ve received and processed your request, we’ll get back to you to detail your project needs and generally sign an NDA to ensure confidentiality.

2

After examining your project requirements, our team will devise a proposal with the scope of work, team size, time, and cost estimates.

3

We’ll arrange a meeting with you to discuss the offer and nail down the details.

4

Finally, we’ll sign a contract and start working on your project with agreed timeline