Alpha creation & research infrastructure
Historical data pipelines, feature computation, experiment tracking and reproducible environments for developing and comparing signals.
High-frequency trading consulting / research & production engineering
Build and validate institutional HFT systems.
TaleStorm is a high-frequency trading consultancy for quantitative funds and proprietary trading desks: alpha research, strategy validation and low-latency production infrastructure.
Built for institutionsQuant fundsProprietary trading firmsHFT desksInstitutional digital-asset teams
01 / Research
Develop and validate alpha, strategies, risk and allocation.
This part of our work is dedicated to research. The stack is built for reproducibility and realistic evaluation, not attractive backtests. Every layer has explicit datasets, assumptions, costs and acceptance criteria.
Alpha validation
Leakage and bias controls, stability analysis, regime sensitivity, out-of-sample and walk-forward testing, and capacity-aware evaluation.
Algorithm development & strategy validation
Strategies built on validated alpha, tested with fees, queue and fill assumptions, latency, slippage, liquidity and failure scenarios.
Strategy risk analytics
Drawdown, tail and concentration metrics, stress tests, factor and venue exposures, limits and explicit strategy shutdown conditions.
Strategy allocation
Portfolio construction and capital allocation using risk budgets, correlation, turnover, capacity and portfolio-level constraints.
02 / Production
Engineer the infrastructure for low-latency execution.
Production covers OMS, PMS, risk, algorithm APIs, market and venue connectivity, operator controls and observability. We separate latency-critical execution from the operational control plane.
Hot path / latency critical
Market event to order transmission.
Minimal hops, bounded work, deterministic behaviour and direct latency measurement.
- 01Market-data gatewayDecode, normalize and publish only the fields required by the strategy.
- 02Strategy runtimeConsume state, evaluate the signal and emit an order intent under a strict contract.
- 03Inline risk checksConstant-time limits required before an order can leave the system.
- 04OMS execution coreOrder state, sequencing, throttles, routing and venue-specific transmission.
Rule: no dashboards, historical queries, reporting or nonessential network calls in the latency-critical path.
Non-hot path / control plane
State, oversight and improvement.
Durable services can favour correctness, recovery, auditability and operator clarity over microseconds.
- 01Position management systemAuthoritative positions, cash, inventory, reconciliation and portfolio views.
- 02Portfolio & risk servicesAggregated exposures, limits, scenarios, alerts and capital-allocation decisions.
- 03Operator control consoleHuman oversight: strategy state, limits, approvals, kill controls and incident context.
- 04Telemetry, audit & replayMetrics, traces, event history, production replay and evidence for the next research cycle.
Rule: slow-path degradation must be observable and contained without silently changing execution behaviour.
Validation & improvement
Close the loop from research to live execution.
We validate each handoff, compare production behaviour with research assumptions and feed measured discrepancies back into the next strategy and architecture iteration.
Datasets, assumptions, invariants, latency budgets, risk limits and acceptance tests.
Costs, queues, partial fills, delays, rejects, liquidity and failure conditions.
Replay and shadow modes verify service contracts before capital is exposed.
Execution quality, latency distributions, risk events and divergence from expected behaviour.
Production evidence becomes a prioritized research, risk and engineering backlog.
Case studies
Selected research and algorithm development.
Representative institutional engagements across research, market making, execution and hedging. Client details are limited where confidentiality applies; no performance claims are implied.
Research infrastructure for short-horizon strategies.
Alpha-discovery pipeline over 10+ TB of raw futures data, from order-book reconstruction to model training.
Market-making strategies for digital assets on centralized venues.
Quoting, inventory and execution logic for digital-asset market making, with hot-path latency work.
Alpha-driven market making for equity markets.
Signals, quoting algorithms and the simulation stack used to validate both.
Quasi-market-taking algorithms for equity markets.
Lead-lag research between equities and futures, implemented as selective liquidity-taking algorithms.
Optimal execution of large equity positions.
Accumulation and unwind algorithms for large positions under market-impact, liquidity and timing constraints.
Improving a short-only trading algorithm.
Signal filtering, machine-learning research and short-specific risk metrics for a systematic short book.
Dynamic impermanent-loss hedging for liquidity positions.
Dynamic spot-and-futures hedge for impermanent-loss exposure in Uniswap liquidity positions.
Ways to work together
Start with the most important technical question.
FAQ
Before we start.
Do you work with retail traders?
No. This offer is designed for institutional teams: quant funds, proprietary trading firms, HFT desks and institutional digital-asset businesses, with existing data, capital and operational requirements.
Do you provide off-the-shelf trading algorithms?
No. TaleStorm develops research and engineering systems around an institution's markets, data, constraints, risk policy and operating environment.
Can you validate an existing alpha or strategy?
Yes. We can review the signal, research pipeline and strategies built on it, including leakage, robustness, transaction costs, execution assumptions, risk metrics and allocation logic.
Can you work on an existing OMS, PMS or risk stack?
Yes. An architecture assessment can identify service ownership, hot/non-hot boundaries, API and state-model issues, latency bottlenecks, recovery gaps and an iterative migration path.
Do you guarantee profitability or a latency number?
No. Trading outcomes depend on markets and involve risk. Latency targets are defined only after the venue, network, hardware, workload and measurement method are known.
How do you handle confidentiality and IP?
Confidentiality, data access, source-code ownership, deployment and handover terms are defined before work begins. An NDA can be arranged where required.
Institutional technical assessment
Bring us the research or production bottleneck.
Share the market, strategy stage, current architecture and highest-risk decision. We will use the first conversation to determine the right research or engineering scope.
TaleStorm provides institutional software engineering and quantitative research services, not investment advice, brokerage or asset management. Trading involves risk, including possible loss of capital. Backtested or simulated results do not guarantee future outcomes.