DUCKQUANT / THE QUANT & AI DIRECTORY
4,091 resources, ranked by in-directory PageRank
Simulated 1-day 99% Monte Carlo VaR with Basel III regulatory backtesting
Decomposing the US equity premium into overnight and intraday returns: replication, stress tests and transaction-cost analysis (SPY 1993-2026)
Decomposing Post-Earnings-Announcement Drift (PEAD) across 5 factor models. Features TAQ transaction-cost analysis, WRDS integration, and block bootstrapping.
Estimate MegaETH gas costs with dual compute and storage metrics, comparing fees to Ethereum L1 for accurate transaction cost analysis.
An optimal execution and transaction cost analysis engine: implementation shortfall decomposition, market impact calibration, and Almgren-Chriss trajectories.
Mini BestEx: equity tick/minute ingestion -> partitioned Postgres -> TWAP/VWAP execution simulation -> Transaction Cost Analysis dashboard.
Evidence-backed case study of strategy evaluation, backtesting, and transaction-cost analysis in IMC Prosperity 4.
Deterministic OCaml and Python lab for institutional execution, order-book simulation and transaction cost analysis.
Cross-sectional momentum strategy with robustness testing, transaction cost analysis, and factor attribution.
Weekly momentum strategy on VN30 with transaction cost analysis
Python/SQL Transaction Cost Analysis (TCA) workflow
This project explores the impact of transaction costs on profitability in high-frequency trading (HFT) and passive investment strategies.
Transaction Cost Analysis & Anomaly Detection Engine
This project analyzed vehicle transaction costs
Python framework for transaction cost analysis, optimal execution modeling, and Monte Carlo simulation of institutional trading strategies.
Public repository by quantskills. Primary language: Python.
End-to-end MDR transaction and cost analysis using SQL Server, Python, Power BI and DAX, with merchant, city and payment-method insights.
Public repository by TheCrickMaster. Primary language: q.
Public repository by TonyCha3713. Primary language: C++.
Master 272 (Paris Dauphine) volatility strategies project: object-oriented replication and backtesting of variance, gamma, skew, and M4 swaps from OTM options, with NAV/PnL decomposition,…
Quantitative research platform for Bitget Reality rTokens with factor discovery, validation, historical backtesting, transaction-cost analysis, live market data, and a research copilot.
Develop TCA framework on TRACE data to compute expected transaction costs and price impact dynamics. Implemented regularized regression techniques to identify key determinants of…
The objective of this task is to determine the optimal timing for executing an order by considering two options: paying half the Bid/Offer spread…
A web dashboard for transaction cost analysis on equity trades.
Public repository by LSEG-API-Samples. Primary language: Python.
Quantitative momentum trading strategies: CSMOM vs TSMOM comparison with parameter optimization. Achieved 24% CAGR and 1.22 Sharpe ratio over 10 years. Complete Python implementation…
A Python implementation of Frazzini & Pedersen’s (2013) Betting Against Beta (BAB) factor, featuring leverage-constrained portfolio construction and transaction cost analysis.
Graph-based spatio-temporal learning for cross-sectional stock selection with out-of-sample backtesting and transaction cost analysis.
Backtests of portfolio insurance strategies - CPPI, OBPI, stop-loss - with drawdown and transaction cost analysis.
To find out if and when an order should be immediately executed by paying (half) the Bid/Offer spread, i.e, MT. Or if would be…
Built a pairs trading strategy in emerging markets using a rolling Kalman-filter beta and spread half-life, with z-score position sizing, and comprehensive back-testing with…
Open source TCA (transaction cost analysis) Python library for FX spot
Trade-surveillance reference implementation on .NET 10 / ASP.NET Core / EF Core / PostgreSQL: idempotent ingestion, transactional outbox, deterministic rules engine, auditable alerts —…
A trade surveillance pipeline that generates a labeled synthetic trading dataset, detects three real market-abuse patterns against it, and measures actual precision/recall rather than…
