Sensor for Home Assistant that gets reset at midnight

[NeurIPS'25] FreqExit: Enabling Early-Exit Inference for Visual Autoregressive Models via Frequency-Aware Guidance

Comprehensive financial risk analysis toolkit with Altman Z-Score bankruptcy prediction, Value at Risk (VaR) calculations, and historical crisis stress testing. Supports US & European markets with automated company classification.

SAMPO: Scale-wise Autoregression with Motion Prompt for Generative World Models

SRVAR toolkit inspired by Grammatikopoulos (2025, Journal of Forecasting)

Value at risk (VaR) is a measure of the potential loss that an asset, portfolio, or firm might experience over a given period of time. Standard deviation, on the other hand, measures how much returns vary over time.

Market risk analytics dashboard in Python and Streamlit that computes portfolio volatility, drawdowns, VaR/ES, rolling correlations, and stress tests (shocks + COVID‑style crisis window) for equity/ETF portfolios. ​

Quantitative trading indicators for Python. Anchored VWAP and Value at Risk with 4 calculation methods.

Crypto risk modeling with VaR/CVaR w/ multi-coin support

Python model measuring Value-at-Risk (VaR) and Expected Shortfall (ES) for a £1m GBP/USD portfolio, with scenario stress testing and client-style reporting.

Beginner Level Python projects

Interactive multi-asset VaR (Parametric, Historical, MC Normal, MC t-Student) with FX & crypto

Tests for VaR estimation of financial instruments, including Kupiec Test(LR-Stats) and Engle Test(QD-Stats).

Text-driven quantitative risk engine that converts natural language portfolio requests into structured VaR, Expected Shortfall, and Basel-style backtesting analytics using a modular multi-phase architecture.

A Monte Carlo simulation project for financial risk analysis of Crude Oil Stocks.

A Python powered CLI that calculates most important descriptive statistics for given assets

1-day 95% VaR on SOFR swaps and equities (AAPL, MSFT, F, BAC) using parametric, Monte Carlo and historical methods.

Model risk validation sandbox for market & credit risk (VaR, ES, EL, backtesting)

Official PyTorch implementation of "LSRS: Latent Scale Rejection Sampling for Visual Autoregressive Modeling". An efficient test-time scaling strategy to enhance VAR image generation quality with minimal overhead.