Search Results for "quantitative" - Page 2
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Showing 47 open source projects for "quantitative"
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Discursive Dilemma
Optimal Decision Rules for the Discursive Dilemma
Accompanying software for the paper "Optimal Decision Rules for the Discursive Dilemma", by A. Alabert, M. Farré and R. Montes (https://arxiv.org/abs/2210.13100). Computes a ranking of the best decision rules according to a quantitative criterion based on the minimisation of the combined probabilities of false positives and false negatives -
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ChangeFormer
A Transformer-Based Siamese Network for Change Detection
Here, we provide the PyTorch implementation of the paper: A Transformer-Based Siamese Network for Change Detection. -
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Machine Learning Financial Laboratory
MlFinLab helps portfolio managers and traders
MlFinLab is a comprehensive Python library designed to support the development of machine learning strategies in quantitative finance and algorithmic trading. The project provides a large collection of tools that implement techniques from academic research on financial machine learning. It covers the full lifecycle of developing data-driven trading strategies, including data preprocessing, feature engineering, labeling techniques, model training, and performance evaluation. -
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Eiten
Statistical and Algorithmic Investing Strategies for Everyone
...It is part of the broader Tradytics ecosystem, which emphasizes AI-driven financial tools for identifying opportunities in the stock market. The repository serves both as a learning resource and as a practical toolkit for traders and developers interested in quantitative finance. It encourages experimentation with different strategies and models, allowing users to adapt techniques to their own trading goals. -
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surpriver
Find big moving stocks before they move using machine learning
...The framework includes modules for retrieving market data, computing technical indicators, and applying anomaly detection algorithms to identify unusual patterns. The project is intended as a research tool for quantitative finance experiments and algorithmic trading strategy development. -
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Python4Proteomics Course
Python course for Proteomics analysis
Python course (in Spanish) for Proteomics analysis using basically Jupyter NoteBooks. For more information, you can have a look at the readme.md file in the source code tree: https://sourceforge.net/p/lp-csic-uab/p4p/code/ci/default/tree/readme.md -
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DEBay
Deconvolutes qPCR data to estimate cell-type-specific gene expression
...The user manual of DEBay: https://sourceforge.net/projects/debay/files/UserManual.pdf Sample data: https://sourceforge.net/projects/debay/files/Test_data/ Citation Information: Vimalathithan Devaraj, Biplab Bose. DEBay: A computational tool for deconvolution of quantitative PCR data for estimation of cell type-specific gene expression in a mixed population. Heliyon, 2020, 6(7), e04489. https://doi.org/10.1016/j.heliyon.2020.e04489 -
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abu
Abu quantitative trading system (stocks, options, futures, bitcoin)
Abu Quantitative Integrated AI Big Data System, K-Line Pattern System, Classic Indicator System, Trend Analysis System, Time Series Dimension System, Statistical Probability System, and Traditional Moving Average System conduct in-depth quantitative analysis of investment varieties, completely crossing the user's complex code quantification stage, more suitable for ordinary people to use, towards the era of vectorization 2.0. -
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TF Quant Finance
High-performance TensorFlow library for quantitative finance
TF Quant Finance is a high-performance library of quantitative finance components built on TensorFlow, aimed at research and production workloads. It implements pricing engines, risk measures, stochastic models, optimizers, and random number generators that are differentiable and vectorized for accelerators. Users can value options and fixed-income instruments, simulate paths, fit curves, and calibrate models while leveraging TensorFlow’s jit compilation and automatic differentiation. ... -
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AIAlpha
Use unsupervised and supervised learning to predict stocks
...The repository explores how artificial intelligence techniques can analyze historical financial data and generate predictions about asset price movements. It provides a research-oriented environment where users can experiment with data processing pipelines, model training workflows, and quantitative trading strategies. The project typically involves collecting market data, transforming financial indicators into machine learning features, and training models to identify patterns that may predict market trends. It also demonstrates how models can be evaluated through backtesting frameworks that simulate how a strategy would perform using historical market conditions. ... -
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fooltrader
Quant framework for stock
...Its applicable objects include quantitative traders, teachers, and students majoring in finance, people interested in economic data, programmers, and people who like freedom and the spirit of exploration. You could write the Strategy using an event-driven or time walkway and view and analyze the performance in a uniform way. -
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A quantitative finance C++ library for modeling, pricing, trading, and risk management in real-life. A cross-platform free/open-source tool for derivatives and financial engineering.
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AstroTortilla
Astrophotography assistant
AstroTortilla is a wrapper around common astrophotography tools intended to automate basic tasks such as polar alignment and goto correction. Not in active development presently. -
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forest01
Automatic delineation of forest borderlines
Forest01 is a tool for the automatic mapping of forest based on Airborne Laser Scanner data. The forest mapping is performed by means of quantitative criteria typical of forest definitions, namely minimum threshold for the height of trees, canopy cover, forest area size and width. -
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pyQPCR is a GUI application written in python that deals with quantitative PCR (QPCR) raw data. Using quantification cycle values extracted from QPCR instruments, it uses a proven and universally applicable model to give finalized quantification resu
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Tushare
TuShare is a utility for crawling historical data of China stocks
Tushare is a Python library that provides access to a wide range of financial data focused on the Chinese stock market. It allows users to retrieve real-time and historical market data, financial reports, index data, and macroeconomic indicators. Tushare is widely used in quantitative trading, data analysis, and academic research. It supports both free and premium data tiers via Tushare Pro, which requires an API token. -
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GASiC
Genome Abundance Similarity Correction
One goal of sequencing based metagenomic analysis is the quantitative taxonomic assessment of microbial community compositions. However, the majority of approaches either quantify at low resolution (e.g. at phylum level) or have severe problems discerning highly similar species. Yet, accurate quantification on species level is desirable in applications such as metagenomic diagnostics or community comparison. -
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fitGCP
Fitting genome coverage distributions with mixture models
...Thus, biases such as fragmented or erroneous reference genomes often remain unaccounted for. Making this information accessible can improve the quality of sequencing experiments and quantitative analyses. fitGCP is a framework for fitting mixtures of probability distributions to genome coverage profiles. Besides commonly used distributions, fitGCP uses distributions tailored to account for common artifacts. The mixture models are iteratively fitted based on the Expectation-Maximization algorithm. Please find the accompanying paper here: http://dx.doi.org/10.1093/bioinformatics/btt147 -
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FABS
Fluorescence and absorption spectroscopy made easy
...FABS was designed with students in mind, as a way to help high schoolers and undergraduates learn about spectroscopy without paying for expensive equipment and software. Accompanying this software is a hardware design, which can be used as a bare-bones spectrometer that will provide quantitative absorption and fluorescence emission spectra at an extremely low cost. It uses only materials that many people can find around their home. -
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Luciano's Quant Blog
Assorted bits of code for quant development
This repo contains code that I share through my blog. It consists of assorted samples that will be useful to amateur quantitative developers or systematic traders. -
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colonyzer image analysis software
Image analysis estimating cell density in arrayed microbial cultures
Image analysis software for quantification of cell density in microbial cultures (e.g. S. cerevisiae) growing on solid agar plates. Specialises in detection of extremely low cell densities. Forms part of the Quantitative Fitness Analysis (QFA) workflow: http://research.ncl.ac.uk/qfa/ Suitable for high-throughput, genome-wide analysis of culture libraries when combined with the following qfa R package: http://qfa.r-forge.r-project.org/ This is the version presented, used and demonstrated in the following manuscripts: Lawless et al. 2010 http://dx.doi.org/10.1186/1471-2105-11-287 Addinall et al. 2011 http://dx.doi.org/10.1371/journal.pgen.1001362 Chang et al. 2011 http://dx.doi.org/10.1534/g3.111.000216 Banks et al. 2012 http://dx.doi.org/10.3791/4018 Development has been moved to github, where Colonyzer has undergone several recent improvements, particuarly making installation easier and analysis faster: https://github.com/CnrLwlss/Colonyzer -
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