Awesome List Updates on Aug 14, 2023

8 awesome lists updated today.

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1. Awesome Quant

Python / Numerical Libraries & Data Structures

• modelx - Python reimagination of spreadsheets as formula-centric objects that are interoperable with pandas.

Python / Financial Instruments and Pricing

• OpenBB Terminal (⭐27k) - Terminal for investment research for everyone.

• pypme (⭐10) - PME (Public Market Equivalent) calculation.

• AbsBox (⭐32) - A Python based library to model cashflow for structured product like Asset-backed securities (ABS) and Mortgage-backed securities (MBS).

• Intrinsic-Value-Calculator (⭐17) - A Python tool for quick calculations of a stock's fair value using Discounted Cash Flow analysis.

Python / Trading & Backtesting

• basana (⭐494) - A Python async and event driven framework for algorithmic trading, with a focus on crypto currencies.

• pysystemtrade (⭐2.5k) - pysystemtrade is the open source version of Robert Carver's backtesting and trading engine that implements systems according to the framework outlined in his book "Systematic Trading", which is further developed on his blog.

• pytrendseries (⭐111) - Detect trend in time series, drawdown, drawdown within a constant look-back window , maximum drawdown, time underwater.

• PyLOB (⭐175) - Fully functioning fast Limit Order Book written in Python.

• PyBroker (⭐1.8k) - Algorithmic Trading with Machine Learning.

Python / Data Sources

• market-prices (⭐72) - Create meaningful OHLCV datasets from knowledge of exchange-calendars (⭐409) (works out-the-box with data from Yahoo Finance).

• tardis-python (⭐110) - Python interface for Tardis.dev high frequency crypto market data

• lake-api (⭐23) - Python interface for Crypto Lake high frequency crypto market data

• tessa (⭐40) - simple, hassle-free access to price information of financial assets (currently based on yfinance and pycoingecko), including search and a symbol class.

• pandaSDMX (⭐125) - Python package that implements SDMX 2.1 (ISO 17369:2013), a format for exchange of statistical data and metadata used by national statistical agencies, central banks, and international organisations.

• cif (⭐55) - Python package that include few composite indicators, which summarize multidimensional relationships between individual economic indicators.

• finagg (⭐410) - finagg is a Python package that provides implementations of popular and free financial APIs, tools for aggregating historical data from those APIs into SQL databases, and tools for transforming aggregated data into features useful for analysis and AI/ML.

Python / Visualization

• market-analy (⭐32) - Analysis and interactive charting using market-prices (⭐72) and bqplot.

R / Data Sources

• rb3 (⭐70) - A bunch of downloaders and parsers for data delivered from B3.

• simfinapi (⭐18) - Makes 'SimFin' data (https://simfin.com/) easily accessible in R.

Julia / FrameWorks

• DataFrames.jl (⭐1.7k) - In-memory tabular data in Julia

• TSFrames.jl (⭐92) - Handle timeseries data on top of the powerful and mature DataFrames.jl

JavaScript / FrameWorks

• PENDAX (⭐42) - Javascript SDK for Trading/Data API and Websockets for FTX, FTXUS, OKX, Bybit, & More.

Rust / Data Visualization

• Barter (⭐789) - Open-source Rust framework for building event-driven live-trading & backtesting systems

• LFEST (⭐51) - Simulated perpetual futures exchange to trade your strategy against.

• TradeAggregation (⭐65) - Aggregate trades into user-defined candles using information driven rules.

• SlidingFeatures (⭐40) - Chainable tree-like sliding windows for signal processing and technical analysis.

• RustQuant (⭐1k) - Quantitative finance library written in Rust.

Reproducing Works, Training & Books / Data Visualization

• Value Investing Studies (⭐81) - A collection of data analysis studies that examine the performance and characteristics of value investing over long periods of time.

• Machine Learning Asset Management (⭐1.7k) - Machine Learning in Asset Management (by @firmai).

• Deep Learning Machine Learning Stock (⭐1.2k) - Deep Learning and Machine Learning stocks represent a promising long-term or short-term opportunity for investors and traders.

• Technical Analysis and Feature Engineering (⭐109) - Feature Engineering and Feature Importance of Machine Learning in Financial Market.

• Differential Machine Learning and Axes that matter by Brian Huge and Antoine Savine (⭐135) - Implement, demonstrate, reproduce and extend the results of the Risk articles 'Differential Machine Learning' (2020) and 'PCA with a Difference' (2021) by Huge and Savine, and cover implementation details left out from the papers.

• systematictradingexamples (⭐293) - Examples of code related to book Systematic Trading and blog

• pysystemtrade_examples (⭐169) - Examples using pysystemtrade for Robert Carver's blog.

• ML_Finance_Codes (⭐1.6k) - Machine Learning in Finance: From Theory to Practice Book

• Hands-On Machine Learning for Algorithmic Trading (⭐1.4k) - Hands-On Machine Learning for Algorithmic Trading, published by Packt

• financialnoob-misc (⭐25) - Codes from @financialnoob's posts

2. Awesome V

Database clients

• vredis (⭐7) - A simple, user-friendly, and comprehensive Redis client.

3. Awesome Graphql

CMS / React

• Graphweaver - Turn multiple datasources into a single GraphQL API.

4. Awesome Git Addons

git-spend

Delete branches with day-offset

$ git branchcut execute -o 7
Switched to branch 'main'
Deleted branch bugfix/test (was e2afad6).
Deleted branch too-old-branch (was 1d3f82d).

Collect and sum the /spend <duration> directives found in commit messages.

$ git spend sum
3 weeks 2 days 1 hour 37 minutes

5. Awesome Substrate

Tools

• Polkadot Vault (formerly Parity Signer) - Upcycle an unused mobile phone into an air-gapped hardware wallet.

• Uptest Runtime upgrade tool (⭐7) - Uptest command line client and libuptest Rust library are two tools used for debugging storage changes and runtime upgrades.

6. Awesome Azure Openai Llm

RLHF (Reinforcement Learning from Human Feedback) & SFT (Supervised Fine-Tuning) / Llama Finetuning

• InstructGPT: Training language models to follow instructions with human feedback: [cnt] is a model trained by OpenAI to follow instructions using human feedback. [4 Mar 2022]
  
  
  cite

7. Awesome Neovim

(requires Neovim 0.5)

• roobert/action-hints.nvim (⭐74) - Show information about the word under the cursor in the statusline or as virtual text.

• roobert/hoversplit.nvim (⭐38) - Automatically updated documentation and information about code symbols in a split window.

Programming Languages Support / Diagnostics

• roobert/f-string-toggle.nvim (⭐29) - Toggle python f-strings.

Web Development / Diagnostics

• roobert/tailwindcss-colorizer-cmp.nvim (⭐321) - Add vscode-style TailwindCSS completion to nvim-cmp.

Syntax / Diagnostics

• roobert/surround-ui.nvim (⭐76) - Helper or training aid for kylechui/nvim-surround.

Tabline / Diagnostics

• roobert/bufferline-cycle-windowless.nvim (⭐38) - A bufferline extension to cycle through windowless buffers to give a more traditional tab based experience.

Motion / Diagnostics

• roobert/tabtree.nvim (⭐37) - Jump between significant code elements, such as brackets, quotes, etc.

8. Awesome Fiber

🚧 Boilerplates / 🌱 Third Party

• amrebada/go-modules (⭐11) - Nest JS like structure for Go Fiber.

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