There are 18 repositories under asset-allocation topic.
Portfolio Optimization and Quantitative Strategic Asset Allocation in Python
Quantitative analysis, strategies and backtests
Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy
Helps you with managing your investments
Conditional Value-at-Risk (CVaR) portfolio optimization and Entropy Pooling views / stress-testing in Python.
Fixed Income Analytics, Portfolio Construction Analytics, Transaction Cost Analytics, Counter Party Analytics, Asset Backed Analytics
Asset Allocation application
Fixed Income Analytics, Portfolio Construction Analytics, Transaction Cost Analytics, Counter Party Analytics, Asset Backed Analytics
Python financial widgets with okama and Dash (plotly)
A flask web app that analyzes your stock portfolio performance, optimizes your asset allocation, and provides performance enhancement alerts.
portfolio-backtest is a python library for backtest portfolio asset allocation on Python 3.7 and above.
This repository consists several bots encoding various algorithmic trading strategies. The aim here is for absolute beginners in stock trading to get familiar with the various aspects of the market. All you need is basics of statistics and python to understand the underlying metrics and conditions utilized to make decisions. Contributions welcome.
Implements different approaches to tactical and strategic asset allocation
Backtesting of different trading strategies by applying different Modern Portfolio Theory (MPT) approaches on long-only ETFs portfolios in Python.
Entropy Pooling in Python with a BSD 3-Clause license.
Value or Momentum? Comparing Random Forests, Support Vector Machines, and Multi-layer Perceptrons for Financial Time Series Prediction & Tactical Asset Allocation
Integrating ESG scores into asset allocation and portfolio optimization through a GUI application.
DRIP Asset Allocation is a collection of model libraries for MPT framework, Black Litterman Strategy Incorporator, Holdings Constraint, and Transaction Costs.
This R Shiny App utilizes the Hierarchical Equal Risk Contribution (HERC) approach, a modern portfolio optimization method developed by Raffinot (2018).
Modern Portfolio Theorem for portfolio optimization and asset allocation
Portfolio rebalancing for the finicky investor. A tool that keeps your assets allocation well balanced
RESTful API for prometheus (stock portfolio allocation & analysis)
Asset Allocation implementation in Python
PDF Statement Data Extractor and Analyzer. A Python script for extracting and analyzing financial data from PDF statements, with a focus on Schwab statements.
Cross asset allocation with mean-variance and mean-CVaR (Expected Shortfall) optimization methods
Master thesis project. The improved estimator of the covariance matrix of asset returns is employed to derive a new trading strategy based on a two-step procedure. First, it shrinks the asset universe via a subset selection, leaving only the most suitable assets. Then, it performs the mean-variance analysis. Back-testing is carried out in the U.S. stock market between 2018 and 2020. For comparison purposes, the code also implements also other strategies, such as the widely-used momentum strategy. The proposed technique is observed to deliver a very good and much more stable performance with respect to its competitors.
Data Analysis And Simulation Of Asset Allocation Strategies For Investing Using Python.
Asset Allocation Strategy using Stock2Vec Clustering
ESG investing web app that takes user inputs to generate personalized equity portfolios and even comparative firm ESG rankings.
Asset Allocation of stocks using quantitative methods