Data Analysis And Simulation Of Asset Allocation Strategies For Investing Using Python.

DRIP Asset Allocation is a collection of model libraries for MPT framework, Black Litterman Strategy Incorporator, Holdings Constraint, and Transaction Costs.

Fixed Income Analytics, Portfolio Construction Analytics, Transaction Cost Analytics, Counter Party Analytics, Asset Backed Analytics

An F# analysis tool for the Scalable Capital robo-advisor

Asset Allocation implementation in Python

RESTful API for prometheus (stock portfolio allocation & analysis)

A flask web app that analyzes your stock portfolio performance, optimizes your asset allocation, and provides performance enhancement alerts.

Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy

Implemented stochastic CVaR model for the optimal asset allocation together with the Bootstrapping and the Monte Carlo scenario generation methods.

Investment Funnel

investment portfolio optimization, mean-variance analysis

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.

Backtesting of different trading strategies by applying different Modern Portfolio Theory (MPT) approaches on long-only ETFs portfolios in Python.

portfolio-backtest is a python library for backtest portfolio asset allocation on Python 3.7 and above.

A simple automated workflow for: 1) identifying investor indifference characteristics 2) strategic asset allocations with optimal risk-return

Calculator for rebalancing investment portfolios using the cash flow strategy.

An algorithmic approach to predicting US Sector ETF price movement using machine learning techniques. The goal was to create an asset allocation framwrok using ETFs as proxies for secotr behavior, and to test different clustering and predictive models to accomplish this goal using the R programming language.

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.…

Whale Return Homework