Abacus
Unverified ML strategy on Multi by Sinbad-The-Sailor. BotFinder score 18 out of 100.
Automatic optimal sequential investment decisions. Forecasts made using advanced stochastic processes with Monte Carlo simulation. Dependency is handled with vine copulas.
Source: github
BotFinder analysis pending.
Abacus
Abacus Automatic sequential investment decisions. Utilizing realistic market simulations to solve portfolio optimization and risk management. Currently only working for domestic stocks. Work in progress. Table of Contents - Getting Started - Portfolio Optimization - Forecasting - Equity Models - Vine Copula Dependency Structure - Risk Management - References Getting Started Portfolio Optimization For portfolio optimzation there are two paradigmes which utilizes the simulation tensor. Stochastic Programming (SP) and Model Predictive Control (MPC). The main difference being SP utilizing all scenarios for one time period, while MPC considers the average scenario over multiple time periods. The implemented models yield different results and can be modified with additional constraints and asset classes to suit any investor. 1. Maximize Expected Utility Domestic Stocks (Stochastic Programming) $$ \begin{align} \text{max} \quad & \mathbb{E}\Big[ U\Big( x1^{\text{cash}} + \sum{a \in A} p{1,a}^{\text{mid}} x{1,a}^{\text{hold}} \Big) \Big]\\ \text{s.t} \quad & x{1,a}^{\text{hold}} = h{0,a}^{\t
⚠ No verified equity curve — no track-record source connected.
Drawdown profile
Data unavailable — contact the owner.
Verification ledger
How the score has moved
Recalculated at each data collection. Transparency means showing the bad weeks too.
No score history is stored yet — only the current score is shown.
Reviews & comments
No reviews collected from the source yet.
⚠ No live verification account connected — ask for proof before buying.
Alerts on changes: coming soon
Prop-firm compatibility not provided.
Open-source maintainer on GitHub.
Data-completeness & trust index (not a profitability rating)