Quant-Trading-Dashboards

Unverified Arbitrage strategy on Indices by SergioIommi. BotFinder score 18 out of 100.

Equities Pair Trading/Statistical Arbitrage and Multi-Variable Index Regression

Source: github

Explorer/Indices/Quant-Trading-Dashboards
18
Data index
IndicesArbitrageMedium risk⚠ Unverified

Quant-Trading-Dashboards

SergioIommiGitHub
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Net return
—
Max drawdown
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Sharpe
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Profit factor
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Win rate
—
Track record
3.1y
BotFinder Analysis

BotFinder analysis pending.

About

Quant-Trading-Dashboards

Equities Pair Trading/Statistical Arbitrage and Multi-Variable Index Regression Small project to experiment with Plotly Dash and MongoDB (NoSQL database) by designing and building a full application to provide an interactive dashboard for traders to easily backtest equities pair trading/statistical arbitrage strategies on US single stocks (Nasdaq-100, S&P 500, Russell 2000) and investigate equity index vs single stock relationships. Video Demonstration - https://www.youtube.com/watch?v=nKMXSsmpTvA Screenshots Equities Pair Trading/Statistical Arbitrage Multi-Variable Index Regression Database (MongoDB) GUI Setup/Install - For the 2 apps I use MongoDB and Python (with few libraries) so before being able to run the apps in a Jupyter Notebook or as Python scripts, directly from the terminal to open them in a browser, we need to install and configure both. - The development and testing for the apps and the database backend have been done under Linux (Ubuntu 22.04.2 LTS) so this guide and steps are the ones I’ve run on such OS, but hopefully they will work on other OS with no/minor adjust

Jupyter NotebookOpen-sourcedashdashboardfeature-selectionkalman-filterlinear-regressionmachine-learningmean-reversionmongodb
Track record

⚠ No verified equity curve — no track-record source connected.

Risk

Drawdown profile

Data unavailable — contact the owner.

Evidence

Verification ledger

Live-audited
Broker-verified
Capital-backed
Tamper-proof
Historical evolution

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.

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Live monitoring

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Alerts on changes: coming soon

Prop-firm compatibility

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Source
SergioIommi
Since 2011 · 1 bots

Open-source maintainer on GitHub.

Trust 0Profile
Score & reliability18/100
Perf data0/35
Community0/25
Evidence8/20
Recency10/10
Verification0/10

Data-completeness & trust index (not a profitability rating)

Source facts
Stars24
Forks7
Open issues0
LanguageJupyter Notebook
License—
Last update2023-11-01
Created2023-08-24
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