Mohamed Salem Almansoori — E‑Portfolio

Self‑motivated student focused on financial markets and computer science. Skilled in Python and data analysis; building and backtesting quantitative trading models. Actively developing JavaScript skills and applied projects.

Contact

📧 m7md.sm22@gmail.com

Focus

Quantitative Trading Programming / Computer Science Backtesting Data Analysis

Skills, Qualities, and Extra‑Curriculars

Finance & Trading

  • CFD/Foreign Exchange
  • Quantitative strategy design
  • Backtesting & evaluation

Programming

  • Python (NumPy, pandas)
  • JavaScript (ES6)
  • Automation & data pipelines

Data & Validation

  • Monte Carlo simulations
  • Exploratory analysis
  • Visualization & reporting

Academic Qualifications

  • AP Computer Science Principles (Current) — The Sheikh Zayed Private Academy for Boys (SZPAB)
  • American Curriculum — GPA: 92.4% — The Sheikh Zayed Private Academy for Boys (SZPAB)
  • AP Human Geography — AP Score: 4 (July 2025)
  • IGCSE’s — Al Yasmina British Academy (July 2024)

Personal Projects

Advanced Quantitative Market Timing Models (Liquidity & Macro)

Personal Project | Jan 2024 – Present

Developed two models to predict intraday market inflection points and volatility peaks by incorporating liquidity and macroeconomic variables.

Open Interest Heatmap Analysis

Python‑based system to analyze open interest and highlight key activity levels; advanced interpolation with daily‑ready insights for strategy development.

Proofs

Liquidity‑Only Timing Model (T* Liquidity) — Formula & Explanation

Formula:
T* = T × [1 − (Change in RRP − Change in TGA)]

Purpose: Estimates the effective length of the trading day based on net liquidity injection or drainage; useful for predicting intraday volatility peaks or reversals.

Inputs:

  • Change in RRP: Reverse Repo Program delta (in trillions)
  • Change in TGA: Treasury General Account delta (in trillions)
  • T: Nominal trading session length (usually 10 hours)

Outputs:

  • T*: Adjusted session length
  • Median inflection time = 08:00 + T*/2 (UTC+2)
Full Macro Timing Model (T* Full Macro) — Formula & Explanation

Formula:
T* = T × [1 − (Change in RRP − Change in TGA + 0.5 × Change in 10Y Yield + 0.05 × Liquidity Shift + 0.5 × Change in SOFR)]

Purpose: Adds funding stress (SOFR), yield drift, and central bank balance sheet shifts for precision timing; best for predicting inflection windows and liquidity reversals.

Inputs:

  • Change in 10Y Yield: US10Y minus DE10Y
  • Liquidity Shift: Fed BS delta minus ECB BS delta (in trillions)
  • Change in SOFR: SOFR delta
  • Change in RRP and TGA as above

Outputs:

  • T*: Adjusted session length
  • Median inflection time = 08:00 + T*/2 (UTC+2)

References

Available upon request.