About Vectara Capital

A systematic approach to
alpha generation

Vectara Capital is a quantitative investment firm that applies rigorous data science, multi-factor models, and institutional-grade risk management to identify structural alpha across global equity markets.

Core Principles

What guides our process

01

Systematic Rigor

Every investment decision is grounded in quantitative analysis. Our models synthesize hundreds of data points into actionable signals with measurable statistical properties.

02

Risk-First Architecture

Inspired by multi-manager platforms, our risk engine operates independently from alpha generation. Drawdown limits, exposure caps, and automated circuit breakers protect capital before profits.

03

Research Intensity

We believe alpha decays and markets evolve. Continuous factor research, walk-forward validation, and adaptive weight calibration ensure our models remain relevant across regimes.

04

Transparency of Process

Every position is accompanied by a detailed investment thesis — a narrative that explains why the data supports the trade, bridging quantitative signals with fundamental understanding.

Leadership

Selim

Founder & Chief Investment Officer

Drawing from deep experience in investment banking and capital markets, Selim founded Vectara Capital to bridge the gap between institutional quantitative investing and modern data science.

His approach combines the analytical rigor of traditional fundamental analysis with systematic factor models and computational methods, creating an investment process that is both intellectually rigorous and operationally scalable.

Prior to founding Vectara Capital, Selim built extensive experience in financial advisory and capital allocation across multiple sectors and geographies.

Capabilities

Quantitative Research

//Multi-factor alpha models across fundamental, technical, sentiment, and macro dimensions
//Walk-forward backtesting with strict out-of-sample validation
//Adaptive signal combination with information coefficient weighting
//Factor decay analysis and regime-conditional performance tracking

Risk Management

//Historical and Monte Carlo Value-at-Risk modeling
//Stress testing across historical and hypothetical scenarios
//Pod-level drawdown management with automated kill switches
//Real-time exposure monitoring — gross, net, sector, factor

Technology

//Proprietary alpha engine with 11 orthogonal factors
//NLP-driven sentiment analysis using financial language models
//Institutional-grade execution with transaction cost optimization
//24/7 monitoring with automated alerting and reporting

Partner with Vectara Capital

We welcome conversations with institutional allocators, family offices, and qualified investors who share our commitment to systematic, research-driven investing.

Get in Touch