Navas & Co. is an investment management firm that employs mathematical and statistical methods in the design and execution of its investment programs.
Founded in 2016. One data-driven approach, applied uniformly across every fund we manage, from offices in Beverly Hills, Cambridge, Austin and New York.
Hypotheses, not hunches
Every strategy begins as a testable claim about how markets behave. It survives only if the data agrees, out of sample and after costs.
Research that runs in production
The same code that evaluates an idea trades it. Our research database, data pipelines and execution systems are one engineered whole, running on redundant facilities each able to carry the firm's trading alone.
Sized to be wrong
Portfolios are constructed so that no single model, market or assumption can determine the outcome. Risk is measured continuously and managed by rule.
In our field, alpha is the return that remains after the market has been accounted for. It is small, it is scarce, and it is the only thing worth measuring.
We built the firm around finding it with discipline: careful data, honest statistics, and the humility to discard most of what we try.
A small group of researchers and engineers who would rather be correct than busy.
We hire people from mathematics, physics, statistics and computer science, and we give them the data, computing and time to do serious work. Teams are small. Credit is shared. Arguments are settled by evidence.
A quantitative investment firm, founded in 2016.
Navas & Co. is an investment management firm that employs mathematical and statistical methods in the design and execution of its investment programs. We manage capital for institutions and qualified investors through systematic strategies in liquid global markets.
One research platform, one risk framework, one team.
Navas & Co. was founded in 2016 on a simple conviction: that markets can be studied with the same care as any other empirical system, and that the discipline to do so, consistently and over long periods, is itself a durable advantage. A decade on, that conviction is reflected in everything about the firm, from the people we hire to the way we size a position.
We apply one uniform, data-driven approach across all of the funds we manage. Every fund draws on the same research database, the same risk framework and the same execution infrastructure, so that what we learn in one program improves all of them.
We are privately held and independent, and we have a significant investment in the funds we manage. Our interests are aligned with those of our investors because we are investors ourselves.
Headquarters. Investment management, portfolio oversight and investor relations.
Research and engineering. Our largest technical group, close to the universities we recruit from.
Satellite office. Engineering and trading-systems support.
Investor relations and trading. Our presence in the financial capital, close to counterparties and clients.
Evidence over narrative
We hold positions because the data supports them, and we exit when it stops. We do not have market views; we have models.
Independence
We answer to our investors and to the evidence. Decisions are made by people who have no incentive other than being right.
Long horizons
We judge strategies, and people, over years rather than quarters. Durable results come from patience with method and impatience with error.
Candor
We report what happened, including what went wrong, in plain language. Our investors should never learn something about us from someone else first.
We treat investing as an empirical science.
Our investment programs are designed and executed by quantitative methods. Decisions are made by models that have been specified in advance, tested on historical data, and reviewed against live results. People design and supervise the system; the system trades. The same data-driven approach is applied uniformly across every fund we manage.
Hypothesis
A specific, falsifiable claim about price behavior, with a reason it should exist and a reason it has not already been arbitraged away.
Data
Point-in-time datasets, cleaned and versioned, so that a test sees only what was knowable at the time.
Evaluation
Out-of-sample testing, realistic transaction costs and explicit penalties for the number of things we tried. Most ideas stop here.
Portfolio construction
Signals are combined and sized under risk, liquidity and turnover constraints, as one portfolio rather than a collection of bets.
Execution
Orders are worked by algorithms that minimize market impact. Fills are measured against the model's assumptions every day.
Review
Live performance is compared to expectation. Models that drift are investigated; models that fail are retired.
Liquid, global, and tradable at scale.
We operate in markets with deep liquidity and reliable data: equities, equity index and fixed-income futures, currencies and commodities across developed and selected emerging exchanges. Breadth matters to us; a modest edge applied across many independent positions compounds more reliably than a large edge applied to a few.
Holding periods range from intraday to several months. Programs are run from a single risk framework so that exposures are understood in aggregate rather than strategy by strategy.
Built for a decade of research, and for the day something fails.
At the center of the firm is a growing research database: ten years of cleaned, point-in-time market and alternative data, together with every hypothesis we have tested against it and how each one fared. New research starts from that record rather than from scratch, and the database compounds in value as the firm does.
Trading runs on redundant computational facilities, each fully capable of supporting our operations on its own. Markets, data feeds and order flow are mirrored across sites, so the loss of any one facility does not interrupt a trading day.
Hard problems, real data, and the time to think.
We look for people who are rigorous by temperament and curious by habit. Prior finance experience is not required; mathematical maturity and strong programming are. Everyone who joins receives on-the-job training in quantitative portfolio management, working alongside people who have built and run these strategies for a decade.
Quantitative Researcher
Develop and test systematic strategies from first idea to live trading. PhD or equivalent depth in a quantitative field; fluency in Python and statistics.
Research Engineer
Build the tools researchers use every day: data pipelines, simulation, feature stores. Strong Python and C++ or Rust; care about correctness and performance.
Software Engineer, Trading Systems
Own low-latency execution and market connectivity. Experience with networking, concurrency and production reliability.
Investor Relations Associate
Support relationships with institutional investors and prepare the firm's reporting. Clear writing, numeracy and discretion.
Quantitative Research Intern
A ten-week research project with a mentor, on a question that matters to the firm. Open to PhD and advanced master's students.
To apply, send a CV and a short note on a problem you have enjoyed solving to the careers address on the contact page.
Rigor
You check your work, state your assumptions and are suspicious of results that look too good.
Range
You are comfortable moving between a proof, a dataset and a code review in the same afternoon.
Clarity
You can explain what you did and why, in writing, to someone who was not in the room.
Judgment
You know the difference between a result and a finding, and when to stop.
Four conversations, one decision.
Introduction
A call about your background and what you want to work on.
Technical
Two sessions on mathematics, statistics and programming, matched to the role.
Research discussion
You present work you are proud of and we take it apart together.
Decision
We tell you promptly, either way.
Get in touch.
We respond to all serious inquiries. Information about our investment programs is available to qualified investors on request.
150 South Rodeo Drive
Beverly Hills, CA 90210
20 University Road
Cambridge, MA 02138
201 W 5th Street, 16th Floor
Austin, TX 78701
386 Park Avenue South
New York, NY 10016
General
info@navasfund.comPress and general inquiries.
Investor relations
ir@navasfund.comFor qualified and institutional investors.
Careers
careers@navasfund.comCV and a short note. No agencies, please.