The Researcher You're Looking For
I’m an Aeronautical and Astronautical Engineering student at Purdue University focused on quantitative finance through the lens of physics and mathematics. My work in market equilibrium research, crypto microstructure strategy research, and nonlinear dynamics simulation shows a consistent pattern: I translate complex systems into mathematical structure and test whether the structure holds.
Deep Curiosity
I’m drawn to problems that sit between disciplines and resist easy answers. That curiosity is what led me from aerospace dynamics into market behavior.
Technical Depth
I’m comfortable working through differential equations, numerical methods, and stochastic structure. I prefer understanding the mechanism over relying on surface-level heuristics.
Collaborative Rigor
I value feedback from professors, researchers, and practitioners who can pressure-test my thinking. I’m open to correction when it makes the work sharper.
Initiative
I don’t wait for perfect conditions to start meaningful work. My strongest projects began as independent attempts to answer questions I genuinely cared about.
Learning Speed
I move quickly when a problem demands new tools or a new domain. That’s how I’ve built across engineering dynamics, economics, and quantitative trading research early on.
Delivery Focus
I care about whether a model can be tested, implemented, and defended. Even in research-heavy work, I push toward outputs that are concrete and usable.
The best models don’t just fit behavior — they explain why the system moves that way in the first place.
Derive, Test, Then Build
I work best on systems that look noisy at first but reveal order when modeled correctly. My process starts with first principles, moves through derivation and validation, and ends in models that can actually stand up to data.
Quant Research
I derive and test models for market behavior, equilibrium, and short-horizon price movement. My focus is on understanding the mechanism beneath the data, not just optimizing outputs.
Signal Design
I build features from dynamic behavior such as velocity, acceleration, curvature, and imbalance. These signals are designed to capture structure in price motion and order-book state.
Backtest Design
I build backtesting systems that prioritize realism over inflated results. That means controlling for look-ahead bias, invalid books, and unrealistic execution assumptions.
Physics Modeling
I translate physical intuition into mathematical systems that can be simulated, solved, and validated. That same habit carries from nonlinear dynamics into financial modeling.
Bring me in when the problem needs mathematical structure, not just statistical surface fit.
From Problem to Model
How I Work
Frame
I define the system clearly before touching the math or the code.
A precise problem statement beats a fast start.
Derive
I build the mathematical structure from first principles whenever possible.
If the assumptions are weak, the model will be too.
Test
I validate models against data, edge cases, and implementation constraints.
Interesting ideas only matter if they survive contact with reality.
Refine
I iterate until the model is both interpretable and useful.
Clarity and performance should improve together.
Building From Day One
An engineering foundation shaped by independent research and early quantitative finance work
B.S. in Aeronautical and Astronautical Engineering
Purdue University
- Expected graduation: December 2028
- GPA: 3.8
- Focused on applying physics and mathematics to financial systems
- Developing early research depth in dynamic systems, modeling, and quantitative finance
Quantitative Research Intern
Raedan Capital
- Researched fair-value prediction signals and strategies across multiple market regimes
- Worked on crypto markets including Bitcoin and Ethereum with 60%+ short-horizon directional accuracy in backtests
- Built Python backtesters with controls for look-ahead bias, crossed books, and realistic fills
- Developed regime-aware research around market-making and conditional directional trading
Independent Researcher, Nonlinear Dynamics
GICLM
- Built a custom RK4 numerical solver in Python for a bridge system with three uncoupled degrees of freedom
- Modeled periodic wind forcing using Newton’s Second Law and matrix-based differential equations
- Simulated structural resonance and identified instability in the rotational degree of freedom
- Extended numerical methods understanding in ways relevant to later financial modeling work
Technologies & Tools
Built through independent research, quantitative internship work, and engineering problem-solving
Programming
Mathematical Modeling
Quant Research
Signals & Statistics
Physics & Dynamics
Trading Infrastructure
What I've Built
Every project here starts with dynamic systems thinking and ends with a model tested against behavior.
Newtonian Dynamics of Market Equilibrium
I developed a market model under ceteris paribus conditions by mapping market behavior to free fall under linear drag. Starting from Newton’s Second Law, I derived analogous ODEs linking physical motion to supply-demand dynamics and tested the resulting framework against Vernon Smith’s 1962 data. After refinement, the model yielded the Ornstein-Uhlenbeck process precisely and offered a structural explanation for how markets move toward equilibrium. This project proved that I can take first-principles physics and turn it into credible financial modeling research.
Impact: <5% error on 22/28 data points | <10% error on 26/28 data points
Quantitative Research at Raedan Capital
At Raedan Capital, I researched fair-value prediction signals and strategy behavior across crypto markets, with a focus on Bitcoin and Ethereum. I designed and tested kinematics-inspired features including velocity, acceleration, curvature, and order-book imbalance to infer short-horizon price movement from local price geometry and book state. I also built Python backtesting systems that enforced realistic assumptions by preventing look-ahead bias, rejecting crossed books, and improving fill realism. This work proved that I can move from theoretical intuition to practical quant research infrastructure.
Impact: 60%+ directional accuracy in backtests | Per-trade Sharpe ≈ 0.5
RK4 Bridge Resonance Simulation
I studied a bridge system with three uncoupled degrees of freedom to explore how RK4 methods could be applied to a second-order physical system through a matrix-based formulation. Using Newton’s Second Law and a periodic forcing term to simulate wind, I modeled the system’s behavior and solved the resulting equations numerically in Python. The simulation showed that under the tested forcing conditions, the rotational degree of freedom became unstable and would fail. This project proved my ability to translate physical systems into solvable mathematical models and extract meaningful insight from simulation.
Impact: Simulated structural resonance behavior | Identified rotational instability under periodic forcing
Client Testimonials
What people say about working with me
"Aarush approaches economic systems with unusual mathematical maturity for an early-career researcher. In his market equilibrium work, he did more than summarize theory—he derived a fresh framework from first principles and tested it against historical data with discipline. What stands out is his willingness to connect physics, mathematics, and economics in a way that is both original and analytically grounded."
Todd Yarbrough
Economics Professor
Purdue University
"During his time at Raedan Capital, Aarush showed strong research instincts and a clear ability to think structurally about markets. He worked on fair-value prediction and regime-sensitive strategy research, while also helping build backtesting systems that avoided common pitfalls like look-ahead bias and unrealistic fills. He brings a rare mix of curiosity, rigor, and quantitative creativity to trading research."
Dhaval Shah
Director
Raedan Capital
"Aarush’s nonlinear dynamics project reflected the way he naturally works: he starts from physical intuition, translates it into mathematics, and follows the implications carefully. In his bridge resonance study, he modeled a multi-degree-of-freedom system, implemented a numerical solver, and identified instability in the rotational mode under periodic forcing. He is at his best when working on difficult problems that require both conceptual depth and technical execution."
Rumana Chaterjee
Teacher
GICLM
Let's Build Something Precise
I’m open to research-driven roles and collaborations in quantitative finance, derivatives modeling, and market microstructure. I’m based in West Lafayette and interested in opportunities that value mathematical rigor, dynamic systems thinking, and early ownership of difficult problems. If the work sits at the intersection of theory, modeling, and implementation, I want to hear about it.
"I bring physics-style reasoning into financial systems and turn dynamic behavior into testable models."
— Aarush Shah
© 2026 Aarush Shah. Transforming visions into reality, one solution at a time.