Daniel Wasserman

I am a programmer with a background in physics and passion for quantitative analysis. My expertise is in data-driven problem solving in Python and Go- I have additional experience working with Java, C++, JavaScript, MATLAB, and HTML. I'm also a cryptocurrency enthusiast, often pondering how decentralized technologies can lay the foundation for the technology rails of the future.

Coding Projects

I'm usually building software projects in Python, Go, Java, Javascript, C++, MATLAB, and more. Below you can find insight into my interests and skillsets. I always have some side projects in the queue that are not quite ready to be open-sourced.

Volatility Surface Visualizer

A surface plot visualization of the cryptocurrency options market's expectation of volatility. Data is queried and served directly from Deribit's API. Plot implied volatility as a function of delta or strike vs time to expiration.

Prediction Market Monitor

A web app for viewing statistics on the world's top betting markets. Data is collected from Predictit, Betfair, and more.

Quantitative Trading Algorithms

In my free time I enjoy designing and implementing trading algorithms. While most of these strategies involve market making and momentum seeking, these algorithms are currently closed-source.

Research

I have conducted undergraduate research during my time in the Physics department at Washington University in St. Louis, as well as independent research on growing cryptocurrency technology and quantitative trading.

Forecasting Cryptocurrency Volatility

My senior honor's thesis at Washington University in St. Louis consisted of creating models for predicting volatility in the cryptocurrency markets and comparing them to benchmark models used in conventional finance.

Radix Simulator

A simulation framework for the Radix tempo protocol specification, a sharded distributed ledger technology designed for high throughput (https://docs.radixdlt.com/kb/learn/whitepapers/tempo)

Grid Search Optimization

Optimized a grid search algorithm for approximating systems under financial stress using parallelization techniques in MATLAB. Research was conducted under the Systems Engineering department at Washington University in St. Louis.

Other Interests

My other hobbies include poker, soccer, music, and exploring the outdoors. You can often find me at the poker tables or running on the hiking trails of Los Angeles.


Connect with me on GitHub, Twitter, and LinkedIn. You may reach me by email at dwasserman@protonmail.com.