Pareto: Next-Gen Trading

Introduction

Similar to Tesla's mission to reduce driving risk with autonomous vehicles, Pareto aims to minimize investment risk with autonomous trading. I approached this through a marketplace of robust trading algorithms and a community of open-source builders to compete for the best trading strategy.

The Technology Stack Behind Pareto

Before delving into the intricacies of Pareto, a basic overview of the tech stack that supports it will be helpful.

At the core of Pareto's server-side operations is Golang, a statically typed, compiled language lauded for its simplicity, efficiency, and resilience. Golang forms the backbone of Pareto's microservice architecture, overseeing user operations, backtesting, and algorithm hosting.

To ensure streamlined deployment, these Golang services are dockerized and then uploaded to Azure Container Registry (ACR), where they are dispatched onto an Azure Kubernetes Service (AKS) cluster. This cluster choreographs the microservices, ensuring their scalability and seamless interaction.

For running intensive backtests on trading strategies, Pareto employs Azure Functions, supplying the necessary compute power to assess the efficacy of varying algorithms. Data storage and management is entrusted to Postgres Flex, promising robust and scalable data services.

On the client-side, Pareto stands solo on the iOS ecosystem with a front-end built with SwiftUI and UIKit. While originally, the application leaned entirely on UIKit, a subsequent transition to SwiftUI allowed for quicker iteration while maintaining pixel-perfect design, amplifying the overall user experience.

The Innovation: Trading Strategy Marketplace

The unique selling point of Pareto, distinguishing it from conventional trading applications, is its exclusive marketplace. Here, algorithm builders have the liberty to publicize their own trading strategies. These strategies are then accessible for users to trade with, enabling builders to generate passive income. This marketplace breeds efficiency, as weaker algorithms are naturally phased out in favor of stronger, more reliable ones.

Moreover, Pareto takes a leap forward by allowing users to select these trading strategies and trade on their behalf. This innovation enables users to transition from emotional, manual trading to harnessing years of financial education at their fingertips. Pareto aspires to be the most dynamically intelligent trading platform, all the while striving to maintain maximum transparency for its users.

The Inspiration Behind Pareto

In 2019, the stark reality hit retail traders when a majority of Robinhood users experienced losses throughout the year. This incident underscored the need for a fresh approach to trading—one that reduces dependence on inexperienced users making trades based on emotion, and instead promotes data-driven decisions rooted in technical analysis and statistics.

While automated trading solutions like Acorns or Stash address this issue to some extent, they often fall short in providing transparency. Users, understandably, wish to have a say in how their money is traded. They want a glimpse into their investment activities, a sentiment that conventional automated trading fails to deliver. Pareto tackles this by developing a trading strategy marketplace that merges the security of robust trading strategies with the exhilaration of active trading.

Challenges and Solutions

Pareto's journey has not been without challenges. A significant hurdle was the need to run a distinct instance of each algorithm for every user to maintain high-frequency trading performance. The expenses related to this approach can be considerable, so a careful integration into the business plan is essential.

While alternatives exist, they often compromise performance—a trade-off that conflicts with Pareto's vision. Moving forward, innovative solutions to scale the trading algorithm instances without skyrocketing costs will be key. A possibility worth exploring could be a low-cost options to be added to an execution queue, rather than having your very own instance.

Design Philosophy

Building Pareto was not only about developing robust tech infrastructure. It was also about delivering a user-friendly experience that fosters trading education and risk awareness. The challenge was to display complex financial data, such as a Sharpe ratio, in an intuitive manner to avoid overwhelming users. How can you get a user to understand semi-advanced statistics before they decide to look at something else on their phone? A definition modal doesn’t cut it.

The solution lay in the power of visualizations. By presenting complex statistical data through dynamic live visuals, users can understand what's happening in real-time and appreciate the risk associated with different trading strategies. As Pareto continues to evolve, visualizations will remain central to its design philosophy.

Takeaway

Overall, the lesson to be learned is there is a lot of space for innovation in the trading space. Today, trading methods are archaic and haven’t kept with the pace of many other technological movements, but the reasons are mostly just political, not technical. My hope is that Pareto is just one of many solutions to bring far better financial technology to the average human.

[ Zach Coriarty ]