Citadel, the multi-trillion dollar hedge fund and market-making behemoth, has hired William Dealtry, a key architect of Man Group's prized database, ArcticDB. This is a high speed data base.

The Simplicity Advantage: Why Streamlit Outshines Grafana and QuestDB for Trading Algorithm Simulations. There is a reason why you should...

Diversification Low Correlation Sharpe Ratio. Diversification spreads risk. Holding positions that react to different economic forces smooths out the bumps in your equity curve.

We will dissect the key metrics that signal opportunity, select prime candidates for our trading focus, and lay out detailed strategic plans for each.

On June 12th, a new frontier was unveiled—a system that represents the culmination of this evolution, demonstrating the incredible power of modern AI tools for crypto arbitrage trading with HFT market making. T

Let’s show how to calculate profit and loss for options contracts​This is where algorithmic analysis provides substantial value, enabling traders to systematically scan the vast options landscape to uncover the most advantageous opportunities.

In the sprawling, hyper-fast digital landscape of modern finance, data is more than just information; it is the lifeblood of every...

As passive investing continues to absorb a substantial share of assets under management, retail quants may emerge as a countervailing, stabilizing force within the market ecosystem.

The S&P 500 Surges which achieved a historic milestone this week, breaking through the psychologically significant 6,000 level as investors responded enthusiastically to encouraging employment data and renewed optimism surrounding US-China trade relations

Based on volatility, recent price momentum, and cash-and-carry options arbitrage strategy opportunities, we identify the five top instruments—BRR, CC, ES, GC, and ALI—with the greatest potential for 10–30-day profits.

Among these, the no arbitrage principle stands as arguably the most crucial. It's a deceptively simple idea: in a well-functioning market, there should be no "free lunch."

The cryptocurrency markets, with their hallmark of most volatile crypto, pervasive regulatory uncertainties, and relentless 24/7 trading cycles, present a uniquely challenging environment for human traders susceptible to emotional decision-making.

Navigating Economic Forecasts and Market Realities: From Replicating Inflation Models to Weekly Trading Signals

The conventional advice is clear: always use a stop loss to cap downside, and employ a stop loss trailing stop loss to protect profits while allowing successful trades to mature.

Now, as large language models (LLMs) like ChatGPT trading demonstrate increasingly sophisticated capabilities, a pressing question emerges: can these AI systems effectively serve as quantitative analysts for trading?

I’m thrilled to share with you an intriguing quantitative finance project that I’ve been working on. This particular project is coded in Python, and while I’ll be rolling out more advanced projects and demos in C++ as we dive deeper into advanced AI with tools like Anthropic, today’s focus is a simpler yet insightful example of pure quant finance. So, let’s check it out!

In this article, we will explore Retrieval-Augmented Generation (RAG), a powerful AI technique that combines database retrieval with large language models (LLMs) to enhance AI-generated responses. We will walk through a basic implementation using LangChain, OpenAI’s GPT, and a PostgreSQL/SQLite database for a trading application.

Minimalism in software development, particularly when leveraging the versatility of Python and its rich standard library, offers a powerful avenue for learning, rapid prototyping, and building specialized tools.

QuantLabs, a prominent name in providing resources and tools for quantitative traders and developers, has recently augmented its public collection of open-source tools with four sophisticated Python A.I. trading scripts.

High-Frequency Trading strategies represents a sophisticated and often complex segment of algorithmic trading, characterized by the rapid execution of a large volume of orders. At its core