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QuantLabsNet.com Public Quant Analytics Group

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Behind the Scenes of Our Algo Trading Engine – Development, Strategy Selection, AI Roles, and More


First off, a quick shout‑out to everyone who joined the live stream tonight – the video, audio, and chat all ran smoothly, which set the perfect stage for a deep‑dive into the world of algorithmic trading. Below is a condensed, yet comprehensive recap of the discussion, expanded with a bit of context to give you the full picture.


1. The Engine’s Development Lifecycle

One of the first questions that came up was about the process we follow when building a trading engine from scratch. The answer isn’t a one‑size‑fits‑all recipe, but most projects follow a familiar cadence:


  1. Idea Generation & Hypothesis – We start with a market observation or a pattern that looks exploitable. This could be a statistical anomaly in price data, a reaction to macroeconomic news, or a microstructure signal gleaned from Level‑2 order flow.

  2. Research & Back‑testing – The hypothesis is tested against historical data using a combination of…


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Lessons From a Quiet Night: What Our C++20 Trading Bots Taught Us About High-Frequency Trading


A forensic analysis of overnight execution logs from a live C++20 / Redis / Rithmic trading stack — July 23–24, 2026


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## 1. Executive Summary


Between 22:10 on the evening of July 23 and roughly 11:00 the following morning, a fleet of nine C++20 strategy bots ran against a Rithmic market-data gateway fronted by a Redis pub/sub bus. The headline number is simple: across more than 15,000 log lines, the system recorded zero trades, zero fills, and zero realized profit and loss. Every heartbeat, in every bot, read `position:0, cumulative_pnl:0.000000`.


A casual reader might call the night a failure. That conclusion would be wrong. Buried inside the structured JSON logs is a rich, honest record of how a low-latency trading system actually behaves when it is healthy enough to ingest live market data but disciplined enough not to fire orders into a market that did not meet its entry…


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Would You Deploy a 3.40 Sharpe Strategy With Only 13 Trades? My 4-Bot NQ Sleeve + the Framework I Used to Decide

Hey all,


Sharing a case study from this week because it forced me to confront the 

small-sample problem in a very concrete way — curious how others handle it.


THE SETUP

My combined backtest fleet (319 profitable bots, 2yr 4h bars) produced a 

4-bot long Nasdaq futures sleeve this week:


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Mastering Derivative Markets: Core Concepts and Course Topics


Hello everyone!

As requested, here is the streamlined list of the specific topics covered in our Advanced Futures and Options course materials for the 2026 academic year. This list strips away the module groupings so you can see exactly which concepts, theories, and practical applications we will be tackling:


  • Historical Perspective and the Birth of Standardization: The evolution from forward contracts to the Chicago Board of Trade (CBOT).

  • Core Market Mechanics: The role of the clearinghouse, initial and maintenance margin requirements, and daily mark-to-market settlement.

  • The Hedger's Dilemma: Understanding and implementing long vs. short cash positions.

  • The Critical Role of Basis Risk: Calculating the basis and understanding how widening or narrowing basis impacts hedging outcomes.


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