iExSan
++Ↄ E x S a n C++ |
The blog currently includes the following entries:
- About ExSan
- ExSan's Novel Data Structure
- Setting Up Backtesting Scenarios for High-Frequency and Low-Latency Trading
- Advanced Clustering Technique for High-Frequency Low-Latency Analysis
- Algorithm for Large-Scale Sparse Covariance Matrix
- Quantum Computing
- Blockchain, Cryptocurrency, and Digital Money
**Exploring Probable Applications and Opportunities for ExSan**
I may add more entries in the future to further develop the blog. Please feel free to explore the content and share it with your peers if you find it interesting.
The Role of Red-Black Trees in Quantitative Finance: A Reflection on ExSan’s Foundations
This LinkedIn post highlights the foundational importance of Red-Black Trees in the development of software for Quantitative Finance. From the inception of ExSan, I made a deliberate choice to base its coding architecture on Red-Black Trees —a decision driven by their efficiency and robustness-.
To my surprise, I recently came across that post revealing how a leading corporation leverages the same concept for its Quant Finance software This discovery reinforces the value of ExSan’s design principles and validates the independent, innovative approach that guided its development. -read the comments- It’s exciting to see how these ideas align with industry practices, underscoring the relevance of ExSan’s foundations in addressing complex financial challenges.
EXSAN currently exceeds 100 000 lines of source code in C++
Contact
Kindest regards,
Roberto Santander (Resume)
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