When Nanoseconds Matter: Ultrafast Trading Systems in C++
Matter: Ultrafast Trading Systems in C++ CppCon 2024 Thursday, 19 September 2024 David GrossIntroduction 2 • About me - Leading the Options Automated Trading Systems team at company - Worked on low-latency systems for 15 years in Trading and DefenseIntroduction 3 • About me - Leading the Options Automated Trading Systems team at Optiver, a global market maker company - - Worked on low-latency systems for 15 years in Trading and Defense • Today’s talk - Engineering low-latency trading systems - Profiling techniques to find bottlenecks - Some principles along the way4 0 码力 | 123 页 | 5.89 MB | 5 月前3Behavior-driven Tests for Microservices-based Algo Trading System
engineer on the electronic trading team at Bloomberg. He has more than 10 years of experience developing financial software, with a specialization in algorithmic trading and pricing systems. He is quant trading systems and reliable software. He holds a master's degree in computer science from Columbia University. Title : Behavior-driven Tests for Microservices-based Algo Trading System natural language style for a microservices-based algo trading system that our engineering team is responsible for. Relevance : For our electronic trading business, it is important to thoroughly test algo0 码力 | 1 页 | 65.24 KB | 5 月前3Building Safe and Reliable Surgical Robotics with C++
the default choice but is not a silver bulletFinal Words 66Trade offs 67 ❖ Trading off performance for safety? ❖ Trading off correctness for safety? ➢ In many cases but not always! Avoiding DMA and slow for others! ➢ Characterize/measure performance implications!Trade offs 68 ❖ Trading off cost for safety? ❖ Trading off flexibility for safety? ➢ All the tooling and processes to mitigate safety issues0 码力 | 71 页 | 4.02 MB | 5 月前3Rethinking Task Based Concurrency and Parallelism for Low Latency C++
Michael A Maniscalco ○ Software Architect and Principal Developer at Lime Trading ○ We develop low latency market data and trading software for use in HFT ● Personal ○ github.com/buildingcpp ■ Work Contracts Execute Logic(Data) Thread Thread Pool Thread ThreadThis Talk: cppcon2024.sched.com Lime Trading: Lime.co Source Code: github.com/buildingcpp/work_contract Contact: wc@michael-maniscalco you to Neva, Dar, Anni, Andrei and Lime TradingQuestions?This Talk: cppcon2024.sched.com Lime Trading: Lime.co Source Code: github.com/buildingcpp/work_contract Contact: wc@michael-maniscalco0 码力 | 142 页 | 2.80 MB | 5 月前3Multi Producer, Multi Consumer, Lock Free, Atomic Queue
com/erez-strauss/lockfree_mpmc_queueAbout me ● C++/C development for over 25 years ● Low Latency - Trading platforms ● Worked in both banks and hedge funds ● Github: https://github.com/erez-strauss ● LinkedIn: MPMC Queue https://github.com/erez-strauss/lockfree_mpmc_queueLockfree, MPMC Queue - Agenda 1. Trading Platform, Latency 2. Queues Environment 3. Queues Requirement 4. Atomic hardware and C++ Atomic MPMC Queue https://github.com/erez-strauss/lockfree_mpmc_queueLockfree, MPMC Queue - Background ● Trading platform - every message is tracked, at microseconds resolution ● Queues are essential data structure0 码力 | 54 页 | 886.12 KB | 5 月前3Course introduction - CS 591 K1: Data Stream Processing and Analytics Spring 2020
Monitor energy consumption for billing purposes 22 Vasiliki Kalavri | Boston University 2020 Stock trading • Discover correlations, identify trends, forecast future values Examples • Find all stocks priced where in the last 5 minutes the average volume has surged by more than 300%. • Find all stocks trading above their 200-day moving average with a market cap greater than $5 Billion that have gained in0 码力 | 34 页 | 2.53 MB | 1 年前3Apache RocketMQ – Trillion Messaging in Practice
Notify Born from multicolored stone project, designed for Taobao B2C Trading Napoli ActiveMQ kernal, designed for B2B Trading and other scenarios MetaQ v1.0 Designed for ordered message,0 码力 | 48 页 | 2.55 MB | 1 年前3Hyperledger Fabric 1.4.9 Documentation
Documentation, Release master (continued from previous page) Face value = 5M USD Current state = trading The most significant change is that of Owner – see how the paper initially owned by MagnetoCorp corresponding change to Owner. Note how Current state allow us to easily identify that the paper is now trading. After 6 months, if DigiBank still holds the the commercial paper, it can redeem it with MagnetoCorp: We’ve seen that paper 00001’s lifecycle is relatively straightforward – it moves between issued, trading and redeemed as a result of an issue, buy, or redeem transaction. These three transactions are initiated0 码力 | 483 页 | 7.48 MB | 1 年前3Hyperledger Fabric 1.4 Documentation
Documentation, Release master (continued from previous page) Face value = 5M USD Current state = trading The most significant change is that of Owner – see how the paper initially owned by MagnetoCorp corresponding change to Owner. Note how Current state allow us to easily identify that the paper is now trading. After 6 months, if DigiBank still holds the the commercial paper, it can redeem it with MagnetoCorp: We’ve seen that paper 00001’s lifecycle is relatively straightforward – it moves between issued, trading and redeemed as a result of an issue, buy, or redeem transaction. These three transactions are initiated0 码力 | 483 页 | 7.48 MB | 1 年前3Hyperledger Fabric 1.4.8 Documentation
Documentation, Release master (continued from previous page) Face value = 5M USD Current state = trading The most significant change is that of Owner – see how the paper initially owned by MagnetoCorp corresponding change to Owner. Note how Current state allow us to easily identify that the paper is now trading. After 6 months, if DigiBank still holds the the commercial paper, it can redeem it with MagnetoCorp: We’ve seen that paper 00001’s lifecycle is relatively straightforward – it moves between issued, trading and redeemed as a result of an issue, buy, or redeem transaction. These three transactions are initiated0 码力 | 483 页 | 7.48 MB | 1 年前3
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