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Inside HFT: Why Speed, Hardware, and Engineering Beat Secret Algorithms

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A software developer explored high-frequency trading (HFT) after a friend claimed to run an ultra-low-latency trading bot, expecting to uncover a complex financial formula. Instead, the investigation revealed that HFT success depends almost entirely on engineering optimizations rather than clever strategies. Key factors include network colocation near exchange servers, kernel-bypass networking, deterministic real-time processing in C or C++, and FPGA hardware acceleration to cut decision times to nanoseconds. An early Python-based prototype that polled order books every 100 milliseconds showed promising back-test results but collapsed under realistic latency simulations. The core lesson was that latency must be measured and reduced systematically at every stage, from network interface card interrupts to application callbacks.

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Inside HFT: Why Speed, Hardware, and Engineering Beat Secret Algorithms · ShortSingh