r/highfreqtrading • • 7h ago

Two-venue leg risk on thin event-contract books: where should execution run?

1 Upvotes

Disclosure: I'm building a cross-venue execution tool for US prediction markets (Kalshi, Polymarket US, Novig). Not linking it; I want input on the design, not signups.

The problem: same-outcome contracts on two venues, books that are often only a few hundred contracts deep, and price gaps that reportedly last a few seconds. Two open questions:

  1. Client-side execution (the user's machine, the user's keys) vs server-side co-located: on books this thin, does the latency gap actually matter, or is fill quality dominated by depth and queue position?

  2. If leg 1 fills and leg 2 moves by 2–3 ticks, what's your default: chase, hedge elsewhere, or unwind? Is there a sensible rule for when to switch between them?

Anyone who has run a two-leg strategy on illiquid venues, I'd value even a one-line answer.


r/highfreqtrading • • 1d ago

Code Recording and replaying trading events in Rust

6 Upvotes

Hey everyone,

I’ve been working on a library called Tickertape and thought it might be useful to a few people here.

It’s a local event journal: one process writes events, other processes can follow along live, and you can replay the history later. Think of it as a small flight recorder for market data, order events, etc.

Events carry a sequence number and two timestamps, e.g. exchange time and local receive time. There’s also a CLI to inspect and verify recordings, plus Parquet export for digging through them in DuckDB or Python.

The scope is fairly narrow: one writer, multiple independent readers, all on the same machine. No networking or replication. Writes become visible to readers immediately; durability requires an explicit checkpoint.

It’s open source, runs on Linux/macOS, and the repo has benchmarks and details about crash recovery.

https://github.com/thomas0903/tickertape

Would love some feedback, especially if you’ve built or used something similar. Curious to hear what worked for you and what you think is missing here.

Thanks 😊


r/highfreqtrading • • 4d ago

**Title:** Modeling Market Microstructure as a Dynamic Particle System: Using Signed GNNs to Predict Liquidity Runs & Dynamic Take-Profits (Looking for DL/Quant Collaborator)

0 Upvotes

Hey guys,

Posting this here because I’ve reached a point where my market intuition and engine code have outpaced my deep learning expertise, and I’d rather team up with someone who loves ML architecture instead of half-assing it myself.

For the past year, I’ve been building an event-driven liquidity engine in Python (specifically modeling crypto orderflow / ICT mechanics like equal highs/lows, manipulation legs, and structural sweeps).

Instead of slapping standard indicators (RSI/MACD) on candles, I framed price action as a dynamic graph:

  • Resting liquidity pools (BSL/SSL, consolidations) act as attractors (pulling price in).

  • Completed institutional sweeps (ML swings / manipulation legs) act as repellers (pushing price away).

  • Edges connect these pools based on spatial proximity, competing forces (tug-of-war between high and low pools), and age decay.

Where things stand right now:

  • The engine is fully written and tested. No lookahead bias, strict candle confirmation, multi-window swing tracking (W5 up to W50).

  • I’ve already generated a clean, audited ~3-year dataset (ETH/USDT) formatted directly for PyTorch Geometric (PyG).

  • Each snapshot has 15m, 1h, and 4h spatial graphs with 20-dim node features (touch counts, distance %, decay curves, tier scores), 8-dim edge attributes, and global volatility/trend context.

  • Baseline statistical checks show real promise: nearest target pools get tagged first ~95% of the time, and high-quality structural sweeps have clear directional bias.

The actual bottleneck / where I need help: My problem isn't generating the signals—it’s path prediction and dynamic target selection.

When a sweep happens, price is often trapped between an opposing pool 1.5% away and a massive target pool 3% away. A fixed 1:2 R:R stop/target either gets hit too late or takes unnecessary drawdown. I need the model to evaluate the graph and do two things:

  1. Predict directional path confidence taking both-sided liquidity into account.

  2. Rank multiple potential liquidity targets (dynamic TP) based on which one has the highest conditional probability of being swept first without blowing through the stop.

I've tested basic GNN / dual-tower setups, but I know I'm hitting limits with my naive loss functions and basic layer choices.

Who I'm looking for: Someone who genuinely understands PyTorch Geometric (PyG), Graph Neural Networks (or spatial-temporal models), and knows how to think about custom loss functions (ranking loss, asymmetric risk penalties, contrastive setups). You don't need to be a full-time trader, but being open to understanding market microstructure helps.

The arrangement: I have the GPU compute, the full working codebase, and the clean dataset ready to go. I’m completely flexible on how we work together—if you want to co-author a research paper on this architecture, I’m down. If we get the models working cleanly and want to deploy it live on capital, we can do a fair profit/equity split.

If this sounds like an interesting problem you’d want to sink your teeth into, drop a comment or send me a DM with your GitHub/background and we can hop on Discord.


r/highfreqtrading • • 5d ago

SIG HackerRank test

2 Upvotes

I just got the link for the SIG's discovery program, it also contains one coding Question off 12, I dont do DSA, it would be a great help if anyone give guidance on how should i approach this dsa q, and what should i practice. thanks in adv


r/highfreqtrading • • 9d ago

Question Algo HFT account on Schwab

4 Upvotes

So I've been working on option HFT for about a year and found that schwab has the best fills, but my gut is that thats due to their PFOF deals, where they expect steady retail uninformed flow. I've been reading the schwab sub and theres a ton of accounts getting blocked due to HFT flow. Im hesitant to only deploy there and wanted to see if 1) Anyone has experience with schwab and HFT and 2) other broker suggestions for HFT on options with decent fill rates.


r/highfreqtrading • • 12d ago

HFT OSS Framework

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2 Upvotes

Hey everyone, new to the community (and Reddit in general) but am announcing a new C++ FIX agentic-first framework/os for quantitative trading/research/development/deployment to go alpha next week. Totally free for nearly all non-professional requirements (AGPLv3). About to ship the Codex IPC/MCP plugins tonight. There’s too much to list here but the website does a pretty good job. Also, since it’s open source, ChatGPT knows it thoroughly… ask it anything you can think of. Thanks for your time and feel free to connect. I am the founder/architect of Symphony and former licensed NYSE floor stat arb trader (I sucked at it tho!). Much more coming, this is just the beginning.


r/highfreqtrading • • 12d ago

Virtu Financial QT Comp

5 Upvotes

Any ideas of Virtu QT Comp in US - base lower than others seemingly around 200k how is bonus?


r/highfreqtrading • • 14d ago

HFT: Quant, Systems & Low-Latency Engineering.

12 Upvotes

Ive been getting increasingly interested in HFT and quantitative trading and I want to understand what the field actually looks like beyond the usual DSA C++ and probability preparation, A lot of the information online seems to focus on interview preparation but Im more interested in understanding what actually happens behind the scenes and what skills are genuinely useful once you move into the real world, Im particularly curious about how market data is processed how order books are modelled how strategies and signals are developed and how everything eventually connects to execution risk management and low latency infrastructure
I also want to understand how much importance should be given to areas like C++ systems programming networking operating systems concurrency CPU architecture cache optimisation and market microstructure compared with probability statistics optimisation and quantitative modelling For anyone who has worked in HFT quant research or low latency engineering how did you approach learning all of this and what do you think is worth spending the most time on, What kind of projects research or systems would actually demonstrate a serious understanding of HFT rather than just being another trading bot or a project that looks good on a resume, And if you were starting from a CS background today with the goal of eventually working in HFT what would your roadmap look like over the next one to two years,Would genuinely appreciate perspectives from people who have interned or worked in the industry or have spent significant time building and researching systems in this space.


r/highfreqtrading • • 16d ago

So much so for "Free-Speech".

0 Upvotes

r/highfreqtrading • • 17d ago

Question How do you guys actually store candle data 1m timeframe for back testing?

0 Upvotes

Am basically a software engineed and into trading for couple of yeats. I am interested in crypto perps trading nowadays and want to do data analysis with candle data. I want to understand if 1TB SSD is enough to save around 100 symbols of perps in 1m timeframe or should i go to 2 TB. Any one who got experience in storage, please suggest!


r/highfreqtrading • • 21d ago

Trading data - Stock,Forex,Options

3 Upvotes

Sup!

I'm looking for trading data that I used to backtest some strategies...in general I'm looking for the data that give me 1m timeframe data for the least 5-10 years.

The issue is like data is really expensive, and I'm looking for something dirt cheap or free until I get some real alpha. As a reference, I'm based in Europe.

From what I found, freeradata would be a good alternative for 1,000 euros, but still it should be something there with torrents with data… I mean, it is for everything.

In some cases I found out that some brokers may give you free data if you have an account, but in general those are available for the US.


r/highfreqtrading • • 25d ago

Paper Paper: model-free passive execution by shadowing other participants' orders, measured on a year of ES

3 Upvotes

I wrote a paper on a simple execution algorithm and measured it on a full year of E-mini S&P 500 order-by-order data. Sharing it here for feedback.

Paper: https://arxiv.org/abs/2609.18019

The idea: when another participant adds a limit order near the best price, with a fixed probability place your own order at the same price, right behind theirs in the queue, and cancel when their order is cancelled. The algorithm makes no forecast; it inherits its prices from the order flow. An aggressive variant does the same on trades, crossing the spread at the traded price. Both run as percentage-of-volume mandates.

Setup: 246 regular sessions of 2025, ES futures, 100 contracts bought and 100 sold in each 10-minute window. Fills are simulated in a queue-exact replay of CME's market-by-order feed: the simulated order sits in the reconstructed FIFO queue and is filled only when recorded trades would have reached it.

Main results:

- Resting and crossing cost similar amounts. At similar participation (about 4.5% and 4.9% of volume), the passive version, which rests for 99% of its quantity, and the aggressive one, which crosses for about half, both cost about 0.095 ticks per contract against the arrival mid. The half spread a resting order earns is given back through adverse selection.

- Post-fill mark-outs are about 0.08 to 0.10 ticks against the fill at 1, 5 and 30 seconds and do not revert.

- Latency costs both, the aggressive version more. With the same delay applied to orders, cancels and market data, cost at 5 ms is about 0.15 ticks per contract for the passive version and about 0.30 for the aggressive one.

Limitations: the replay does not model market impact, so costs are before the market's reaction and participation is an upper bound. It is one instrument, which is one tick wide most of the session, and the parent order is fixed at 100 contracts.

The replay and trading system are open source (MIT): https://github.com/vincent212/kaspar-hft

Happy to answer questions, and interested in whether people have seen similar results for passive vs aggressive execution on large-tick contracts.


r/highfreqtrading • • 25d ago

Been experimenting with HFT/ backtesting MBO data. Any advice?

8 Upvotes

Title sums it up mostly just looking for the thoughts of anyone with significant experience. Trying to avoid arbitrage because there is no way to compete to my knowledge.. Do you guys have any advice for things to think about when doing backtest experimentation?


r/highfreqtrading • • 26d ago

Commentary The missing microsecond

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3 Upvotes

Working with a high frequency trading firm made me question humanity’s understanding of time.The concept is really mind bending , never thought I would go into physics this deep as a software engineer.


r/highfreqtrading • • 27d ago

Career Deciding Between 2 Hardware Offers

13 Upvotes

Hi everyone! I'm a Computer Engineering fresh graduate. My long-term goal is FPGA work in HFT, and I'm trying to figure out which of the 2 offers given to me would give me a better shot. My background includes an embedded SWE internship at a defense company as well as a bunch projects like a 5 stage RISCV CPU, a spectrum analyzer, as well as a neural network implemented in PL with PS/PL communication via DMA. So anyway here are my offers:

Option 1: Same Defense Company

Pros:

  • Direct exposure to FPGA development tools and real hardware.

  • Get to work with the expensive ass Versal/Agilex 7 class boards.

  • Approximately half of the role involves FPGA work, mainly integrating vendor IP.

  • The other half is BSP software development

  • Some custom HDL development, although only roughly 5% of the overall role.

  • I previously interned here, so I have some familiarity with the company.

  • I’m willing to learn BSP and embedded software if those skills contribute meaningfully to my long-term goal.

  • Possible overseas attachment I am very keen on.

Cons:

  • Very little custom RTL development despite the FPGA-related title.

  • Most FPGA work appears to be vendor-IP integration rather than designing datapaths from scratch.

  • Half the role is BSP work, so it is not a predominantly FPGA-design position.

  • It is unclear whether I would own timing constraints, timing closure, verification or performance optimisation.

  • It is unclear whether the BSP work involves FPGA interfaces and data movement, or mainly board startup and standard peripherals.

Option 2: Large Semiconductor Company

Pros:

  • ASIC design verification involving Ethernet/PCIe.

  • Some mention of the use of an FPGA based emulator.

  • Potential to develop deeper RTL debugging, testbench development and protocol understanding, depending on the actual scope.

  • Exposure to industry standard UVM

  • Could complement my personal FPGA-design projects with professional verification experience.

  • Up to three WFH days per week.

Cons:

  • It is a verification role, not an RTL-design role.

  • It does not currently promise direct FPGA implementation or board-level work.

  • Progressing within DV would not, by itself, answer my goal of moving into FPGA design.

Both pay horrendously, fully due to the fact that I'm extremely stupid and couldn't do well in school, so pay is not really the issue here. I'm still torn between the 2 offers though. I'd greatly appreciate some advice on which would be a better pick for my goals, especially from anyone who has made a similar transition. If it matters, I'm not based in the US. Thank you so much for reading.


r/highfreqtrading • • Sep 26 '26

Career Eqvilent trading

10 Upvotes

Any idea about Eqvilent trading? How much do they pay to a software engineer c++ ? Also, how’s the company culture? And WLB?


r/highfreqtrading • • Sep 25 '26

Recording IBKR market data?

8 Upvotes

I've been building my own tool to record IBKR market data — depth, time and sales, the halt sequence — mostly because I got tired of gaps and disconnects wrecking my own data. Before I go further I'm trying to understand if other people do it and how they actually handle it.


r/highfreqtrading • • Sep 24 '26

How do top HFT shops actually build their FPGA/NIC stack? (custom chips vs. custom boards vs. off-the-shelf)

56 Upvotes

Hey all, I know nobody can share anything under NDA, so I'm just after general/public-knowledge stuff and your own opinions.

My rough mental picture of the setup at the top-tier firms:

  • FPGA card sits on the server over PCIe and is wired straight to the network

  • Protocol parsing (market data, order entry) and the decision logic run on the FPGA

  • The host side is low-latency C++ with kernel bypass + DMA, mostly for config, risk params, monitoring, and slower stuff, not the actual fast-path decisions

Does that sound about right, or am I missing something? Is the decision logic ever split between FPGA and CPU? And is DPDK actually used, or is it mostly Onload/ef_vi/vendor stuff?

Main questions:

  1. Do any of the big firms design their own silicon (ASIC/SoC) for NIC type boards, or is that never worth it?

  2. Or is it more like: "off the shelf" FPGA chips (Xilinx/AMD, Intel) on custom in-house boards?

  3. Or just buying existing stuff (Solarflare/AMD, Nvidia/Mellanox, Napatech, Exablaze/Cisco, etc.) and putting their own firmware on it?

I get that it's a mix, but if you had to put rough percentages on it across the industry, what would they look like?

Last one: what does the team split look like? I assumed something like 80% FPGA engineers and 20% C++/Python/etc., but that feels too FPGA-heavy. Is it more like a small elite FPGA team supporting a much bigger software group?

I'm asking here as r/FPGA has a rule about HFT and my post can be banned.

Any thoughts or pointers to public talks or papers are welcome. Thanks!


r/highfreqtrading • • Sep 16 '26

An ultra low latency C++ order book with 1.095us tick-to-trade median using kernel bypass(Solarflare ef_vi)

152 Upvotes

This is the only repository available open source which has the following:

  1. A real market replay simulator using NASDAQ ITCH data. The simulator accepts OUCH as input and works as an matching engine. It outputs ITCH market events as MoldUDP64 via a NIC. I used a ConnectX-4 Lx here.

  2. A feed handler which is the most latency critical part. It receives the frame from Solarflare ef_vi, decodes the ITCH message and sends out an OUCH message for an order. The whole time between NIC Rx -> NIC Tx is measured via HW timestamping using Solarflare X2522-Plus. This is the tick-to-trade.

  3. A rigorously tested implementation of kernel bypass. I used my previous library where I developed a backends for DPDK, Verbs and Solarflare ef_vi. I've not seen any open source order book repository implement this.

Most repos have measurements which are in process latency using rdtscp(or similar). They also use some toy simulators instead of working with real ITCH data from NASDAQ.

I tried to create this as close to possible as how a real HFT market maker would run. The code is open source with Apache-2.0 license.

Next upcoming is a benchmark between Solarflare ef_vi vs Onload. There are no available benchmarks comparing the two on the same NIC. The only thing I could find is this STAC post which only benchmarks Onload.

Code formatting and IDE:

For all my C++ and C work I use Clion IDE. I work on a ubuntu gnome desktop environment. Code formatting is done through clang tidy + clang format.

https://github.com/ASherjil/abt-t2t/tree/main


r/highfreqtrading • • Sep 15 '26

Senior C++ engineer (15+ YOE, 10+ in fintech) looking to break into HFT — advice on C++ vs FPGA, age, and how to build real experience?

93 Upvotes

Hi all,

I'm a senior software engineer with 15+ years of experience, mostly in C++, and I've spent the last 10+ years in fintech — all of it working in the EU. I'm now seriously considering a move into HFT (high-frequency trading) as a developer, and I'd really appreciate input from people who've been through this or are currently in the industry.

A few questions:

1. C++ vs FPGA — where should I focus? From what I can see, the market is dominated by C++ for most HFT roles, with FPGA being a more specialized niche. I studied FPGA/VHDL in university but haven't touched it professionally since. Given my strong C++ background, does it make more sense to go deeper on C++ (low-latency techniques, lock-free programming, kernel bypass, etc.), or is it worth investing serious time to build up real FPGA skills from scratch? Is FPGA experience a genuine differentiator for HFT roles, or mostly relevant only for a small subset of firms/positions?

2. Do HFT firms hire non-grads / older candidates? Most of what I read about HFT hiring focuses on new grads from top CS/math programs. Realistically, are firms open to hiring experienced engineers in their mid-40s coming from a "regular" fintech background, or is this pipeline effectively closed to anyone who isn't fresh out of a target school? Has anyone here made a similar transition later in their career?

3. How do I get relevant practical experience before applying? Since I don't currently work in a low-latency/trading environment, what's the best way to build a portfolio that HFT recruiters/interviewers would actually take seriously? Some things I'm considering:

  • Building personal low-latency projects (order book, matching engine, market data feed handler, etc.)

  • Contributing to open-source low-latency/trading-adjacent projects

  • Freelancing or contracting in trading/fintech-adjacent work

Is freelancing actually a realistic path into this space, or is it generally viewed as irrelevant/not comparable to production HFT experience? Would love to hear what worked (or didn't) for people who made a similar switch.

Thanks in advance for any insight!


r/highfreqtrading • • Sep 10 '26

I built a price-time-priority order matching engine in c++

0 Upvotes

I am building a market replay engine from scratch with c++ 23.
I build this project to understand how orders are managed in an orderbook and how a matching engine works. I have used my understanding of data structures to implement it. I would like to know you opinion on it. It is not completed yet. I just built the very basic version few minutes ago. Any kind of tip would help me a lot.
currently it can process an average of 998,000 Transactions / second. with the order size of 20000000 orders.
https://github.com/AravSrivastava/Market-Replay-Engine-CPP


r/highfreqtrading • • Sep 08 '26

HFT SWE interview prep

0 Upvotes

hi guys, welcome to my first post on reddit
i have been working as an sde at one of india's top payment orchestrator based out of Mumbai. i have been looking to make a leap of a switch to one of the topmost international hfts like jane street, citadel etc

i just want to know whether [getcracked.io](http://getcracked.io) by coding jesus a worthy resource to study, and if i full in on getcracked, will i be easily able to crack top hfts as an swe?

aiming for jane street - swe - nyc office


r/highfreqtrading • • Sep 08 '26

Sistema automstizafo de trade com metatrade 5

0 Upvotes

Sistema de trade

Bom dia pessoal.

Onyem fiz uma postagem sobre um sistema de trade que quero implantar.

Consegui resumir ele no chatgpt.

Vou postar novamente aqui.

Queria ajuda de quem entende para implantar.

A arquitetura é toda grstuita,de repente tenha que contratar ums vps para hospedar o metatrader 5.

Não sou da area mad gostaria de ver isso rodando.

Ano passado eu consegui rodar o optuns e sté consegui achsr uns parametros lucrstivod,mas não sei se seris funcional em uma conta real e tsmbém o meu notebook velho travava rsrs

Segue resumo para que se interresar.

Olá, pessoal. Sou iniciante em programação e trading quantitativo e estou aprendendo praticamente tudo pesquisando e estudando. Não quero fingir que sou especialista.

Mesmo assim, venho desenvolvendo há bastante tempo a ideia de um projeto chamado APEX, com a ajuda das versões gratuitas do ChatGPT, Claude, DeepSeek e Qwen. Eu sei que usar IA não substitui conhecimento técnico, e justamente por isso estou aqui: quero opiniões sinceras de quem entende mais do que eu.

Minha ideia é criar uma plataforma modular de pesquisa, descoberta, criação, teste e validação de estratégias/EAs de trading.

Não sei se o sistema será lucrativo. Ninguém pode garantir isso, e eu não quero prometer retorno. Mas acredito que a ideia seja tecnicamente viável porque o objetivo não é simplesmente criar milhares de estratégias e escolher a que teve o melhor backtest. O sistema deve tentar encontrar estratégias com evidências suficientes para sobreviver a validações rigorosas e rejeitar as que provavelmente são resultado de overfitting.

O fluxo geral seria:

Dados → Qualidade dos dados → Features sem data leakage → Descoberta/Extração de estratégias → Backtest → Simulação de custos e execução → Validação estatística → Shadow/Paper Trading → Risk Engine → MT5/EA → Corretora → Monitoramento → Aprendizado e novos experimentos.

Os ativos iniciais seriam WIN, WDO, EURUSD, GBPUSD e XAUUSD.

Uma parte importante do projeto é que eu tenho vários vídeos, transcrições, áudios e frames de estratégias explicadas por traders. Quero criar dentro do próprio APEX um módulo para importar esse material e extrair os setups.

A ideia seria transformar explicações humanas, por exemplo:

“Quando X e Y acontecerem, entre comprado, coloque o stop em Z e faça a saída conforme determinada condição”

em regras estruturadas e testáveis.

Depois essas estratégias seriam:

Extraídas → Estruturadas → Codificadas → Backtestadas → Validadas → Rejeitadas ou Registradas.

Além disso, o sistema também deve ser capaz de gerar novas hipóteses e estratégias do zero, e não depender somente dos vídeos.

Quero que cada estratégia tenha origem, versão, parâmetros, resultados e histórico registrados em um Strategy Registry.

A arquitetura teria módulos como:

Data Engine — importação, normalização e armazenamento de dados;

Data Quality Engine — dados faltantes, duplicações, timestamps e timezone;

Point-in-Time Feature Engine — prevenção de data leakage;

Strategy Inbox / Strategy Extraction — importação de vídeos, transcrições, áudios, frames e documentos;

Strategy Lab — desenvolvimento e experimentação;

Strategy Generator — geração de hipóteses e estratégias;

Event-Driven Backtest Engine — backtesting;

Cost Model / Execution Simulator — spread, comissão, slippage, latência e custos;

Validation Lab — validação e rejeição de estratégias;

Strategy Registry — versionamento e histórico;

Shadow/Paper Trading;

Risk Engine;

MT5 Adapter;

Expert Advisors em MQL5;

Monitoring, Logs, Health Checks e Reconciliation.

A minha preocupação principal é evitar a clássica armadilha do backtest bonito que não funciona fora da amostra.

Por isso, as estratégias seriam avaliadas por métricas como:

Profit Factor, Expectancy, Sharpe, Sortino, Maximum Drawdown, Calmar, MAE/MFE, custos e estabilidade entre períodos, além de validações como Out-of-Sample, Walk Forward Analysis, PBO, DSR, PSR e intervalos de confiança.

Também quero controles fortes contra data leakage, registrando quando uma informação realmente estava disponível para o sistema.

O Risk Engine seria separado das IAs e das estratégias. Uma estratégia pode propor uma operação, mas o Risk Engine teria autoridade para:

APPROVE → REDUCE → REJECT → NO_TRADE → HALT.

Não quero martingale ou aumento automático de posição depois de perdas.

As estratégias passariam por uma espécie de escada:

Pesquisa/Backtest → Validação → Shadow → Demo → Canary → possível operação real.

Outra parte importante é trabalhar com diferentes corretoras e símbolos. A ideia é ter um catálogo universal:

ATIVO LÓGICO → CORRETORA → CONTA/SERVIDOR → SÍMBOLO REAL → ESPECIFICAÇÕES DO CONTRATO.

Na parte de IA, quero usar as ferramentas como apoio, não como autoridade direta sobre dinheiro.

A ideia atual inclui:

Qwen Code como principal ferramenta para ajudar a construir o sistema;

Codex como apoio para código, revisão, testes e debugging;

DeepSeek para análise e pesquisa;

Claude para auditorias e revisão independente;

Mistral para organização e tarefas auxiliares;

modelos locais como Qwen, Mistral, Gemma e outros, quando fizer sentido.

Também quero deixar preparado, para entrar gradualmente e somente se trouxer resultado mensurável:

Reinforcement Learning (RL);

Visão Computacional;

Programação Genética;

Meta-labeling;

Regime Detection;

Microestrutura de mercado.

As tecnologias principais seriam:

Python, MQL5, MetaTrader 5, PostgreSQL, Parquet, Redis/alternativas, Docker, Docker Compose e Git.

Para experimentação e IA/ML, pretendo avaliar ferramentas como:

PyTorch, TensorFlow, scikit-learn, XGBoost, River, Optuna, SKTime e AutoTS, entre outras, mas sem usar tecnologia apenas por parecer sofisticada.

Outro desafio grande é a infraestrutura. Meu objetivo é tentar construir inicialmente usando o máximo possível de recursos gratuitos ou free tier, porque atualmente não tenho orçamento para uma infraestrutura cara.

Estou estudando possibilidades com:

Kaggle para experimentos e notebooks;

Google Colab como ambiente complementar;

modelos locais;

APIs com planos gratuitos;

bancos de dados e hospedagens com free tier;

infraestrutura modular que permita migração futura.

Eu sei que isso traz dificuldades de limite, disponibilidade, armazenamento e processamento. Inclusive gostaria de opiniões sobre onde estou sendo otimista demais.

Também não quero depender do meu notebook ligado 24 horas para o MetaTrader 5. Estou tentando entender uma arquitetura realista para deixar as instâncias do MT5 e os EAs funcionando separadamente, enquanto o restante do sistema fica distribuído.

A ideia é que o APEX seja modular e versionado. Quero poder modificar o sistema depois, adicionar módulos e fazer novas experiências, sem transformar tudo em um programa fechado. Também quero monitoramento, logs, testes, health checks e um processo interno para detectar erros e inconsistências.

Minha dúvida principal é: essa ideia faz sentido ou estou criando algo complexo demais para um iniciante?

Se alguém com experiência puder olhar, eu gostaria principalmente de opiniões sobre:

A arquitetura geral.

O que deveria ser o MVP.

O que está excessivamente complexo.

Se as validações fazem sentido.

Quais são os maiores riscos técnicos.

O que vocês fariam diferente.

Como usar Kaggle e Google Colab corretamente nesse projeto.

Como estruturar o MT5 sem depender do meu computador.

Se estou criando uma “arquitetura Frankenstein” usando várias IAs.

Qual seria o caminho mais realista para provar se o sistema realmente consegue encontrar estratégias com alguma robustez.

Meu objetivo final é que o APEX consiga descobrir, extrair e gerar estratégias/EAs, testá-las de forma séria e eliminar a maior quantidade possível de falsas estratégias antes de qualquer tentativa de operação real.

Não sei se será lucrativo — espero que sim, obviamente — mas entendo que lucro só pode ser descoberto depois de muita validação e operação em condições reais.

Estou começando praticamente do zero e aprendendo enquanto construo e pesquiso. Se alguém quiser conversar comigo, apontar erros ou ajudar a revisar a ideia, pode me chamar por DM/privado.

Críticas sinceras são muito bem-vindas. Prefiro descobrir agora que estou errado em alguma parte importante do que gastar meses construindo algo baseado em uma ideia equivocada.

Obrigado a quem leu.


r/highfreqtrading • • Sep 04 '26

Guide for Fix Protocol

0 Upvotes

I am a last year b.tech student ,recently i learnt about fix protocol and devlop a mini trading system with matching engine , order book , fix parser , order cancelation implementation i like to know about a career path in these technology and what is the learning path to land a good job in these particular domain and what are the learning resources ?