Pocket Option Pattern-Discovery & Trading App Development

@sajjadtaghvaeifr

Hello, I trust you're doing well. I am well experienced in machine learning algorithms, with nearly a decade of hands-on practice. My expertise lies in developing various artificial intelligence algorithms, including the one you require, using Python, and similar tools. I have worked with pytorch, and tensorflow to develop DL models, .I hold a doctorate from Tohoku University and have a number of publications in the same subject. My portfolio, which showcases my past work, is available for your review. Your project piqued my interest, and I would be delighted to be part of it. Let's connect to discuss in detail. Warm regards. please check my portfolio link: https://www.freelancer.com/u/sajjadtaghvaeifr

@denisSolution

Hi, I'm Denis, a full-stack developer with experience building trading automation systems involving real-time data processing, backtesting engines, and live execution logic. I understand your core challenge: ensuring absolute consistency between backtest logic and live execution, with strict step limits, immediate entry on pattern completion, and no fabricated data. The technical scope includes: a candle pattern engine generating 2^N combinations dynamically and detecting them in real-time without look-ahead bias; step sequencing logic enforcing hard limits (e.g., 2 STEP = exactly two trades per sequence); a backtester using genuine Pocket Option data with proper validation; and a live engine handling connection loss, payout verification, and balance checks. My approach: start with architecture review and data flow mapping, then build the pattern engine and step sequencer with unit tests. Develop the backtest engine validated against live logic, followed by the live execution layer with error handling and reconnection logic. Dashboard and journal logging run in parallel, with continuous validation and edge case testing (insufficient balance, payout changes, connection failures). One realistic risk is Pocket Option API rate limits or data gaps. I'd handle this with request queuing, historical data caching, and clear messaging when data is insufficient rather than inventing candles. I'm ready to start immediately. Let's discuss the details. Thanks, Denis.

@lazarr4

Hello, I can build a pattern-discovery and trading system for Pocket Option that uses real market data and enforces strict step limits to prevent over-trading. I developed a similar system for a crypto trading client—it dynamically generated all possible candle patterns and enforced step limits to avoid look-ahead bias while improving win rates by 15%. I’d approach this by using a modular architecture with separate backtester and live engine components, ensuring the exact same logic is applied in both. The biggest improvement will come from validating every trade against real payout data and enforcing step limits at every stage. Proper setup will reduce the risk of over-trading while ensuring every trade follows the exact same rules in backtesting and live execution. I’ll also include detailed logging to track every decision and trade, including why steps were skipped. Once the project is done, I’ll review the system with you to confirm it meets all requirements before handing it over. If this sounds useful, I’d be happy to discuss the details further. Thanks, Lazar.

@qualityxenter

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@ayesha86664

Hi there! I understand the main challenge is building a reliable Pocket Option trading system using only verified data, with no fake results, look-ahead bias, or incorrect trade sequences. I have experience in trading software, backtesting systems, real-time market data, statistical analysis, risk management, and web dashboards. I can build dynamic pattern generation, sequence handling, trade logging, and transparent performance statistics. My approach will keep backtesting and live execution based on the same core logic. I will enforce the selected 1 to 4 step limit, verify payout and risk before every trade, handle real-time data carefully, and record every trade, skipped trade, error, and decision. I will also make the system state persistent so restarts do not duplicate trades or reset sequences incorrectly. Data validation, missing candles, connection issues, unknown order status, and insufficient data will be handled safely. check our work https://www.freelancer.com/u/ayesha86664 Can you confirm which official Pocket Option API or data access method you want to use? Let me know if you’re interested & we can discuss it. Best Regards Ayesha

@ykarora26

With extensive experience in developing automated trading applications, I understand the need to build a comprehensive Pocket Option pattern-discovery and automated trading software. My expertise in real-time data validation and candle pattern analysis aligns perfectly with your project requirements. How can we ensure the software adapts to different market conditions seamlessly? Regards, Yogesh Kumar

@codeandcommand

Backtesting Pocket Option patterns needs clean historical data first, before any ML model is worth building. I would pull the price feeds, tag setups statistically, then train a pattern classifier and wire it into a simple trading dashboard with risk limits built in. Can start today, working version in 4 days. Budget and timeline here are rough based on the post, we will firm both up once we cover the full scope. Want to jump on a quick call?

@DesmondTwoTwo

Hi, I'm Stefan. This caught my attention mainly because of the detailed requirements for real-time data integrity and the complex pattern discovery involved. I've developed automated trading systems that require precise data handling and intricate user interfaces, so I’m well-prepared for this project. Here's how I'd approach it: ▸ Start by ensuring all market data is legitimately sourced and validated for integrity. ▸ Develop a robust candle pattern engine to generate and detect combinations dynamically in real time. ▸ Implement comprehensive logging and error handling to ensure seamless live execution and backtesting accuracy. I genuinely enjoy diving deep into projects like this, treating the outcome as if it were my own venture. A great project often begins with a good conversation, so reach out and let's talk it through. Regards, Stefan.

@Cruz1217

Hi, the requirement for a real-time pattern discovery and automated trading application with strict execution rules and risk management is quite challenging. I'd approach this by setting up a robust backtesting engine that can handle various market and timeframe combinations, and then integrate it with a live trading module that enforces the selected step count and risk settings. My focus would be on ensuring the backtest and live logic are identical, with no look-ahead bias, to provide accurate and reliable results. I've seen cases where poorly designed trading applications can lead to significant losses due to incorrect risk management or flawed execution logic. To avoid this, I'll implement a comprehensive risk management system that checks payout and risk before every trade, and enforces the selected step count and daily/session limits. The client can expect a professional application with transparent statistics, robust error handling, and a user-friendly interface that allows for easy configuration and monitoring of trades.

@PINESCRIPTERR

Hi, I can build the application around a single consistent pattern/sequence engine shared by backtest, simulation, demo, and live modes, with strict step limits, real market/account data, payout and risk checks before every trade, persistent sequence state, detailed journaling, and transparent statistics without fabricated results or look-ahead bias. I’ll also structure the architecture so pattern generation, direction sequences, risk management, execution, and dashboard reporting remain configurable and independently testable. Question 1: Does Pocket Option provide an official API/WebSocket interface that exposes the required market data, payout information, account data, and order execution for your intended integration? Question 2: Should the initial implementation target all markets/timeframes immediately, or should we first validate the complete engine against one supported market and timeframe before expanding it? Regards, Houssame.

@muhammadsaad90

Hello I can build your pattern discovery, backtesting, simulation, and trading application with a strong focus on accurate data and identical backtest and live execution logic. I have experience with real time APIs, WebSockets, trading systems, backtesting, risk management, and automated execution. I’ll implement dynamic candle pattern detection, strict 1 to 4 step limits, immediate next step execution after confirmed losses, payout and risk checks, complete trade logging, and transparent statistics without using fake or assumed data. I’ll start by validating the legitimate Pocket Option data and API capabilities, then build the data and backtesting engine before moving to simulation, demo, and live execution. Thanks

@yacinebsd

Hey, I reviewed the full specification and understand that the key requirement is one consistent trading engine shared across backtesting, simulation, demo and live execution. I can build the system around dynamic 2^N candle-pattern generation, exact entry timing, hard 1–4 step limits, BUY/SELL sequences, payout checks, configurable risk rules, persistent sequence state, detailed trade journaling and transparent statistics without look-ahead bias. I have experience with Python backend development, APIs, WebSockets, databases, real-time processing and data-analysis systems, which fits this project well. My approach would be to first build and validate the common strategy/execution engine, then add backtesting and simulation, and finally connect Demo/Live execution using only legitimate Pocket Option data and available account access. I will not fabricate candles, payouts, balances or results. Anything unavailable will be clearly marked as not testable. I can start immediately and would first verify the available Pocket Option data/account integration before implementing live execution. Best regards, Yacine

@albert1025dev

==== Hi - Albert here ==== "POCKET OPTION PATTERN DISCOVERY & TRADING" — you need one deterministic engine where real data, pattern detection, backtesting, risk rules, and live execution all follow exactly the same sequence logic. I’d separate market-data validation, pattern generation, backtesting, sequence state, risk controls, and execution into testable modules. The selected 1–4 step limit would be enforced centrally, with payout and risk rechecked before every trade, persistent state preventing duplicate execution after reconnects, and every skipped or executed decision logged with its reason. Backtests would use the same event flow as live execution to avoid look-ahead differences. Can you provide the legitimate Pocket Option API/WebSocket documentation or confirm the exact supported data and trading interface available to the application? Looking forward to work with you

@toqeer74

Hi, The challenge lies in developing a complete trading application that uses legitimate market data for precise candle pattern recognition and risk management. How will you make sure the real-time data integrity and validation checks are flawlessly implemented throughout the trading process? Here's how I'd do it: - Start by setting up a solid API connection to Pocket Option to fetch real-time market data and make sure it passes integrity checks. - Implement the candle pattern engine using efficient data structures to dynamically generate all possible combinations based on user input and validate patterns in real-time. - Create a dashboard that displays live statistics, trade logs, and risk management data to provide complete visibility of trading actions and outcomes. I can have a working version of the core data-fetching functionality ready on a test link within a day. What types of risk management configurations are you considering including in the application? Toqeer S

@areebat90

HEY There , I had prevously experince in trading as well . so would love to work on this prject !!!! I read your project requirements carefully and I can build your complete **Pocket Option Pattern Discovery, Backtesting, Simulation, Demo & Automated Trading Platform** exactly according to your requirements. The system will use **only legitimate market/account data**, dynamically generate all candle patterns and BUY/SELL sequences, enforce the strict **1–4 step limit**, execute the next step immediately after a confirmed loss, and check real payout and risk conditions before every trade. This is EXACLTLY how i will build your project !! 1> First, I’ll connect the app with legitimate Pocket Option data. 2> Then I’ll build the candle and pattern detection system. 3> I’ll develop the 1–4 step trading sequence logic. 4> Next, I’ll add backtesting and make sure there is no look-ahead bias. 5> I’ll add payout, risk and money-management controls. 6> Then I’ll build Simulation, Demo and Live trading modes. 7> I’ll add trade history, sequence state and detailed statistics. 8> Finally, I’ll build the dashboard and add proper error handling and safety controls Most importantly, **the backtest logic and live execution logic will be identical**, with no fake data, fabricated results or hard-coded winning strategies. Do you have access to a Pocket Option API for real-time data and trading? Just message me start immediately !!!! Areeba

@BesterDevenier

This project is a great match for my experience, and I’d be happy to put my skills to work and help bring your vision to life. I understand the importance of using legitimate Pocket Option market data and ensuring data integrity, which aligns perfectly with my extensive experience working on a wide range of projects for clients. I’m confident in my ability to understand what a client needs, deliver high-quality work, and communicate clearly throughout the project. I would approach your goal by developing a robust backtesting engine that accurately reflects live trading conditions, ensuring seamless functionality. I would love to chat more about your project! Regards, Bester Devenier

@WebGraphics4You

Hello, As an experienced full-stack developer and machine learning specialist, I'm uniquely equipped to tackle the rigorous demands of your Pocket Option Pattern-Discovery and Trading App. I've got a track record of validating real data with precise analytics, ensuring that the information we use is not only verified but also genuinely reflective of market trends. My proficiency in market research is a key asset in this project, allowing me to create an application that guarantees only legitimate conditions halt trade sequences. Your project's vision aligns perfectly with my expertise in creating end-to-end solutions that drive significant results. I'm well-versed in building strategic trading applications that encompass backtesting, simulation, implementation, and risk management - all areas mentioned in your project requirements. The fact that I can merge this technical acumen with creative storytelling and growth-driven engagement places me as the ideal candidate for delivering more than just functional software - a 500 chars Thanks!

@kafupeople

Hi I’d build this around one shared execution engine for BACKTEST, SIMULATION, DEMO and LIVE, so the exact-entry rule, hard 1/2/3/4-step limit, loss → immediate next step behavior, payout checks and risk limits cannot drift between modes. I’d start by proving the real Pocket Option data/account path and validating timestamps, OHLC, gaps and duplicates. If historical candles or payout data genuinely aren’t available, the system will report NOT TESTABLE rather than manufacture a result. The pattern engine will generate the 2^N Green/Red combinations dynamically, while the sequence engine independently generates the valid BUY/SELL paths and persists the current step so a reconnect or restart cannot duplicate a trade. For the first working milestone, I’d demonstrate one pattern from real data through backtest/replay with the same execution state machine, including exact entry timing, step-limit enforcement and a journal showing every trade or skipped-trade reason. From there the same core can expand into the full dashboard and Demo/Live flow. Thanks, Belal

@manishashree12

Hello there, I understand you need a comprehensive Pocket Option pattern-discovery, backtesting, and automated trading application developed from scratch. My approach would be to meticulously validate real data, dynamically generate candle patterns, and enforce exact entry rules. Leveraging my expertise in backtesting engines and risk management, I will ensure the application supports multiple markets, timeframes, and sequences while maintaining transparency in statistics. Would you like to discuss further details on how we can proceed with this project? Thanks, Manisha