Institutional Swing Trading Analysis System

@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 Matlab, Python, and similar tools. 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

@prabhathk5

Hi Sir Hope you doing well! I’ve reviewed your requirement and would like to discuss it further. I’m Prabhath — an MQL4/MQL5, Pine Script, Python, and C++ developer with strong experience in building trading systems, advanced studies, and institutional-grade algorithmic solutions. I develop Expert Advisors, indicators, dashboards, data tools, and custom trading utilities for MT4/MT5 and TradingView. As an active trader, I work with concepts like ICT, SMT, market structure, liquidity models, order blocks, FVGs, VWAP, and volume-based logic. I build EAs and indicators that follow precise rules and match the user’s trading methodology perfectly. My expertise includes: Institutional-grade EA and indicator development ICT/SMT-based trading systems Pine Script indicators and automated strategies Python tools for data analysis, signals, and external integrations C++ modules for high-performance components Backtesting, forward testing, and full strategy optimization Strategy development, refinement, and consulting Once we discuss your project over a short call to confirm all details before starting. This ensures perfect clarity and avoids misunderstandings. I fix and optimize existing trading code by removing errors, correcting logic issues, and making your EA/indicator/bot stable and production-ready. Thank you.

@loxtic

Hi, how are you doing? I have considerable experience building automated, institutional-grade trading analytics with Python, Pandas, NumPy, DuckDB/PostgreSQL, and vectorized data processing, and I’ve delivered backtesting engines and dashboards for NSE-like data. I’ve deployed end-to-end data pipelines, scoring engines, and reporting modules that run on schedule with alerts and exportable reports. I can demo prior work and adapt to your phased deliverables, data sources, and UI needs. Let me know further if interested.

@bizvivo

I lead a seasoned team of trading software developers, data scientists, and full stack engineers with 20+ years of combined experience delivering enterprise grade solutions. We specialize in automated trading bots, having built systems around RSI, MA, MACD, Bollinger Bands, harmonic and Fibonacci strategies. Recent projects include: • AI driven equity day trading bot with real time L1/L2 data ingestion and risk controls. • Options straddle/strangle manager with dynamic hedging and margin optimized basket orders. • Multi asset scalping bot tuned for ultra low latency execution. • Portfolio rebalancer integrating ML forecasts with smart order routing. • Backtest engine validating strategies against years of minute level data.

@alluankit01

Hi, I can build Phase 1 of your Institutional Swing Trading Analysis System in Python, covering database design, automated NSE data ingestion, scheduler, validation, logging, and the foundation for indicators, scoring, reports, and dashboard modules. The best solution is to first create a clean PostgreSQL/DuckDB schema for prices, indicators, fundamentals, delivery, shareholding, bulk/block deals, sector data, signals, settings, and logs. Then I’ll build the automated daily pipeline to download, validate, clean, store, and prepare data for the screening engine without manual work. I’m comfortable with Python, Pandas, NumPy, PostgreSQL/DuckDB, NSE data workflows, financial analytics, backtesting foundations, scheduled pipelines, logging, Excel/PDF reporting, and Streamlit dashboards. Deliverables for Phase 1 will include: * Database schema * Data ingestion pipeline * Daily scheduler * Validation and cleaning logic * Historical data storage * Configurable settings structure * Error/data/API logs * Git repository * Installation guide * Technical documentation I’ll focus on a stable, scalable foundation first so later phases like indicators, SMC/Wyckoff pattern detection, institutional scoring, backtesting, reports, and alerts can be added cleanly. Best regards Ankit

@Abror86

Hi — Abror-Yakubov here from Uzbekistan, "INSTITUTIONAL SWING TRADING ANALYSIS SYSTEM" — you need an automated engine that turns market data into reliable daily trade research. I’ll build this with a clean Python pipeline: data ingestion, PostgreSQL/DuckDB storage, indicator calculations, scoring rules, reports, dashboard, and backtesting. A key decision is keeping the scoring engine configurable, so weights and filters can change without rewriting the system. The main challenge will be handling bad market data and avoiding false signals. I’ll add validation, logs, and historical testing so each signal can be reviewed before trusting it. How do you want to source NSE data initially: paid API, broker API, or public market datasets? Looking forward to working with you.

@Sahyadri96

Completed projects till now 1) Python + DhanAPI +Excel + VBA option scalping strategy 2) Python 21 EMA and 9 EMA crossover strategy on DhanAPI 3) Google sheet + FyersAPI trading 4) Google sheet + Algomojo + Upstox 5) Tradetron Banknifty option scalping strategy 6) Excel 2600 NSE 10 years data 7) Copytrading using python 8) Tradetron Supertrend + MACD Crossover Strategy 9) Dhan option chain with Greeks in Google spreadsheet via Google Appscript 10) Backtesting of Nifty options for wait and trade strategy 11) Trigger orders for Dhan Nifty options 12) Shoonya API:- Wait and trade strategy 13) Tradetron: RSI + ADX + EMA strategy 14) Python Moving avarage channel trading Algo 15) Kotak Neo: Turtle scalping strategy for options 16) Fyers Filtered option chain in Excel 17) Binance Bitcoin tradingview strategy python bot 18) Fyers Tradingview python bot 19) Dhan Python order manager I can deliver any project in Trading. Readymade setups for Python available

@snath88

Hi, Drop me a message — I'll share a quick prototype based on what I understood. If it matches your expectations, we can move forward. Thanks!

@JoseRCarvas

Hi - this is a data/quant build in my core lane: automated end-of-day pipelines that pull market data, compute structured signals, score/rank, and emit reports without manual steps. Python + pandas + a scheduler is exactly how I'd do it. I want to scope honestly: the full spec (SMC, Wyckoff, market-structure, quant + fundamental screening, institutional-grade) is a real platform, not a weekend script. So Milestone 1 (this bid) delivers the working engine end-to-end on a defined signal subset: automated NSE EOD data ingestion, a market-structure + accumulation/volume scoring layer, ranking, and a daily report - runnable unattended on a schedule. That proves the architecture with something you can act on. Then we add the remaining methodologies (Wyckoff phases, fundamental screen, extra SMC rules) as scored milestones on top of the same engine. Two things to align first: which data source you want for NSE EOD (broker API / provider), and - critically - your exact scoring rules per methodology, since I implement your logic, I don't invent trading signals. INR 25,700 for M1, ~18 days, escrow-funded milestone before I start. - Ricardo (5.0 stars)

@NEHABHAT92

With a background in web and mobile development, I bring a unique perspective and skill set to your project. Over the past 9+ years, I have honed my skills in Python, PHP, Java, and more- languages that will prove vital to building the Institutional Swing Trading Analysis System you are seeking. Additionally my prior work on e-commerce and CMS based websites has prepared me well for the complexities of this job. As a seasoned developer, I understand the importance of thoroughness and precision - key aspects for this institutional-grade decision support platform project. I'm familiar with all elements involved in the completion of your Swing Trading System - right from data collection and processing using tools like Pandas, NumPy, TA-Lib to generating reports as PDFs, Dashboard or Excel sheets.I'm comfortable working with your preferred technology stack including Python 3.12+, DuckDB/PostgreSQL database, Plotly for visualization purposes and Git for source control. Moreover,I embrace an automated approach which means building scheduled tasks to automate data collection (1D Hourly), validate it, clean it and calculate indicators as per your mentioned indicators.I guarantee my work will involve no manual interventions further increasing its reliability. Your satisfaction is my ultimate goal so rest assured that i will be fully dedicated to realizing your project needs to align perfectly with what you envisioned as your end product. I’m thrilled at the prospect

@camilob44

You want an automated, institutional-grade NSE swing-trading engine — pulls the market after close, scores and ranks setups on SMC/Wyckoff plus delivery and institutional-flow signals, and ships daily reports and backtests with zero manual work. I've built trading harnesses and backtesting setups before, and I own the whole data side end-to-end (ingest → normalized store → indicators → signals → deploy), so I'd start where the system lives or dies: Phase 1 — an automated post-close pipeline (Bhavcopy, OHLCV, delivery %, bulk/block deals, FII/DII, shareholding) landing in a normalized PostgreSQL/DuckDB schema on an APScheduler/cron job with validation and logging — then build the indicator and scoring engine, the vectorbt backtester, and the Streamlit dashboard on that foundation, across the phases you laid out. This is the full-pipeline profile the job needs, not a notebook-only screener. One question that decides both feasibility and accuracy: do you have a budgeted market-data source in mind (a paid NSE API), or should the pipeline run off NSE's public Bhavcopy plus delivery/shareholding feeds? Phase 1 (data pipeline + DB + scheduler) is the first milestone, with later phases milestoned as we lock scope — so you validate real, working data before committing further.

@TechizeBuilder

Dear Client, I read "Institutional Swing Trading Analysis System" carefully and understand you need a solid desktop application built for daily real-world use. My hands-on experience with Python, PostgreSQL aligns directly with what you need. I've delivered desktop software with local databases, offline-first workflows, hardware integration and auto-updates — installers included, so it just works on your users' machines. A few quick questions to get us started: 1. Which platforms must it run on — Windows, macOS, Linux? 2. Do you have a stack preference (e.g. Electron, .NET, Java), or should I recommend one? 3. Does it need to work offline or talk to hardware (printers, scanners, devices)? Thanks & Regards, Deepak

@heenafullstacken

For Institutional Swing Trading Analysis System, I can turn the source-to-destination requirement into a dependable pipeline that is easy to operate after delivery. The build can include ingestion, transformations, schema checks, incremental loading, duplicate protection, scheduling, alerts, retries, and clear run documentation. My first step would be a compact source/volume/frequency/SLA map, followed by the simplest architecture that meets the actual workload. What are the source systems, target warehouse, approximate daily volume, and acceptable processing delay? Data work: https://www.freelancer.in/u/heenafullstacken Regards, Heena A Plus IT House

@MthokoD

Hey there, looking forward to hearing from you. Your requirement for an automated Institutional Swing Trading Analysis System is intriguing, especially the focus on institutional accumulation and quantitative analysis. The challenge of processing vast amounts of market data and producing actionable insights without manual intervention is a complex yet critical endeavor. I have delivered robust trading platforms that automate data collection, scoring, and reporting, ensuring seamless performance. I can provide a solution that aligns with your goal of generating high-conviction trading opportunities. Your emphasis on a sophisticated scoring engine and backtesting functionalities resonates with my background. While my profile is new here, my decade-long experience in building quantitative trading systems speaks for itself. My previous work involved creating similar platforms that effectively analyze market structures and deliver reliable performance metrics. Let’s discuss the specific indicators you want to prioritize for the scoring engine to align expectations. Chat Soon, Warm Regards Mthoko