Trading Performance & Risk Analytics

@devendrathakur12

Hello, I would love if I get the chance to work on your project. I built many trading insight dashboard and I enjoy turning raw trading data into meaningful decisions using Python, Pandas, NumPy, Jupyter, and Excel, with a focus on transparent calculations for returns, drawdown, win rate, exposure, and portfolio risk. The final workflow will be easy to rerun whenever you add new trades. One question I have is, do your brokerage statements include cash deposits and withdrawals separately, or should performance calculations infer them from account balance changes? Can we connect over a chat to discuss more about the project? Best regards, Dev Singh

@ayazakhtar75

Hi Client , As an experienced data analyst proficient in various tools including Python and Excel, I'm ready to turn your extensive trading history into comprehensive, actionable insights. What could be more important to a trader than understanding the real behavior of their portfolio? I bring powerful scripting skills to bear in order to streamline workflows and provide clear, trustworthy performance analytics for your account. Whether you need precise figures for return, drawdown, win-rate or exposure, my focus on clean, efficient code ensures accurate outputs that you can trust. In addition to performance analytics, risk analysis plays a crucial role in decision-making. As someone who likes to dig deep and uncover hidden patterns, I'm confident about providing you with a complete picture of where your portfolio may be vulnerable. With my understanding of various forms of risk analysis such as value-at-risk, stress tests, custom scenarios - blended with data-driven logic - we can evaluate risks better and make well-informed and sound decisions. To ensure transparency and easy reproduction even in your absence, I create reproducible workbooks or scripts so that you are equipped to refresh the analysis yourself with new trades. I provide this along with a well-summarized report detailing methods applied, findings and most importantly actionable recommendations tailored for your portfolio. Let's get started on this project right away!

@corpmember29

HELLO, I HAVE CAREFULLY REVIEWED YOUR REQUIREMENTS AND UNDERSTAND THAT YOU NEED A RELIABLE PERFORMANCE AND RISK ANALYTICS SOLUTION THAT TRANSFORMS RAW BROKERAGE STATEMENTS INTO ACTIONABLE INSIGHTS, WITH FULL TRANSPARENCY INTO RETURNS, RISK EXPOSURE, DRAWDOWNS, AND PORTFOLIO BEHAVIOR. WITH 10+ YEARS OF EXPERIENCE IN PYTHON, DATA ANALYTICS, FINANCIAL REPORTING, SQL, MACHINE LEARNING, AND QUANTITATIVE ANALYSIS, I CAN BUILD A REPRODUCIBLE ANALYTICS FRAMEWORK THAT AUTOMATICALLY PROCESSES YOUR TRADE HISTORY AND GENERATES PROFESSIONAL PERFORMANCE REPORTS. ANALYSIS WILL INCLUDE: • Total & Annualized Returns • Win Rate & Profit Factor • Risk/Reward Analysis • Maximum Drawdown • Exposure & Position Sizing Analysis • Sharpe & Sortino Ratios • Trade Distribution Analysis • Equity Curve Visualization • Value-at-Risk (VaR) • Stress Testing & Scenario Analysis • Portfolio Concentration Risk • Custom Risk Metrics Based on Strategy Type DELIVERABLES: • Fully Documented Python Script or Workbook • Automated Data Import from Brokerage Statements • Performance & Risk Analytics Dashboard • Plain-Language Executive Summary Report • Methodology Documentation • Walkthrough Session for Future Updates • Source Code & Ownership I WILL PROVIDE COMPLETE SOURCE CODE, DOCUMENTATION, AND 2 YEARS OF FREE ONGOING TECHNICAL SUPPORT FOR THE DELIVERED SOLUTION. I EAGERLY AWAIT YOUR POSITIVE RESPONSE. THANKS

@tangramua

Dear ,   We carefully studied the description of your project and we can confirm that we understand your needs and are also interested in your project. Our team has the necessary resources to start your project as soon as possible and complete it in a very short time.   We are 25 years in this business and our technical specialists have strong experience in Python, Statistics, R Programming Language, Risk Management, Financial Analysis, Statistical Analysis, Data Analytics, Data Analysis and other technologies relevant to your project.   Please, review our profile https://www.freelancer.com/u/tangramua where you can find detailed information about our company, our portfolio, and the client's recent reviews.   Please contact us via Freelancer Chat to discuss your project in details.    Best regards, Sales department Tangram Canada Inc.     

@mobimubasir

I can turn your brokerage statements into clear performance + risk insights using Python — reproducible script that ingests trade history and outputs return, drawdown, win-rate, exposure, VaR/stress tests with transparent logic. Once you share the trade file format, I’ll confirm turnaround + send a short plain-English report and a quick walk-through so you can refresh it yourself with new trades.

@maxscender

I can help you build a robust, reproducible analytics engine for your trading data. I will use Python (Pandas/NumPy) to create a modular script that standardizes your brokerage exports, cleans the data, and calculates critical performance metrics like Calmar/Sharpe ratios, Maximum Drawdown, and Win/Loss expectancy. To address risk, I will implement a Value-at-Risk (VaR) model—using both historical and Monte Carlo simulation methods—to provide a clear view of potential portfolio vulnerability. The deliverable will be a Jupyter Notebook that keeps the logic transparent, allowing you to re-run the analysis simply by swapping in new raw trade files. I will also provide a concise summary report that translates these statistical outputs into actionable insights regarding your exposure and strategy efficiency.

@nrajuu07

I'm a quantitative analyst experienced in portfolio performance analysis and risk modeling. I'll ingest your full trade history, calculate precise returns, drawdowns, win rates, exposure metrics, and implement comprehensive risk analysis — VaR, stress testing, scenario analysis, or a tailored blend — with fully transparent logic. Deliverables include a reproducible Python/R script or workbook, a plain-language report with findings and actionable recommendations, and a walkthrough for independent updates. Ready to discuss preferred format and start immediately

@Aaleen110

I understand you need to transform raw brokerage statements into actionable trading performance and risk analytics, focusing on precise metrics like return, drawdown, and win-rate, alongside transparent, data-driven risk assessments such as VaR or stress tests to identify portfolio vulnerabilities. I previously built a similar analytics platform for a prop trading firm that delivered real-time performance dashboards and identified key risk exposures, leading to a 15% reduction in unexpected drawdowns. My approach will involve developing a Python-based solution utilizing Pandas for data manipulation, NumPy for calculations, and Matplotlib/Seaborn for visualizations. You will receive a reproducible Jupyter Notebook or a standalone Python script that ingests your brokerage data, calculates all specified performance metrics, and executes chosen risk analysis techniques. The output will be a clear summary report with interactive charts and tables detailing account behavior and risk profile. What is the typical format and frequency of your brokerage statements? Ready to start as soon as you confirm scope.

@alizain721

When raw brokerage statements are treated as summary numbers, hidden concentration, leverage, and wash trades often distort the true return and risk picture — your brief nails the danger: you need trade-level reconstruction that produces transparent metrics, not opaque headline returns. My plan is a focused, reproducible pipeline that ingests your trade history, rebuilds positions and cash flows, and produces clean performance and risk outputs: realized and time-weighted return, max drawdown, win-rate, trade-level attribution, exposure and turnover, plus configurable risk analysis (historical and parametric VaR, stress tests, custom scenario injections, and Monte Carlo where appropriate). I will document the logic so every calculation is auditable. What I will deliver and how: - A Jupyter notebook (Python: pandas, numpy, scipy, empyrical/pyfolio) that reads your CSV/Excel trade files, normalizes fills/cash/dividends, reconstructs P&L, and outputs tables/charts and exportable CSVs. - A short plain-language PDF summarizing methods, key findings, and prioritized recommendations to reduce identified vulnerabilities. - A 30-minute recorded screen walkthrough plus step-by-step notes so you can refresh the analysis with new trades. Relevant work: on Tax Plan Hero I built a rules-driven ingestion and reporting engine that normalized bank transactions into a single model and produced downloadable reports — the same data-cleaning and transparent-rule approach applies here. Quick practical questions so I can start: - Preferred input format: CSV or Excel? Please share one representative raw trade file (including fills, timestamps, commissions, dividends if available). - Do you prefer Python notebook output or an Excel workbook for running updates? Estimated turnaround for the base deliverables: 3–5 business days after I receive a sample file. My proposed bid is $11.50. Which sample file can you upload now?

@kaimenyijohn5

AM READY TO START ASAP: BROKERAGE STATEMENT ANALYSIS – PERFORMANCE METRICS (RETURN, DRAWDOWN, WIN-RATE, EXPOSURE) + RISK ANALYSIS (VAR, STRESS TESTS, SCENARIOS) Hello, I am John K., MSc Econ & Statistician, 15+ years, 1,000+ projects, 4.9⭐. My expertise includes financial performance analytics, risk management (VaR, stress tests, scenario analysis), Python/R/Excel, and trade data analysis. My understanding is: You need your brokerage statements transformed into performance and risk insights. Performance metrics: return, drawdown, win-rate, exposure, and other behavior indicators. Risk analysis: VaR, stress tests, custom scenarios – transparent and data-driven. Deliverables: reproducible workbook/script (Python/R/Excel) that ingests trade history, outputs metrics, a plain-language report summarizing findings and recommendations, and a quick walk-through for future updates. I will deliver: ✅ A reproducible analysis script/workbook. ✅ Performance and risk metrics with clear interpretation. ✅ A plain-language report and refresh instructions. I am ready to begin. Let's connect via chat to receive your raw trade files and discuss your preferred toolset (Python, R, or Excel). Respectfully, John K.

@markupdudes

Hi, I understand you need clear, trustworthy performance and risk analytics from your brokerage statements. With experience in Python, R, and Excel for financial data analysis, I specialize in transforming raw trade history into precise, insightful metrics like return, drawdown, win-rate, and exposure. I’ll also perform transparent, data-driven risk analyses using value-at-risk, stress tests, or custom scenarios based on your portfolio’s unique profile. I will deliver a reproducible script or workbook that ingests your trade data, a plain-language report summarizing the results and recommendations, and a walkthrough to help you refresh the analysis independently. Let’s discuss your preferred toolset and timeline to start promptly. I estimate a turnaround of around 5 days for a thorough, high-quality delivery. Which file format do you prefer for providing your trade data? Best regards,

@Synet

Turning brokerage statements into trustworthy performance numbers is harder than it looks because most statement formats mix realized and unrealized PnL inconsistently, and if you're running any options or dividend-paying positions, the raw numbers will lie to you without adjustments for cost basis and income attribution. The right approach is to parse the statements with Python into a normalized trade ledger, then calculate time-weighted returns (TWRR) alongside drawdown analysis and Sharpe ratio metrics, all built reproducibly so you can rerun it each month when new statements arrive. I'd start by delivering a working Python script that parses your statement format and outputs a clean performance dashboard, at $50 the price is above your listed range because building a statistically sound analytics layer with proper risk metrics takes several careful hours to do right, not just a quick pivot table. I can have a first version ready within 48 hours of receiving a sample statement. Are you trading a single asset class like equities, or do you also have options or futures positions in there, because the return calculation methodology changes significantly depending on which instruments are involved? Best, Salma Noreen

@jk31

Depending on how much data you provide, I think, I could do it within 1-5 days. Probably even faster. I know both, Python and R, well. But more likely is Python (Jupyter). I would/could export the data into Excel and PDF (human-friendly). I am a PhD-level data scientist with 10+ years of experience. Plus, I am a trader since 2017. Doing backtesting from time to time. I didn't trade all the time but the first and the last 3 years I was trading intensively. So I have an idea about what to look for. I will come to conclusions within several hours. < 10 hours. I give the timespan up to 5 days only for my own security - if things appear which I have to do.

@mayr81

Hi there, I'd love to turn your brokerage trade files into clear, trustworthy performance and risk insights using transparent, data-driven analytics in US native spoken English. I’m experienced with financial/statistical analysis and building reproducible workflows that ingest full trade history and output metrics like return, drawdown, win-rate, exposure, and other account-behavior indicators. For risk, I can implement the most appropriate mix, e.g., historical/parametric Value-at-Risk, volatility and drawdown-based measures, stress tests, and customizable scenarios, so you can see exactly where the portfolio is vulnerable and why. You’ll get a reproducible Python (or R/Excel, your choice) workbook/script, plus a short plain-language report summarizing methods, assumptions, and actionable recommendations. I’ll also include a brief walk-through so you can rerun the analysis when you add new trades, without getting stuck. To make sure the logic matches your trading reality, which fields are included in your raw exports (fills vs orders, timestamps, fees, instrument identifiers), and do you want risk computed on a portfolio-of-trades basis or on a time-series equity curve? Best regards!

@ziedb4

Hi there, ​Transforming raw brokerage statements into an institutional-grade risk matrix requires rigorous statistical handling—especially when modeling tail-end risks and portfolio vulnerabilities. I can build a clean, transparent, and reproducible analytics pipeline that provides sharp, data-driven clarity on your true trading behavior. ​?️ My Preferred Toolset & Methodology ​I highly recommend a Python-based data pipeline (utilizing Pandas, NumPy, and financial analytics packages like QuantStats or empyrial) delivered via an organized Jupyter Notebook or standalone script. This guarantees your core deliverable is 100% reproducible; you will be able to ingest new trade logs and refresh the entire analysis instantly. ​Here is the analytical framework I will implement for your history: ​Advanced Performance Telemetry: I will calculate precision-focused figures including time-weighted returns, rolling Win-Rates, Profit Factor, Sharpe/Sortino ratios, and a detailed Maximum Drawdown curve (including peak-to-trough duration analysis). ​Quantitative Risk Modeling: I will run a multi-method Value-at-Risk (VaR) simulation (Historical and Parametric) at 95\% and 99\% confidence intervals to isolate your maximum expected loss boundaries.

@jay8mac

Lets chat, a free consultation and no obligation. I understand you need a clean, professional, and user-friendly solution for your "Trading Performance & Risk Analytics" project. My skills in PHP, Java, JavaScript are a perfect fit for this project. While I am new to freelancer.com, my extensive experience delivers integrated, automated solutions. Regards, Jason McLachlan

@jeremiasg17

Hello! I've built a similar analytics system for brokerage statements that significantly improved performance tracking and risk analysis for my clients. I can show you the implementation in chat if you're interested. My approach would start with ingesting your trade history into a Python script, enabling detailed calculations for return, drawdown, and exposure. I’d also integrate various risk analysis methods tailored to your portfolio, ensuring transparency in the logic. To dive deeper, could you share what specific metrics you prioritize for performance and risk? This will help tailor the analysis to your needs. If you’re open, I can share my similar build, and we can explore if it fits your project.

@alyn48

Hello, I can transform your brokerage statements into clear, data-driven performance and risk insights. I’ll deliver a reproducible workbook or script (Python, R, or Excel) that ingests your full trade history and calculates returns, drawdowns, win-rate, exposure, and other key metrics. Risk will be analyzed via transparent, data-driven methods—VaR, stress tests, custom scenarios, or a blend tailored to your portfolio. You’ll also receive a concise, plain-language report summarizing findings, methodology, and actionable recommendations, plus a short walkthrough so you can refresh the analysis on your own. Best regards.

@sjohn117

Hi,\n\nI’m Sean, an AI & Full-Stack Developer with over 10 years of experience, specializing in data analytics and financial analysis. I understand your need for precise trading performance insights and robust risk analytics derived from your brokerage statements.\n\nI have developed similar projects that provide actionable insights using Python and R, ensuring that clients have clarity on their investment performance and vulnerabilities. Utilizing statistical analysis, I can create a reproducible workbook or script that will process your trade history to deliver the requested performance and risk metrics.\n\nMy approach guarantees clean code, thorough testing, and comprehensive documentation, ensuring you can easily refresh the analysis as new trades come in. I aim to deliver an initial version of your project within one week to facilitate a quick turnaround. What formats do you prefer for the raw trade files, and which toolset would you like me to use for analysis? \n\nThanks,\nSean