Institutional performance metrics & portfolio analysis

the platform is currently missing the standard risk-adjusted performance ratios and benchmarking capabilities required in an institutional environment.

To bridge the gap between retail trade logging and professional quantitative tracking, I highly recommend integrating the following hedge fund metrics into the primary Analytics dashboard:

1. Relative Performance & Benchmarking

Portfolio vs. Benchmark Overlay: The ability to map our equity curve directly against a selected benchmark index (e.g., mapping the Nifty 50 against our equity momentum sleeve, or a broad commodity index against our systematic futures).

Alpha & Beta: To quantify our exact outperformance relative to the broader market and our portfolio's systematic market risk.

Information Ratio & Tracking Error: To measure our risk-adjusted returns strictly against our chosen benchmark.

2. Absolute Risk & Return Ratios

Sharpe & Sortino Ratios: To measure standard risk-adjusted return and downside deviation (the latter being critical for evaluating trend-following models without penalizing upside volatility).

Calmar Ratio: To evaluate average annualized return strictly against the Maximum Drawdown.

3. Advanced Drawdown & Distribution Analytics

Drawdown Duration (Time Underwater): Beyond just the percentage depth of a drawdown, measuring the exact number of days or months the portfolio takes to recover its high-water mark is an essential mandate for capital allocation.

Skewness & Kurtosis: Because systematic trend-following relies heavily on capturing the "fat tails" of market moves, natively measuring the skew of our trade distribution is vital for proving the mathematical edge of our systems.

Daily Value at Risk (VaR): To provide a statistical baseline for the maximum expected loss across the combined portfolio.

Recovery Factor: Net profit divided by Maximum Drawdown.

Monthly Standard Deviation / Variance: To track portfolio volatility over time.

Currently, systematic traders have to export raw CSV data out of JournalPlus into custom Python/Excel environments to calculate these basic institutional metrics. Adding these natively would instantly elevate JournalPlus from a retail journaling tool to a comprehensive portfolio management dashboard for emerging quantitative managers.

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Upvoters
Status

In Review

Board
💡

Feature Request

Date

15 days ago

Author

Akshay Kachwaha

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