Results for “trading-journal”

Track investment theses across their lifecycle — from screening idea to closed position with postmortem. Register theses from screener outputs, manage state transitions, attach position sizing, review due dates, and generate postmortem reports with P&L and MAE/MFE analysis.

Analyze weekly price charts for stocks, indices, crypto, or forex to identify trends, support/resistance, and probabilistic scenarios based purely on chart data.

Generate falsifiable trade strategy hypotheses from market data, trade logs, and journal snippets, with ranked hypothesis cards, experiment designs, kill criteria, and optional strategy.yaml export.

Publish and consume blockchain-verified trading signals on Base. Register as a signal provider, publish trades with transaction hash proof, and subscribe to top performers via REST API.

Trade perpetuals on Arbitrum's Nexus DEX with autonomous agent support, including position management, thesis publishing, and leaderboard tracking.

Evaluates account-level drawdown and losing-streak rules from local thesis files to decide whether new trade risk is allowed, without external APIs.

Provides expert guidance for systematic backtesting of trading strategies, covering methodology, stress testing, bias prevention, and result interpretation.

Identifies and analyzes statistical arbitrage opportunities through pair trading, using correlation analysis, cointegration testing, and z-score calculations to generate entry/exit signals for market-neutral strategies.

Reviews trading strategy drafts for edge plausibility, overfitting risk, sample size adequacy, and execution realism, outputting PASS/REVISE/REJECT verdicts with confidence scores.

Aggregate closed trades from trader-memory-core into a weekly performance report with win rate, expectancy, profit factor, R-multiple, MAE/MFE, and pattern breakdowns by source skill, exit reason, sector, and mechanism.

Track weekly funding rounds across configurable verticals with primary-source verification, per-round analysis, and risk assessment.

Interact with the Taco crypto trading platform via API to fetch market data, manage positions, and compute technical indicators across multiple exchanges.

Synthesize market breadth, regime, and flow signals into a unified capital commitment recommendation with exposure ceiling, bias, and action guidance.

Analyzes earnings-season implied volatility: historical IV crush, implied move forecast, IV Rank strategy tag, and a priced Iron Condor quote ready to trade.

Registers a trading agent on zHive, fetches crypto signals, posts predictions with conviction, and competes for accuracy rewards.

Record and analyze post-trade outcomes for trading signals, tracking false positives, missed opportunities, and regime mismatches to generate feedback for signal aggregation and skill improvement.

Runs a nightly automated retrospective on autonomous trading strategy performance, computing win rates, fee drag, holding period buckets, direction bias, and producing data-driven improvement suggestions.

Designs and backtests systematic trading strategies using technical indicators, fundamental analysis, and statistical models, with clear entry/exit rules, risk controls, and documentation.

Trade stocks and crypto via Alpaca API, including market data, order placement, portfolio management, and account info, with support for paper and live trading.