Investment thesis
Sentiment & news — economic intuition. Information is absorbed into prices with a delay that scales with dissemination friction. By quantifying news tone, fear/greed positioning, and aggregated sentiment, the strategy captures the gap between information arrival and market clearing — a behavioural premium that exists because human attention is finite.
Risk-adjusted performance — live track record
Forward-tested daily against live market data. Metrics derived from end-of-day portfolio marks; methodology documented on the Due Diligence and About pages.
| Return | Value | Risk-adjusted | Value | |
|---|---|---|---|---|
| Current portfolio worth | $10000.00 | Sharpe ratio | 0.00 | |
| Total return | 0.00% | Sortino ratio | 0.00 | |
| CAGR | 0.00% | Calmar ratio | 0.00 | |
| Volatility (annualised) | 0.00% | Profit factor | 0.00 | |
| Days live | 26 | Maximum drawdown | 0.00% |
Process consistency
| Positive months | 0.0% |
| Best month | 0.00% |
| Worst month | 0.00% |
| Recovery from max drawdown | no drawdown recorded |
Equity curve
Live track record — forward-tested performance from the strategy's production start date.
Drawdown profile
Underwater curve — percentage below the running high-water mark. Institutional allocators read this before the equity curve.
Current holdings
| Symbol | Quantity |
|---|---|
| USD | 10000.0000 |
Research & documentation
- Strategy deep-dive: StockNewsSentimentBot: strategy deep-dive & live performance
- Reference implementation:
tradingbot/stocknewssentimentbot.py - Framework: python_tradingbot_framework (open source, fully inspectable)
Related strategies
Other strategies in the Sentiment & news family:
- FearGreedBotQQQ · research note- FearGreedBotQQQInverse · research note Or view the full strategy roster.
For professional investors
Request the investor deck, DDQ, and extended analytics. Firm-gated and reviewed manually.
Request access