Results for “backtest”
11 skills
smith6jt-cop backtest-persistence
Save backtest results to SQLite database for comparison. Trigger when: (1) tracking backtest history, (2) comparing model performance, (3) querying best backtests.
3
smith6jt-cop multi-tf-backtesting
Multi-timeframe backtesting combining 15Min + 1Hour model signals. Trigger when: (1) multi-TF backtest, (2) combining timeframe signals in backtest, (3) validating multi-TF strategy, (4) --multi-tf CLI flag.
3
nvidia cufolio
Build, optimize, backtest, rebalance, or analyze stock portfolios using NVIDIA-accelerated Mean-CVaR optimization with cuOpt GPU solver.
2.2k · bundle
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tradermonty strategy-pivot-designer
Detect when backtest iteration has stalled and generate structurally different strategy pivot proposals to break out of local optima.
2.3k · bundle
affaan-m ai-regression-testing
Prevents AI-introduced regressions with sandbox-mode API testing, automated bug-check workflows, and patterns that catch blind spots where the same model writes and reviews code.
226k
machenjie regression-testing
`analysis-agent`/`task-agent`/`review-agent`: use for recurrence guards on known defects, incidents, or escaped failures; skip speculative risk without a prior failure mechanism.
4 · bundle
dvy1987 agent-run-retro
Run a structured retrospective after development-phase runs of your product's agents — interview the owner in plain language about what went well and poorly, draft ranked improvement hypotheses, then design and run small n=1/n=2 experiments with pre-declared success criteria, guardrails, stop conditions, and a cost/ROI kill-switch. Load when the user says how did that run go, retro this run, the agent output was bad, what should we improve, draft hypotheses, run a small experiment, or after repeated dev runs of an agentic system produce uneven quality. Priority: output quality over performance over cost, each with diminishing-returns stops. NOT a product A/B test (experimentation), NOT coding-agent harness repair (harness-evolution), NOT production-scale learning (runtime-learning-loop).
3 · bundle
gabrielmoreira vibe-trading
Backtests quantitative trading strategies across 9 engines and 25 data sources, analyzes trade journals, and runs multi-agent research teams.
17
smith6jt-cop post-training-workflow
Post-training model validation workflow: gating, backtesting, walk-forward validation, deployment decisions. Trigger after GPU training completes.
3
dokhacgiakhoa quant-analyst
Build financial models, backtest trading strategies, and analyze market data. Implements risk metrics, portfolio optimization, and statistical arbitrage. Use PROACTIVELY for quantitative finance, trading algorithms, or risk analysis.
505
smith6jt-cop joint-multi-tf-v560
v5.6.0 joint multi-TF model: single model per symbol with broadcast 1Hour context replaces dual 15Min/1Hour models. Trigger: (1) replacing weighted-voting model aggregation, (2) adding broadcast features to vectorized env, (3) limited training data + worried about overfitting from doubling obs_dim, (4) backtest builder mismatch with newer feature counts.
3