This thesis can be turned into a fully backtested trading algorithm using AlgoThesis. Our AI agents will identify the right tickers, detect catalysts, build strategies across multiple lenses, and backtest against real market data.
When you submit this thesis, our three AI agents — the Thesis Agent, Catalyst Agent, and Risk Agent — will collaborate to build multiple strategies with different risk profiles, all backtested on 12 months of real price data.
The Thesis Agent analyzes "EVs are overhyped, legacy auto will catch up and margins wil..." and identifies TSLA, F, GM as the most relevant instruments to express this view.
Earnings reports, Fed meetings, sector rotation signals, and macro data releases are scanned to time entries and exits around real catalysts.
A 1-year backtest runs against real market data with DCA, dip buying, scale-out, and trailing stop logic. Only strategies that pass risk thresholds are recommended.
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