| ORATs — Driven By Data returns with a genuinely feature-focused episode, walking through a brand-new addition to the platform’s stock scanner: fully integrated technical indicators. Host Tyler is joined by ORATS founder Matt for a demo-heavy episode that’s aimed squarely at traders who want to combine fundamental options analytics with classic technical screening in a single workflow. The core pitch is simple but important for anyone who’s used the ORATS platform before: the stock scanner and option scanner are designed to work as a funnel. Because the option scanner can only comfortably handle around 25 symbols at a time given how detailed its analytics are, the stock scanner’s job is to narrow the universe down first. Technical indicators — RSI, moving averages, MACD crossovers, and custom ratios built from any combination of available fields — are the newest layer added to that narrowing process, sitting alongside existing fundamental filters like PE ratios, valuation metrics, and the platform’s deep bench of implied and historical volatility measures. What makes the episode more than just a feature announcement is the live demo built around the “Auto” AI agent, ORATS’ natural-language assistant. Rather than manually building filters, Matt and Tyler simply ask Auto conversational questions — what are some good technical indicators for identifying overbought names given a market that’s had a strong run — and watch it construct actual custom ratios and scanner criteria in response, including things like price relative to the 200-day moving average and MACD crossover timing. Auto explains its own reasoning as it works through the scanner’s technical fields, which is a nice transparency touch that helps users understand why a stock got flagged rather than just trusting a black box. The demo lands on SpaceX as an example of a name showing textbook overbought characteristics — elevated RSI that’s pulled back slightly from its high — which the hosts use as the jumping-off point for a full workflow walkthrough: saving the scan results, sending them into the option scanner, and building an actual trade. They land on a short call spread in a name they refer to as “Docysine” in the transcript audio, walking through the trade builder’s payoff visualization and even placing it in ORATS’ paper trading integration to show the full loop from idea to simulated execution. The episode also covers a practical, often-overlooked detail: adding an implied-versus-historical-volatility valuation filter to the stock scan itself, so that names surfaced by the technical screen are simultaneously pre-filtered for volatility that’s attractively priced for premium selling. Tyler suggests adding a volatility “slope” filter too, since a flatter term structure is generally more favorable for selling calls. It’s a small addition, but it’s the kind of layered, multi-factor screening that separates a serious scanning workflow from a simple technical-indicator checklist. Matt closes with a broader point about how Auto is wired into ORATS’ full API suite, including historical intraday data, meaning developers and data API clients can use the same conversational agent to help write their own queries against ORATS’ dataset rather than just using it inside the dashboard. That’s a meaningful extension of the tool beyond the retail-facing scanner, positioning Auto as infrastructure for more sophisticated users as well. Overall, this is a genuinely useful episode for anyone who already uses ORATS and wants to combine technical setups with the platform’s options-specific analytics, and it’s a good showcase of how natural-language AI agents are starting to lower the learning curve on platforms that have historically required a fair amount of expertise to use well. The hosts close by pointing viewers to the trading tools tab on the ORATS website to try the stock scanner live, with the usual sign-off thanking Tradier for hosting the show. |
