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Unlock the power of a consistent investing process! In today’s video, Dave walks through the three-step routine he uses every week to evaluate market conditions, identify high-quality stocks, and uncover powerful thematic opportunities—all using Seeking Alpha's analytics platform. This video is sponsored by Seeking Alpha, now running its Black Friday sale through early December! 🎯 Learn more about Alpha Picks (and get 20% off!): https://marketmisbehavior.com/alphapicks 🔍 What We Cover in This Video Why a consistent process matters more than predicting the future Using Seeking Alpha’s Market Data to read market conditions How sector rotation and factor performance reveal shifts in leadership Scanning for stocks with strong technical and fundamental characteristics Understanding Seeking Alpha’s Quant Factors (valuation, growth, profitability, momentum, revisions) Deep dives into example stocks: Micron (MU), Deutsche Bank (DB), and Newmont Mining (NEM) How Alpha Picks identifies high-conviction stock ideas Reviewing notable Alpha Picks such as Super Microcomputer (SMCI), Modine (MOD), and AppLovin (APP) Exploring thematic opportunities (AI, semiconductors, biotech, defense, casinos, and more) Integrating technical analysis with quantitative insights for a more robust investing routine 👉 Follow Dave on X: https://x.com/DKellerCMT 👉 Follow Dave on Bluesky: https://bsky.app/profile/dkellercmt.b... 👉 Follow Dave on Facebook: / marketmisbehavior 👉 Follow Dave on Instagram: / marketmisbehavior The content in this presentation should not be considered as a recommendation to buy or sell any security. All information is intended for educational purposes only and in no way should be considered as investment advice. Some of the links in this description and in the video may be affiliate links, which means you pay nothing more and it helps me to make Market Misbehavior awesome! As an Amazon Associate, I earn from qualifying purchases. For full disclaimer, please see our website: https://www.marketmisbehavior.com/dis.... * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *