How Geologist Aaron McMahon Uses A.I. to Identify Potential Mining Stock 10-Baggers

Mining Stock Education - A podcast by Mining Stock Education

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Geologist Aaron McMahon explains how A.I. can help identify potential mining stock 10-baggers in this MSE episode. He reveals his competitive advantage in finding potential outsized opportunities in early-stage exploration mining stocks. Aaron reviews the reasons for common modeling errors in mineral resource estimation. Furthermore, he also shares how retail investors can learn to invest like a fund. Aaron McMahon is a geologist and an international mining investment professional who uses technology and science to increase the speed and quality of investment decisions. He consults high net worth investors, funds and institutions by providing high-quality mineral economic analysis for drill-stage gold and copper companies. 0:00 Intro 1:12 Aaron’s background 4:42 Resource Estimation 8:29 Modeling errors in resource estimation 11:32 Aaron’s competitive edge with early-stage projects 14:00 Invest pre or post drilling? 15:40 People vs Project? 20:05 Metal Preference? 21:10 How to invest like a fund 32:49 Express DCF 38:39 AI Assisted Investor Tools https://aaronmcm.com/ Sign up for our free newsletter and receive interview transcripts, stock profiles and investment ideas: http://eepurl.com/cHxJ39 Mining Stock Education (MSE) offers informational content based on available data but it does not constitute investment, tax, or legal advice. It may not be appropriate for all situations or objectives. Readers and listeners should seek professional advice, make independent investigations and assessments before investing. MSE does not guarantee the accuracy or completeness of its content and should not be solely relied upon for investment decisions. MSE and its owner may hold financial interests in the companies discussed and can trade such securities without notice. MSE is biased towards its advertising sponsors which make this platform possible. MSE is not liable for representations, warranties, or omissions in its content. By accessing MSE content, users agree that MSE and its affiliates bear no liability related to the information provided or the investment decisions you make. Full disclaimer: https://www.miningstockeducation.com/disclaimer/