Financial Advisors Control $5 Trillion in Investor Wealth. Are They Buying Bitcoin? - Ep.222
Ric Edelman, founder of Edelman Financial Engines, and Matthew Kolesky, president at Arbor Capital, discuss the state of Bitcoin adoption amongst financial advisors, who control $5 trillion in investor wealth. In this episode, they talk about:
- their background and why they got into crypto (1:25)
- how most RIAs (registered investment advisors) view digital assets and the hassle of buying crypto on a client’s behalf (8:59)
- what percentage of financial advisors have already invested in bitcoin and how many more will come into the space by next year (18:20)
- how RIADAC -- the RIA Digital Assets Council -- is educating financial advisors about crypto (21:59)
- their favorite methods to explain Bitcoin and other digital assets (25:22)
- the different ways financial advisors are getting bitcoin/crypto exposure for their clients (35:32)
- why RIAs use investment vehicles to purchase Bitcoin rather than spot-buying the actual asset (39:58)
- why GBTC is trading at a deficit to the bitcoin price and their thoughts on a bitcoin ETF (44:40)
- the percent allocation to crypto they feel comfortable with for their clients (54:26)
- how they rebalance crypto holdings, whether they use yield-bearing crypto products yet, and projections for 2021 (57:35)
Thank you to our sponsors!
Download the Crypto.com app and get $25 with the code “Laura”: https://crypto.onelink.me/J9Lg/unchainedcardearnfeb2
Indexed Finance: https://indexed.finance/
Episode links:
Ric Edelman
- Twitter: https://twitter.com/ricedelman?ref_src=twsrc%5Egoogle%7Ctwcamp%5Eserp%7Ctwgr%5Eauthor
- RIADAC: https://riadac.com/
Matt Kolesky
- Twitter: https://twitter.com/mkolesky
- Arbor Capital: https://www.acminc.com/ + https://digital.arbor.capital/
Helpful Links:
- Bitwise ETF Trends + Survey of Financial Advisors
- Fidelity’s Bitcoin Investment Thesis
- RIADAC’s 12 Predictions for 2021
- RIADAC 1% Allocation strategy
- Arbor Capital’s “True Digital Asset SMA”
- Grayscale BTC Premium Flips Negative
- Blockchange
Learn more about your ad choices. Visit megaphone.fm/adchoices
Available Results
Generated results are saved to your library for reuse and search.
Choose Template
Pick the result you want. You can review provider and model before generating.
A concise first-pass summary for understanding the episode quickly.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
Explicit actions, next steps, habits, recommendations, and things to avoid.
Repeatable methods, frameworks, mental models, processes, and systems.
A dedicated inventory of concrete resources named in the episode.
A concise first-pass summary for understanding the episode quickly.
A detailed readable summary organized by chapter or topic.
A navigable map of subjects, topic flow, and suggested chapters.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Reusable atomic knowledge units extracted from the episode.
A comprehensive extraction focused on health practices, protocols, claims, and safety caveats.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
Explicit actions, next steps, habits, recommendations, and things to avoid.
A dedicated inventory of concrete resources named in the episode.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.
A concise first-pass summary for understanding the episode quickly.
A detailed readable summary organized by chapter or topic.
A navigable map of subjects, topic flow, and suggested chapters.
A comprehensive, source-grounded extraction of the reusable knowledge in an episode.
Reusable atomic knowledge units extracted from the episode.
A comprehensive extraction focused on health practices, protocols, claims, and safety caveats.
A comprehensive extraction focused on opportunities, strategy, markets, and company building.
Scientific findings, mechanisms, studies, hypotheses, and the limits of the evidence discussed.
Technologies, AI models, technical methods, capabilities, limitations, and adoption implications.
Investment theses, assets, catalysts, valuation reasoning, time horizons, and risks.
Chronologies, actors, causes, consequences, turning points, and competing historical interpretations.
Policies, proposals, stakeholders, arguments, implementation constraints, and predicted effects.
Career paths, skills, hiring signals, workplace decisions, transitions, and limitations of the advice.
Behavioral mechanisms, biases, motivation, habits, emotions, interventions, and evidence limitations.
Economic mechanisms, incentives, indicators, market structure, forecasts, and uncertainty.
Leadership principles, team systems, organizational design, culture, feedback, and failure modes.
Audience, positioning, messaging, acquisition, retention, experiments, metrics, and failed approaches.
Teaching methods, learning strategies, practice, feedback, assessment, and effectiveness evidence.
Theses, premises, arguments, objections, values, thought experiments, and unresolved questions.
Communication patterns, conflict, boundaries, expectations, repair methods, and contextual limitations.
Books, papers, authors, courses, and other learning resources mentioned in the episode.
Repeatable methods, frameworks, mental models, processes, and systems.
Explicit actions, next steps, habits, recommendations, and things to avoid.
Memorable statements and important claims with attribution and source context.
A dedicated inventory of concrete resources named in the episode.
A dedicated analysis of warnings, limitations, trade-offs, weak evidence, and uncertainty.