Stop Chasing Money and Build Wealth That Matters

Tiffany Cianci discusses the growing risks in private equity and private credit, including excessive debt, questionable valuations, limited transparency, and struggling investment funds that cannot exit their holdings. She explains how continuation funds and shadow banking may be concealing financial problems while shifting risks onto pension funds and everyday investors. We also examine speculative AI investments, unprofitable data centers, rising borrowing costs, and the potential consequences of allowing private equity and private credit into more 401(k) plans. Tiffany shares practical steps investors can take to question their retirement plan trustees, evaluate investment risks, and advocate for greater accountability. We discuss... The growing risks in private equity and private credit, including excessive debt, questionable valuations, and limited transparency. How private equity firms are increasingly struggling to sell their investments, leading to a growing backlog of unsold businesses and greater reliance on continuation funds. Continuation funds can create conflicts of interest when firms move assets between funds to provide liquidity to existing investors. Weak oversight and limited disclosure make it difficult for investors to assess the true value and risks of private equity and private credit investments. How private equity firms use leverage and repeated acquisitions to increase debt burdens and potentially push businesses toward bankruptcy. Rising interest rates and adjustable-rate debt are putting additional pressure on private equity-backed companies and private credit lenders. The expansion of private credit has created a shadow banking system that operates with fewer safeguards and transparency requirements than traditional banks. How allowing private equity and private credit into more 401(k) plans could shift investment losses onto everyday Americans and retirement savers. High management and performance fees can significantly reduce returns for individual investors compared with traditional index funds. Pension funds are exposed to private market risks, with reported returns sometimes falling far short of the estimates used to justify investments. Concerns about financial arrangements between AI companies, chipmakers, and data center operators that may obscure underlying risks. How corporate consolidation and lobbying can create monopolies that harm small businesses and consumers. How regulation can be used by dominant corporations to limit competition and drive smaller businesses out of the market. The need to enforce antitrust laws and improve oversight without imposing disproportionate regulatory burdens on small businesses. Today's Panelists: Kirk Chisholm | Innovative Wealth Phil Weiss | Apprise Wealth Management Greg Dupont | Advocate Wealth Solutions

The world is ending tomorrow! Or maybe it was the next day... We talk the risks of AI hype and the fear surrounding it, with many thinking it may be used by technology companies and politicians to justify government regulation, limit competition, and protect valuations. We also discuss it's potential benefits and limitations, the importance of measuring real productivity gains, the risks of over-reliance on AI in education and professional decision-making, and why AI should enhance human capabilities rather than replace critical thinking. We also talk the including the growing gap between mortgage payments and rents, economic growth forecasts, concentrated stock market returns, the relative appeal of bonds, real estate valuations, and historical election-year market patterns. Market weakness beneath rising indexes signals an unhealthy market, so keep your investments diversified, watch your risk management, and be patient rather than chasing expensive AI stocks or taking excessive risks. We discuss... How fear surrounding AI may be used by technology companies and politicians to influence public opinion and justify government regulation. Whether AI companies are exaggerating existential risks to accelerate development, attract investment, and discourage competition. That AI should be viewed as a software tool rather than a human-like entity capable of independently taking over the world. How AI could transform existing software businesses by integrating new capabilities rather than making established companies obsolete. Why AI is particularly effective at repetitive tasks and iteration, including coding, scientific research, drug development, and generating creative content. Why businesses should measure AI's actual return on investment rather than assume that adopting the technology automatically improves performance. Why AI should support human capabilities rather than replace the effort and experience needed to develop expertise. Whether AI companies should be held legally responsible for harm caused by their products and whether liability protections undermine accountability. Concerns about AI companies entering biological research and the potential risks of developing powerful technologies without sufficient safeguards. Caution against relying on AI to make investment decisions, arguing that it can assist with research but remains limited in qualitative analysis and judgment. The widening gap between mortgage payments and rental costs, noting that mortgage payments have risen much faster than rents and wages since 2019. International GDP growth forecasts for 2026 and 2027, questioning the assumptions behind projections for Iran's economic recovery. The concentration of stock market returns, with a small number of companies accounting for most of the S&P 500's gains. How higher Treasury yields make bonds more competitive with stocks and provide investors with an alternative source of income. The relationship between Treasury yields and rental property capitalization rates, suggesting that higher bond yields could pressure real estate valuations. The sharp decline in mortgage applications from pandemic-era peaks as housing affordability deteriorates. The growing influence of AI-related stocks in the S&P 500 and the risks associated with elevated valuations and speculative enthusiasm. The broad weakness beneath rising market indexes, noting that most Russell 3000 stocks have experienced declines of at least 10%. Why healthy markets typically feature broad participation in rising prices rather than gains concentrated in a handful of stocks.

Zero jobs will be lost to AI and we will tell you the reason why as we discuss the future of AI and the growing risks of investing in the AI boom. We talk how AI could improve existing software, why specialized robots may be more practical than humanoid designs, and how overhyped expectations could lead to an AI market bubble. We also examine the concerns about AI companies lobbying for regulations that could limit competition, the risks of relying on AI for learning and communication, and the dangers of overbuilding data centers and infrastructure. Investors should be warned about excessive AI exposure, concentrated portfolios, and rising interest rates. We discuss... Whether AI will eliminate jobs or primarily change how people work. The AI boom compared to the dot-com bubble and how excessive investment can lead to overbuilding and market crashes. How AI could improve existing software platforms by making company data easier to access and analyze. Whether expensive AI models can maintain their competitive advantages as open-source alternatives improve. How AI companies may use fear-based marketing and regulatory lobbying to protect their businesses from competition. How excessive reliance on AI can weaken critical thinking, learning, writing skills, and knowledge retention. Practical ways to use AI for research, productivity, and data analysis without becoming overly dependent on it. The AI bubble as a risk to investing, unrealistic growth expectations, excessive infrastructure spending, and potential financial risks. Concentrated investment portfolios and the risks of putting too much money into a single company or technology sector. Weakening real estate markets and how rising interest rates are putting pressure on property valuations. Why investors should compare the returns on risky investments with relatively safe U.S. Treasury yields. Higher interest rates could put further pressure on stock prices and other income-producing investments. The importance of managing risk, questioning market hype, and maintaining a cautious approach to investing.

David Miller discusses the unexpected strategy that can win when stocks are at their lowest. David shares about trend following, managed futures, and the importance of combining investment strategies that perform differently across market environments. He explains how Catalyst Mutual Funds uses trend following alongside equities to help reduce drawdowns, the challenges of whipsaw markets, and why diversification should mean combining uncorrelated strategies rather than simply owning more stocks. We also talk the impact of the Iran war, oil prices, gold, interest rates, and the upcoming midterm elections on markets. We discuss... David Miller shares his journey from an early passion for investing to launching Catalyst Mutual Funds. Catalyst was built around the idea of using free cash flow yield and return on capital to identify attractive companies. Trend following can perform particularly well during major bear markets when traditional equities are struggling. Combining managed futures with equities can create a portfolio with stronger risk-adjusted returns and smaller drawdowns. Investors should think of diversification as combining uncorrelated strategies rather than simply owning more stocks. Mean-reversion strategies can complement trend following by performing better when markets are volatile but lack a clear direction. How oil prices, gold, interest rates, and the Iran war have affected markets in 2026. Why the U.S. economy has been more resilient to higher oil prices because the country is now a major oil exporter. How the upcoming midterm elections could influence U.S. policy, oil prices, inflation, and the Federal Reserve. Investors should build portfolios that can perform across different economic and market environments rather than relying on a few high-growth stocks. Combining complementary strategies may be more practical than trying to predict the next Apple or Nvidia. Today's Panelists: Kirk Chisholm | Innovative Wealth Barbara Friedberg | Barbara Friedberg Personal Finance Douglas Heagren | Mergent College Advisors Follow on Facebook: https://www.facebook.com/moneytreepodcast Follow LinkedIn: https://www.linkedin.com/showcase/money-tree-investing-podcast Follow on Twitter/X: https://x.com/MTIPodcast For more information, visit the full show notes at https://moneytreepodcast.com/strategy-that-can-win-david-miller-858

AI companies are worth zero and we are going to tell you why. Today we discuss the rapid evolution of AI, what AI and AGI actually mean, and the importance of clean, reliable data. We also talk the risks of AI hallucinations and misinformation, privacy concerns, and the possibility that open-source models will eventually become good enough to challenge expensive frontier models. We also ask if AI companies really have durable competitive advantages, it's impact on jobs, the parallels to the internet bubble, and the difficulty of knowing which companies will ultimately benefit from AI. Investors should remain cautious as always and avoid chasing AI hype and expensive valuations. Protect yourselves from the eventual market revaluation, and recognize that future opportunities may emerge after the current AI boom loses momentum. Today we discuss... AI as an advanced form of machine learning and an interactive interface for analyzing large amounts of data. Why clean, reliable data is essential for AI to produce useful results. Whether artificial general intelligence has a clear definition and whether current AI has already surpassed traditional versions of the Turing test. How AI can create value by identifying patterns in large datasets that would be difficult for humans to analyze manually. The AI boom compared to the early internet and argue that today's leading AI companies may not necessarily be the long-term winners. Open-source AI models could eventually become good enough for most users and eliminate the need for expensive frontier models. Whether calls for AI regulation could partly be an attempt by large companies to limit competition and create regulatory capture. AI's potential impact on employment, arguing that most jobs will likely change rather than disappear entirely. The importance of protecting private information and avoiding putting sensitive data into public AI systems. Whether AI-generated content and AI agents could create a declining chain of increasingly unreliable information. Being bullish on AI technology does not necessarily mean being bullish on AI stocks or companies. The possibility of overinvestment in AI-related computing infrastructure and semiconductors. An eventual AI market revaluation could create significant losses but also produce major investment opportunities.