How Much Higher Can Stock Market Climb? | Jessica Inskip

David Lin
5 Apr 202437:49

Summary

TLDRJessica Inip, the director of education and product at OptionsPlay and co-host of the Market Maker podcast, discusses the latest earnings releases, stock market outlooks, and the growing role of AI in financial markets. She emphasizes the importance of focusing on AI and technology sector earnings, despite overall market challenges. Jessica also shares insights on the potential impact of the gig economy and the Fed's role in the market, highlighting the opportunities in tech stocks and the transformative power of AI in various industries.

Takeaways

  • 📈 Technical analysis of the market shows upward trends with the 13, 26, and 40 moving averages indicating overall market health.
  • 💡 Earnings season and AI advancements are potential catalysts for market movement and growth.
  • 🌐 The focus on AI and technology sectors is more significant than other industries for future market performance.
  • 🔄 Market consolidation is normal and finding support points is essential for continued upward momentum.
  • 📊 Earnings revisions and positive quarters suggest a positive trajectory for the market despite some misses.
  • 💭 The gig economy and its impact on labor market data could influence the Fed's decisions and market direction.
  • 🏠 Housing market considerations and the potential for rate cuts to stimulate supply are important to watch.
  • 📉 Inflation concerns and the Fed's balancing act between controlling inflation and maintaining economic growth.
  • 🚀 AI's role in the fifth industrial revolution and its potential to boost productivity and economic growth.
  • 🌟 The impact of AI on various sectors, including technology, healthcare, and financial services, and its transformative potential.
  • 🎧 Jessica's podcast aims to educate the public, especially women and beginners, on financial concepts and stock market workings in a relatable manner.

Q & A

  • What is the primary focus of the discussion in the transcript?

    -The primary focus of the discussion is on the trends in the technology sector, particularly in relation to earnings, moving averages, and the role of AI in the markets. It also touches on the broader market outlook, the impact of earnings season, and the potential influence of the Federal Reserve's decisions.

  • How does Jessica view the trend of the NASDAQ 100 based on her analysis?

    -Jessica views the trend of the NASDAQ 100 as waning, as it is not hugging the higher end of the band. However, she sees this as a normal consolidation phase before the market goes higher, with a catalyst potentially being the earnings season or developments in AI.

  • What is Jessica's perspective on the overall stock market performance?

    -Jessica believes that the overall stock market performance should not be solely focused on the 'Magnificent Seven' stocks. She emphasizes looking at broader participation, such as the S&P 500 equal weight and the Russell index, to get a more accurate picture of market health.

  • How does the gig economy factor into the discussion of the labor market and Fed policy?

    -The gig economy is seen as a potential wild card in the labor market. It could provide a different picture of employment that may not be fully captured in traditional data, potentially leading to a cooler labor market than realized, which could influence the Fed's decision on interest rates.

  • What does Jessica think about the yield curve inversion and its implications for a recession?

    -Jessica acknowledges the historical correlation between yield curve inversion and recession but suggests that this time might be different due to the Fed's quick responses to economic issues and the advancements in technology that provide more tools for managing the economy.

  • How does Jessica view the role of AI in the fifth industrial revolution?

    -Jessica sees AI as a pivotal element in the fifth industrial revolution, emphasizing its role in increasing productivity and transforming various sectors. She believes that AI's rapid development and integration into workflows will lead to significant changes in how we live and work.

  • What are some potential catalysts for the market to move higher, according to Jessica?

    -Jessica mentions the earnings season and developments in AI as potential catalysts for the market to move higher. She also suggests that a shift in the Federal Reserve's policy could serve as a catalyst later in the year.

  • How does Jessica analyze the performance of tech stocks?

    -Jessica uses a combination of fundamental analysis, looking at earnings and growth narratives, and technical analysis, using moving averages to determine trends. She also takes into account the broader market context and the specific performance of companies within the tech sector.

  • What is Jessica's take on the impact of AI on productivity and the job market?

    -Jessica believes that AI will significantly increase productivity and could change the job market by automating certain tasks. However, she also notes that AI could create new opportunities and demand for skills related to its development and implementation.

  • What are some of the sectors that Jessica sees benefiting from the AI explosion?

    -Jessica highlights sectors such as cloud computing, cybersecurity, and semiconductors as key beneficiaries of the AI explosion. She also mentions that AI will impact the technology sector itself, as it can help streamline coding and other technical processes.

  • How does Jessica's podcast contribute to financial education?

    -Jessica's podcast aims to demystify financial concepts and stock market workings, particularly for those who may be new to investing or find traditional financial jargon intimidating. It focuses on teaching in relatable terms and encourages questions to foster better understanding.

Outlines

00:00

📈 Market Trends and Earnings Discussion

The paragraph discusses the impact of tech earnings on market trends, specifically focusing on the 13, 26, and 40 moving averages. These averages indicate whether the market is rising or falling and act as support and resistance levels. The conversation highlights that although the trend may be waning, it signals consolidation rather than a downturn. The speakers welcome Jessica Inip, an expert in education and product at Optionsplay, to discuss earnings releases, market outlooks, and the role of AI in the markets. Jessica shares her insights on the importance of earnings growth in the AI sector and the overall positive consumer resilience. The discussion also touches on the broader market performance beyond the 'Magnificent Seven' stocks and the potential impact of the FED's interest rate decisions.

05:01

📊 Technical Analysis and Market Participation

This paragraph delves into Jessica's approach to technical analysis, emphasizing the use of 13, 26, and 40 moving averages on weekly charts to gauge market health. She explains that these averages represent one, two, and three quarters, respectively, and their upward slope indicates positive earnings growth. Jessica notes that while the NASDAQ 100 has seen a significant rise, some consolidation is normal. She also discusses the importance of broader market participation, comparing the S&P 500 equal weight index favorably to the NASDAQ 100. The conversation then shifts to potential market narratives supporting bullish sentiment, such as the gig economy and the possibility of a FED pivot. Jessica also shares her thoughts on the implications of the increasing number of people holding multiple jobs, suggesting it could indicate a more resilient consumer base.

10:02

💡 The Yield Curve and Economic Indicators

The discussion in this paragraph revolves around the yield curve's inversion and its traditional indication of an impending recession. However, Jessica suggests that this time might be different due to the Fed's quick response to economic issues and the use of technology in resolving banking system crises. She also considers the impact of AI on productivity and labor supply, and how these factors could influence the Fed's decisions. The conversation touches on the potential for a rate cut and its implications for the housing market and inflation. Jessica provides a nuanced view of the economic indicators, highlighting the complexity of interpreting current market signals.

15:03

🌐 The Fifth Industrial Revolution and AI's Role

In this paragraph, Jessica introduces the concept of the fifth industrial revolution, characterized by the rise of AI and machine learning. She explains how these technologies build upon previous industrial advancements and are poised to transform various sectors. Jessica emphasizes the rapid pace of AI development and its potential to increase productivity significantly. She also discusses the challenges of integrating AI into legacy systems and the need for guardrails to ensure ethical use. The conversation explores the future implications of AI, including the potential for virtual assistants and the shift in valuable job skills, such as coding. Jessica argues that AI is still underestimated and has vast potential for growth and innovation.

20:07

🚀 Tech Stocks and AI's Impact on Subsectors

The focus of this paragraph is on the performance of tech stocks, particularly in relation to AI. Jessica references a Morgan Stanley report that suggests tech earnings have historically been underestimated, leading to significant earnings surprises. She discusses the potential for further growth in AI-related stocks, including those in the semiconductor industry. Jessica also highlights the importance of cloud computing and cybersecurity in the AI ecosystem. She mentions the strategic moves by major tech companies to capture market share in AI and the opportunities for companies like IBM and Google. The conversation underscores the broad impact of AI across various technology subsectors and the potential for continued innovation and growth.

25:09

🎙️ Launching a Podcast for Financial Education

Jessica shares the story behind launching her podcast, which aims to educate the masses on financial concepts in a relatable manner. She explains her motivation to shift from traditional financial roles to a platform where she can speak freely about investing. The podcast, co-hosted by a friend, focuses on making complex financial topics accessible, especially to women and those new to the world of finance. Jessica discusses the importance of understanding fundamental concepts like the role of the FED, yield curves, and inflation before engaging in specific investment strategies. She expresses her satisfaction in helping listeners have 'light bulb' moments and emphasizes the podcast's goal to empower individuals through financial literacy.

30:09

🔗 Connecting with Jessica's Podcast

In the final paragraph, Jessica provides information on how to access her podcast for those interested in learning more about finance. She mentions that the podcast is available on all major podcast platforms, including Spotify, Apple Podcasts, and Good Pods, and also on YouTube. Jessica encourages listeners to visit their website, marketmakak herp podcast.com, for additional resources and episode equity. The conversation concludes with gratitude for the opportunity to share her insights and a reminder for viewers to follow her work across platforms.

Mindmap

Keywords

💡Tech Earnings

Tech earnings refer to the financial profits reported by technology companies. In the context of the video, it's emphasized that the performance of tech earnings is a significant factor driving market trends, particularly the 13, 26, and 40 moving averages which are used to analyze stock price movements. The discussion indicates that a strong tech earnings season or positive surprises can act as a catalyst to push the market higher.

💡Moving Averages

Moving averages are technical analysis tools used to smooth out price data and identify trends in securities. The video specifically mentions the 13, 26, and 40-day moving averages, which help to determine whether a stock's price is increasing or decreasing over specific time frames. These averages also serve as support and resistance levels, indicating price points where the stock may reverse its direction.

💡AI (Artificial Intelligence)

AI refers to the simulation of human intelligence in machines that are programmed to think and learn like humans. In the video, AI is highlighted as a key area of focus for market growth and innovation, with the potential to significantly impact various sectors. The discussion suggests that AI's role in the market is growing and could be a positive narrative for the future.

💡Earnings Season

Earnings season is the period during which publicly traded companies release their financial results for a given quarter or fiscal year. It is a critical time for investors as it provides insights into a company's financial health and can influence stock prices. In the video, the speaker mentions that earnings season can act as a catalyst for market movement, with positive earnings often driving stock prices higher.

💡Market Outlook

A market outlook refers to an expert's predictions or expectations about the direction or trend of financial markets. It includes analysis of various economic indicators, corporate earnings, and other factors that might influence investor sentiment and asset prices. In the video, the market outlook is discussed in relation to the performance of technology stocks and the potential impact of AI on market trends.

💡Support and Resistance

Support and resistance are terms used in technical analysis to describe price levels where buying or selling is likely to occur. Support is a price level where a stock is expected to find buying interest, preventing it from falling further. Resistance is a price level where selling interest is expected to overcome buying interest, preventing the stock from rising further. In the video, these concepts are used to analyze the movement of stock prices and predict future market behavior.

💡Gig Economy

The gig economy refers to a labor market characterized by the prevalence of short-term contracts or freelance work as opposed to permanent jobs. It often involves flexible, temporary, or independent work, usually facilitated by digital platforms. In the video, the gig economy is mentioned as a factor that could influence the broader market and the Fed's decisions, as it represents a shift in the labor market that may not be fully captured in traditional employment data.

💡Fed Pivot

A Fed pivot refers to a change in the monetary policy stance of the Federal Reserve, typically in response to evolving economic conditions. This could involve changes in interest rates or other measures to stimulate or cool down the economy. In the video, a potential Fed pivot is discussed in the context of how it might be influenced by factors such as the gig economy and AI's impact on productivity.

💡Yield Curve

The yield curve is a graph that plots the interest rates of bonds with equal credit quality but differing maturity dates. It is used to analyze the health of an economy, with the shape of the curve indicating expectations for future economic growth. An inverted yield curve, where short-term rates are higher than long-term rates, has historically been seen as a predictor of recessions. In the video, the yield curve's inversion and reversion are discussed in relation to potential economic indicators.

💡Inflation

Inflation refers to the rate at which the general level of prices for goods and services is rising, and subsequently, purchasing power is falling. Central banks attempt to limit inflation and avoid deflation to keep the economy running smoothly. In the video, the discussion of inflation is tied to the Federal Reserve's policy decisions and the potential impact of AI and other factors on the economy.

Highlights

The discussion focuses on the impact of technology earnings on moving averages, which reflect market trends and act as support and resistance levels.

The current market trend is considered waning, but this is seen as a period of consolidation rather than a decline, with the potential for a catalyst like earnings season to push the market higher.

AI and technology stocks are pivotal to market focus, with demand and earnings within this sector viewed as particularly important.

The overall market performance may be skewed by a few large stocks, with broader market indices like the Russell showing a flatter performance over the last two years.

Market participation is key, with technical indicators like the S&P 500 equal weight showing more positive positioning than the standard S&P 500.

The NASDAQ 100 has seen a significant run-up since the beginning of 2023, with the potential for a pullback on the horizon.

The use of moving averages on a weekly basis provides a qualitative quantitative approach to technical analysis, with the 13, 26, and 40-week averages used to gauge market health.

AI is expected to play an increasingly significant role in the markets, with productivity gains potentially leading to a shift in the labor market and Fed policy.

The gig economy may present a wildcard in the labor market, with data on its impact still limited, potentially affecting Fed policy and market sentiment.

The yield curve's inversion and subsequent reversion to normal may not necessarily indicate an imminent recession, as past patterns suggest, due to rapid responses to economic issues.

Inflation remains a concern, with the Fed's actions and statements suggesting a continued focus on reaching the 2% target, despite current rates remaining above 3%.

The potential for the Fed to cut rates is discussed, with the implications for growth and market performance hinging on the underlying reasons for such a move.

AI's impact on productivity and the potential for it to transform various sectors, including financial services and healthcare, is highlighted, with the expectation that it will streamline and enhance many processes.

The importance of cybersecurity and the need for innovative solutions in this area, as AI and technology continue to advance, is noted.

Jessica's podcast aims to educate and demystify financial concepts for a broader audience, particularly focusing on making complex topics more relatable and understandable.

The podcast covers a range of topics from basic financial education to current market updates, providing a comprehensive resource for those interested in finance and self-directed investing.

Jessica's shift from working for larger brokerage firms to her current role reflects a desire to communicate more freely and accessibly about finance and investing.

Transcripts

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but as soon as we start ramping up into

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Tech earnings that's what's driving that

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13 26 and 40 moving averages which

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essentially just shows the trend is is

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it going up is it going down and it acts

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as a means of support and resistance as

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well and that right that right now says

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the trend is waning because it's not

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hugging that higher end of the band but

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that just means a little bit of

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consolidation we'll find some support

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then we just need a catalyst to push us

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higher and normally that catalyst is is

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the earning season or somebody could

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tweet something who knows well we're

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joined today by Jessica inip she is the

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director of education and product at

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optionsplay and the co-host and founder

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of the market maker podcast we'll be

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talking about uh the latest earnings

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releases as well as stock uh Market

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outlooks and uh how AI is going to be

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playing a bigger role in our markets

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welcome to the show Jessica thank you

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for being here yeah absolutely it's a

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pleasure to be here glad we can connect

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and excited for today's conversation uh

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thank you very much I've seen you on um

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CNBC and Yahoo and yeah you you were

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great on other media so I wanted to get

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you on my show so thanks for being here

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you've also got your own show which we

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can uh chat about towards the end of the

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um uh interview so stay tuned to learn

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more about uh Jessica's uh podcast as

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well and uh I want to talk first about

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earning so uh a lot of disappointments

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from yesterday we're speaking on

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Thursday today but the markets didn't do

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well yesterday we have a bit of a bounce

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today um are you concerned about uh

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earnings missing a lot of estimates this

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quarter no not necessarily because the

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focus is more more on AI and technology

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and I want to make sure that I see the

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demand there and earnings within that

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sector specifically so that is okay

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whereas if I see earnings misses and

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more and retailers and things like that

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that all goes into the broader picture

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of the all overall macro environment

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where I want to see what the FED is

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pulsating so meaning when we go through

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earning season not only is it are we

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still seeing earnings growth so for

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example when we're we finalized q1 and

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now getting into Q2 getting those q1

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earnings we've had earnings revisions

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down but it's not as much and that's

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normal so that's a positive sign and

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earnings have also bottomed as of last

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year since we have positive quarters and

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we're still on that trajectory of

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positive Porters that still is good so

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overall I focus more from the earnings

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perspective on that growth picture in

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the AI narrative which is seemingly

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positive and then I just want to see the

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broader participation and then earning

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can give us an insight into company's

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Health overall consumer spending and

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awareness and that that to me still

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seems positive we keep saying they're

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hanging in there the consumers and they

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they certainly are resilient is the word

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yeah and certainly you've heard this

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before but if you take away the

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Magnificent Seven stocks I think it's

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maybe just five of them now uh the

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broader Market hasn't done as well so

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even just looking at the Russell it's

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been pretty much flat for the last two

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years um bit of a rebound the last year

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so how would you how would you respond

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to the argument that the overall stock

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market isn't really doing that great

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it's just a few stocks and you have to

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be it's an environment to be really

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selective right now yeah so I think if

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you're looking at the earnings it we can

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pull data and I think paint any picture

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we want which is so interesting with the

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market mechanics but I I do agree in the

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sense from the earnings view but we have

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to remember that the Market's

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forward-looking and when we look at

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broader participation that's when I

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focus more on a technical view so

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looking at the S&P 500 equal weight for

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example that is definitely more

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positively positioned from that Ford PE

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ratio than the S&P 500 and same with the

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russle and so I see broader

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participation as in there's demand for

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those Securities looking at the

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functions of supply and demand versus

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the solely just that Magnificent Seven

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or that narrow rally that we saw within

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the NASDAQ 100 having that natural

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rotation as is definitely good now

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within the Russell I know earlier in the

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year and I was inclusive of this or the

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famous Tom Lee coming in and saying

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value value value that of course is with

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the indication that the FED is going to

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cut rates those smaller businesses that

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dep are a little more Capital intensive

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or need those funds are going to

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positively benefit from a less

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restrictive Fed so that I I there is

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certainly risk there depending on what

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the FED does but we still have a lot of

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data until we till we get to that point

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and really understand it but I still I

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see this

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as I don't see what we're in this

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euphoric phase it's just this natural

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rotation that we're having and that's

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healthy and I think that's a good sign

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and I've really I'm I'm pounding the

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table on AI I have for quite some time

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and I know we'll talk about that in a

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little bit as well yeah we will um let's

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talk about the NASDAQ so um a big runup

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since all the way extending to the

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beginning of

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2023 and um I know you've you know

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analyzed Trends a lot are we due for a

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pullback Jessica yeah so I like to look

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at the NASDAQ 100 rather than the NASDAQ

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Composite just because the NASDAQ

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Composite is a little more diverse now

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so if we want it but it tends to leaps

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so from a technical perspective I have a

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very different charting view than most

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people but it it's because it's a I like

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to call it qualitative quantitative if

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you will okay so I I use the 13 26 and

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40 moving averages on a weekly basis i'

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normally look minimum to two to two to

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three years on a chart and the reason

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why I use the 1326 and 40 if you look at

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that time frame 13 weeks represents one

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quarter 26 is 2 and then 40 is three so

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since we look at the markets quarterly

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we kicked this off stop talking about

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earnings I want to look at the charts

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technically from that same type of lens

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so if you look at my charts you'll see

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the 13 26 and 40 moving averages I want

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to see them very simple at this point

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just sloping upwards if they slope

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upwards that means pric is increasing on

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a rolling quarter basis and that is good

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indicative of earnings without even

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looking at the fundamental aspect I

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still see that on the NASDAQ 100 it's

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gone a little far and that's okay so on

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top of that what I do is I add a simple

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actually first technical indicator I

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ever learned over a decade ago Ballinger

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bands it's it represents two standard

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deviations from a price so if you take

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the math behind it and you have an

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upwards Trend you can utilize that for

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strength of a trend because it's hugging

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the higher end of the range that's

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waning a little bit so consolida

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is absolutely normal before we go higher

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but if we pull when we started earnings

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and what's really accelerated us into

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those rally modes it tends to be that

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ramp up as we consume that data but as

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soon as we start ramping up into Tech

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earnings that's what's driving that 13

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26 and 40 moving averages which

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essentially just shows the trend is is

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it going up is it going down and it acts

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as a means of support and resistance as

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well and that right that right now says

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the trend is waning because it's not

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hugging that higher end of the band but

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that just means a little bit of

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consolidation we'll find some support

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then we just need a catalyst to push us

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higher and normally that catalyst is is

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the earning season or somebody could

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tweet something who knows what will

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happen with AI um we okay so besides Ai

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and potentially a Fed pivot later on in

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the year uh which we'll talk about what

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other narratives are there that could

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support this bullish sentiment going

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into the rest of uh Q you know Q3 and Q4

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yeah so I think there is certainly a lot

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with the domestication that we have of

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Industrials I think that could certainly

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serve as a bullish narrative and also

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the gig economy that's something we

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haven't talked about I we talk about it

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often but there actually isn't a lot of

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data on it so I I try to do my research

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and dig down through these rabbit holes

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and the FED hasn't done a research

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report or have the good enough data to

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do some analysis since it it was I I

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don't have the exact dat off top of my

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mind I apologize but it was in the early

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2000s area so it's been too much time

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but now the gig economy is so much more

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prevalent meaning it's all related in in

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a way besides I think it's hard to say

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besides fed pivot and AI because I think

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AI increases productivity which gives us

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more balance in the labor market which

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could lead to a Fed pivot but then also

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the gig economy is could be a different

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picture of the labor market that we're

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not seeing that could also lead to Fed

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stance so it's this big puzzle that

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comes together but the gig economy could

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be the wild card because we don't have

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the exact data of when that filters into

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the employment picture because if if you

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have that you may your side hustle could

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be 1099 and a means of income so you're

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not collecting unemployment because

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you're not eligible for it and if you're

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not collecting unemployment and you're

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not eligible for it we're not going to

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see you come into the data but if you

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lose your W2 income versus your side

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hustle or gig economy or those

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Freelancers that has a much larger impct

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impact on your expenses than the W2 or

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then you get what I'm saying so that

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that right there could be a bigger

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bigger issue that would emerge meaning

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we might have a cooler labor market than

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we realize which would lead to more to a

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a a more likelihood of a Fed pivot and

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cutting of rates but it's hard to see

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that and that to me is

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our something I'm watching it's the

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biggest risk but it could also be the

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biggest Catalyst um I've seen reports

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that uh the US economy has seen the most

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number of people holding multiple jobs

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at the same time I think you've alluded

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to this just now a lot of economists

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I've talked to don't see this as a great

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sign though Jessica because if you need

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multiple jobs you're clearly not doing

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as well as you could and the broader

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economy isn't supporting that kind of

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wage growth that many people would like

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to see which is why people need multiple

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jobs uh what do you think about that

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yeah I mean it's some instances so it

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depends on what that is so if you have

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multiple W2 income I would argue that

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but if you hold multiple as in that 1099

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income or you're going into freelancer

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that to me is a different type of

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consumer base that we have right now

play10:10

it's a different type of economy jenz is

play10:12

a completely different animal they are

play10:14

entrepreneural spirits and they they

play10:17

don't they're just very different they

play10:19

consume content differently they aren't

play10:22

necessarily looking for that normal

play10:24

corporate job that my generation was

play10:27

used to and perhaps they saw what we

play10:29

experience you Millennials are the most

play10:31

educated generation they also have the

play10:34

most debt they have the least assets

play10:37

whereas the entrepreneurs and anything

play10:39

that could come out of that did better

play10:40

and they have more easier access to that

play10:43

due to technology I mean even thinking

play10:45

about the great financial crisis in 2008

play10:48

you lost your job you couldn't go you

play10:51

know get sell affiliate links or get

play10:53

things like that with on the social

play10:55

media platforms you couldn't go drive

play10:56

for Uber you couldn't do these things so

play10:58

that creates more of a resilient

play11:00

consumer so I could I could definitely

play11:02

argue it both ways if you don't have

play11:03

enough to eat to meet your ends meet and

play11:06

you have to get another job to support

play11:08

you that is absolutely bad and I would

play11:09

see that terrible however if you're on

play11:11

the younger generation side where you

play11:14

are on this financial literacy train and

play11:16

the intent of you getting another job

play11:19

isn't for W2 but to create a the word is

play11:22

side hustle for yourself then that

play11:25

that's a not a bad thing at all yeah

play11:28

Millennials have pretty much everything

play11:30

going for them now except homes but

play11:32

that's a topic for a different

play11:33

discussion that's so true um how do you

play11:36

feel about the yield curve having

play11:38

inverted and then now it's rein verting

play11:40

if you take a look at just how it's

play11:42

behaved throughout history every not

play11:44

every single time but in most instances

play11:46

in the past whenever the yield curve I'm

play11:48

taking the 10-year MTH as a two-year as

play11:50

an example whenever the yield curve has

play11:52

um inverted to negative territory a

play11:55

recession usually follows a few months

play11:57

after that um now the yield curve has

play12:00

tended to had to reinert back to zero

play12:03

before a recession officially hits we're

play12:04

almost there it's almost back to zero uh

play12:07

is that cause for concern for you at

play12:10

least as an indicator that a recession

play12:11

is coming yeah you know it's hard to

play12:13

argue the the data there and I believe

play12:15

the average time is 13 months when it

play12:18

first inverts before we head into that

play12:20

recession territory but I think it makes

play12:22

sense to take a step back and I I hate

play12:26

saying the words this time is different

play12:29

because I I just I absolutely despise

play12:31

that but I'm saying it now so uh

play12:35

thinking about what the yield curve

play12:38

inversion causes is that credit crunch

play12:42

or that crisis there or the FED just

play12:45

moves too far too fast and they tip us

play12:47

into a recession because they affect the

play12:49

front end of the curve and what I'm

play12:50

thinking about what happened is is we

play12:52

had that with svb and we fixed that in a

play12:55

weekend I mean I didn't do anything but

play12:57

the FED fixed it in a weekend yeah

play12:59

and that's different than past

play13:02

recessions we've had some time aside

play13:05

from covid and it it's we do have more

play13:08

technology we do have access to data the

play13:10

FED is being more transparent than usual

play13:12

I think Powell even said this in one of

play13:14

his earlier speeches where the FED is

play13:18

really shifting their market dynamics

play13:20

and I love reading their studies when

play13:21

you pull them out when that they they

play13:23

really suff so quietly sometimes but one

play13:26

of his statements was you know the

play13:27

market is anticipating our every move

play13:30

and I chuckled I said well the Market's

play13:31

forward looking we always anticipating

play13:33

everyone's every move but it was

play13:35

something that clicked to him and the

play13:37

person who is making the decisions about

play13:41

the rates it's important to take his

play13:44

mindset aside from my own because he's

play13:46

going to have the bigger impact meaning

play13:49

I I think this time is different because

play13:51

we have had some

play13:52

negative negative connotation negative

play13:55

things happen within the economy within

play13:58

the banking system and they've been

play14:01

resolved really really quickly and now

play14:04

since we've have this restrictive

play14:06

environment the FED has a toolbox so

play14:08

it's possible that we'll hit that

play14:10

recession territory but if that happens

play14:13

I really think that the the fed's gonna

play14:16

they will step in very quickly and now

play14:18

they can and that is definitely a good

play14:20

sign but everything points back to AI

play14:23

increase in productivity if you started

play14:26

this hiking cycle with saying we've got

play14:27

an overheated labor market and all of

play14:30

the sudden you have this new technology

play14:31

that increases productivity and we have

play14:33

a labor Supply issue and now all of the

play14:35

sudden we have immigration come in I

play14:37

really think Powell should just play the

play14:38

lotto at this point is he keeps having

play14:40

things work for

play14:42

him he might say that a lottery winning

play14:45

is only transitory like inflation is oh

play14:48

there we go speaking of inflation um is

play14:51

that are we heading down towards 2%

play14:54

because the data hasn't been indicating

play14:55

a steepening trend downwards right we're

play14:57

still above 3% um for both headline and

play15:00

core and uh I'm looking at the CM fed

play15:03

watch tool there isn't a significant

play15:04

probability of a cut even by June I mean

play15:07

it's it's over 50% but it's not

play15:09

significant so what's your take on

play15:11

inflation and ultimately what the fed's

play15:12

going to do yeah that was interesting we

play15:15

got the ECB data there was their their

play15:17

flash numbers and theirs came down

play15:19

considerably and they also had some

play15:21

surprises in January and February so

play15:25

when we get our information perhaps

play15:27

especially with the Manu manufacturing

play15:28

that we got yesterday it would be a

play15:29

little better I don't like being in the

play15:31

business of predicting that we're going

play15:33

to get there but what I do want to

play15:36

consider is his stance and what he's

play15:38

looking at is he balancing credibility

play15:42

or what is the give and take at this

play15:44

point so he does consistently say we're

play15:46

on emission to 2% I like to call it

play15:50

Powell for swifties because if you're a

play15:52

Taylor Swift fan I apologize I'm

play15:54

bringing it to this but you analyze

play15:57

everything that that woman says to

play15:59

understand because they she just caters

play16:01

to those stem girls we do the same thing

play16:03

with fed Powell the way that he says

play16:05

something to indicate what he's going to

play16:07

do he has consistently said 2% but my

play16:10

question is what is he willing to give

play16:12

up in order to get to that place and I

play16:14

see him

play16:16

shifting language just ever so SL

play16:19

slightly which is why I like to relate

play16:20

it to that

play16:22

analogy it's a marathon or yeah it is a

play16:25

marathon we're at that last leg that

play16:28

last leg perhaps might be the hardest I

play16:30

don't run a marathon but that's what

play16:31

people say I'm more of a weights person

play16:34

but I I that to me is is the hardest

play16:39

part but we're still on the right track

play16:42

and he said on the last meeting he wants

play16:44

to see continuation of the trend that

play16:46

we're on which means to me that he'll

play16:49

cut as long as he thinks we're getting

play16:51

to that 2% and what I think The

play16:53

Balancing Act and the chess game that

play16:55

has to happen here he made that

play16:57

statement that he feels like rents is

play16:59

going to because of the lag effects that

play17:00

you're very aware of rents are going to

play17:02

come in to that data and that's what's

play17:04

going to help contribute to inflation

play17:06

actually coming down because we might we

play17:09

we're seeing that service and perhaps

play17:11

goods are normalizing at this moment so

play17:13

services to me is is the risk as they

play17:15

have been with stickiness but if rents

play17:17

comes down which really hits people's

play17:21

expenses that could be really good for

play17:23

the inflation picture he just didn't

play17:24

know what the timing was but The

play17:26

Balancing Act is this housing Supply

play17:29

issue that we have arguably you're I

play17:32

mean I I do own a home and I have a 3%

play17:34

mortgage rate there is no way I'm

play17:35

selling it I'm going to live here

play17:37

forever because I don't why would I I'd

play17:41

end up cost me 40% more to buy the home

play17:44

that's for sale across the street in my

play17:45

neighborhood that just logically doesn't

play17:48

make sense and then you multiply people

play17:49

like me plus the older generation that

play17:52

has most of the wealth until they

play17:54

downgrade which I'm sure will happen an

play17:56

interest rate cut arguably could help

play17:59

the inflation situation by creating a

play18:01

housing Supply well okay

play18:04

so we're not going to talk about housing

play18:05

too much but would you be interested in

play18:07

selling your home suppose mortgage rates

play18:09

come down to maybe not as close to 3%

play18:12

but maybe closer to 5% or 4% and

play18:16

assuming the value of your home has

play18:17

appreciated significantly you're going

play18:19

to lock in your capital gains yes you

play18:21

might pay a little bit more and morgage

play18:23

uh uh expenses from buying a home across

play18:26

the street but you're still locking in

play18:28

gains would you consider that if

play18:29

mortgage rates come down a bit

play18:32

more yeah I mean I I personally I'm not

play18:35

looking to move but if I was absolutely

play18:38

because that Balancing Act makes sense

play18:39

okay and and I think that will certainly

play18:41

help so which which argues could we

play18:44

could make the argument there that

play18:46

cutting interest rates getting that

play18:50

tenure down a little more will

play18:52

definitely definitely help the housing

play18:54

market for that reason alone yeah it'll

play18:56

soften some assets I've heard the

play18:57

argument as well that the fed may only

play18:59

cut when he sees signs of a Slowdown in

play19:02

the economy or when the unemployment

play19:04

rate goes up and so cutting may not be

play19:06

actually indicative of growth it could

play19:08

be indicative of the opposite which

play19:10

would signal perhaps a correction in the

play19:13

stock markets if he's cutting for bad

play19:15

reasons right yeah that's such a great

play19:18

statement it's the why there's I get so

play19:21

many questions on that do you so if the

play19:22

fed's going to cut Jessica are are the

play19:25

markets going to Surge well it depends

play19:26

on the why why are they cutting

play19:29

get absolutely very beautiful Point

play19:31

speaking of Taylor Swit I think her AOS

play19:33

tour generated five billion dollar for

play19:35

the for the economy could be funny if

play19:38

that's the reason fed's the fed's not

play19:40

cutting it's because Taylor Swift is you

play19:41

know actually contributing to growth um

play19:43

but I digress um okay there's studies on

play19:46

that there's studies on that okay I'm

play19:49

sure you've looked into those studies um

play19:51

so ultimately um okay let's talk about

play19:54

AI now you uh you submitted a piece to

play19:57

me thank you for that and you've talked

play19:58

about how we're currently in the fifth

play20:00

Industrial Revolution tell us about your

play20:02

thesis

play20:03

there yeah so there has

play20:07

been so thinking about the revolutions

play20:10

that we've had it's

play20:12

compounding where if you look at the

play20:14

movement that we have had when we just

play20:17

had railroads or water steam and

play20:20

mechanization and those assembly lines

play20:23

they were building on one another that

play20:26

ultimately grow in compounds so going

play20:29

back to the 1800s I don't think we have

play20:31

to go through them all individually but

play20:33

perhaps the 2000s there we had a dotom

play20:36

bubble in the 2000s is because we had

play20:38

companies we did not understand somebody

play20:40

put.com behind their company name

play20:42

everyone was excited about the internet

play20:44

from a valuation perspective it was very

play20:46

difficult to valuate because we didn't

play20:48

understand the revenue drivers that were

play20:49

there fast forward to today we use the

play20:52

internet in the worldwide web absolutely

play20:53

everywhere in every single vertical with

play20:56

every way every shape and formed which

play21:00

is proves that point of compounding

play21:03

2010s is when we got to that networking

play21:05

and machine learning meaning now we're

play21:08

at this different place where has

play21:09

compounded where the framework has been

play21:11

built via the Internet computers

play21:13

electronics and introducing Automation

play21:15

and now we have machine learning and now

play21:17

we have extremely smart now we're

play21:19

getting in the 2020s of self-learning

play21:21

cognitive collaboration of machines and

play21:24

there is so much that that can do was

play21:26

coding is being taken away and that l

play21:28

language will soon be human I think it's

play21:30

interesting it used to be so valuable to

play21:32

have the skill python on your resume

play21:35

that's of the shift and we have to shift

play21:37

with those revolutions meaning there's

play21:39

this wonderful piece that I sent to you

play21:41

or the screenshot from Morgan Stanley

play21:43

where they were going through these

play21:46

previous revolutionary periods and it

play21:50

was 38% that analyst weren't projecting

play21:54

because it's difficult to evaluate but I

play21:56

think the difference of difficult

play21:57

evaluation vers versus the 2000s and now

play22:00

is these are mature companies not with

play22:03

clear paths to profitability not

play22:05

companies that are in a garage with DOT

play22:08

trying to figure it out which we know

play22:10

Apple started there at some point but

play22:14

this this is different for that reason

play22:16

alone and we are seeing real demand

play22:20

which translates to real Revenue yes a

play22:23

lot of it is forward-looking and there's

play22:25

the supply chain issues and things of

play22:27

that nature but there is so much

play22:32

underestimation I believe within this

play22:34

entire entire AI because it also moves

play22:37

so fast once I feel like I learn how to

play22:40

do something within AI there's a new

play22:42

Plug-In or feature that I have to figure

play22:44

out and that is good but that also means

play22:48

that we have we haven't even tapped into

play22:51

it

play22:52

yet can you give us a glimpse of the

play22:54

future I think most people watching the

play22:57

show who aren't content creators or

play22:59

maybe work in finance professionally

play23:01

haven't really integrated their workflow

play23:03

with AI yet um think about if you're

play23:05

working in an office and you've got

play23:06

Legacy systems that are in place you

play23:08

don't have to switch right away and so

play23:10

most people don't use AI as much as um

play23:13

some others and so uh it's difficult for

play23:15

many people to understand exactly why

play23:17

there's this big hype around it can you

play23:19

just give us a sense of how our lives

play23:21

could change in the next 5 to 10 years

play23:24

absolutely so having a your own virtual

play23:28

assist would be a piece of it but having

play23:31

guard rails as well where you can make

play23:33

your own type of collaborative type of

play23:35

experiences so think about let's go real

play23:38

back in time if you're a member on

play23:39

Microsoft products I'm also advocating

play23:42

for this if you remember clippy yeah I I

play23:44

I knew you were going to say that as

play23:45

soon as you said

play23:47

Microsoft clippy I loved clippy I really

play23:50

think they should be bring clippy back

play23:51

that's where copilot should be be be

play23:54

amazing um nonetheless I digress but

play23:57

clippy help that that was a new

play24:00

iteration within a magical tool that we

play24:03

had where you could instead of a

play24:04

typewriter we're writing on the computer

play24:07

it's saving time that's why it's a

play24:09

productivity increase so if we moved

play24:11

from a typewriter to a computer to

play24:14

utilizing a Word document you don't have

play24:16

to erase things you just backspace it so

play24:18

now we're very quick and then if you

play24:20

don't understand how to use it oh you've

play24:22

got clippy who can help you when you

play24:24

search and ask but you have to be very

play24:26

specific within the commands clippy is

play24:28

not a person so now there is a tool

play24:31

where if you want to learn think about

play24:32

it integrated onto your computer and

play24:34

there are versions of that already and

play24:36

you could set that up if you know how to

play24:38

integrate very well where you could just

play24:42

speak to someone that could go through

play24:44

your data and understand what's needed

play24:46

there or you could say I have all of

play24:48

these files on my desktop and you could

play24:50

do this today if you want can you please

play24:52

find any research that I have done on

play24:54

artificial intelligence put that

play24:56

together on a Word document and then

play24:57

summarize the bullet points for me that

play25:00

is incredible and that that is a very

play25:03

small use case there's Automation and

play25:06

triggers where you can have it do one

play25:08

task learn to do another you can give it

play25:10

guard rails and then it can train itself

play25:12

so where that's where AI is right now is

play25:14

on that inference and acceleration piece

play25:17

where it it you teach it to train itself

play25:20

which is scary in its own way shape or

play25:22

form but if you think about what it is

play25:25

it mimics human behavior so so even for

play25:29

I was working on some research yesterday

play25:31

I had it create an infinite um and I got

play25:35

this from somebody uh I I wish I

play25:36

remembered his name so I can give him

play25:37

credibility right now but I I'll send it

play25:39

to you afterwards called it the infinite

play25:41

focus group where I had chat gbt give me

play25:46

uh for something I was looking to work

play25:47

on a list of people that would be in

play25:49

that focus group and it was my podcast

play25:51

and I said okay what are they going to

play25:53

why would they want to listen to my

play25:54

podcast give me their demographic where

play25:56

they are their family things like that

play25:58

then I said hey very humanely very

play26:02

humanely it be nice to to chat GPT I

play26:05

want you to inject some truth serum in

play26:07

them and we're going to have a

play26:08

conversation and I want to know what

play26:09

their trepidations are really that they

play26:11

wouldn't tell in in front of that Focus

play26:14

Group in front of people and then I got

play26:16

a very different response which turns

play26:18

into marketing gold so meaning there's

play26:20

just so many use cases that you can

play26:22

utilize purely from its implications

play26:25

today but it it can analyze

play26:29

very very quickly which is such an aid

play26:32

to productivity and I believe there was

play26:34

uh this this study was about six months

play26:38

ago the people who use AI tools right

play26:41

now are 40% more productive and that's a

play26:44

very small use case of people so imagine

play26:48

when that's more widely adopted and put

play26:51

into those bigger corporations which is

play26:54

in the works that takes some time if you

play26:55

ever worked on the procurement side it

play26:57

takes a while while to to get those

play26:59

things across the line but once they do

play27:02

then we're going to really see some

play27:03

changes ultimately investment

play27:05

appications yeah I mean have we missed a

play27:06

boat on companies like Nvidia perhaps we

play27:09

haven't gotten in but are the

play27:10

fundamentals still there for

play27:12

growth I I think so I mean there is

play27:15

definitely some demand Po and they're

play27:18

constantly constantly innovating and I

play27:21

think that is good to see their uh uh

play27:24

the uh their their blackw chip that

play27:27

looks promising they also another one

play27:28

that could integrate directly onto your

play27:30

computer so now your computer is AI that

play27:32

the cooling of chips so they're taking

play27:34

all of their problems and they're also

play27:35

looking to solve them as well and so

play27:38

it's not just one product that is

play27:41

necessary and also the AI pool is a

play27:44

really big pie and we have a sliver of

play27:47

that pie which means there's still

play27:48

market share to go around there's still

play27:51

lots of innovation that's needed and as

play27:53

long as they're still innovating then I

play27:55

do believe that there's still

play27:56

opportunity there well you've done

play27:58

actually some calculations uh you've you

play28:01

basically have a table of tech stocks

play28:04

and it says here the average of every

play28:06

stock mentioned has beat earnings by

play28:08

32% and um the conclusion is based on

play28:12

the underestimation average we have

play28:14

another 11% on average of earning

play28:16

surprises to the already revised higher

play28:18

can you just tell us walk us through

play28:20

what you did

play28:21

there yeah absolutely so that was based

play28:23

on the Morgan Stanley report where they

play28:24

said the earnings estimates were

play28:27

constantly beat for previous Evolutions

play28:31

or revolutions if you will so going back

play28:33

to that do area that was about

play28:37

38% so if we're at and this so I used

play28:41

the 32% is including penist because they

play28:44

were an early adopter I want to take

play28:46

that out because that was a skew of aund

play28:49

or two 200% and that that just Skuse the

play28:52

data so um if you take that out we've

play28:55

got about another 11% focusing just on

play28:59

AMD Nvidia Microsoft Google meta and

play29:01

Amazon so that that's where that came

play29:04

from since those are 177% all right now

play29:08

and if the average is a 38% surprise

play29:11

yeah the difference there is 11% of

play29:13

growth ultimately which Subs sector of

play29:15

tech would benefit most from the AI

play29:17

explosion besides let's say

play29:20

semiconductors yeah so I actually still

play29:23

like Google Amazon is just popped up on

play29:26

my list as late um because of the

play29:30

different touch points that are there so

play29:33

Google was my first pick a while ago

play29:36

because when you look at how to build a

play29:39

large language model they had most of

play29:41

the touch points and what I find very

play29:43

interesting is the VC funding and I I

play29:45

don't know if you've um seen any

play29:48

research on this but they basically fund

play29:50

themselves in a way it's this circular

play29:53

Capital as in they're investing in those

play29:55

companies that have ai and they give

play29:58

them Cloud credits and since they're

play30:00

investing in them then they capture the

play30:02

revenue on it as well so it's like

play30:03

circular Capital within that way the

play30:06

major ones are doing that but and and

play30:09

all of them require Nvidia which I find

play30:11

very interesting if you have the cloud

play30:12

you know you have to have so either

play30:14

you're going to pay that really high

play30:15

price point for the Nvidia chip or

play30:17

you're going to use something that has

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Cloud that already buys that Nvidia chip

play30:22

that you're going to need for those

play30:23

large language models so there's lots of

play30:25

solutions that are there those are the

play30:27

obvious but I think it's going to shift

play30:30

so we start with building those models

play30:33

that is that that that starting point

play30:37

the infrastructure and then it's the

play30:39

implementation so those that I think are

play30:41

going to emerge are the ones that take

play30:44

the headwinds and make them Tailwinds so

play30:46

now that we've got this grid issue

play30:49

there's opportunity there cyber security

play30:51

is going to be extremely important

play30:53

opportunity there the cooling that we

play30:56

need it requires a lot of Commodities

play30:59

that's opportunity I I flagged IBM uh I

play31:03

feel like that was about yeah that was

play31:05

last

play31:06

year

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yeah um IBM I think is also a really

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good opportunity because the way that

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they've researched Watson X they they've

play31:16

had some earning surprises but they also

play31:18

have a lot more demand and that just the

play31:21

increas is is amazing so besides just

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the semiconductors there is a lot of sub

play31:27

seor s that will fees out really really

play31:30

well for AI but I think the biggest

play31:33

sector that's going to have an impact on

play31:35

AI and this not for the reasons that you

play31:38

think is technology meaning because it

play31:41

can write code itself it's going to

play31:43

streamline technology even more so not

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just AI itself it's the implementation

play31:49

because now I'm looking into the

play31:49

implementation into Financial Services

play31:51

into Healthcare and and with the largest

play31:54

data set but the largest data set is in

play31:56

fact technology I I know so I I know

play31:59

Engineers are working on ways that AI

play32:02

can help us code in English in plain

play32:04

English which would be a complete Game

play32:05

Changer because you no longer have to

play32:07

learn a language anybody can code uh

play32:10

that would really re yeah that would

play32:12

really change things speaking of jobs

play32:13

that could be taken away from AI I hope

play32:15

podcast hosts isn't one of them um and

play32:18

that leads to our next discussion you

play32:20

have a podcast yourself so you know not

play32:24

a robot can't replace Jessica and your

play32:26

co-host uh at least not yet tell us why

play32:29

you launched your podcast and what

play32:30

that's all about yeah absolutely and

play32:33

thank you for asking I I sincerely

play32:35

appreciate that so I I've worked in

play32:37

finance now for about 15 years which is

play32:39

unbelievable to me and I made this

play32:41

really big career shift never forget the

play32:44

day February 22nd of 2022 where I uh

play32:48

stopped working for the bigger brokerage

play32:50

firms and I I work for a vendor called

play32:52

options play and that allowed me the

play32:54

opportunity to not be constrained by

play32:55

Financial licenses and for lack of a

play32:58

better word say whatever I want sure so

play33:01

so uh my friend I've always taught her

play33:03

about self-directed investing but

play33:06

obviously you can't talk about that on

play33:09

social media when holding those type of

play33:11

licenses that I did so I'm I'm no longer

play33:13

licensed voluntarily and she had this

play33:16

idea that said hey Jessica every time

play33:18

you tell me something I tell other

play33:20

people and I know more people can

play33:22

benefit from this and on top of that

play33:24

I've been the first female in a lot of

play33:27

places

play33:28

and where I find that the investing Gap

play33:31

is derived from it's not

play33:35

that it yes it is an oversaturated

play33:38

Market with men but men have to talk

play33:40

about stock market do not if you ever

play33:42

meet a a Wall Street bro as they call it

play33:45

they don't they don't shut up but what

play33:47

happens when they try to explain it to

play33:48

you it's in relatable terms not to me I

play33:52

don't know anything about football and I

play33:54

don't really care about it I I I don't

play33:55

get it because it's not my language and

play33:58

so that's what our podcast is is it

play34:00

shifts it from that type of language to

play34:03

just something that's a little more

play34:04

relatable to women on the the mass and

play34:08

he she's the as well anyone is is here

play34:11

to listen but we break down how the

play34:13

stock market works in those type of

play34:15

terms so I teach her I she says that I

play34:19

made the biggest risk because I gave up

play34:20

my licenses and talk about it but I

play34:22

think she took an even bigger risk

play34:24

because she sits there live and say is I

play34:28

don't understand how this works break it

play34:30

down again and it takes a lot of Courage

play34:32

for someone to say I don't understand

play34:33

that I don't understand that but the

play34:34

results been and all of our feedback is

play34:37

thank you for asking the questions that

play34:38

I'm too afraid to ask I finally get how

play34:40

it works and it's been so rewarding not

play34:43

only getting that feedback but watching

play34:46

her progress even we did a recent

play34:49

episode on how to lock in higher rates

play34:52

using a CD ladder and using treasuries

play34:54

and things of that nature but before we

play34:57

even and that's the first time we

play34:58

physically placed a trade because it's a

play35:00

self-directing investing education

play35:02

podcast that was episode 31 she needed

play35:05

all of that primer beforehand to

play35:07

understand who the FED is what they do

play35:10

what an inverted yield curve is even

play35:12

what the treasury is with supply and

play35:13

demand and the debt ceiling and and all

play35:16

of that and understanding inflation to

play35:18

get to that point as to why that's

play35:20

needed and I just love those light bulb

play35:23

moments so if you tune into to that I

play35:24

know that was a long answer so I

play35:26

apologize corrupted your friended now

play35:29

all that all she's going to talk about

play35:30

at dinner parties is the fed and then

play35:32

inverted y curves and CD ladders so yeah

play35:36

that it's possible yeah you've changed

play35:38

her life For Better or Worse who knows

play35:40

um but certainly we'll tune into that uh

play35:43

that is so but but I mean presumably

play35:45

this could be for anybody who is

play35:46

interested in finance who is just

play35:47

starting to learn right it doesn't um it

play35:50

sounds like you're just educating the

play35:51

masses about basic Financial

play35:54

Concepts yeah we still do stock market

play35:56

updates absolutely absolutely so so we

play35:58

bring it all together so this is how it

play36:00

works but here's also how it works today

play36:03

and then also what's happened in the

play36:04

past so it's definitely ramping up there

play36:07

and it and she comes with questions so

play36:09

there was a uh question that she had

play36:12

about dark pools and how they work so we

play36:14

went into detail and we talk about dark

play36:16

PS we so it it's definitely relevant to

play36:19

today we haven't gotten any technicals

play36:22

or anything too deep just yet but if you

play36:25

want to learn how the stock market works

play36:27

from start to finish that's absolutely

play36:30

the in the intent of it okay well uh

play36:32

where can we uh where can we find this

play36:34

podcast and follow your work on other

play36:36

platforms as well yeah thank you for

play36:39

asking so it's available everywhere that

play36:42

a podcast is streaming on your favorite

play36:44

podcast app I probably can't even name

play36:46

them all so it's on all the major ones

play36:48

of course Apple

play36:49

Spotify uh good pods even Google podcast

play36:53

just went away so you can find us on

play36:54

YouTube music and we do also upload to

play36:56

Youtube We haven't put our RSS feed into

play36:58

YouTube music because we want to keep

play37:00

the video there so know that so I

play37:02

definitely recommend the best place

play37:03

would be Spotify or good pods but we

play37:06

also have a website it's called Market

play37:08

makak herp podcast.com and there every

play37:11

episode we include what's called episode

play37:14

Equity where if it needs a supporting

play37:16

article we'll put that there anytime

play37:19

that we have additional takeaways that

play37:22

goes into our blog which is called our

play37:24

dividends we have lots of fun with the

play37:25

names you can see okay

play37:28

okay yeah I'll definitely will put the

play37:29

links in the description down below so

play37:30

make sure to follow Jessica and her work

play37:33

there thank you very much for your time

play37:34

we'll speak again soon yeah thank you so

play37:37

much it was a pleasure I really enjoyed

play37:38

it yeah thank you for watching don't

play37:39

forget to like And

play37:48

subscribe

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