<![CDATA[Foresee Markets]]>Foresee Markets is a podcast about how structured thinking, quantitative research, and artificial intelligence intersect with real-world investing. Hosted by applied economics practitioner Alejandro Ramirez Lemus and mathematician and AI researcher Serhii Nikolaiev, the show explores how capital moves through modern financial systems and how investors can make decisions under uncertainty.

Each episode examines the mechanics behind markets: liquidity, asset classes, portfolio construction, risk management, and the role of data in financial decision-making. Through conversations that combine economic reasoning, mathematical structure, and practical market experience, the podcast breaks down how models behave outside of theory — in live market conditions where volatility, inflation, and imperfect information shape outcomes.

Rather than offering predictions, trading tips, or short-term speculation, Foresee Markets focuses on understanding the frameworks that drive long-term investment thinking.

The goal is to help listeners see markets more clearly — and approach capital allocation with discipline, structure, and perspective.

]]>foreseemarkets.comRiverside.fm (https://riverside.com)Thu, 28 May 2026 15:06:25 GMTMon, 09 Mar 2026 13:38:24 GMT60Foresee Markets<p><b>Foresee Markets</b> is a podcast about how structured thinking, quantitative research, and artificial intelligence intersect with real-world investing. Hosted by applied economics practitioner<a rel="noopener noreferrer nofollow" href="https://www.linkedin.com/in/alejandro-nexus/" target="_blank"> Alejandro Ramirez Lemus</a> and mathematician and AI researcher <a rel="noopener noreferrer nofollow" href="https://www.linkedin.com/in/sergii-nikolaiev/" target="_blank">Serhii Nikolaiev</a>, the show explores how capital moves through modern financial systems and how investors can make decisions under uncertainty.</p><p>Each episode examines the mechanics behind markets: liquidity, asset classes, portfolio construction, risk management, and the role of data in financial decision-making. Through conversations that combine economic reasoning, mathematical structure, and practical market experience, the podcast breaks down how models behave outside of theory — in live market conditions where volatility, inflation, and imperfect information shape outcomes.</p><p>Rather than offering predictions, trading tips, or short-term speculation, Foresee Markets focuses on understanding the frameworks that drive long-term investment thinking.</p><p>The goal is to help listeners see markets more clearly — and approach capital allocation with discipline, structure, and perspective.</p>serialForesee Marketssocial@foreseemarkets.comno<![CDATA[Episode 9: The Algorithm Exited Everything. Here's Why That's a Good Sign]]>On May 1st, 2026, the algorithm did something unexpected — it exited all positions and moved to cash. No stocks to buy. No trades to place. Just a signal that said: wait.

In this episode, Alejandro and Serhii explain why that's not a failure — it's the system working exactly as intended.

They walk through three live paper accounts sitting entirely in cash, a portfolio that returned 25% from January to May while the S&P 500 returned 5.8% over the same period, and a recovery rate of 92% on overnight gap exits — meaning when the algorithm said sell, it almost always knew when to get back in.

The core insight: holding cash is a position. And knowing when not to buy is just as valuable as knowing what to buy.

One stock per sector. Always the top performer. Rotated out the moment something better appears. A win rate of 33% — and still 25% return in four months.

The algorithm doesn't predict. It measures. And sometimes what it measures tells you to do nothing.

⏱️ Timestamps:

0:00 – Introduction

0:39 – Why the algorithm exited everything

1:49 – Cash as a position — what it signals

2:23 – Live account walkthrough: three paper portfolios in cash

3:02 – Portfolio performance: 25% vs S&P's 5.8% (Jan–May)

5:32 – One stock per sector — why this works

8:55 – Win rate 33.3% and what it actually means

10:35 – What a full cash position tells you about the market

13:36 – Overnight gap risk and the 92% recovery rate

16:01 – What happens Monday when the algorithm reruns

――――――――――――――――――――

Foresee Markets — AI, quantitative research, and structured thinking applied to real market conditions.

🎙️ Hosted by Alejandro Ramirez Lemus and Serhii Nikolaiev.

💬 Tell us in the comments: Would you trust an algorithm to move you to cash automatically? Like, subscribe, and hit the bell so you never miss an episode of Foresee Markets.

――――――――――――――――――――

📹 During the podcast, important visual information is sometimes presented alongside the discussion. For the full experience, we recommend watching the episode on https://www.youtube.com/@ForeseeMarkets

This podcast is intended for educational purposes only and should not be considered financial or investment advice.

]]>5812e1db-def0-4062-aecd-392c73ad7766Tue, 19 May 2026 17:31:05 GMT<p>On May 1st, 2026, the algorithm did something unexpected — it exited all positions and moved to cash. No stocks to buy. No trades to place. Just a signal that said: wait.</p><p></p><p>In this episode, Alejandro and Serhii explain why that's not a failure — it's the system working exactly as intended.</p><p></p><p>They walk through three live paper accounts sitting entirely in cash, a portfolio that returned 25% from January to May while the S&amp;P 500 returned 5.8% over the same period, and a recovery rate of 92% on overnight gap exits — meaning when the algorithm said sell, it almost always knew when to get back in.</p><p></p><p>The core insight: holding cash is a position. And knowing when not to buy is just as valuable as knowing what to buy.</p><p></p><p>One stock per sector. Always the top performer. Rotated out the moment something better appears. A win rate of 33% — and still 25% return in four months.</p><p></p><p>The algorithm doesn't predict. It measures. And sometimes what it measures tells you to do nothing.</p><p></p><p>⏱️ Timestamps:</p><p>0:00 – Introduction</p><p>0:39 – Why the algorithm exited everything</p><p>1:49 – Cash as a position — what it signals</p><p>2:23 – Live account walkthrough: three paper portfolios in cash</p><p>3:02 – Portfolio performance: 25% vs S&amp;P's 5.8% (Jan–May)</p><p>5:32 – One stock per sector — why this works</p><p>8:55 – Win rate 33.3% and what it actually means</p><p>10:35 – What a full cash position tells you about the market</p><p>13:36 – Overnight gap risk and the 92% recovery rate</p><p>16:01 – What happens Monday when the algorithm reruns</p><p></p><p>――――――――――――――――――――</p><p></p><p>Foresee Markets — AI, quantitative research, and structured thinking applied to real market conditions.</p><p>🎙️ Hosted by Alejandro Ramirez Lemus and Serhii Nikolaiev.</p><p></p><p>💬 Tell us in the comments: Would you trust an algorithm to move you to cash automatically? Like, subscribe, and hit the bell so you never miss an episode of Foresee Markets.</p><p></p><p>――――――――――――――――――――</p><p></p><p>📹 During the podcast, important visual information is sometimes presented alongside the discussion. For the full experience, we recommend watching the episode on <a rel="noopener noreferrer nofollow" href="https://www.youtube.com/@ForeseeMarkets" target="_blank">https://www.youtube.com/@ForeseeMarkets</a></p><p></p><p>This podcast is intended for educational purposes only and should not be considered financial or investment advice.</p>no00:17:101Episode 9: The Algorithm Exited Everything. Here's Why That's a Good Signfull<![CDATA[Episode 8: $17,500 in Two Weeks and the Algorithm Did It Automatically]]>Two weeks. $387,000 deployed. $17,500 returned. Zero manual trades.

In this episode, Alejandro and Serhii check back in on the live paper portfolio and the numbers are hard to ignore. The algorithm ran completely on its own, selected four stocks from a universe of 3,000 assets, managed trail stops automatically via API, and produced a 2.2% weekly gain. Annualised, that's 116%.

No news feed. No human intervention. Just technical data, volume analysis, and how each stock was performing against its benchmark and the S&P 500.

They also walk through BKR Baker Hughes which the algorithm bought right before a strong earnings call, without reading a single headline. The system identified the signal from technical data and volume analysis alone. Then, live on screen during the episode, the portfolio crossed $18,000 in gains.

No predictions. No hype. Just a system doing exactly what it was built to do.

⏱️ Timestamps:

0:00 – Introduction

1:36 – How the algorithm works — quick recap

2:41 – Live portfolio walkthrough

3:53 – Calculating the annualised yield

8:00 – Current positions and how they were selected

11:35 – BKR: bought before earnings without reading the news

18:52 – Portfolio hits $18,000 live on screen

20:02 – What comes next: bringing this to the public

21:31 – Paper trading explained

――――――――――――――――――――

Foresee Markets — AI, quantitative research, and structured thinking applied to real market conditions.

🎙️ Hosted by Alejandro Ramirez Lemus and Serhii Nikolaiev.

💬 Tell us in the comments: What would you want the algorithm to analyse next? Like, subscribe, and hit the bell so you never miss an episode of Foresee Markets.

――――――――――――――――――――

📹 During the podcast, important visual information is sometimes presented alongside the discussion. For the full experience, we recommend watching the episode on https://www.youtube.com/@ForeseeMarkets

]]>8eb20916-0d46-4a67-bc68-0826ec501895Tue, 19 May 2026 17:27:26 GMT<p>Two weeks. $387,000 deployed. $17,500 returned. Zero manual trades.</p><p></p><p>In this episode, Alejandro and Serhii check back in on the live paper portfolio and the numbers are hard to ignore. The algorithm ran completely on its own, selected four stocks from a universe of 3,000 assets, managed trail stops automatically via API, and produced a 2.2% weekly gain. Annualised, that's 116%.</p><p></p><p>No news feed. No human intervention. Just technical data, volume analysis, and how each stock was performing against its benchmark and the S&amp;P 500.</p><p></p><p>They also walk through BKR Baker Hughes which the algorithm bought right before a strong earnings call, without reading a single headline. The system identified the signal from technical data and volume analysis alone. Then, live on screen during the episode, the portfolio crossed $18,000 in gains.</p><p></p><p>No predictions. No hype. Just a system doing exactly what it was built to do.</p><p></p><p>⏱️ Timestamps:</p><p>0:00 – Introduction</p><p>1:36 – How the algorithm works — quick recap</p><p>2:41 – Live portfolio walkthrough</p><p>3:53 – Calculating the annualised yield</p><p>8:00 – Current positions and how they were selected</p><p>11:35 – BKR: bought before earnings without reading the news</p><p>18:52 – Portfolio hits $18,000 live on screen</p><p>20:02 – What comes next: bringing this to the public</p><p>21:31 – Paper trading explained</p><p></p><p>――――――――――――――――――――</p><p></p><p>Foresee Markets — AI, quantitative research, and structured thinking applied to real market conditions.</p><p></p><p>🎙️ Hosted by Alejandro Ramirez Lemus and Serhii Nikolaiev.</p><p></p><p>💬 Tell us in the comments: What would you want the algorithm to analyse next? Like, subscribe, and hit the bell so you never miss an episode of Foresee Markets.</p><p></p><p>――――――――――――――――――――</p><p></p><p>📹 During the podcast, important visual information is sometimes presented alongside the discussion. For the full experience, we recommend watching the episode on <a rel="noopener noreferrer nofollow" href="https://www.youtube.com/@ForeseeMarkets" target="_blank">https://www.youtube.com/@ForeseeMarkets</a></p>no00:22:561Episode 8: $17,500 in Two Weeks and the Algorithm Did It Automaticallyfull<![CDATA[Episode 7: The Six-Dimensional System That Beats the Market]]>Most people have heard of the stock market. Very few understand what's actually moving it.

In this episode, Alejandro and Serhii walk through the full system live on screen — what the six-dimensional model is, how it measures a stock's position inside its sector, how risk morphs over time, and how the algorithm decides to buy, hold, trim or exit. With real backtest results from 2020 to 2026.

No predictions. No hype. Just the infrastructure, explained clearly for anyone who wants to understand how a quantitative system actually works.
One thing worth knowing before you dive in: a 37% win rate can still beat the S&P by 2x — if the system manages risk better than the market does.
Foresee Markets — AI, quantitative research, and structured thinking applied to real market conditions. Hosted by Alejandro Ramirez Lemus and Serhii Nikolaiev.

⏱️ Timestamps:
0:00 – Introduction
0:33 – The idea behind the model
1:52 – What is a six-dimensional system?
3:40 – Quantum mechanics and the particle metaphor
8:46 – Backtest results: 2020–2026
11:00 – Polymorphic risk — how the system adapts
13:15 – Trouble assets: when to exit
18:00 – Overnight gap risk analysis
22:20 – Live portfolio walkthrough
27:00 – How the product works for brokers
28:49 – Recap & next steps

---

Foresee Markets — AI, quantitative research, and structured thinking applied to real market conditions.

🎙️ Hosted by Alejandro Ramirez Lemus and Serhii Nikolaiev.

---

💬 Tell us in the comments: What part of the system do you want us to go deeper on next? Like, subscribe, and hit the bell so you never miss an episode of Foresee Markets.

---

📹 During the podcast, important visual information is sometimes presented alongside the discussion. For the full experience, we recommend watching the episode on https://www.youtube.com/@ForeseeMarkets

]]>ee21767a-e320-4f57-bf49-bb3594c117c5Tue, 19 May 2026 17:23:46 GMT<p>Most people have heard of the stock market. Very few understand what's actually moving it.<br /><br />In this episode, Alejandro and Serhii walk through the full system live on screen — what the six-dimensional model is, how it measures a stock's position inside its sector, how risk morphs over time, and how the algorithm decides to buy, hold, trim or exit. With real backtest results from 2020 to 2026.<br /><br />No predictions. No hype. Just the infrastructure, explained clearly for anyone who wants to understand how a quantitative system actually works.<br />One thing worth knowing before you dive in: a 37% win rate can still beat the S&amp;P by 2x — if the system manages risk better than the market does.<br />Foresee Markets — AI, quantitative research, and structured thinking applied to real market conditions. Hosted by Alejandro Ramirez Lemus and Serhii Nikolaiev.<br /><br />⏱️ Timestamps:<br />0:00 – Introduction<br />0:33 – The idea behind the model<br />1:52 – What is a six-dimensional system?<br />3:40 – Quantum mechanics and the particle metaphor<br />8:46 – Backtest results: 2020–2026<br />11:00 – Polymorphic risk — how the system adapts<br />13:15 – Trouble assets: when to exit<br />18:00 – Overnight gap risk analysis<br />22:20 – Live portfolio walkthrough<br />27:00 – How the product works for brokers<br />28:49 – Recap &amp; next steps<br /><br />---<br /><br />Foresee Markets — AI, quantitative research, and structured thinking applied to real market conditions.</p><p></p><p>🎙️ Hosted by Alejandro Ramirez Lemus and Serhii Nikolaiev.</p><p></p><p>---<br /><br />💬 Tell us in the comments: What part of the system do you want us to go deeper on next? Like, subscribe, and hit the bell so you never miss an episode of Foresee Markets.<br /><br />---</p><p></p><p>📹 During the podcast, important visual information is sometimes presented alongside the discussion. For the full experience, we recommend watching the episode on <a rel="noopener noreferrer nofollow" href="https://www.youtube.com/@ForeseeMarkets" target="_blank">https://www.youtube.com/@ForeseeMarkets</a></p>no00:29:151Episode 7: The Six-Dimensional System That Beats the Marketfull<![CDATA[Episode 6: How To Get Into Crypto From Zero]]>A lot of people are curious about crypto but don't know where actually to start, not because it's complicated, but because no one explains the basics without assuming you already know them.

In this episode of the Foresee Markets Podcast, Alejandro and Serhii walk through everything from scratch, live on screen. What crypto actually is, how to set up a MetaMask wallet, how to fund it using fiat, and how to spend it in a real store using the Coinbase debit card.

Alejandro sets up the full infrastructure during the episode. Serhii provides the systems context — how blockchains, tokens, wallets, and exchanges connect.

The key honest point from the conversation: crypto is not a traditional currency. It doesn't preserve value the way cash does — it moves with the market. Understanding that risk before you enter is what makes the difference.

One reminder worth repeating: your private keys are your responsibility. Never share them. If lost, there is no recovery — unlike a bank account.

A practical, no-hype episode for anyone who's been waiting for a clear starting point.

During the podcast, important visual information is sometimes presented alongside the discussion. For the full experience, we recommend watching the episode on YouTube.

This podcast is intended for educational purposes only and should not be considered financial or investment advice.

]]>f87c026a-6dca-4e9b-8eca-5bfa6e8875fcWed, 22 Apr 2026 13:30:00 GMT<p>A lot of people are curious about crypto but don't know where actually to start, not because it's complicated, but because no one explains the basics without assuming you already know them.</p><p>In this episode of the Foresee Markets Podcast, Alejandro and Serhii walk through everything from scratch, live on screen. What crypto actually is, how to set up a MetaMask wallet, how to fund it using fiat, and how to spend it in a real store using the Coinbase debit card.</p><p>Alejandro sets up the full infrastructure during the episode. Serhii provides the systems context — how blockchains, tokens, wallets, and exchanges connect.</p><p>The key honest point from the conversation: crypto is not a traditional currency. It doesn't preserve value the way cash does — it moves with the market. Understanding that risk before you enter is what makes the difference.</p><p>One reminder worth repeating: your private keys are your responsibility. Never share them. If lost, there is no recovery — unlike a bank account.</p><p>A practical, no-hype episode for anyone who's been waiting for a clear starting point.<br /><br />During the podcast, important visual information is sometimes presented alongside the discussion. For the full experience, we recommend watching the episode on <a rel="noopener noreferrer nofollow" href="https://youtu.be/3WA_veig4E0?si=NNDH3ZQW9V3ilwCs" target="_blank"><b>YouTube</b></a>.<br /><br />This podcast is intended for educational purposes only and should not be considered financial or investment advice.</p>no00:20:591Episode 6: How To Get Into Crypto From Zerofull<![CDATA[Episode 5: How To Read Volume In Markets]]>In October 2025, a stock dropped 50% in a single session. Alejandro had been watching it — and the volume data had been signalling something was wrong for weeks before it happened.

This episode walks through that case study in detail on a live chart. The core observation: when you see unusually high volume with almost no price movement, that is not noise. It means large participants are exchanging positions without moving the market — and a significant price move is likely to follow. Whether it goes up or down depends on the broader context, but the signal itself is reliable.

Alejandro and Serhii also cover how to use trail stop-losses to protect open positions, why after-hours order placement matters, and how to track a stock against its sector benchmark — in this case consumer staples via XLP — to anticipate broader selloffs before they hit individual positions.

The lesson is not to avoid volatile stocks. It is to read the data they are already giving you.

During the podcast, important visual information is sometimes presented alongside the discussion. For the full experience, we recommend watching the episode on YouTube.

This podcast is intended for educational purposes only and should not be considered financial or investment advice.

]]>85906849-9bb3-4659-80aa-c4169bf04158Wed, 15 Apr 2026 14:03:48 GMT<p>In October 2025, a stock dropped 50% in a single session. Alejandro had been watching it — and the volume data had been signalling something was wrong for weeks before it happened. <br /><br />This episode walks through that case study in detail on a live chart. The core observation: when you see unusually high volume with almost no price movement, that is not noise. It means large participants are exchanging positions without moving the market — and a significant price move is likely to follow. Whether it goes up or down depends on the broader context, but the signal itself is reliable. <br /><br />Alejandro and Serhii also cover how to use trail stop-losses to protect open positions, why after-hours order placement matters, and how to track a stock against its sector benchmark — in this case consumer staples via XLP — to anticipate broader selloffs before they hit individual positions. <br /><br />The lesson is not to avoid volatile stocks. It is to read the data they are already giving you. </p><p></p><p>During the podcast, important visual information is sometimes presented alongside the discussion. For the full experience, we recommend watching the episode on <a rel="noopener noreferrer nofollow" href="https://youtu.be/3WA_veig4E0?si=NNDH3ZQW9V3ilwCs" target="_blank">YouTube</a>.<br /><br />This podcast is intended for educational purposes only and should not be considered financial or investment advice.</p>no00:16:1615Episode 5: How To Read Volume In Marketsfull<![CDATA[Episode 4: Can AI Beat The S&P 500?]]>A $1,000,000 portfolio built on AI-driven equity selection returned 62% over the period — compared to 46% on the S&P 500 over the same timeframe. That's 16 percentage points ahead of the benchmark on a fully automated system. 

In this episode, Alejandro walks through how that system actually works — starting from a universe of 3,100 companies filtered by market capitalisation ($400M+ threshold) and liquidity, down to 127 investable positions selected by the algorithm. Serhii walks through the mathematical logic behind the filtering and portfolio construction. 

They also address something most quantitative content avoids: the limitations. The system underperformed early while it was learning. There were periods where the S&P recovered faster. And AI cannot process unstructured signals like geopolitical events unless explicitly programmed to — that gap still requires human judgment. 

The takeaway is not that automation beats everything. It's that the right combination of systematic discipline and informed oversight is what actually outperforms. 

During the podcast, important visual information is sometimes presented alongside the discussion. For the full experience, we recommend watching the episode on platforms where the video version is available.

This podcast is intended for educational purposes only and should not be considered financial or investment advice.

]]>33bfe9e6-e48e-4a64-bbf5-c0dc9d49a04aWed, 08 Apr 2026 14:07:13 GMT<p>A $1,000,000 portfolio built on AI-driven equity selection returned 62% over the period — compared to 46% on the S&amp;P 500 over the same timeframe. That's 16 percentage points ahead of the benchmark on a fully automated system. </p><p></p><p>In this episode, Alejandro walks through how that system actually works — starting from a universe of 3,100 companies filtered by market capitalisation ($400M+ threshold) and liquidity, down to 127 investable positions selected by the algorithm. Serhii walks through the mathematical logic behind the filtering and portfolio construction. </p><p></p><p>They also address something most quantitative content avoids: the limitations. The system underperformed early while it was learning. There were periods where the S&amp;P recovered faster. And AI cannot process unstructured signals like geopolitical events unless explicitly programmed to — that gap still requires human judgment. </p><p></p><p>The takeaway is not that automation beats everything. It's that the right combination of systematic discipline and informed oversight is what actually outperforms. </p><p></p><p>During the podcast, important visual information is sometimes presented alongside the discussion. For the full experience, we recommend watching the episode on platforms where the video version is available.</p><p></p><p>This podcast is intended for educational purposes only and should not be considered financial or investment advice.</p>no00:14:4314Episode 4: Can AI Beat The S&P 500?full<![CDATA[Episode 3: How Assets Behave In Volatile Markets]]>Several weeks ago, Alejandro and Serhii built a portfolio based on a straightforward thesis: during supply shocks, commodity ETFs and broad equity markets tend to move in opposite directions. The portfolio — built around oil, wheat, corn and diversified commodity funds — has since grown by 13.04% while the S&P 500 declined by 1.89% over the same period. 

This episode walks through why that happened. The difference between owning a commodity and owning a commodity company. How oil supply disruptions create negative correlation with equities. Why Exxonand crude oil diverged sharply over the same five-day window. All of it shown on screen, with live data. 

The numbers are real. The portfolio is real. The analysis is grounded in what markets actually did, not what they were supposed to do. 

During the podcast, important visual information is sometimes presented alongside the discussion. For the full experience, we recommend watching the episode on platforms where the video version is available.

This podcast is intended for educational purposes only and should not be considered financial or investment advice.

]]>2ec3f3d8-3171-4b77-b387-8689906af0bfWed, 01 Apr 2026 13:47:35 GMT<p>Several weeks ago, Alejandro and Serhii built a portfolio based on a straightforward thesis: during supply shocks, commodity ETFs and broad equity markets tend to move in opposite directions. The portfolio — built around oil, wheat, corn and diversified commodity funds — has since grown by 13.04% while the S&amp;P 500 declined by 1.89% over the same period. </p><p></p><p>This episode walks through why that happened. The difference between owning a commodity and owning a commodity company. How oil supply disruptions create negative correlation with equities. Why Exxonand crude oil diverged sharply over the same five-day window. All of it shown on screen, with live data. </p><p></p><p>The numbers are real. The portfolio is real. The analysis is grounded in what markets actually did, not what they were supposed to do. </p><p></p><p>During the podcast, important visual information is sometimes presented alongside the discussion. For the full experience, we recommend watching the episode on platforms where the video version is available.</p><p></p><p>This podcast is intended for educational purposes only and should not be considered financial or investment advice.</p>no00:43:1813Episode 3: How Assets Behave In Volatile Marketsfull<![CDATA[Special Episode: How Market Patterns Repeat]]>The same geometric pattern in the S&P 500 that appeared during the 2018–2020 period and repeated through 2025 is showing up again in March 2026. Different macroeconomic triggers each time — tariffs, a pandemic, geopolitical tension — but the same market structure on the chart.

In this episode, Alejandro and Serhii map all three cycles side by side on live SPY data. Based on prior cycles, they identify early April as a potential inflection point where the current drop may begin to stabilise. They're clear that this is pattern recognition, not prediction — and that the math can be misleading.

They also discuss where they are personally positioning capital while waiting for the market to find its floor, including short-duration government bonds currently yielding around 4%.

During the podcast, important visual information is sometimes presented alongside the discussion. For the full experience, we recommend watching the episode on platforms where the video version is available.

This podcast is intended for educational purposes only and should not be considered financial or investment advice.

]]>c0021784-7993-40df-bd75-094ef38195eaWed, 25 Mar 2026 14:43:37 GMT<p>The same geometric pattern in the S&amp;P 500 that appeared during the 2018–2020 period and repeated through 2025 is showing up again in March 2026. Different macroeconomic triggers each time — tariffs, a pandemic, geopolitical tension — but the same market structure on the chart. <br /><br />In this episode, Alejandro and Serhii map all three cycles side by side on live SPY data. Based on prior cycles, they identify early April as a potential inflection point where the current drop may begin to stabilise. They're clear that this is pattern recognition, not prediction — and that the math can be misleading. <br /><br />They also discuss where they are personally positioning capital while waiting for the market to find its floor, including short-duration government bonds currently yielding around 4%.</p><p></p><p>During the podcast, important visual information is sometimes presented alongside the discussion. For the full experience, we recommend watching the episode on platforms where the video version is available.</p><p></p><p>This podcast is intended for educational purposes only and should not be considered financial or investment advice.</p>no00:12:381Special Episode: How Market Patterns Repeatfull<![CDATA[Episode 2: How To Open An International Charles Schwab Brokerage Account]]>Before you can participate in markets, you need the infrastructure to do so. This episode is about exactly that — opening a brokerage account, understanding the account types available, preparing the right documentation, and navigating the platform from a blank account to a live trade order including what happens when your first order gets rejected and how to adjust it.

Alejandro and Serhii walk through the full process on screen. They also get into order types, limit pricing, and what the platform flags when your order can’t be executed — and why — the kind of detail that only becomes clear when you're actually inside the interface.

During the podcast, important visual information is sometimes presented alongside the discussion. For the full experience, we recommend watching the episode on platforms where the video version is available.

This podcast is intended for educational purposes only and should not be considered financial or investment advice.

]]>54103643-d204-4d25-b489-e1131f1b7858Wed, 18 Mar 2026 14:42:06 GMT<p>Before you can participate in markets, you need the infrastructure to do so. This episode is about exactly that — opening a brokerage account, understanding the account types available, preparing the right documentation, and navigating the platform from a blank account to a live trade order including what happens when your first order gets rejected and how to adjust it.<br /><br />Alejandro and Serhii walk through the full process on screen. They also get into order types, limit pricing, and what the platform flags when your order can’t be executed — and why — the kind of detail that only becomes clear when you're actually inside the interface.</p><p></p><p>During the podcast, important visual information is sometimes presented alongside the discussion. For the full experience, we recommend watching the episode on platforms where the video version is available.</p><p></p><p>This podcast is intended for educational purposes only and should not be considered financial or investment advice.</p>no00:15:051Episode 2: How To Open An International Charles Schwab Brokerage Accountfull<![CDATA[Emergency Episode: Protecting Capital During Volatility]]>Geopolitical shocks don’t just move headlines — they move markets, currencies, and access to capital. 

In this special episode of the Foresee Markets Podcast, Alejandro Ramirez Lemus and Serhii Nikolaiev discuss how individuals can think about financial resilience during periods of sudden uncertainty. 

The conversation explores practical considerations such as digitizing money, maintaining liquidity across borders, and how different asset classes can behave during volatility. 

A timely discussion on financial preparedness when stability cannot be taken for granted. 

During the podcast, important visual information is sometimes presented alongside the discussion. For the full experience, we recommend watching the episode on platforms where the video version is available.

This podcast is intended for educational purposes only and should not be considered financial or investment advice.

]]>b8d073ed-a6fc-46f8-8bc3-c410fd48e62eWed, 11 Mar 2026 16:35:30 GMT<p>Geopolitical shocks don’t just move headlines — they move markets, currencies, and access to capital. </p><p>In this special episode of the Foresee Markets Podcast, Alejandro Ramirez Lemus and Serhii Nikolaiev discuss how individuals can think about financial resilience during periods of sudden uncertainty. </p><p>The conversation explores practical considerations such as digitizing money, maintaining liquidity across borders, and how different asset classes can behave during volatility. </p><p>A timely discussion on financial preparedness when stability cannot be taken for granted. </p><p></p><p>During the podcast, important visual information is sometimes presented alongside the discussion. For the full experience, we recommend watching the episode on platforms where the video version is available.</p><p></p><p>This podcast is intended for educational purposes only and should not be considered financial or investment advice.</p>no00:55:1712Emergency Episode: Protecting Capital During Volatilityfull<![CDATA[Pilot: Turn Money Into Assets]]>Leaving money in cash feels responsible. But inflation doesn't wait, and doing nothing is still a decision.

In pilot episode, Alejandro is joined by mathematician and AI researcher Serhii Nikolaiev to break down what it actually takes to move from idle capital to a structured portfolio.

They explore acquisition power, liquidity risks, and how sectors like real estate and ETFs really behave when you treat your money like an employee that works 24/7.

This episode is not about tips or forecasts. Just clear thinking on where to start — and why most people don't.

During the podcast, important visual information is sometimes presented alongside the discussion. For the full experience, we recommend watching the episode on platforms where the video version is available.

This podcast is intended for educational purposes only and should not be considered financial or investment advice.

]]>fa17cdab-97fb-4b97-ba62-2f675afaf152Mon, 09 Mar 2026 14:21:30 GMT<p>Leaving money in cash feels responsible. But inflation doesn't wait, and doing nothing is still a decision.</p><p></p><p>In pilot episode, Alejandro is joined by mathematician and AI researcher Serhii Nikolaiev to break down what it actually takes to move from idle capital to a structured portfolio.</p><p></p><p>They explore acquisition power, liquidity risks, and how sectors like real estate and ETFs really behave when you treat your money like an employee that works 24/7.</p><p></p><p>This episode is not about tips or forecasts. Just clear thinking on where to start — and why most people don't.</p><p></p><p>During the podcast, important visual information is sometimes presented alongside the discussion. For the full experience, we recommend watching the episode on platforms where the video version is available.</p><p></p><p>This podcast is intended for educational purposes only and should not be considered financial or investment advice.</p>no00:44:5411Pilot: Turn Money Into Assetsfull