<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="3.10.0">Jekyll</generator><link href="https://liamleelym.github.io/leeyatming//leeyatming/feed.xml" rel="self" type="application/atom+xml" /><link href="https://liamleelym.github.io/leeyatming//leeyatming/" rel="alternate" type="text/html" /><updated>2026-09-21T09:47:35+00:00</updated><id>https://liamleelym.github.io/leeyatming//leeyatming/feed.xml</id><title type="html">LEE YatMing</title><subtitle>A blog about Liam YatMing LEE</subtitle><entry><title type="html">Examining Berkshire Hathaway’s Cash Holdings: A Signal of Economic Uncertainty?</title><link href="https://liamleelym.github.io/leeyatming//leeyatming/BH/" rel="alternate" type="text/html" title="Examining Berkshire Hathaway’s Cash Holdings: A Signal of Economic Uncertainty?" /><published>2024-09-09T00:00:00+00:00</published><updated>2024-09-09T00:00:00+00:00</updated><id>https://liamleelym.github.io/leeyatming//leeyatming/BH</id><content type="html" xml:base="https://liamleelym.github.io/leeyatming//leeyatming/BH/"><![CDATA[<p>Investors often worry that Warren Buffett’s substantial cash holdings signal a looming recession. Each time Berkshire Hathaway’s cash reserves reach a record high, it makes headlines. But is this really an indicator of a bearish stock market?</p>

<h2 id="berkshire-hathaways-cash-holdings">Berkshire Hathaway’s Cash Holdings</h2>
<p>As the chart shows, Berkshire Hathaway’s cash holdings from 1996 to 2023 reveal a consistent trend of increasing cash reserves. While the total cash amount often attracts attention and makes headlines, evaluating these reserves as a percentage of the company’s total assets provides a deeper understanding of its financial strategy and overall health.<br /></p>

<p><img src="https://github.com/user-attachments/assets/e80be857-81aa-4281-bdca-a561b7cb5b28" alt="2-1" /><br /></p>

<p>Data Source: Berkshire Hathaway’s Filings data</p>

<h2 id="cash-holdings-as-a-percentage-of-market-capital">Cash Holdings as a Percentage of Market Capital</h2>
<p>By comparing Berkshire Hathaway’s market capitalization with its total cash levels, we observe that both metrics have risen over the years.</p>

<p><img src="https://github.com/user-attachments/assets/2e9fc82b-b79e-4b90-82b2-e60acdacd865" alt="2-2" /><br /></p>

<p>Data Source: Berkshire Hathaway’s Filings data</p>

<h2 id="berkshire-hathaways-cash-holdings-level">Berkshire Hathaway’s Cash Holdings Level</h2>
<p>Notably, over the past decade, Berkshire’s cash holdings have remained relatively stable, averaging around 16% of total assets. This suggests that the current cash position aligns closely with the firm’s long-term average.<br /></p>

<p>Even when considering the last five years, Berkshire Hathaway’s cash holdings are at a normalized level, significantly below the peak of nearly 40% observed in 2004. This context is crucial, as it indicates that the current cash reserves are not an anomaly but rather a part of a broader strategic framework. And cash reserve is required for Berkshire Hathaway to use for operational needs, insurance payouts, and potential investment opportunities.<br /></p>

<p>Thus, investors should not adopt a bearish view of the stock market simply because Berkshire Hathaway’s cash holdings have reached a record high.<br /></p>

<p><img src="https://github.com/user-attachments/assets/6741b8df-acab-405f-9d2e-20c606cbf8b3" alt="2-3" /><br /></p>

<p>Data Source: Berkshire Hathaway’s Filings data</p>

<h2 id="conclusion">Conclusion</h2>
<p>In conclusion, while Berkshire Hathaway’s cash holdings may initially appear concerning, they should not be interpreted as a bearish signal for the stock market. The current cash position is in line with historical averages and serves strategic purposes essential for the company’s operations and growth. Therefore, investors should avoid a pessimistic outlook on the stock market based solely on Berkshire Hathaway’s cash reserves. A comprehensive analysis of cash holdings in relation to total assets provides a more accurate perspective.<br /></p>]]></content><author><name>Liam</name></author><category term="blog" /><category term="Berkshire Hathaway" /><category term="Warren Buffett" /><category term="Recession" /><category term="Systematic Risk" /><summary type="html"><![CDATA[Stock Market Decisions]]></summary></entry><entry><title type="html">Can Investors Rely on the Effective Federal Funds Rate for Stock Market Decisions?</title><link href="https://liamleelym.github.io/leeyatming//leeyatming/EFFR/" rel="alternate" type="text/html" title="Can Investors Rely on the Effective Federal Funds Rate for Stock Market Decisions?" /><published>2024-09-02T00:00:00+00:00</published><updated>2024-09-02T00:00:00+00:00</updated><id>https://liamleelym.github.io/leeyatming//leeyatming/EFFR</id><content type="html" xml:base="https://liamleelym.github.io/leeyatming//leeyatming/EFFR/"><![CDATA[<p>Investors often believe that changes in interest rates, specifically cuts, can lead to lower financing costs, increased lending, and ultimately a boost to the economy, and it leads to the stock price going up. This report examines the relationship between Federal Reserve (Fed) interest rate changes and the performance of the S&amp;P 500 Index, highlighting the periods of rate cuts and hikes.
The following are the historical periods when the Fed implemented interest rate cuts and hikes, using the FOMC Meeting date for the start and end points (from 1990 to 2024)</p>

<p>Rate Cut Periods: <br />
August 1, 2019 to March 16, 2020<br />
September 18, 2007 to December 16, 2008<br />
January 31, 2001 to June 25, 2003<br />
July 6, 1995 to November 17, 1998<br />
July 13, 1990 to September 13, 1991<br /></p>

<p>Rate Hike Periods: <br />
March 17, 2022 to July 26, 2023<br />
December 17, 2015 to December 20, 2018<br />
June 30, 2004 to June 29, 2006<br />
June 30, 1999 to May 16, 2000<br />
February 4, 1994 to February 1, 1995<br /></p>

<p><img src="https://github.com/user-attachments/assets/193d784e-4196-49b4-b41e-8f256cb8d6ce" alt="1-1" /></p>

<p><img src="https://github.com/user-attachments/assets/058ddbe7-8a05-4e04-b952-75a1e7662b67" alt="1-2" /></p>

<p>Data Source: Board of Governors of the Federal Reserve System, Yahoo Finance</p>

<h2 id="observations">Observations</h2>
<p>While investors anticipate that rate cuts will stimulate economic activity and enhance stock prices, historical data suggests that these periods do not consistently correlate with notable increases in the S&amp;P 500. Similarly, expectations surrounding rate hikes often lead to concerns about potential declines in stock prices. However, the performance of the S&amp;P 500 during these periods has shown resilience, with no clear trend indicating a downturn solely due to rate increases.</p>
<h2 id="granger-causality-test-results">Granger-Causality Test Results</h2>
<p>To further investigate the relationship between the effective federal funds rate and the S&amp;P 500, a Granger-causality test was conducted. The results are as follows:</p>

<div class="language-python highlighter-rouge"><div class="highlight"><pre class="highlight"><code><span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="n">pd</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="n">np</span>
<span class="kn">import</span> <span class="nn">statsmodels.api</span> <span class="k">as</span> <span class="n">sm</span>
<span class="kn">from</span> <span class="nn">statsmodels.tsa.stattools</span> <span class="kn">import</span> <span class="n">adfuller</span>
<span class="kn">from</span> <span class="nn">statsmodels.tsa.api</span> <span class="kn">import</span> <span class="n">VAR</span>

<span class="k">def</span> <span class="nf">check_stationarity</span><span class="p">(</span><span class="n">series</span><span class="p">):</span>
    <span class="n">result</span> <span class="o">=</span> <span class="n">adfuller</span><span class="p">(</span><span class="n">series</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">result</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>  

<span class="n">p_values</span> <span class="o">=</span> <span class="p">{</span><span class="n">col</span><span class="p">:</span> <span class="n">check_stationarity</span><span class="p">(</span><span class="n">data2</span><span class="p">[</span><span class="n">col</span><span class="p">])</span> <span class="k">for</span> <span class="n">col</span> <span class="ow">in</span> <span class="n">data2</span><span class="p">.</span><span class="n">columns</span><span class="p">}</span>
<span class="k">print</span><span class="p">(</span><span class="n">p_values</span><span class="p">)</span>

<span class="k">for</span> <span class="n">col</span> <span class="ow">in</span> <span class="n">data2</span><span class="p">.</span><span class="n">columns</span><span class="p">:</span>
    <span class="k">if</span> <span class="n">p_values</span><span class="p">[</span><span class="n">col</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mf">0.05</span><span class="p">:</span>
        <span class="n">data2</span><span class="p">[</span><span class="n">col</span><span class="p">]</span> <span class="o">=</span> <span class="n">data2</span><span class="p">[</span><span class="n">col</span><span class="p">].</span><span class="n">diff</span><span class="p">().</span><span class="n">dropna</span><span class="p">()</span>

<span class="n">model</span> <span class="o">=</span> <span class="n">VAR</span><span class="p">(</span><span class="n">data2</span><span class="p">)</span>
<span class="n">results</span> <span class="o">=</span> <span class="n">model</span><span class="p">.</span><span class="n">fit</span><span class="p">(</span><span class="n">maxlags</span><span class="o">=</span><span class="mi">15</span><span class="p">,</span> <span class="n">ic</span><span class="o">=</span><span class="s">'aic'</span><span class="p">)</span>

<span class="n">causality_results</span> <span class="o">=</span> <span class="n">results</span><span class="p">.</span><span class="n">test_causality</span><span class="p">(</span><span class="s">'S&amp;P500'</span><span class="p">,</span> <span class="s">'effective_federal_funds_rate'</span><span class="p">)</span>
<span class="k">print</span><span class="p">(</span><span class="n">causality_results</span><span class="p">.</span><span class="n">summary</span><span class="p">())</span>
</code></pre></div></div>
<p><img src="https://github.com/user-attachments/assets/5132bf38-00d8-46c8-b521-80fcac7dc1c5" alt="Screenshot 2024-09-03 154056" /></p>

<h2 id="analysis-of-granger-causality-test">Analysis of Granger-Causality Test</h2>
<p>Since the p-value is much higher than the 0.05 significance level, we fail to reject the null hypothesis. This indicates that the effective federal funds rate does not have a predictive influence on the S&amp;P 500. In other words, changes in the effective federal funds rate do not forecast movements in the S&amp;P 500 index.</p>
<h2 id="conclusion">Conclusion</h2>
<p>In conclusion, the data indicates that Fed policy turning points do not significantly influence the movement of the S&amp;P 500 Index. A review of the S&amp;P 500 Index during these periods reveals that the expectation that rate cuts or hikes are reliable predictors of future stock performance may be overstated.<br /></p>

<p>Investors should look beyond interest rate movements when assessing market conditions, as a broader range of economic factors can provide crucial insights. Key indicators such as GDP growth, inflation trends, and consumer confidence reflect the overall health of the economy. Additionally, global events, sector performance, and central bank policies beyond just rate changes can significantly impact markets. All of these elements contribute to understanding potential scenarios, including “soft landing” and “hard landing” for the U.S. economy. Therefore, investors should base their investment decisions on a comprehensive evaluation of these factors to ensure compliance and informed strategy.</p>]]></content><author><name>Liam</name></author><category term="blog" /><category term="soft landing" /><category term="EFFR" /><category term="S&amp;P500" /><category term="rates cut" /><summary type="html"><![CDATA[Stock Market Decisions]]></summary></entry></feed>