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	<title>Quantifiable Edges</title>
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	<link>https://quantifiableedges.com</link>
	<description>Assessing Market Action With Indicators &#38; History</description>
	<lastBuildDate>Mon, 26 Oct 2026 02:49:52 +0000</lastBuildDate>
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	<title>Quantifiable Edges</title>
	<link>https://quantifiableedges.com</link>
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		<title>SPX is About to Enter an Incredibly Bullish Seasonal Period</title>
		<link>https://quantifiableedges.com/spx-is-about-to-enter-an-incredibly-bullish-seasonal-period/</link>
					<comments>https://quantifiableedges.com/spx-is-about-to-enter-an-incredibly-bullish-seasonal-period/#respond</comments>
		
		<dc:creator><![CDATA[Rob Hanna]]></dc:creator>
		<pubDate>Mon, 26 Oct 2026 03:00:00 +0000</pubDate>
				<category><![CDATA[Quantitative Study]]></category>
		<category><![CDATA[seasonality]]></category>
		<category><![CDATA[#seasonality]]></category>
		<category><![CDATA[$SPX]]></category>
		<category><![CDATA[$SPY]]></category>
		<guid isPermaLink="false">https://quantifiableedges.com/?p=4846</guid>

					<description><![CDATA[With the calendar about to change from October to November, the market will enter its “Best 6 Months”. The “Best 6 Months” tendency was first published by Yale Hirsch, founder of the Stock Trader’s Almanac, in 1986. The concept behind the “Best 6 Months” is simple. Hirsch’s research suggests that over the last several decades &#8230;]]></description>
										<content:encoded><![CDATA[
<p>With the calendar about to change from October to November, the market will enter its “Best 6 Months”. The “Best 6 Months” tendency was first published by Yale Hirsch, founder of the Stock Trader’s Almanac, in 1986. The concept behind the “Best 6 Months” is simple. Hirsch’s research suggests that over the last several decades the market has made a massive portion of its gains between November and April. And during the remaining 6 months, it has generally struggled to make headway. I’ll also note that since publishing the tendency many years ago, the edge has persisted, with the “Best 6 Months” continuing to outperform the “Worst 6 Months”.</p>



<p>Another bit of good news is that the market is shifting into the 3rd year of the Presidential cycle. At Quantifiable Edges I measure the Presidential Cycle years from November – October rather than January – December. That allows the cycle years to better match up with the elections, which take place in early November. And while the elections are always during the 1st week of November, I always start the cycle year on November 1st. This makes for easy evaluation when combining it with the “Best 6 Months” cycles. In general, the 3rd year of the Presidential Cycle has been a strong one.</p>



<p>When the Best 6 Months and the 3rd Year of the Presidential Cycle have been active at the same time, the results since 1950 have been outstanding.  In the table below I have listed out each instance.</p>



<p></p>



<figure class="wp-block-image size-large"><img fetchpriority="high" decoding="async" width="1024" height="710" src="https://quantifiableedges.com/wp-content/uploads/2026/10/image1-1024x710.png" alt="Table of SPX returns from November to April during year 3 of the Presidential Cycle, 1950 to present" class="wp-image-4845" srcset="https://quantifiableedges.com/wp-content/uploads/2026/10/image1-1024x710.png 1024w, https://quantifiableedges.com/wp-content/uploads/2026/10/image1-300x208.png 300w, https://quantifiableedges.com/wp-content/uploads/2026/10/image1-768x532.png 768w, https://quantifiableedges.com/wp-content/uploads/2026/10/image1.png 1515w" sizes="(max-width: 1024px) 100vw, 1024px" /></figure>



<p></p>



<p>All 19 instances since 1950 have shown gains. Of course there have been drawdowns along the way. The 1974-75 period saw SPX pull back 13.2% from its October closing price before rebounding and finishing April 18.1% above the October closing price. And in 2018-2019 there was a 13.5% drawdown from the October close before finishing April 8.6% above it. But overall the stats have been incredibly lopsided.  The average full 6-month period saw a net gain of 14.79% and a median gain of 15.24%. Long-term seasonality does not get any better.</p>



<p>Much more information on these indicators and others can be found in the <a href="https://quantifiableedges.com/subscribers/signup/mtc2023">Quantifiable Edges Market Dynamics course</a>. While that course can be purchased on its own, it is also available free with any annual <a href="https://quantifiableedges.com/subscribers/signup/index/c/goldsub">gold subscription</a> to Quantifiable Edges.</p>



<p></p>



<p></p>



<p><strong><em>Want research like this delivered directly to your inbox on a timely basis?</em></strong>&nbsp;<a href="https://eepurl.com/K3A2r" target="_blank" rel="noreferrer noopener">Sign up for the Quantifiable Edges Email List.</a></p>



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					<wfw:commentRss>https://quantifiableedges.com/spx-is-about-to-enter-an-incredibly-bullish-seasonal-period/feed/</wfw:commentRss>
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		<title>One Backtest Might Just Be Lucky</title>
		<link>https://quantifiableedges.com/one-backtest-might-just-be-lucky/</link>
		
		<dc:creator><![CDATA[Rob Hanna]]></dc:creator>
		<pubDate>Thu, 13 Aug 2026 11:00:00 +0000</pubDate>
				<category><![CDATA[Correlation]]></category>
		<category><![CDATA[Quantitative Study]]></category>
		<guid isPermaLink="false">https://quantifiableedges.com/?p=4833</guid>

					<description><![CDATA[“One Backtest Might Just Be Lucky”, which is the 3rd in my series of short videos with the new Quantifiable Edges Correlation Tool, has been posted to the Quantifiable Edges YouTube channel. The Correlation Tool can be accessed under Extras -&#62; Correlation Tool for anyone that is logged in to the site. Free access simply &#8230;]]></description>
										<content:encoded><![CDATA[
<p>“One Backtest Might Just Be Lucky”, which is the 3rd in my series of short videos with the new Quantifiable Edges Correlation Tool, has been posted to the Quantifiable Edges YouTube channel.</p>



<p></p>



<figure class="wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio"><div class="wp-block-embed__wrapper">
<iframe title="One Backtest Might Just Be Lucky" width="940" height="529" src="https://www.youtube.com/embed/vuPaos-ME9k?feature=oembed&#038;enablejsapi=1" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
</div></figure>



<p></p>



<p>The Correlation Tool can be accessed under Extras -&gt; Correlation Tool for anyone that is logged in to the site. Free access simply requires a login (name &amp; email). <a href="https://quantifiableedges.com/subscribers/signup/correlation">Signup here</a>.</p>



<p></p>



<p></p>



<p><strong><em>Want research like this delivered directly to your inbox on a timely basis?</em></strong>&nbsp;<a href="https://eepurl.com/K3A2r" target="_blank" rel="noreferrer noopener">Sign up for the Quantifiable Edges Email List.</a></p>



<p><strong><em>How about a</em></strong>&nbsp;<a href="https://quantifiableedges.com/subscribers/signup/index/c/freetrial">free trial to the Quantifiable Edges Gold subscription</a>?</p>
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		<title>How August and September Have Fared After June &#038; July Both Close Lower</title>
		<link>https://quantifiableedges.com/how-august-and-september-have-fared-after-june-july-both-close-lower/</link>
		
		<dc:creator><![CDATA[Rob Hanna]]></dc:creator>
		<pubDate>Mon, 03 Aug 2026 14:15:00 +0000</pubDate>
				<category><![CDATA[Quantitative Study]]></category>
		<category><![CDATA[seasonality]]></category>
		<category><![CDATA[#seasonality]]></category>
		<category><![CDATA[$SPX]]></category>
		<guid isPermaLink="false">https://quantifiableedges.com/?p=4829</guid>

					<description><![CDATA[Both June and July saw SPX close lower. Seasonality for those two months it is generally favorable. But since 1950, two of the weakest months are August (3rd worst) and September (worst). So in this weekend’s letter I decided to see how August and September fared when we already had June and July slipping. The &#8230;]]></description>
										<content:encoded><![CDATA[
<p>Both June and July saw SPX close lower. Seasonality for those two months it is generally favorable. But since 1950, two of the weakest months are August (3rd worst) and September (worst). So in this weekend’s letter I decided to see how August and September fared when we already had June and July slipping. The table below gives us an answer.</p>



<p></p>



<figure class="wp-block-image size-large"><img decoding="async" width="1024" height="725" src="https://quantifiableedges.com/wp-content/uploads/2026/08/image1-1024x725.png" alt="" class="wp-image-4828" srcset="https://quantifiableedges.com/wp-content/uploads/2026/08/image1-1024x725.png 1024w, https://quantifiableedges.com/wp-content/uploads/2026/08/image1-300x212.png 300w, https://quantifiableedges.com/wp-content/uploads/2026/08/image1-768x544.png 768w, https://quantifiableedges.com/wp-content/uploads/2026/08/image1-1536x1087.png 1536w, https://quantifiableedges.com/wp-content/uploads/2026/08/image1.png 1575w" sizes="(max-width: 1024px) 100vw, 1024px" /></figure>



<p></p>



<p>After down closes in both June and July. August has generally been a toss-up. Sometimes it got a bit of a rebound and sometimes it didn&#8217;t. But regardless of whether August rebounded or not, September numbers look pretty terrible. Eleven out of the thirteen Septembers closed lower and many of them by sizable amounts. This seems worth keeping in mind while we consider other intermediate-term evidence that emerges over the next 3-4 weeks.</p>



<p></p>



<p></p>



<p><strong><em>Want research like this delivered directly to your inbox on a timely basis?</em></strong>&nbsp;<a href="https://eepurl.com/K3A2r" target="_blank" rel="noreferrer noopener">Sign up for the Quantifiable Edges Email List.</a></p>



<p><strong><em>How about a</em></strong>&nbsp;<a href="https://quantifiableedges.com/subscribers/signup/index/c/freetrial">free trial to the Quantifiable Edges Gold subscription</a>?</p>
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		<title>How Changing Correlation Impacts the Range of Probable Outcomes</title>
		<link>https://quantifiableedges.com/how-changing-correlation-impacts-the-range-of-probable-outcomes/</link>
		
		<dc:creator><![CDATA[Rob Hanna]]></dc:creator>
		<pubDate>Mon, 27 Jul 2026 04:30:00 +0000</pubDate>
				<category><![CDATA[Quantitative Study]]></category>
		<category><![CDATA[Correlation]]></category>
		<guid isPermaLink="false">https://quantifiableedges.com/?p=4824</guid>

					<description><![CDATA[“How Changing Correlation Impacts the Range of Probable Outcomes”, which is the 2nd in my series of short videos with the new Quantifiable Edges Correlation Tool, has been posted to the Quantifiable Edges YouTube channel. The Correlation Tool can be accessed under Extras -&#62; Correlation Tool for anyone that is logged in to the site. &#8230;]]></description>
										<content:encoded><![CDATA[
<p>“How Changing Correlation Impacts the Range of Probable Outcomes”, which is the 2nd in my series of short videos with the new Quantifiable Edges Correlation Tool, has been posted to the Quantifiable Edges YouTube channel.</p>



<p></p>



<figure class="wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio"><div class="wp-block-embed__wrapper">
<iframe loading="lazy" title="How Changing Correlation Impacts the Range of Probable Outcomes" width="940" height="529" src="https://www.youtube.com/embed/z7ZXzbZkIfk?feature=oembed&#038;enablejsapi=1" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
</div></figure>



<p></p>



<p>The Correlation Tool can be accessed under Extras -&gt; Correlation Tool for anyone that is logged in to the site. Free access simply requires a login (name &amp; email). <a href="https://quantifiableedges.com/subscribers/signup/correlation">Signup here</a>.</p>



<p></p>



<p></p>



<p><strong><em>Want research like this delivered directly to your inbox on a timely basis?</em></strong>&nbsp;<a href="https://eepurl.com/K3A2r" target="_blank" rel="noreferrer noopener">Sign up for the Quantifiable Edges Email List.</a></p>



<p><strong><em>How about a</em></strong>&nbsp;<a href="https://quantifiableedges.com/subscribers/signup/index/c/freetrial">free trial to the Quantifiable Edges Gold subscription</a>?</p>
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		<title>Three Benefits of (Non)Correlation</title>
		<link>https://quantifiableedges.com/three-benefits-of-noncorrelation/</link>
		
		<dc:creator><![CDATA[Rob Hanna]]></dc:creator>
		<pubDate>Wed, 22 Jul 2026 11:00:00 +0000</pubDate>
				<category><![CDATA[Correlation]]></category>
		<category><![CDATA[Quantitative Study]]></category>
		<guid isPermaLink="false">https://quantifiableedges.com/?p=4821</guid>

					<description><![CDATA[“Three Benefits of (Non)Correlation”, which is the 1st in my series of short videos with the new Quantifiable Edges Correlation Tool, has been posted to the Quantifiable Edges YouTube channel. The Correlation Tool can be accessed under Extras -&#62; Correlation Tool for anyone that is logged in to the site. Free access simply requires a &#8230;]]></description>
										<content:encoded><![CDATA[
<p>“Three Benefits of (Non)Correlation”, which is the 1st in my series of short videos with the new Quantifiable Edges Correlation Tool, has been posted to the Quantifiable Edges YouTube channel.</p>



<p></p>



<figure class="wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio"><div class="wp-block-embed__wrapper">
<iframe loading="lazy" title="Three Benefits of (Non)Correlation" width="940" height="529" src="https://www.youtube.com/embed/otbtJ8AD0ws?feature=oembed&#038;enablejsapi=1" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
</div></figure>



<p></p>



<p>The Correlation Tool can be accessed under Extras -&gt; Correlation Tool for anyone that is logged in to the site. Free access simply requires a login (name &amp; email). <a href="https://quantifiableedges.com/subscribers/signup/correlation">Signup here</a>.</p>



<p>Or how about a <a href="https://quantifiableedges.com/subscribers/signup/index/c/freetrial">free trial</a> to the Quantifiable Edges Gold subscription?</p>
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		<title>Introducing the Quantifiable Edges Hypothetical Correlation Tool</title>
		<link>https://quantifiableedges.com/introducing-the-quantifiable-edges-hypothetical-correlation-tool/</link>
		
		<dc:creator><![CDATA[Rob Hanna]]></dc:creator>
		<pubDate>Tue, 21 Jul 2026 20:30:00 +0000</pubDate>
				<category><![CDATA[Quantitative Study]]></category>
		<category><![CDATA[Correlation]]></category>
		<guid isPermaLink="false">https://quantifiableedges.com/?p=4816</guid>

					<description><![CDATA[I am excited to introduce the Quantifiable Edges Hypothetical Correlation Tool. I find a lot of people understand diversification, but few grasp how important correlation is when choosing diversifiers. Combining strategies that don&#8217;t move in lockstep is a huge key for improving the risk and return of the whole. It&#8217;s easy to say &#8220;diversification works.&#8221; &#8230;]]></description>
										<content:encoded><![CDATA[
<p>I am excited to introduce the Quantifiable Edges Hypothetical Correlation Tool. I find a lot of people understand diversification, but few grasp how important correlation is when choosing diversifiers. Combining strategies that don&#8217;t move in lockstep is a huge key for improving the risk and return of the whole. It&#8217;s easy to say &#8220;diversification works.&#8221; It&#8217;s much harder to grasp why, or to see how much. Hopefully our new Hypothetical Correlation Tool will help make that clearer.</p>



<p>The Hypothetical Correlation Tool lets you define a handful of &#8220;models&#8221; (each just an expected return and a volatility), choose how correlated they are, decide how much of each to hold, and then watch a Monte Carlo simulation play out thousands of hypothetical futures. It reports the blended portfolio&#8217;s compound return, volatility, Sharpe ratio, and worst drawdown, draws the growth of $10,000, and even shows you which models to overweight or underweight to maximize risk-adjusted return. Here is a quick look:</p>



<p></p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="835" height="1024" src="https://quantifiableedges.com/wp-content/uploads/2026/07/image1-835x1024.png" alt="" class="wp-image-4815" srcset="https://quantifiableedges.com/wp-content/uploads/2026/07/image1-835x1024.png 835w, https://quantifiableedges.com/wp-content/uploads/2026/07/image1-245x300.png 245w, https://quantifiableedges.com/wp-content/uploads/2026/07/image1-768x942.png 768w, https://quantifiableedges.com/wp-content/uploads/2026/07/image1.png 1141w" sizes="auto, (max-width: 835px) 100vw, 835px" /></figure>



<p></p>



<p>A few things you can explore in about two minutes:</p>



<ul class="wp-block-list">

<li>Drag a correlation slider from +1 toward −1 and watch a blend&#8217;s volatility melt away while its return holds up.</li>


<li>Flip on &#8220;crisis correlation&#8221; to see why diversification tends to fail exactly when you need it most.</li>


<li>Hit &#8220;new draw&#8221; a few times to feel how much any single backtest is just luck.</li>


<li>Check out the “User Guide” (button top right) for more detailed instruction on how to use the tool.</li>

</ul>



<p>Note: These are not real returns and not a forecast of any strategy. Every number it produces is a hypothetical simulation generated by a mathematical model, for educational purposes only.  It&#8217;s built only to illustrate the mechanics of diversification and correlation.</p>



<p>I’ll be doing series of posts and short demos where I will use the tool to walk through specific ideas. These include the rebalancing bonus, the limits of diversification in a crash, and the math of leverage. I hope you like the tool. Stay tuned for the first few mini-demos!</p>



<p>To access the tool you simply need to login to Quantifiable Edges. (Even an old expired trial will work.) Once logged in, simply look for the Correlation Tool under the “Extras” menu item. If you don’t have a Quantifiable Edges login, you can <a href="https://quantifiableedges.com/subscribers/signup/correlation">sign up for the Correlation Tool (free) here</a>.</p>



<p></p>



<p></p>



<p><strong><em>Want research like this delivered directly to your inbox on a timely basis?</em></strong>&nbsp;<a href="https://eepurl.com/K3A2r" target="_blank" rel="noreferrer noopener">Sign up for the Quantifiable Edges Email List.</a></p>



<p><strong><em>How about a</em></strong>&nbsp;<a href="https://quantifiableedges.com/subscribers/signup/index/c/freetrial">free trial to the Quantifiable Edges Gold subscription</a>?</p>
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		<title>Using Claude Code to Backtest with RealTest</title>
		<link>https://quantifiableedges.com/using-claude-code-to-backtest-with-realtest/</link>
		
		<dc:creator><![CDATA[Rob Hanna]]></dc:creator>
		<pubDate>Tue, 23 Jun 2026 18:05:00 +0000</pubDate>
				<category><![CDATA[Quantitative Study]]></category>
		<category><![CDATA[Videos]]></category>
		<category><![CDATA[#AI]]></category>
		<category><![CDATA[$SPX]]></category>
		<category><![CDATA[$SPY]]></category>
		<guid isPermaLink="false">https://quantifiableedges.com/?p=4790</guid>

					<description><![CDATA[Here is a new video I just posted to the Quantifiable Edges YouTube channel showing how I use Claude Code to build models and optimizations in RealTest. Want research like this delivered directly to your inbox on a timely basis?&#160;Sign up for the Quantifiable Edges Email List. How about a&#160;free trial to the Quantifiable Edges &#8230;]]></description>
										<content:encoded><![CDATA[
<p>Here is a new video I just posted to the Quantifiable Edges YouTube channel showing how I use Claude Code to build models and optimizations in RealTest.</p>



<p></p>



<figure class="wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube wp-embed-aspect-16-9 wp-has-aspect-ratio"><div class="wp-block-embed__wrapper">
<iframe loading="lazy" title="Claude Code for Realtest Testing" width="940" height="705" src="https://www.youtube.com/embed/n444wX0QC6s?feature=oembed&#038;enablejsapi=1" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
</div></figure>



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<p><strong><em>Want research like this delivered directly to your inbox on a timely basis?</em></strong>&nbsp;<a href="https://eepurl.com/K3A2r" target="_blank" rel="noreferrer noopener">Sign up for the Quantifiable Edges Email List.</a></p>



<p><strong><em>How about a</em></strong>&nbsp;<a href="https://quantifiableedges.com/subscribers/signup/index/c/freetrial">free trial to the Quantifiable Edges Gold subscription</a>?</p>
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		<title>A TICK TomOscillator Study Suggesting a Monday Bounce</title>
		<link>https://quantifiableedges.com/a-tick-tomoscillator-study-suggesting-a-monday-bounce/</link>
		
		<dc:creator><![CDATA[Rob Hanna]]></dc:creator>
		<pubDate>Sun, 07 Jun 2026 23:30:00 +0000</pubDate>
				<category><![CDATA[Quantitative Study]]></category>
		<category><![CDATA[$SPX]]></category>
		<category><![CDATA[$SPY]]></category>
		<category><![CDATA[$TICK]]></category>
		<guid isPermaLink="false">https://quantifiableedges.com/?p=4779</guid>

					<description><![CDATA[Using closing TICK values as a sentiment indicator is something I learned a long time ago my friend and fellow market analyst, Tom McClellan of McClellan Financial Publications (click for Tom’s article on closing TICK). Tom uses the NYSE closing TICK readings to measure recent end-of-day sentiment. I introduced the TICK Tomoscillator several years ago. &#8230;]]></description>
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<p>Using closing TICK values as a sentiment indicator is something I learned a long time ago my friend and fellow market analyst, Tom McClellan of McClellan Financial Publications (click for Tom’s article on closing TICK). Tom uses the NYSE closing TICK readings to measure recent end-of-day sentiment. I introduced the TICK Tomoscillator several years ago. For those that are not familiar with the TICK Tomoscillator, you may find a detailed description in the May 13, 2011 blog. The Tomoscillator % Rank Friday came in below 1%, meaning Friday’s reading is among the lowest 1% in the last year. The study below uses the Tomoscillator % Rank reading rather than just the raw reading. </p>



<p></p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="663" src="https://quantifiableedges.com/wp-content/uploads/2026/06/image1-1024x663.png" alt="" class="wp-image-4778" srcset="https://quantifiableedges.com/wp-content/uploads/2026/06/image1-1024x663.png 1024w, https://quantifiableedges.com/wp-content/uploads/2026/06/image1-300x194.png 300w, https://quantifiableedges.com/wp-content/uploads/2026/06/image1-768x497.png 768w, https://quantifiableedges.com/wp-content/uploads/2026/06/image1.png 1439w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p></p>



<p>With 23 of 25 instances closing up the next day, there has been a strong bullish inclination. And the line going from lower left to upper right is extremely straight. This is the first time this study has triggered since 2024, but I&#8217;ve liked it for a long time and it&#8217;s always on my radar.</p>



<p></p>



<p></p>



<p><strong><em>Want research like this delivered directly to your inbox on a timely basis?</em></strong> <a href="https://eepurl.com/K3A2r" target="_blank" rel="noreferrer noopener">Sign up for the Quantifiable Edges Email List.</a>  <strong><em>Also note you can now read the Quantifiable Edges blog and other &#8220;stuff&#8221; from Rob <a href="https://realrobhanna.substack.com/" target="_blank" rel="noopener">on his new Substack</a>.</em></strong></p>



<p><strong><em>How about a</em></strong>&nbsp;<a href="https://quantifiableedges.com/subscribers/signup/index/c/freetrial">free trial to the Quantifiable Edges Gold subscription</a>?</p>



<p></p>
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		<title>Memorial Week History And The One Day That&#8217;s Been Consistent</title>
		<link>https://quantifiableedges.com/memorial-week-history-and-the-one-day-thats-been-consistent/</link>
		
		<dc:creator><![CDATA[Rob Hanna]]></dc:creator>
		<pubDate>Mon, 25 May 2026 11:00:00 +0000</pubDate>
				<category><![CDATA[Quantitative Study]]></category>
		<category><![CDATA[seasonality]]></category>
		<category><![CDATA[$SPX]]></category>
		<category><![CDATA[$SPY]]></category>
		<guid isPermaLink="false">https://quantifiableedges.com/?p=4762</guid>

					<description><![CDATA[The week of Memorial Day has shown some interesting tendencies over the years. It has been less consistent recently. The chart below examines SPX performance from the Friday before Memorial Day to the Friday after it. There was no substantial edge apparent throughout the 70s, but starting in 1983 through 2009 there was a substantial &#8230;]]></description>
										<content:encoded><![CDATA[
<p>The week of Memorial Day has shown some interesting tendencies over the years. It has been less consistent recently. The chart below examines SPX performance from the Friday before Memorial Day to the Friday after it.</p>



<p></p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="665" src="https://quantifiableedges.com/wp-content/uploads/2026/05/image1-3-1024x665.png" alt="" class="wp-image-4760" srcset="https://quantifiableedges.com/wp-content/uploads/2026/05/image1-3-1024x665.png 1024w, https://quantifiableedges.com/wp-content/uploads/2026/05/image1-3-300x195.png 300w, https://quantifiableedges.com/wp-content/uploads/2026/05/image1-3-768x498.png 768w, https://quantifiableedges.com/wp-content/uploads/2026/05/image1-3.png 1439w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p></p>



<p>There was no substantial edge apparent throughout the 70s, but starting in 1983 through 2009 there was a substantial bullish tendency. The last 16 years this week has seen more of a struggle. But there remains one day during Memorial Day week where the upside tendency seems to have persisted. That day is Thursday.</p>



<p></p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="665" src="https://quantifiableedges.com/wp-content/uploads/2026/05/image2-3-1024x665.png" alt="" class="wp-image-4761" srcset="https://quantifiableedges.com/wp-content/uploads/2026/05/image2-3-1024x665.png 1024w, https://quantifiableedges.com/wp-content/uploads/2026/05/image2-3-300x195.png 300w, https://quantifiableedges.com/wp-content/uploads/2026/05/image2-3-768x498.png 768w, https://quantifiableedges.com/wp-content/uploads/2026/05/image2-3.png 1439w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p></p>



<p>A 70% win rate and a strong, steady move higher suggest Thursday looks like a pretty good day from a seasonal standpoint. Traders may want to keep this in mind for later this week.</p>



<p></p>



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		<item>
		<title>A Historical Look at the Top 20 6-week $SPX Rallies Since 1950</title>
		<link>https://quantifiableedges.com/a-historical-look-at-the-top-20-6-week-spx-rallies-since-1950/</link>
		
		<dc:creator><![CDATA[Rob Hanna]]></dc:creator>
		<pubDate>Fri, 15 May 2026 17:11:22 +0000</pubDate>
				<category><![CDATA[Quantitative Study]]></category>
		<category><![CDATA[$SPX]]></category>
		<category><![CDATA[$SPY]]></category>
		<guid isPermaLink="false">https://quantifiableedges.com/?p=4688</guid>

					<description><![CDATA[A few days ago on X, Charlie Bilello pointed out SPX had gained more than 16% over the previous six weeks and that&#8217;s one of the biggest six-week rallies of all time. I looked back at the top 20 non-overlapping 30-trading-day rallies since 1950. They can all be found in the table below. Shaded rows &#8230;]]></description>
										<content:encoded><![CDATA[
<p>A few days ago on X, Charlie Bilello pointed out SPX had gained more than 16% over the previous six weeks and that&#8217;s one of the biggest six-week rallies of all time.  I looked back at the top 20 non-overlapping 30-trading-day rallies since 1950. They can all be found in the table below.</p>



<p></p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="896" src="https://quantifiableedges.com/wp-content/uploads/2026/05/image1-2-1024x896.png" alt="" class="wp-image-4685" srcset="https://quantifiableedges.com/wp-content/uploads/2026/05/image1-2-1024x896.png 1024w, https://quantifiableedges.com/wp-content/uploads/2026/05/image1-2-300x263.png 300w, https://quantifiableedges.com/wp-content/uploads/2026/05/image1-2-768x672.png 768w, https://quantifiableedges.com/wp-content/uploads/2026/05/image1-2-1536x1344.png 1536w, https://quantifiableedges.com/wp-content/uploads/2026/05/image1-2.png 1852w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p></p>



<p>Shaded rows are those instances where there was less than a 20% drawdown at the start of the rally. The current instance saw one of the shallower drawdowns. Only 1955, 1976, and 1982 saw rallies that were not coming out of larger drawdowns than the current one. After such strong rallies whether they were bear or non-bear, the next month generally did not see much progress. But longer-term results were quite impressive. After the 19 prior 6-week rallies, SPX averaged +18.8% over the next year with a 94.4% win rate, versus a +9.4% / 74.5% baseline. Below you can see the signal versus the baseline numbers.</p>



<p>Signal vs baseline forward returns (top 20 rallies)</p>



<p></p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="1024" height="175" src="https://quantifiableedges.com/wp-content/uploads/2026/05/image2-2-1024x175.png" alt="" class="wp-image-4686" srcset="https://quantifiableedges.com/wp-content/uploads/2026/05/image2-2-1024x175.png 1024w, https://quantifiableedges.com/wp-content/uploads/2026/05/image2-2-300x51.png 300w, https://quantifiableedges.com/wp-content/uploads/2026/05/image2-2-768x131.png 768w, https://quantifiableedges.com/wp-content/uploads/2026/05/image2-2.png 1087w" sizes="auto, (max-width: 1024px) 100vw, 1024px" /></figure>



<p></p>



<p>Lastly a little graphic showing the one-year forward returns after each of the 6-week rallies:</p>



<p></p>



<figure class="wp-block-image size-large"><img loading="lazy" decoding="async" width="703" height="357" src="https://quantifiableedges.com/wp-content/uploads/2026/05/image3.png" alt="" class="wp-image-4687" srcset="https://quantifiableedges.com/wp-content/uploads/2026/05/image3.png 703w, https://quantifiableedges.com/wp-content/uploads/2026/05/image3-300x152.png 300w" sizes="auto, (max-width: 703px) 100vw, 703px" /></figure>



<p></p>



<p>So the momentum over the recent six-week period seems to be positive. We&#8217;ve seen this other ways but I thought this was an interesting look. Also impressive is that looking at the eight non-bear instances the average drawdown was only 8.29%, while the average run-up was 18.96%. There are certainly risks out there, but strong moves like we have seen recently tend to be a positive over the intermediate and long term.</p>



<p></p>



<p></p>



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