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    <title>STOCKS AND STATS</title>
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    <description>Data Science Meets Investing - A Podcast for Advanced Listeners Who Are Interested in Data and Markets</description>
    <pubDate>Fri, 23 Sep 2022 05:49:00 -0300</pubDate>
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        <copyright>Copyright 2022 All rights reserved.</copyright>
    <category>Business:Investing</category>
    <ttl>1440</ttl>
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          <itunes:summary>We use Data Science Methodology for Investing. Our Episodes can be considered as little brain snacks to the interested investor.</itunes:summary>
        <itunes:author>Stocks And Stats</itunes:author>
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        <title>Was Warren Buffett just LUCKY? - Stocks and Stats #3</title>
        <itunes:title>Was Warren Buffett just LUCKY? - Stocks and Stats #3</itunes:title>
        <link>https://stocksandstats.podbean.com/e/was-warren-buffett-just-lucky-stocks-and-stats-3/</link>
                    <comments>https://stocksandstats.podbean.com/e/was-warren-buffett-just-lucky-stocks-and-stats-3/#comments</comments>        <pubDate>Fri, 23 Sep 2022 05:49:00 -0300</pubDate>
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                                    <description><![CDATA[<p>If stock returns were completely random, all good fund managers would be good due to luck, not skill. And their stories would belong to the fantasy section of a book store (at best), including the books about Warren Buffett. Here, we will discuss if Buffett and other successful fund managers were just lucky or if they really have an edge.</p>
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                                                            <content:encoded><![CDATA[<p>If stock returns were completely random, all <em>good</em> fund managers would be <em>good</em> due to luck, not skill. And their stories would belong to the fantasy section of a book store (at best), including the books about Warren Buffett. Here, we will discuss if Buffett and other successful fund managers were just lucky or if they really have an edge.</p>
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        <itunes:summary>If stock returns were completely random, all good fund managers would be good due to luck, not skill. And their stories would belong to the fantasy section of a book store (at best), including the books about Warren Buffett. Here, we will discuss if Buffett and other successful fund managers were just lucky or if they really have an edge.</itunes:summary>
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        <itunes:duration>473</itunes:duration>
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        <title>Never use THIS distribution when modelling Stock Market Returns - Stocks and Stats #2</title>
        <itunes:title>Never use THIS distribution when modelling Stock Market Returns - Stocks and Stats #2</itunes:title>
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                    <comments>https://stocksandstats.podbean.com/e/never-use-this-distribution-when-modelling-stock-market-returns-stocks-and-stats-2/#comments</comments>        <pubDate>Fri, 23 Sep 2022 05:46:40 -0300</pubDate>
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                                    <description><![CDATA[<p>When modelling stock market returns, every data scientist has to answer how stock returns are distributed. The “normal” answer would be: They are normally distributed. However, research has shown that stock returns are probably not normally distributed, because large jumps in stock prices occur frequently which makes it highly unlikely for returns to be normally distributed.</p>
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                                                            <content:encoded><![CDATA[<p>When modelling stock market returns, every data scientist has to answer how stock returns are distributed. The “normal” answer would be: They are normally distributed. However, research has shown that stock returns are probably not normally distributed, because <em>large</em> jumps in stock prices occur frequently which makes it highly unlikely for returns to be normally distributed.</p>
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        <itunes:summary>When modelling stock market returns, every data scientist has to answer how stock returns are distributed. The “normal” answer would be: They are normally distributed. However, research has shown that stock returns are probably not normally distributed, because large jumps in stock prices occur frequently which makes it highly unlikely for returns to be normally distributed.</itunes:summary>
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        <title>Why Mean Reversion of PE-Ratios is WRONG - Stocks and Stats #1</title>
        <itunes:title>Why Mean Reversion of PE-Ratios is WRONG - Stocks and Stats #1</itunes:title>
        <link>https://stocksandstats.podbean.com/e/why-mean-reversion-of-pe-ratios-is-wrong-stocks-and-stats-1/</link>
                    <comments>https://stocksandstats.podbean.com/e/why-mean-reversion-of-pe-ratios-is-wrong-stocks-and-stats-1/#comments</comments>        <pubDate>Fri, 23 Sep 2022 05:44:28 -0300</pubDate>
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                                    <description><![CDATA[<p>"The price-earnings ratio of this share is below its historical mean, this is a good opportunity to buy now!". The basic principle behind such sentences is mean reversion.</p>
<p>What this means is that asset prices or pricing ratios revert to their historical mean. Today I will show you under what conditions mean reversion can work and why its simple approach usually leads to wrong conclusions about the pricing of a share.</p>
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                                                            <content:encoded><![CDATA[<p>"The price-earnings ratio of this share is below its historical mean, this is a good opportunity to buy now!". The basic principle behind such sentences is mean reversion.</p>
<p>What this means is that asset prices or pricing ratios revert to their historical mean. Today I will show you under what conditions mean reversion can work and why its simple approach usually leads to wrong conclusions about the pricing of a share.</p>
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        <itunes:summary>Asset prices or pricing ratios revert to their historical mean. Today I will show you under what conditions mean reversion can work and why its simple approach usually leads to wrong conclusions about the pricing of a share.</itunes:summary>
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