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   Lee Wenzel

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Using Data to Capitalize on Behavioral Finance

         December 11, 2016  What Moves Stock Prices4.pdf

How do we explain that stock movements correlate so tightly with each other?  Are there ways to systematically take advantage of what we know about stock correlations?  Why are investors so phobic of volatility, when it is more predictable than price and is essential for gains?  Are there systematic ways to take advantage of irrational behavior revealed by behavioral finance?  Momentum shows us that stocks go up  ̶  until they don't. Is one ahead to buy stocks trending up, or to buy stocks that have dropped and expect a reversion to the mean?

These are some of the questions to which we sought answers by looking at monthly returns over twelve years and over a million rows of data. Variables include volatility, correlation, and price.  The resultant portfolios are working nicely.         

Playing Defense

       December 30, 2015.   Playing Defense.pdf

In this two-page summary I first review my effort to replicate and create a portfolio from the liquidity findings of the Ibbotson et.al. article below.  While my data were not useful for that purpose, they were very useful in the discovery of a portfolio with very low draw-downs and high annual returns (16.7%, including time in cash).  What is most dramatic is that the number of stocks selected by the screen correlate with returns over the next year (p of .00000435).  Since 2003, months with a screen selection count of 15-29 have not had a loss the consequent twelve months and had average returns of 24.7%.  Screen counts of 30 or more have not had a loss and had annual returns of 27.0%.  Study the table.  

Using Screen Counts to Forecast Market Trends  

       November 12, 2012    Counts Forecast Returns.pdf

Serendipitously I discovered that the number of stocks conforming to criteria for a specific screen corresponded to the returns from that screen over the next year.  For high counts occurring 29% of the time the relationship held true without exception.  Since almost every screen or set of criteria that one might construct will also correlate with market returns, this has some interesting implications.  Detailed data is provided in tables and charts.  

Factors   

    Small Cap Advantage

         December 13, 2015.  Factor-Market Capitalization.pdf

Similar to with value and growth, charts and some methodological description are shown in the endeavor to find a pattern of superior performance between large and small cap stocks.  In looking at data other than are reported here, I generally find that small cap stocks outperform, but as a result of exceptional returns from a small number of stocks.  If I remove the outliers or cap their returns in the analysis, the large cap stocks outperform.  I see the same thing between value and growth, with value stocks being more similar in their returns.  

    Cycles for Value and Growth

        December 13, 2015.    Factor-Value Growth.pdf

The divergence between value and growth since 2000 is shown on several charts in the search for investable patterns.  There are definitely periods—sometimes extended periods—when either value or growth has far superior returns.  And there is a reversion to the mean.  However, the length of the cycles is not consistent.  For example, value has been underperformed growth in a serious way for the past twenty months or so, but how long that will continue is hard to know.

     Style Reversion to the Mean 

        December 4, 2015.   If Factor Returns Are Predictable_Why is There an Investor Return Gap.pdf

Styles or factors run in predictable cycles, with most investors exiting and changing managers, funds or investments when they should be buying.  The article was published by Research Affiliates and is written by Jason Hsu, Ph.D.  Below are reports on my endeavors to test and implement this very provocative article.  

     Momentum

       November 27, 2015. Momentum or Reversal.pdf

Every time I buy a portfolio of nicely trending stocks, they seem to reverse.  The paper describes a study of weekly percent change since 2009 for the largest 3,000 stocks.  I made several interesting discoveries in addition to clear evidence that for the last six years, stocks going down (and still around) give far better returns than stocks going up.  

     Quality as Measured by the Piotroski F-Score

         December 3, 2015   Quality and Piotroski F-Screen.pdf

The Stock Investor Pro Piotroski F-Score is a measure of a firm's healthy financials and fundamentals.  Is it a useful measure of quality?  I discovered some surprises in this examination.    

When Should One Buy Quality Stocks? 

      November 7, 2012    Risk-On Risk-Off.pdf

It is easy to naively assume that one should always buy quality stocks, but some markets reward quality stocks and sometimes risk-on markets reward low-quality stocks.  Identifying quality is the easy part.  The more complicated part involves indicators for risk-on and risk-off markets, and knowing how to hedge the risks for each type of market.

 

Why is it harder to beat the market?

     July 10, 2013.   Why it's harder to get market-beating returns.pdf

Not only Wenzel Analytics, but active managers in general are having more trouble beating the market. This analysis presents data on changes in correlations and the number of stocks significantly exceeding market returns.  While indexed products are a common response, are they also the cause of the changed market dynamics?  The last page addresses what an investor might do.

Analysis of AAII Shadow Stock Screen

       December 10, 2012.  Shadow Stock Analysis.pdf

AAII Shadow Stock screen frequently publishes updates on its Shadow Stock Screen (SSS), a small cap screen available through their Stock Investor Pro stock data and software.  Should you invest using the screen?  Perhaps more useful than the detailed assessment of the screen is the methodology for how to evaluate or improve upon a screen.     

      

Stock Screen Rotation 

            June, 2009  Stock Screen Rotation.pdf

Whether looking at AAII stock screens or those I have developed, I find it hard to find stock screens that produce a consistent count month after month, year after year, with consistent high performance and consistent performance from all the stocks selected.  Would we get better returns using the current best performing screens?  The answer is no.  But we get exceptional returns when using specific ranks other than the best.  Here is an overview report.

 

Cyclicals as Stand-in for Commodities                

Commodities should be part of everyone's asset allocation for the next few years.  Cyclical stocks track the commodities, and are more practical to buy for the average investor.  The paper ends with our choice of nine stocks from the index. 

 

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