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I seek to liberate investors from the chains of borrowed opinions by teaching metric awareness that leads to the formation of your own opinions. I am a retail investor that gathers, processes and analyzes significantly more data than average. I share that data in my articles. I let the data do... More
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  • EPS Projection Accuracy - Region Banks Of The North And East 0 comments
    Mar 22, 2014 2:07 PM

    I do my coding, my data, and my output in javascript. I do not use a database program. I believe I have more control of the appearance of the output by doing in this way. I occasionally do weird stuff - thus I want that extra freedom. But there are limits to my coding abilities - and limits to the extra effort I am willing to produce. Sometimes I live with some errors. And the upcoming data contains one of those errors.
    For most sectors, I change the negative earning projections to a token positive amount. P/E ratios based on negative earnings is garbage output. Regional banks of the North and East is the one sector where I experimented with inputting negative earning numbers. When it comes to changes in negative earning projections, the data will be in error. I want my algorithms to be easy to read - easy to change - and easy to update. Clouding the code with "if statements" to correct the output would sub-optimize my efforts - so I do not do it. Be aware that when a negative projection changes to a positive projection, the math still produces a negative change in this output.
    Even with those faults, I believe that awareness of this data is important. For example, if one were choosing between two banks with near equal yields and dividend projection CAGRs - Bank A and Bank B - for an upcoming purchase. It is logical to compare their P/E ratios and dividend to EPS ratios. That kind of comparison is elementary. But what if one of the banks had greater EPS projection accuracy? That would be a big factor in my decision. And that is a reason why I believe there should logically be significant differences in the required rate of returns in this sector.

    Changes in intra-year EPS projection estimates by Year
    This test highlighted significant differences in EPS accuracy - Banks EPS accuracy is lacking, even when grading with a liberal curve
     20062007200820092010201120122013Accuracy
    compChngChngChngBeginEndChngBeginEndChngBeginEndChngBeginEndChngBeginCurChngRating

    ASBC-9%-10%-43%1.54-1.26-182%0.66-0.10-115%0.580.6716%0.890.9911%1.021.108%4.0
    BBT-5%-7%-25%2.201.15-48%1.461.16-21%1.771.802%2.372.6914%2.922.89-1%3.5
    CHCO0%1%-42%3.072.68-13%2.752.47-10%2.562.674%2.582.736%2.963.063%2.2
    CMA-0%-11%-71%1.34-0.77-157%-0.740.88-219%1.802.1117%2.222.6620%2.643.0014%4.2
    FITB-27%-29%-96%-0.460.67-246%-0.330.63-291%1.081.2213%1.411.6316%1.592.0227%5.0
    FMBI0%-30%-27%1.77-0.71-140%0.34-0.27-179%0.440.42-5%0.710.10-86%0.951.0612%4.5
    FMER-15%-8%-3%1.360.90-34%1.171.02-13%1.321.06-20%1.121.207%1.251.18-6%2.5
    FULT-9%-23%-89%0.590.31-47%0.590.590%0.770.75-3%0.860.79-8%0.830.830%2.5
    HBAN-3%-87%-94%0.91-6.14-775%-0.410.27-166%0.460.6030%0.610.6811%0.650.7211%5.0
    MBFI0%-1%-33%1.45-0.91-163%0.910.19-79%0.750.55-27%1.451.5910%1.691.796%3.8
    MTB1%-25%-34%3.962.89-27%3.695.6954%6.036.8213%6.897.549%8.218.382%2.8
    NBTB0%-11%0%1.831.53-16%1.521.669%1.721.71-1%1.821.64-10%1.631.651%1.0
    NTRS0%8%21%3.973.16-20%3.382.65-22%3.262.68-18%2.992.89-3%3.343.00-10%1.5
    ONB-14%-6%-13%0.820.13-84%0.330.4433%0.600.7220%0.980.95-3%1.031.00-3%2.5
    SNV2%-44%-94%-0.94-4.20347%-1.07-1.4132%-0.18-0.17-6%0.140.10-29%0.140.140%5.0
    SUSQ-5%-27%-37%1.16-0.05-104%0.170.13-24%0.450.40-11%0.680.8424%0.930.92-1%3.5
    USB0%-14%-36%1.850.97-48%1.511.7315%2.142.3912%2.642.879%3.083.00-3%2.0
    VLY-10%-9%-42%1.13-0.33-129%0.840.81-4%0.860.84-2%0.840.74-12%0.710.63-11%2.8

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