Uncle Stock scores

term description formula
Advice Advice based on Uncle Stock score and Uncle's expected price yield (target price). The combination generates a (Strong) Sell/Hold/Buy advice.
Expected return and reversal can add a trading recommendation: Wait/Act.		 Uncle Stock score > 72% Uncle Stock score [60% - 72%] Uncle Stock score [45% - 60%] Uncle Stock score [30% - 45%] Uncle Stock score < 30%
Categories Collection of company categories. Value: Is undervalued and Trap score < 6
Value trap: Is undervalued and Trap score > 5
Overvalued: Price / Intrinsic Value > 2
Growth: Revenue.rCAGR > 10%
Income: Net Payout yield.5y avg > 4%
Junk: Financial Health score < 28% and Predictability Score < 28%
Improving: Piotroski F-score > 7
Deteriorating: Piotroski F-score < 3
Is undervalued Boolean indication whether a stock appears to be trading for less than its intrinsic or book value. Price to Book Value < 1 or Price / Intrinsic Value < 1
Trap score Score [0-12], to measure the probability of a value trap. Value traps are investments that are trading at low levels and present as buying opportunities but are actually misleading.
Uncle Stock score Score up to 100, based on a broad selection of financial ratios, combining tenets of both growth investing and value investing, to look for Growth At A Reasonable Price (GARP). where suspicious results is based on negative Enterprise Value, very low Price/ NCAV, very high Free Cash Flow yield, no dividend, very high growth rate.% and country being China.
Then:
1. cap score to min −890, max 650.
2. normalized score = (score + 890) ÷ 1420. Now we have a number from 0% to 100%
Remarks:
for percentages: represent 20% as 0.2.
logarithm(value) = signOf(value) × ln(abs(value) + 1)
Quality score Score up to 100, measuring how good the company is in terms of efficiency and potential for continued growth. Then:
1. cap score to min −47, max 45.
2. normalized score = (score + 47) ÷ 92. Now we have a number from 0% to 100%
3. stretch it using a sigmoid function, making values around 50% move away from the centre.
Remarks:
for percentages: represent 20% as 0.2.
logarithm(value) = signOf(value) × ln(abs(value) + 1)
Value score Score up to 100, measuring value by comparing market value to income and balance. Then:
1. cap score to min 0 max 2.2.
2. normalized score = score ÷ 2.2. Now we have a number from 0% to 100%
Remarks:
for percentages: represent 20% as 0.2.
logarithm(value) = signOf(value) × ln(abs(value) + 1)
Yield score Score up to 100, based on a broad selection of financial ratios measuring how cheap a stock is based on its income. Then:
1. cap score to min −1160, max 1010.
2. normalized score = (score + 1160) ÷ 1810. Now we have a number from 0% to 100%
3. stretch it using a sigmoid function, making values around 50% move away from the center.
Remarks:
for percentages: represent 20% as 0.2.
logarithm(value) = signOf(value) × ln(abs(value) + 1)
Balance score Score up to 100, based on a broad selection of financial ratios measuring price versus assets and financial health.
  • + 2.1 × logarithm(Financial Health score
  • + 0.9 × logarithm(Balance value score)
    • Then:
    1. cap score to min 0, max 3
    2. normalized score = score ÷ 3. Now we have a number from 0% to 100%
    Remarks:
    for percentages: represent 20% as 0.2.
    logarithm(value) = signOf(value) × ln(abs(value) + 1)
Balance value score Score up to 100, based on a selection of financial ratios measuring market value versus Balance sheet. Then:
1. cap score to min −450, max 620.
2. normalized score = (score + 450) ÷ 1080. Now we have a number from 0% to 100%
3. stretch it using a sigmoid function, making values around 50% move away from the centre.
Remarks:
for percentages: represent 20% as 0.2.
logarithm(value) = signOf(value) × ln(abs(value) + 1)
Financial Health score Score up to 100, based on a broad selection of financial ratios measuring financial health. Then:
1. cap score to min −2200, max 840.
2. normalized score = (score + 2150) ÷ 2990. Now we have a number from 0% to 100%
3. stretch it using a sigmoid function, making values around 50% move away from the centre.
Remarks:
for percentages: represent 20% as 0.2.
logarithm(value) = signOf(value) × ln(abs(value) + 1)
Growth rate A company's annual growth, based on income and balance evolution. Growth rate.dimension = median(bag(weight(sub-metric, metric) occurrences of metric, over all metrics with existing weight(sub-metric, metric))). The following metrics are used: Growth rate.% represents the growth of the business, but to be seen as a score to compare, not an absolute number. Growth rate.b/on CAGR represents the annual growth of the income. An average of income CAGRs.
Predictability Score Score up to 100, measuring the predictability of the earnings growth. Then:
1. cap score to min -13, max 48.
2. normalized score = (score + 13) ÷ 61. Now we have a number from 0% to 100%
Piotroski F-score F-Score and percentage score based on Priotroski's 9 different fundamental components Number [0-10]: F-Score + Percentage ÷ 100
F-Score [0-9]: (year values) Percentage: (year values) normalized to 100.
logarithm(value) = signOf(value) × ln(abs(value) + 1)
Mohanram G-score Partha Mohanram's G-Score seeks to separate out the winning growth/glamour stocks from the fallen stars. Number [0-8]: G-Score + Percentage ÷ 100
G-Score [0-8]: (year values) Percentage: (year values) normalized to 100.
logarithm(value) = signOf(value) × ln(abs(value) + 1)
Montier C score Score [0..6], James Montier aimed to create a simple scoring system that would highlight companies that may be 'cooking the books'.
Levermann score Score based on Susan Levermann's Fundamental, Valuation, Psychological and Technical criteria Number score [−12-12]: Levermann number + Percentage
Levermann number [−11-11]:
  • if Return on Equity.% > 20%: +1, < 10%: −1
  • if EBIT Margin.% > 12%: +1, < 6%: -1
  • if Equity ratio.% > 25%: +1, < 15%: −1
  • if Price / EPS.ratio < 12: +1, > 16: −1
  • if Price / EPS.b/on 5y avg < 12: +1, > 16: −1
  • if analyst recommendation > 2.5: +1, < 1.51: −1
  • if EPS revisions ratio > 1.05: +1, < 0.95: −1
  • if Price.half yr change > 5%: +1, < -5%: −1
  • if Price.1y change > 5%: +1, < -5%: −1
  • if Price.half yr change > 5% and Price.1y change +1, < 5%: +1
  • if Price.half yr change < −5% and Price.1y change > −5% : −1
  • if Price.diff ind 30d change < −3% and Price.diff ind 60d change < −6% : +1
  • if Price.diff ind 30d change > 3% and Price.diff ind 60d change > 6% : −1
  • if Earnings per share.1y growth (forward) > 5%: +1, < −5%: −1
Percentage: normalized to 100.
logarithm(value) = signOf(value) × ln(abs(value) + 1)
Company score Score based on five key figures for a company. Number [0..6] : Number-Score + Percentage ÷ 100(
Score [0-6]: (year values) Percentage: (year values) normalized to 100.
logarithm(value) = signOf(value) × ln(abs(value) + 1)
O'Shaughnessy Value Composites Three This factor is interesting for investors who're looking for stocks with the best value characteristics, but are indifferent to whether these companies pay a dividend. normalized to 100.
logarithm(value) = signOf(value) × ln(abs(value) + 1)
Greenblatt score Score based on Greenblatt's Magic Formula parameters. average of normalized to 100.
logarithm(value) = signOf(value) × ln(abs(value) + 1)
Pim Van Vliet score Score combining price momentum with shareholder yield. Sum of
  • logarithm(Price.1y change)
  • 3 × logarithm(Net Payout yield)
  • −0.25 × logarithm(Price.SD 252)
normalized to 100.
logarithm(value) = signOf(value) × ln(abs(value) + 1)
ERP5 score Score based on the ERP5 score factors as designed by the MFIE Capital team. It combines the Greenblatt Magic formula with ideas developed by Graham & Dodd. average of logarithm(value) = signOf(value) × ln(abs(value) + 1)
Slater score Score up to 100, focussing on finding small growth stocks before they hit the big time. normalized to 100.
logarithm(value) = signOf(value) × ln(abs(value) + 1)
Altman Z score The formula may be used to predict the probability that a firm will go into bankruptcy within two years. Uses multiple corporate income and balance sheet values to measure the financial health of a company.
Ohlson O-Score Probability for predicting bankruptcy based on a multi-factor financial formula postulated in 1980 by Dr. James Ohlson as an alternative to the Altman Z-score for predicting financial distress. Any results larger than 50% suggests that the firm will default within two years. logistic of:
Beneish M-score The Beneish M score was created by Professor Messod Beneish. In many ways it is similar to the Altman Z score, but optimized to detect earnings manipulation rather than bankruptcy. An M-Score of greater than -2.22 signals that the company is likely to be a manipulator.
Dechow F-Score Score from Patricia Dechow that can be used as a red flag or signal of the likelihood of earnings management or misstatement. Predicted Value =
F-score = logistic(-Predicted Value) ÷ 0.0037
ESG score A score that evaluates how sustainably a company is conducting business.
Environment score A score that evaluates a company by its environmental criteria, like energy use, waste, pollution, natural resource conservation and treatment of animals.
Social score A score that evaluates a company by its business relationships.
Governance score A score that measures accuracy and transparency of accounting methods and whether stockholders are allowed to vote on important issues.