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Forensic Value Stock Analysis: The Highest Positive And Negative Scoring Stocks For December

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Includes: AMRX, AQST, ARDX, AX, BBCP, BGCP, BIMI, CARB, CASH, CPST, CRESY, CRMD, DIS, EPZM, GCAP, GE, INFY, IRS, KALV, MNRL, PACD, PEGI, QTT, THC, TK, TROX, VSLR, YCBD, ZIXI
by: JD Henning
JD Henning
Value, momentum, portfolio strategy, investment advisor
Summary

The new December selections for both Positive and Negative Forensic Value stocks released in alternating months with the Piotroski-Graham Value selections.

10 Positive and 10 Negative forensic 1-year portfolios have been completed since 2017, revealing significant differences in stock returns and price behavior.

The two most recent negative forensic portfolios are up significantly: August +39.57% and October +38.75%.

The Forensic Algorithms applied in these selections are: Beneish M-score, Altman Z-score, Ohlson O-probability score, and Montier C-score, using a combined 28 fundamental accounting ratios.

Value stocks have been trailing momentum stocks and benchmark averages for the past two years, but evidence of a value breakout is emerging near year end.

Introduction to the Positive/Negative Forensic Value Stock Selections

This quantitative study continues a series of multi-year test now using the top four forensic algorithms applied to detect bankruptcy risk, earnings manipulation, and financial irregularities. This forward testing study compiles portfolio selections from the highest positive and highest negative scoring stocks across the U.S. stock exchanges to measure performance variances between portfolios and benchmark indexes.

The different algorithms created by Beneish, Ohlson, and Altman are well-documented from financial literature and rely exclusively on fundamental data, including year-over-year operational performance measures. The combination of all three bankruptcy and financial irregularity algorithms creates a unique "deep dive" on key value characteristics and applies a total of 22 different fundamental financial variables for assessment. The newest addition of the Montier C-Score began in August, and the combination of accounting variables has increased to 28.

Recent examples of Forensic Algorithm applications

Prior examples of the application of these forensic financial algorithms can be found in several of my recent articles and interviews that have been published widely, including Hong Kong and India:

Each of the 3 stocks tested in 2019 did not reveal irregularities according to the forensic models as significantly as claimed in each of the different allegations. Subsequently, General Electric (GE) regained over 40% from its lows, Disney (DIS) has gone on to new all-time highs, and Infosys (INFY) is still under review by PwC, while the stock has regained over 10% from its lows.

A new "Tesla Test" for December will also be released shortly - be sure to follow my articles with real-time alerts for the latest updates. The methods and independent detection success of these four different forensic algorithms are detailed in the methodology section at the end of this article.

Value factors showing a year-end positive reversal

As the Block Rock Investment chart illustrates well below, value stocks have been struggling since their peak in early 2018. Value has been significantly underperforming MSCI World benchmark returns for nearly two years. Some evidence of a positive reversal toward a value breakout is emerging near the end of 2019. These returns since 2017 are also highly correlated with the Positive and Negative Forensic value stock returns.

Market positioning in both [momentum and value] factors looked to have become stretched heading into the recent market shakeup. Investors had piled into momentum stocks, leaving many value equities unloved. Before the reversal, the value factor had been trading near the bottom of its historical valuation range, so may have been overdue for a correction. In contrast, momentum had been trading near the top of its historical valuation ranges.

~ Mike Pyle, Blackrock Investment Institute

Negative Scoring Forensic Value Stocks for December

A sample of 3 top stocks out of more than 8,000 stocks screened from the group of adverse scoring stocks is shown below. These stocks qualified on each of the four Forensic algorithms. The results are sorted along the Ohlson O-score probability percentage in descending order.

In recent articles, I have started breaking down the forensic scores by industry. This not only provides many additional stocks to consider, but may reveal key forensic stock patterns unique to sectors, and may even show forensic conditions of each sector in the markets. Remember that only the most extreme adverse and positive scoring stocks are measured by this analysis to qualify across each of the different algorithms.

Top Negative Forensic Stocks by Sector (up to 3 stocks)

Expanding the list of negative forensic stocks by dropping the Montier score increases the available stocks to consider from 6 up to 21 stocks.

Symbol Name Sector Beneish Altman Ohlson
TROX Tronox Holdings plc Basic Materials −1.92 1.00 74.56%
CRESY Cresud Sociedad Anonima Consumer Goods −2.07 0.25 58.33%
YCBD cbdMD, Inc. Consumer Goods 0.32 −4.09 96.51%
GCAP GAIN Capital Holdings, Financial −1.96 0.77 75.35%
BGCP BGC Partners, Inc. Financial −1.72 0.18 69.67%
AX Axos Financial, Inc. Financial 1.38 −0.58 80.78%
AMRX Amneal Pharmaceuticals, Healthcare −2.20 0.91 83.71%
THC Tenet Healthcare Corporation Healthcare −0.95 0.94 72.26%
ARDX Ardelyx, Inc. Healthcare 0.61 −1.20 58.57%
TK Teekay Corporation Industrial Goods −1.40 0.26 57.05%
BBCP Concrete Pumping Holdings Industrial Goods 5.46 0.76 59.40%
BIMI NF Energy Saving Corporation Industrial Goods 4.22 −2.00 93.89%
PACD Pacific Drilling S.A. Oil & Gas 1.10 −2.22 57.30%
PEGI Pattern Energy Group Inc. Oil & Gas 11.98 0.36 83.02%
MNRL Brigham Minerals, Inc. Oil & Gas 110.18 0.82 53.22%
IRS IRSA Inversiones y Representaciones Services −0.032 0.24 52.59%
QTT Qutoutiao Inc. Technology −1.47 −4.82 93.14%
ZIXI Zix Corporation Technology −1.39 −0.027 56.78%
CARB Carbonite, Inc. Technology −2.19 0.63 83.14%
VSLR Vivint Solar, Inc. Utilities −0.51 0.28 90.55%

Total Forensic Negative Stocks by Sector

Healthcare continues to have the highest representation of irregularly scoring stocks flagged by these algorithms. These results may reflect accounting idiosyncrasies unique to each sector.

Charts of the top 5 highest adverse scoring stocks across all four forensic algorithms are shown below:

Aquestive Therapeutics (AQST)

Nov-25-19 08:56AM Aquestive shares jump on FDA approval MarketWatch +17.26%

(Source: FinViz)

Aquestive Therapeutics, Inc., a specialty pharmaceutical company, focuses on identifying, developing, and commercializing various products to address unmet medical needs. The company markets Sympazan, an oral soluble film formulation of clobazam for the treatment of lennox-gastaut syndrome; Suboxone, a sublingual film formulation of buprenorphine and naloxone for the treatment of opioid dependence; and Zuplenz, an oral soluble film formulation of ondansetron for the treatment of nausea and vomiting associated with chemotherapy and post-operative recovery in the United States and internationally.

Meta Financial Group (CASH)

Meta Financial Group, Inc. operates as the holding company for MetaBank that offers various banking products and services in the United States. The company accepts various deposit products, including statement savings accounts, money market savings accounts, negotiable order of withdrawal accounts, and checking accounts; and deposits related to prepaid cards, which primarily comprise checking accounts and certificate accounts.

Capstone Turbine Corporation (CPST)

Capstone Turbine Corporation develops, manufactures, markets, and services microturbine technology solutions for use in stationary distributed power generation applications worldwide. It offers microturbine units, components, and various accessories for applications, including cogeneration comprising combined heat and power (CHP) and integrated CHP, as well as combined cooling, heat, and power; and renewable energy, natural resources, and critical power supply. The company's microturbines are also used as battery charging generators for hybrid electric vehicle applications.

Positive Scoring Forensic Selections for December

Out of more than 8,000 stocks screened across all the US exchanges, only a few stocks qualified this month with positive scores across all four forensic algorithms and with a price above $2/share.

This is a measure of low probabilities of bankruptcy or earnings manipulation that are being tested to find correlations to price returns over a one-year buy/hold strategy. These three stocks are sorted along the Ohlson O-score for their probability percentage of bankruptcy. There was no overlap from the last Positive Forensic portfolio in October.

These forensic scores do not necessarily forecast stock price growth, though it would seem likely that stocks with low risk of bankruptcy, low probability of corporate distress, low chance of earnings manipulation, and low probability of financial irregularities on deep fundamental analysis should provide a safer value proposition for investors going forward. Joseph Beneish has documented positive returns from favorable Beneish M-score

Charts of these top 3 highest positive scoring stocks across all three forensic algorithms are shown below:

Epizyme Inc. (EPZM)

Epizyme, Inc., a late-stage biopharmaceutical company, discovers, develops, and commercializes novel epigenetic medicines for patients with cancer and other diseases primarily in the United States. The company's lead products candidate is tazemetostat, an inhibitor of the EZH2 histone methyltransferase, which is in the Phase II clinical trial for patients with relapsed or refractory non-hodgkin lymphoma; Phase II clinical trial for relapsed or refractory patients with mesothelioma characterized by BAP1 loss-of-function; and Phase II clinical trial for adults and Phase I clinical trial for children with epithelioid sarcoma and other INI1-negative solid tumors. It also develops tazemetostat in combination with R-CHOP that is in the Phase Ib/II clinical trials in elderly patients with DLBCL; and tazemetostat in combination with PD-L1 inhibitor, which is in Phase Ib/II clinical trials for the treatment of patients with relapsed or refractory metastatic non-small cell lung cancer.

KalVista Pharmaceuticals (KALV)

KalVista Pharmaceuticals, Inc., a clinical-stage pharmaceutical company, discovers, develops, and commercializes small molecule protease inhibitors. The company's product portfolio comprises small molecule plasma kallikrein inhibitors targeting hereditary angioedema and diabetic macular edema; and oral plasma kallikrein inhibitors.

CorMedix, Inc. (CRMD)

CorMedix, Inc., a biopharmaceutical company, focuses on developing and commercializing therapeutic products for the prevention and treatment of infectious and inflammatory diseases in the United States and internationally. It primarily focuses on the development of its lead product candidate, Neutrolin, an anti-infective solution for the reduction and prevention of catheter-related infections and thrombosis in patients requiring central venous catheters in clinical settings, such as dialysis, critical/intensive care, and oncology.

Methodology Review

The purpose of this monthly value selection list is to provide investors with additional tools to evaluate financial irregularities according to three different detection models from academic research. Circumstances surrounding firms are always subject to change, open to extenuating circumstances, and models by their very nature always contain a degree of error.

Again, it is important to stress that firms identified by these academic models may not be in actual distress or suffer from any adverse irregularities whatsoever. These models are certainly not foolproof and were designed by academic researchers to improve the chance of detection of irregularities leading to bankruptcy, earnings manipulation, or to flag the presence of financial distress.

At the same time, these models are among the best peer-reviewed forensic models in the financial literature and have some significant documented value.

The Beneish model for example has "correctly identified, in advance of public disclosure, a large majority (71%) of the most famous accounting fraud cases that surfaced after the model’s estimation period" (Beneish, Lee, & Nichols, 2013, p. 57).

Further, in a survey of 169 chief financial officers of public companies, Dichev, Graham, and Rajgopal (2012) reported that respondents estimated that approximately 20% of all companies manage earnings to misrepresent economic performance. While three different financial forensic models are applied in the selection of these portfolios, researchers associated with testing the M-score described their approach in this way:

Our main hypothesis was that companies that share traits with past earnings manipulators (i.e., those that “look like manipulators”) represent a particularly vulnerable type of growth stock. Because of their strong recent growth trajectory, these companies are likely to be more richly priced. At the same time, they exhibit a number of potentially problematic characteristics, indicative of either lower earnings quality or a more challenging economic environment. Although the accounting games such companies engage in might not be serious enough to warrant legal action, we posited that their earnings trajectory is more likely to disappoint investors (i.e., they have lower earnings quality)"

(Beneish, Lee, & Nichols, 2013, p. 57).

To my knowledge, no similar longitudinal study of positive and adverse forensic scoring using all three models simultaneously has ever been conducted before. The significant benefits of these portfolios are already emerging in two short months. It is also important to constructively consider why such anomalies may exist in these stock selections at this moment in time. The resulting data which varies from month to month may prompt firms and investors to consider further due diligence of publicly available financial characteristics to mitigate any risk or error present in the marketplace.

Conclusion

20 portfolios (10 positive forensic value / 10 negative forensic value) have completed a 1-year testing period since July 2017. A clear pattern of returns follows the Blackrock Investment chart of value stock performance with extremely strong gains in 2017, followed by large declines in 2018 and a positive reversal beginning in 2019. Initially, portfolio selections produced returns around 100% and have steadily declined over time to some of the lowest returns from the August 2018 stocks. Not until recently have we seen the value portfolios of these selections begin to recover as described back in September:

Value Picks Crush Momentum In First Major Reversal Since 2009: What's Next

Whether this pattern reflects stocks that are not participating in current record corporate buyback activity or the marketplace that has been affected by quantitative tightening from the Fed is not clear.

Despite strong financial statements, low risk of bankruptcy or earnings manipulation, the Positive Forensic stocks are not generating as strong positive returns since 2017 as value selection tool.

The Negative Forensic value portfolios are showing much stronger gains from the low levels of being out of favor with the last 5 months positive. The August portfolio is up +39.57%, and October selections are up +38.75% in just two months. Positive reversal conditions toward the extremely positive gains we experienced in 2017 have begun to emerge here in late 2019. A major similarity between 2017 and late 2019 is the strong positive Fed intervention of quantitative easing that may be driving a search for out-of-favor opportunities for large gains.

In the prior reports, the difference in returns beyond a 1-year holding period for the Positive and Negative forensic value portfolios was 32.64%. Now into December, we are seeing negative forensic scores generally outperforming positive forensic scores across all measures. We can continue to assess what this may mean, as adverse selections would normally be expected to underperform the more positive forensic selections. It may reflect that higher financial irregularities could be related to management's willingness to take higher risks in anticipation of off-book opportunities, pending FDA approvals, or favorable mergers/acquisitions only on management's radar screens.

Prior tests in the literature of the Beneish M-score have shown the algorithm to generate excellent results on an annual basis for positive scores. The tests continue, and more explanations may develop over time.

I trust this research and stock selections will give you added value to your investment goals and returns in 2019!

JD Henning, PhD, MBA, CFE, CAMS

References

Altman, E. I. (1968). The Prediction of Corporate Bankruptcy: A Discriminant Analysis. The Journal of Finance, 23(1), 193–194. doi:10.1111/j.1540-6261.1968.tb03007.x

Beneish, M. D. (1999). The Detection of Earnings Manipulation. Financial Analysts Journal, 55(5), 24–36. doi:10.2469/faj.v55.n5.2296

Beneish, M. D., Lee, C. M. C., and Nichols, D. C. (2013). Earnings Manipulation and Expected Returns. Financial Analysts Journal, 69.2, 57-82

Ohlson, J. A. (1980). Financial Ratios and the Probabilistic Prediction of Bankruptcy. Journal of Accounting Research, 18(1), 109. doi:10.2307/2490395

Disclosure: I am/we are long FNGU. I wrote this article myself, and it expresses my own opinions. I am not receiving compensation for it (other than from Seeking Alpha). I have no business relationship with any company whose stock is mentioned in this article.