Introduction to the Positive/Negative Forensic Value Stock Selections
This quantitative study continues a series of multi-year test of the top three forensic algorithms used to detect bankruptcy risk, earnings manipulation, and financial irregularities. My forward testing 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. Now with the addition of Montier C-Score beginning in August, the number of assessment variables has increased to 28.
The methods and independent detection success of the four different forensic algorithms are detailed in the methodology section at the end of this article.
Negative Scoring Forensic Value Selections for August:
A sample of the top 4 out of 8 stocks out of more than 8,000 stocks screened are the only adverse scoring stocks across each of four Forensic algorithms. The results are sorted along the Ohlson O-score probability percentage in descending order.
Based on additional input from a fellow Certified Fraud Examiner and consultant for a big four accounting firm, I am breaking down the forensic scores by industry. This not only provides many additional stocks to consider but may also 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, that is they must be able to qualify across four 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 8 up to 22 stocks.
|(SBGL)||Sibanye Gold Ltd||Basic Materials||-1.32||0.90||67.27%|
|(CRK)||Comstock Resources||Oil & Gas||1.21||0.53||50.74%|
|(PLUG)||Plug Power, Inc.||Oil & Gas||206.96||-3.65||88.06%|
|(MDR)||McDermott Intl.||Oil & Gas||-0.96||-0.39||92.64%|
|(CRESY)||Cresud S.A.||Consumer Goods||6.43||0.23||53.90%|
|(NIO)||NIO Inc.||Consumer Goods||-2.04||-3.00||91.19%|
|(SUPV)||Grupo Supervielle S.A.||Financial||-2.05||0.80||91.58%|
|(GGAL)||Grup Financiero Galicia||Financial||3.03||0.81||88.70%|
|(MARA)||Marathon Patent Group||Industrial Goods||19.83||-33.34||98.80%|
|(ELTK)||Eltek LTD||Industrial Goods||31.00||-0.21||94.96%|
|(ORN)||Orion Group Holdings||Industrial Goods||-0.29||0.82||72.33%|
|(VLRS)||Controladora Vuela Co.||Services||-2.20||0.86||77.56%|
|(VERB)||Verb Technology Co.||Technology||0.29||-96.55||100%|
Total Forensic Negative Stocks by Sector
No Utility Sector stocks emerged from the screen. These results may reflect accounting idiosyncrasies unique to each sector.
Charts of the top 4 highest adverse scoring stocks across all four forensic algorithms are listed below:
Precision BioSciences (DTIL)
Precision BioSciences, Inc. operates as a genome editing company and develops therapeutic products in the United States. It operates through two segments, Therapeutic and Food. The company offers ARCUS, a genome editing platform to cure cancers and genetic disorders.
Sorrento Therapeutics (SRNE)
Sorrento Therapeutics, Inc., a clinical-stage biotechnology company, primarily engages in the discovery and development of therapies focused on oncology and the treatment of chronic cancer pain worldwide.
Plug Power Inc. (PLUG)
Plug Power Inc., an alternative energy technology provider, engages in the design, development, manufacture, and commercialization of hydrogen and fuel cell systems for the material handling and stationary power markets primarily in North America and Europe. It focuses on proton exchange membrane (PEM) fuel cell and fuel processing technologies, fuel cell/battery hybrid technologies, and related hydrogen storage and dispensing infrastructure.
Axos Financial (AX)
Axos Financial, Inc. operates as the holding company for BofI Federal Bank that provides consumer and business banking products in the United States. The company offers deposits products, including consumer and business checking, demand, savings, and time deposit accounts. It also provides single-family and multifamily mortgage secured lending products; commercial real estate secured and commercial lending products; specialty finance factoring products; prime loans to customers secured by new and used automobiles; and term unsecured personal loans to individual borrowers, as well as overdraft lines of credit.
Positive Scoring Forensic Selections for August:
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 share 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 four stocks are sorted along the Ohlson O-score for their probability percentage of bankruptcy.
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 4 highest positive scoring stocks across all three forensic algorithms are listed below:
AnaptysBio, Inc. (ANAB)
AnaptysBio, Inc., a clinical-stage biotechnology company, engages in developing antibody product candidates focused on unmet medical needs in inflammation.
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 NHL.
KalVista Pharmaceuticals, Inc. (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.
Moderna, Inc. (MRNA)
Moderna, Inc., a clinical-stage biotechnology company, develops therapeutics and vaccines based on messenger RNA for the treatment of infectious diseases, immuno-oncology, rare diseases, and cardiovascular diseases. As of February 15, 2019, the company had 11 programs in clinical trials and a total of 20 development candidates in six modalities comprising prophylactic vaccines, cancer vaccines, intratumoral immuno-oncology, localized regenerative therapeutics, systemic secreted therapeutics, and systemic intracellular therapeutics.
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 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 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 selection 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.
18 portfolios (9 positive forensic value / 9 negative forensic value) have completed a one-year testing period since July 2017. A clear pattern of declining returns from strong value-based forensic selections that analyze 22 different fundamental variables can be seen in the charts below. Initially, portfolio selections produced returns around 100% and have steadily declined over time to some of the lowest returns from the August 2018 stocks.
Whether this pattern reflects stocks that are not participating in current record corporate buyback activity or the marketplace that is has been affected by quantitative tightening from the Fed is not clear. A shift toward momentum investing or technical behavioral trading may be overtaking fundamentals in the current environment. Adding the Montier C-score is expected to provide additional discriminant power of the forensic fundamental tests to see if stronger variation between Positive, Negative, and Benchmark Index returns can be identified.
In the prior reports, the difference in returns beyond a one-year holding period for the Positive and Negative forensic value portfolios was 32.64%. Through June 2019 this difference was still significant but was reduced to 18.78%. Now into August, the difference has further declined with Positive portfolios beating Negative portfolios beyond the 1-year holding period by only 15.49%. Deteriorating market conditions may be adversely skewing the results, but the significant outcomes are well within the intended 1-3 year effective range of the models' design.
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. Deterioration in the models may be a significant concern for those stocks screened above. The tests continue and more explanations may develop over time.
The prior article for June is available here: Forensic Value Selections For June: Long-Term Positive Picks Beating Negative By +18.78%
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
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
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Disclosure: I/we have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. 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.