In thie piece we will review the quality ratios and quant metrics for shares of Tetra Tech, Inc. (TTEK). Avid investors might be interested in how the quality ratios are stacking up for the Industrials firm. Robert Novy-Marx, a professor at the university of Rochester, discovered that gross profitability has as much power predicting stock returns as traditional value metrics. He found that while other quality measures had some predictive power, especially on small caps and in conjunction with value measures, gross profitability generates significant excess returns as a stand alone strategy, especially on large cap stocks.The Gross profitability for Tetra Tech, Inc. (TTEK) is 0.19621.
Dedicated investors often strive hard to set themselves up for success. Finding long-lasting success in the stock market may not be an easy endeavor. The mindset of a short-term trader may differ greatly from that of a long-term investor. Investors often have to be prepared for many different situations. Obtaining the proper knowledge about stocks and the investing world is typically a main goal for active traders and investors. Once the investor is armed with knowledge, they may be able to see things that others cannot. This may involve staying up to date on various fundamentals, technicals, and macro-economic conditions.
Professor Novy-Marx’s key insight was that you don’t need to go further down the income statement as these numbers may get manipulated with accounting tricks. To identify really profitable firms, one should look at the top line, not the bottom line. In one of his papers, Novy-Marx compares gross profitability to the other most famous strategies such as Greenblatt magic formula, Piortoski F-Score, etc.
New investors may be looking at the soaring stock market and wondering if now is a good time to try and get in on the action. Leaping into the market without proper research or a solid plan may leave the investor on the short end of the stick. Creating a stock investing plan can be as simple or complex as the individual chooses. Sometimes, keeping things simple may be the best way to go. Other times, there may be more than meets the eye, and a deep-dive into the crucial data may be required. New investors may be extremely excited to start buying stocks. They may have heard some great water cooler talk about the next big stock. There is always a possibility that the hot stock chatter may end up coming to fruition, but it could just as likely turn out to be terribly erroneous. Many individuals in the financial world will be quick to provide these can’t lose picks, but until this information is thoroughly researched, investors may want to proceed with caution.
Total Asset Growth
In their 2008 paper, professors Cooper, Gulen and Schill provided evidence that a firm’s assets growth rates are strong predictors of future abnormal returns.
“The findings suggest that corporate events associated with asset expansion (i.e., acquisitions, public equity offerings, public debt offerings, and bank loan initiations) tend to be followed by periods of abnormally low returns, whereas events associated with asset contraction (i.e., spin-offs, share repurchases, debt prepayments, and dividend initiations) tend to be followed by periods of abnormally high returns.” – Cooper, Gulen & Shill in Asset Growth and the Cross-Section of Stock Returns. In a study on US data during the period 1967-2007, they find that:
– A hedge portfolio rebalanced annually that is long (short) the stocks of companies with the lowest (highest) percentage growth in total assets over the previous 12 months generates an average annual return of 22%.
– This asset growth effect is stronger for small capitalization stocks, but is still substantial for large capitalization stocks.
– The effect is strongest in the month of January.
– Asset growth rate retains large explanatory power for future stock returns after accounting for firm size, book-to-market ratio and momentum. In fact the asset growth effect is at least as powerful in explaining returns as these other widely used factors.
We calculate asset growth as follows:
Total Asset Growth = (Total AssetsTotal Assets y-1) − 1. Tetra Tech, Inc. (TTEK) has a total asset growth number of 0.029786.
Net Debt to Market Cap
This ratio gives a sense of how much debt a company has relative to its market value. Companies with high debt levels compared to their peers can be volatile. We calculate it as follows:
Net Debt to Market Cap = (Total Debt−Cash and ST Investments) / Market Cap
Tetra Tech, Inc. (TTEK) has a net debt to market cap ratio of 0.602702.
Altman Z Score
Tetra Tech, Inc. (TTEK) has an Altman Z score of 4.168441. The Z-Score for predicting bankruptcy was published in 1968 by Edward I. Altman, who was assistant professor of finance at New York University at that time. It measures the financial health of a company based on a set of income and balance sheet values. The Altman Z-Score predicts the probability that a firm will go bankrupt within 2 years. In its initial test, the Altman Z-Score was found to be 72% accurate in predicting bankruptcy two years before the event. In a series of subsequent tests, the model was found to be approximately 80%–90% accurate in predicting bankruptcy one year before the event
Atman built the model by applying the statistical method of discriminant analysis to a dataset of publicly held manufacturers. Since then he has published new versions based on other datasets for private manufacturing (Z’-Score), non-manufacturing, service companies and companies in emerging markets. (Z”-Score)
Please also note that the original dataset used was quite small and consisted of only 66 firms of which half filed for bankruptcy. All companies were manufacturers and small firms (total assets less than $1m) were removed.
There are many factors that can affect the health of a company. This is one reason why stock trading can be extremely difficult at times. Because there are always so many things to take into consideration, it may be next to impossible to create a formula that will continually beat the market. Even after all the data has been scrutinized and the numbers have been crunched, the investor still has to make sense of the information and figure out what to do with it. Knowing how to use the information about publically traded companies can end up being the difference between handsome gains and devastating losses.
Value Composite Three (VC3) is another adaptation of O’Shaughnessy’s value composite but here he combines the factors used in VC1 with buyback yield. 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.
VC3 is the combination of the following factors:
As with the VC1 and VC2, companies are put into groups from 1 to 100 for each ratio and the individual scores are summed up. This total score is then put into groups again from 1 to 100. 1 is cheap, 100 is expensive.
The scorecard also displays variants of the VC3 where the score is calculated for the selected company compared to peer companies in the same industry, industry group or sector.
Please note that we use Book-to-Market instead of P/B since it allows a more accurate sorting compared to P/B. Stocks with a high B/M show up at the top of the list, stocks with negative B/M are at the bottom of the list. For the same reason we use Earnings-to-Price instead of Price-to-Earnings and Cash flow-to-price instead instead of Price-to-cash flow.
Also important is that we always make sure that companies with the same score get added to the same percentile. For stock universes where the number of stocks is less than 100, we make sure that the stocks are still allocated to percentiles from 0 to 100 instead of 0 to the total number of stocks. This is particularly relevant for the industry, industry group or sector variants where if additional filters are used, the number of stocks often drops below 100.
Tetra Tech, Inc. (TTEK) has a VC3 of 21.
Successful stock market traders and investors don’t usually just become that way overnight. There are often many years of experience behind those winning trades. The amount of data available to investors these days is staggering. Investors have to be able to focus on the provided information and decide which data should be followed and prioritized. Many investors will be keeping a watchful eye on the next round of company earnings reports. As companies start to report quarterly numbers, investors may be able to sift through the data and make some projections on how the stock will perform over the next few quarters.
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