On November 15, 2018, SA News Editor Brandy Betz reported the following news on Nvidia Corporation (NVDA). Nvidia -17% on downside guide as crypto boom ends. This earnings report was quite a shock to investors and as a result, many ran for the exits. We at Friedrich Global Research love when this happens, as we have been patiently waiting for Nvidia to finally have a bad quarter. As potential investors in Nvidia, we have little doubt that the company will soon recover to its former glory, as its future prospects are quite bright. We can say this with confidence as Nvidia is a key player in Gaming, Professional Visualization, Datacenters, and Hi-Tech Automotive. For a company to be involved in just one of these high growth industries would be sufficient to consider Nvidia as a potential investment, but for it to be involved in all four, is something unique indeed. Nvidia, in our opinion, has gone from overbought to fairly valued and we believe that it will “sooner than later” become oversold, as the panic selling in its shares has been fast and furious. In this article, we will present some unique ratios that our Friedrich Investing System uses and will present a real-time quantitative analysis that will demonstrate the power of free cash flow in the investment process. In doing so, we will also teach everyone how to analyze one’s portfolio holdings on Main Street vs. Wall Street. At the same time, we will also explain how the methodology involved in this analysis came about.
Main Street is where Nvidia operates and Wall Street is where its shares trade. The Nvidia shares that one can purchase on Wall Street are in the public domain and the company has little control over how each share will trade. Nvidia is required to release its earnings reports each quarter and from time to time, it also provides press releases to its shareholders (and the general public) giving updates on how its operations are doing on Main Street. Main Street is where Nvidia invests in its own operations and sells to its customers. How well the CEO of Nvidia and its management do in selling those products, determines how profitable the company will be. Wall Street then reacts based on the success or failure of management to meet its goals. Main Street and Wall Street are thus interlinked, but because anyone with a computer, an internet connection, and a brokerage account can buy or sell any stock at any time, expertise is not a requirement in order to invest on Wall Street. This results in Wall Street being a very dangerous place to operate in as many investors tend to operate through emotion or tend to follow the herd in and out of stocks. During bull markets, investors feel like they can do no wrong as “the rising tide lifts all boats.” But when a bear market suddenly shows up, these same investors tend to panic and like lemmings stampede over the cliff. Thus, we have the classic case of “greed vs. panic.” Having noticed this problem some 30 years ago, I spent the last three decades building an algorithm called Friedrich. Our algorithm was designed to assist all investors (both Pro and Novice alike) and give them the ability to quickly compare a company’s Main Street operations, to its Wall Street valuation (Overbought or Oversold condition). Friedrich can do this on an individual company basis or assist users in analyzing an entire index like the S&P 500, an ETF, Mutual Fund, or individual portfolio, with the use of our Portfolio Analyzer. Many years ago, while reading Berkshire Hathaway’s (BRK.A) (BRK.B) 1986 letter to shareholders, I discovered a ratio, which Mr. Buffett entitled “Owner Earnings,” or what we may consider to be Mr. Buffett’s version of “Free Cash Flow.” To my amazement, in that little footnote, Mr. Buffett explains how to use it and basically states that it is one of the key ratios that he and Charlie Munger used in analyzing stocks. In that article, he defined the term “owner earnings” as the cash that is generated by the company’s business operations.
[Owner earnings] represent [A] reported earnings plus [B] depreciation, depletion, amortization, and certain other non-cash charges… less [C] the average annual amount of capitalized expenditures for plant and equipment, etc. that the business requires to fully maintain its long-term competitive position and its unit volume.” I have used this free cash flow ratio for decades, using data from the Value Line Investment Survey, whose founder was Arnold Bernhard. Mr. Bernhard was a big fan of free cash flow and probably introduced it sooner than Mr. Buffett did. I know this as I was able to calculate the FCF ratio using old Value Line’s sheets for my 60-year backtest of the DJIA from 1950-2009. In the backtest that I mentioned above, I demonstrated that if one can purchase a company whose shares are selling for 15 times or less, its Price to Free Cash Flow Ratio, that the probability of success will dramatically increase in most cases. I have renamed the ratio the Bernhard Buffett Free Cash Flow ratio in honor of both men. The following is how that ratio below is calculated. Price to Bernhard Buffett Free Cash Flow Ratio = Sherlock Debt Divisor/[(net income per share + depreciation per share) + (capital spending per diluted share)] Sherlock Debt Divisor = Market Price Per Share – ((Working Capital – Long-Term Debt)/Diluted Shares Outstanding)) The above are the ratios I use when analyzing a stock on Wall Street and below are the ratios I use when analyzing a stock on Main Street. FROIC means “Free Cash Flow Return on Invested Capital” Forward Free Cash Flow = [((Net Income + Depreciation) (1+ % Revenue Growth rate)) + (Capital Spending)] FROIC = (Forward Free Cash Flow)/(Long-Term Debt + Shareholders’ Equity) What the FROIC ratio does is tell us how much forward free cash flow the company is generating on Main Street relative to how much total capital it has employed. So, if a company invests $100 in total capital on Main Street and generates $20 in forward free cash flow, it, therefore, has a FROIC of 20%, which we consider excellent. This is just one of the key ratios (66 in total) that we use to identify how a company is performing on Main Street, as it is our belief that if a company is making a killing on Main Street that this news will eventually show up on Wall Street’s radar.
So, let us begin our analysis and at the same time try to teach everyone how to do a similar analysis on one’s own portfolio. In analyzing Nvidia’s Price to Bernhard Buffett FCF ratio, we must first analyze Nvidia Sherlock Debt Divisor. Here is a detailed definition of what that ratio is: Sherlock Debt Divisor = A major concern that I have these days in analyzing companies is the amount of debt each takes on relative to its operations and whether management is abusing this situation by taking on more debt than it requires. Debt, when used wisely, allows for what is called leverage and leverage can be extremely beneficial within certain parameters. On the other side of the coin, the use of debt can also be excessive and put a company’s future in jeopardy. So, what I have done to determine if a company’s debt policy is beneficial or abusive, is to create the Sherlock Debt Divisor. What the Divisor does is punish companies that use debt unwisely and rewards those who successfully use debt as leverage. How do I do this? Well, I take a company’s working capital and subtract its long-term debt. If a company has a lot more working capital than long-term debt, I reward it and punish those whose long-term debt exceeds its working capital. So, if this result is higher than the current stock market price, then leverage is being used and the more leveraged a company is, the worse the results of this ratio will be and the less attractive its stock will be as an investment. Thus, having successfully defined the Sherlock Debt Divisor, we need the following four bits of financial data in order to calculate it for Nvidia. TTM for those who don’t know is “trailing 12 months” or as close to real-time data as we can get, based on when each company reports. Market Price Per Share = $144.71 Working Capital = Total Current Assets – Total Current Liabilities Total Current Assets = $11,386,000,000 Total Current Liabilities = $1,608,000,000 Working Capital = $9,778,000,000 Long-Term Debt = $1,987,000,000
Diluted Shares Outstanding = 625,000,000 Sherlock Debt Divisor = Market Price Per Share – ((Working Capital – Long-Term Debt)/Diluted Shares Outstanding)) Sherlock Debt Divisor = $144.71 – (($9,778,000,000 – $1,987,000,000)/625,000,000)) Sherlock Debt Divisor = $144.71 – $12.46 = $132.25 Since Nvidia has less Long-Term Debt vs. Working Capital, we, therefore, must reward it and use the new $132.25 as our new numerator in all our calculations. Price to Bernhard Buffett FCF Ratio = Sherlock Debt Divisor/[(net income per share + depreciation per share) + (capital spending per diluted share)] Sherlock Debt Divisor = $132.25 Net Income per diluted share = $4,694,000,000/625,000,000 = $7.51 Depreciation per diluted share = $241,000,000/625,000,000 = $0.39 Capital Spending per diluted share = $-813,000,000/625,000,000 = $-1.30 $7.51 + $0.39 + ($-1.30) = $6.60 Price to Bernhard Buffett Free Cash Flow Ratio = $132.25/$6.60 = 20.04 Now, if one goes to our FRIEDRICH LEGEND (on what is considered a good or bad result), you will notice that our result of 20.04 is considered average. We last ran our data file for Nvidia on November 21, 2018, and our Friedrich Algorithm gave a recommendation to our subscribers that Nvidia is a “Hold” as our Friedrich Data File and Chart below show. There you will also find the last ten years of Nvidia’s Price to Bernhard Buffett Free Cash Flow results. Now that we have taught everyone how to calculate our Price to Bernhard Buffett Free Cash Flow ratio, let us now move on and teach everyone how to calculate our FROIC ratio.
This is how we calculate it: FROIC means “Free Cash Flow Return on Invested Capital” Forward Free Cash Flow = [((Net Income + Depreciation) (1+ % Revenue Growth rate)) + (Capital Spending)] FROIC = (Forward Free Cash Flow)/(Long-Term Debt + Shareholders’ Equity) Net Income per diluted share = $4,694,000,000/625,000,000 = $7.51 Depreciation per diluted share = $241,000,000/625,000,000 = $0.39 Capital Spending per diluted share = $-813,000,000/625,000,000 = $-1.30 $7.51 + $0.39 + ($-1.30) = $6.60 Revenue Growth Rate TTM = 27.8% [(($7.51 + $0.39) (127.8%)) + ($-1.30) =$8.79 Long-Term Debt = $1,987,000,000 Shareholders Equity = $9,475,000,000 Diluted Shares Outstanding = 625,000,000 FROIC = (Forward Free Cash Flow)/ (Long-Term Debt + Shareholders’ Equity) $8.79/$18.34 = 48% FROIC = 48% Now, if one goes to my FRIEDRICH LEGEND again (on what is considered a good or bad result), you will notice that our result of 48% is an excellent result and tells us that Nvidia on Main Street generates $48 in forward free cash flow for every $100 it invests in total capital employed. On Main Street, Nvidia is doing great, while on Wall Street, it is becoming more attractive as investors panic out of it. Now, if one can build a portfolio containing similar excellent Main Street results and buy all at attractive Price to Bernhard Buffett Free Cash Flow ratio results, then your portfolio should be a star on both Main Street and Wall Street. Finding companies that have excellent results on Main Street and Wall Street (simultaneously) these days is, unfortunately, like trying to find a needle in a haystack. Going forward, our current oversold price as shown in both the data file and chart above give us a bargain price of $124.24 and we believe that Nvidia share price could easily hit that target price. Nvidia’s all-time high hit $289.36 on October 1, 2018, so if we can pick it up at $124.24, we will be picking it up after a -57.06% drop. If you enjoyed this article, please make sure to hit the follow button at the top of this article, as we plan to produce more articles using the same format in the future. Also, please feel free to comment below if you have any questions.
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.
Additional disclosure: This analysis is not an advice to buy or sell this or any stock; it is just pointing out an objective observation of unique patterns that developed from our research. Factual material is obtained from sources believed to be reliable, but the poster is not responsible for any errors or omissions, or for the results of actions taken based on information contained herein. Nothing herein should be construed as an offer to buy or sell securities or to give individual investment advice.