V YSOKÁ ŠKOLA EKONOMICKÁ V P RAZE Fakulta financí a účetnictví
katedra financí a oceňování podniku
BAKALÁŘSKÁ PRÁCE
2021 Cristian Slivca
V YSOKÁ ŠKOLA EKONOMICKÁ V P RAZE Fakulta financí a účetnictví
katedra financí a oceňování podniku Finance/Finance a účetnictví
Financial analysis of Nvidia Corp.
Autor bakalářské práce: Cristian Slivca
Vedoucí bakalářské práce: Ing. František Poborský, Ph.D.
Rok obhajoby: 2021
Čestné prohlášení
Prohlašuji, že jsem bakalářskou práci na téma „Financial analysis of Nvidia Corp.“ vypracoval samostatně a veškerou použitou literaturu a další prameny jsem řádně označil a uvedl v přiloženém seznamu.
V Praze dne 18/05/2021
...
Cristian Slivca
Abstrakt
Tato práce si především klade za cíl provést finanční analýzu významné americké technologické společnosti - Nvidia Corp. Analýza byla provedena pomocí standardních finančních metod a nástrojů, včetně vertikální a horizontální analýzy, analýzy srovnatelných podniků, a poměrových ukazatelů. Každý z finančních výkazů byl podrobně rozebrán, analyzován, a vysvětlen. Kromě toho tato práce vysvětluje některé specifické aspekty společnosti, které doplňují hlavní analýzu, a poskytuje užitečné informace, například strategická akvizice, výdaje na výzkum a vývoj, analýza zpětných odkupů akcí. V celé práci jsou předem definovány všechny metody, ukazatele. Každá část analýzy zahrnuje malý závěr, který hodnotí příslušnou stranu společnosti. Tato práce analyzuje a uvažuje společnost z pohledu kapitálového investora, a částečně jako dluhového investora. Na základě provedených analýz růstu, kvality zisku, analýzy peněžních toků, finanční situace a budoucích výhledů, lze konstatovat, že by společnost měla být považována za rozumnou dlouhodobou investici, která dosáhla nadprůměrný, a vynikající výsledek v minulosti, a který se by se neměl přerušovat i v budoucnu. Navzdory několika zjištěným nevýhodám, které jsou převáženy větším počtem příznivých aspektů, nalezených v rámci této analýzy – poměrovými ukazateli podniku, solventnosti, krátkodobou likviditou a obratem celkových aktiv, se na nakonec společnost opakovaně považuje za ambiciózní dlouhodobou investici.
Klíčové slova: technologická společnost, analýza, finanční výkaz, růst, akvizice, investice, kvalita zisků, peněžní tok, výhled, Nvidia, vertikální analýza, horizontální analýza, analýza srovnatelných podniků, poměrové ukazatele.
Abstract
This thesis aims to mainly perform the financial analysis of a prominent American tech company - Nvidia Corp. The analysis was done by the use of standard financial methods, and tools, including vertical, horizontal, peer group, and ratio analysis. Each of the three financial statements was analyzed in part and elaborated.
Besides that, the paper explains some specific aspects of the company that complement the main analysis and gives useful information. Throughout the paper, all the methods, and ratios are defined beforehand and applied thereafter. Each part of the analysis is accompanied by a conclusion. The paper regards this analysis, and the company from the perspective of an equity investor, and partly as a credit investor. As a result of reading this paper, based on the conclusions deduced from the analysis of growth, earnings quality, cash flow analysis, financial condition, and prospects, the company should be viewed as a reasonable long term investment, which has achieved higher than average, outstanding results in the past, and is expected to fare likewise in the future. Despite the several drawbacks, which are offset in outsize by the brighter aspects found within the analysis concerning the relative valuation, solvency condition, short term liquidity, and the use of assets, eventually, the Company is repeatedly found as a promising long term investment.
Keywords: tech company, analysis, financial statements, growth, acquisition, investment, quality of earnings, prospects, Nvidia, vertical analysis, horizontal analysis, peer group, financial ratios
Table of contents
Preface ... 7
1 Introduction ... 7
1.1 The reasons behind choosing Nvidia ... 8
1.2 About the Company ... 8
1.3 Core target markets ... 9
1.3.1 Gaming ... 9
1.3.2 Professional visualization ... 9
1.3.3 Data centers ... 9
1.3.4 Automotive ... 9
2 Objectives and methodology ... 10
2.1 Methodology ... 10
3 Financial analysis of the Company ... 11
3.1 Financial reporting standards ... 12
3.2 Revenue analysis ... 12
3.3 Revenue breakdown by market ... 14
3.4 Profitability analysis ... 14
3.5 Company’s R&D analysis ... 16
3.6 Balance sheet analysis ... 17
3.6.1 Asset structure ... 19
3.6.2 Activity ratios... 20
3.6.3 Long, and short term liquidity ... 22
3.6.4 Capital structure ... 24
3.6.5 Solvency analysis ... 26
3.6.6 Shares buyback analysis ... 27
3.7 Capital efficiency ... 28
3.8 Cash flow analysis ... 30
3.9 Peer group analysis ... 31
3.9.1 P/E, Forward P/E, P/B, P/S ... 33
3.9.2 ROA, ROE ... 34
3.9.3 Gross, and profit margin ... 35
3.9.4 Short term liquidity, and solvency ... 36
3.9.5 DuPont analysis ... 37
3.9.6 Past and expected growth... 38
3.9.7 Historical market performance ... 39
4 ARM acquisition ... 41
Conclusion ... 42
Seznam použité literatury a pramenů ... 43
List of graphs and tables ... 44
List of Annexes ... 45
7
Preface
I am a student at the Prague University of Economics and Business, studying at the Faculty of Finance and Accounting. Financial analysis has been a field of my interest within last five years. Considering my interest in investing, and the financial world in general, I find this knowledge to be very practical.
Due to my interest in this field, and the fact that I was always close to analyzing, and following growth companies, which are part of some of the emerging industries, I was certain about my decision of choosing Nvidia Corp for my bachelor thesis analysis.
This bachelor thesis is mainly written for those, who would ever consider Nvidia as an investment, or just for the matter of having a glimpse into the analysis of the company. I do hope that this thesis will be helpful, and practical for the one interested in viewing the company as an investment prospect.
8
1 Introduction
The financial analysis represents a thorough process of evaluating a company, including but not limited to its profitability, capital structure, capital efficiency, and liquidity, based on past financial statements by the use of diverse analytical methods and standardized techniques.
In general, financial analysis can be viewed from many standpoints, such as of investors, management, government, special-purpose institutions, etc. In this paper, I will mainly present, assess, comment, and make relevant recommendations as an investor.
In this thesis, I will be covering and performing the financial analysis of the Nvidia Corporation (hereinafter as “the Company”, “Company”, “Nvidia”).
1.1 The reasons behind choosing Nvidia
A lot of factors can be embedded in the decision-making process of choosing specifically Nvidia for this paper analysis. I will highlight some of them.
The Company's core business is in one of the most quickly growing industries, and its byproducts have an exponentially growing demand globally.
The Company has been a thriving star among its peers. During the last 5 years, it has shown phenomenal market performance, which was not achieved by many companies within the same sector.
During the last decade, it has gone through significant changes, from the financial and business point of view. Therefore, making its financial analysis even more interesting.
1.2 About the Company
Nvidia Corporation is an American multinational technology company incorporated in Delaware and based in Santa Clara, California. It has been founded on April 5, 1993, by Jensen Huang, Curtis Priem, and Chris Malachowsky. Currently, the Company is headquartered in Santa Clara, California, U.S.
The current CEO & President of the Company is Jensen Huang, and CFO is Colette M. Kress. As of January 2019, the Company had 13,227 employees.
9
It designs graphics processing units (GPUs) for the gaming and professional markets, as well as system on a chip unit (SoCs) for the mobile computing and automotive market. It serves customers worldwide.
It is a publicly listed company traded on NASDAQ and is the component of the NASDAQ-100 Index and S&P500 Index with the ISIN US67066G1040.
1.3 Core target markets
The Company has overtaken new directions in recent years. It is permanently discovering and investing in its R&D centers. It is worth to notice what are the business segments that the Company is committed to at the moment. The Company states them to be just four (according to SEC financial statements, IR, and FAQ page). These four main segments or target markets will be each described below.
1.3.1 Gaming
Anyone knowing at least something about the gaming industry knows that Nvidia is an iconic company that produces one of the most performant, powerful, high-end video cards used in computers and consoles.
1.3.2 Professional visualization
The technology used in their video cards is not limited just to solve gaming but supporting graphical design software, video creating applications or virtually anything which requires complex data rendering.
1.3.3 Data centers
With the booming cloud services industry, Nvidia has not been a laggard, and its developed accelerated computing platform is giving the modern data centers the power to accelerate deep learning, machine learning, and high-performance computing (HPC) workloads (source).
1.3.4 Automotive
The Company has engaged in the automotive industry, which has gone through big changes in the last decade. The Company is developing a computer platform called Nvidia Drive, aimed at providing autonomous car and driver assistance functionality powered by deep learning.
10
2 Objectives and methodology
The main goal of this thesis is to assess the financial condition, review, and comment on the changes that the Company has undergone in its profitability, growth, and capital structure, make recommendations regarding the weaker sides of the Company.
To achieve these objectives, I will be using various methods and tools of financial analysis that will be defined and described in the following sections and throughout this paper.
I will be comparing the Company, based on a set of selected financial ratios, to the closest peer group within the industry to assess its relative financial positioning and health in the market. In other words, I will be doing peer group analysis.
The analysis will mainly examine growth, profitability, capital structure, efficiency, activity, and liquidity
2.1 Methodology
The methods, which I will be mainly using for the analysis are vertical analysis, horizontal analysis, and financial ratio analysis of both book and market values.
The ratios used in this paper will include the most commonly used in financial analysis and complemented by some industry-specific ratios, if necessary.
Any analysis tool or ratio that requires any specific elaboration, used in the paper will be defined before its application. The analysis per se will follow the introduction to the topic and be complemented by a relevant interpretation.
11
3 Financial analysis of the Company
The main part of the financial analysis starts in this paragraph. Each of the following subparagraphs is concerned with a specific aspect of financial analysis.
The financial ratios based on book values will be valid as of the most recently reported financial report of FY2020.
The market-based ratios and indicators, which serve as the basis for the peer analysis will be stated in the respective paragraph(s). The reported period for each selected competitor might not coincide with Nvidia’s latest reported period.
Throughout the paper, I will be mostly using 10 year time period (or 10 fiscal years) for my analysis, to better view the historical development, and have a better perspective on the development, observe longer-term structural trends of the Company, without being falsely distracted by any short term signals.
However, I will provide a brief overview of the Company’s historical income statements in the table below.
Table 1 Nvidia historical brief income statements
Income statement (in million $)
Fiscal Year 2010 2012 2014 2016 2018 2020
Revenue 3 543 $ 4 280 $ 4 682 $ 6 910 $ 11 716 $ 16 675 $
Gross profit 1 409 $ 2 226 $ 2 599 $ 4 063 $ 7 171 $ 10 396 $
Total operating
expenses 1 153 $ 1 578 $ 1 840 $ 2 129 $ 3 367 $ 4 666 $
Operating income 256 $ 648 $ 759 $ 1 934 $ 3 804 $ 4 532 $
Interest income 19 $ 20 $ 28 $ 54 $ 136 $ 57 $
Interest expense - 3 $ - 3 $ - 46 $ - 58 $ - 58 $ - 184 $ Income before
income tax 271 $ 662 $ 755 $ 1 905 $ 3 896 $ 4 409 $
Net income 253 $ 562 $ 631 $ 1 666 $ 4 141 $ 4 332 $
Weighted average shares
Diluted 589 625 563 649 625 628
Net income per share
Diluted 0.43 $ 0.90 $ 1.12 $ 2.57 $ 6.63 $ 6.90 $
Dividend per
common share 0.00 $ 0.08 $ 0.34 $ 0.49 $ 0.61 $ 0.00 $
Source: Nvidia’s reported financial statements
12
3.1 Financial reporting standards
The Company’s financial reports are disclosed according to the US GAPP. The financial data was taken from the official SEC Edgar website that requires the Company to publish its financial data through 10-Q and 10-K forms. All the reports are in US Dollars. The selected financial data will be attached in the Annex section.
The Company’s FY2020 is ending in the Q4 of 2021, on 31January 2021.
3.2 Revenue analysis
The top-line analysis of the Company starts with the visualization of the historical revenues that the Company has had starting with the fiscal year (hereinafter as “FY”) of 2010 in the chart below.
Each data point in the graph represents the year-end reported financial revenue until the latest reported FY2020.
Graph 1 Nvidia historical reported revenue
Source: Nvidia’s reported financial statements
By exploring the last decade of the Company's top-line, we can see that from FY2010 until the latest FY2020, the Company has had its sales increased by 370 % or a CAGR of 16.75 %. It is worth noting that the biggest increase happened during the
3 543 $ 4 130 $
5 010 $ 6 910 $
9 714 $ 11 716 $
16 675 $
$ 2 000 $ 4 000 $ 6 000 $ 8 000 $ 10 000 $ 12 000 $ 14 000 $ 16 000 $ 18 000 $
2009 2011 2013 2015 2017 2019 2021
Revenue, in million $
13
last 5 years, which started in FY2015. During that period alone, the revenue has increased by 233 %.
This explosive rise can be explained by the crypto industry boom, which got its peak of attention exactly around 2017 when the Bitcoin price peaked during December. The reason for the Company being positively affected by that is that its main product (GPUs, i.e. gaming graphic cards) is one of the most used hardware for crypto mining, due to their efficiency and computing power.
One more important note to the revenue growth can be seen in the most recent FY, which was 53% YoY. The cause of that is the high demand from the Gaming and Data Center markets. Yearly the revenues in these segments have skyrocketed almost twofold.
Breaking down the year-over-year (hereinafter as “YoY”) revenues growth starting with FY2011, and ending FY2020, in the table below.
Table 2 Nvidia historical computed revenue growth rates (%)
Fiscal Year 11 12 13 14 15 16 17 18 19 20
Yearly revenue growth rate
(%)
13 7 -4 13 7 38 41 21 -7 53
Source: proprietary calculations based on reported financial statements
For the given period the Company had only 2 out of 10 yearly revenue decreases.
However, these declines can be negligible. To illustrate it, I have calculated the average of the positive and negative YoY growth rates, which are 24 %, and -5.2 % respectively. That is almost a ratio of 5 to 1 which shows that the Company’s revenue growth has been historically high. The average growth rate for the followed period is 18.2 %, which is an impressive number considering that the following period is an entire decade.
14
3.3 Revenue breakdown by market
The Company’s revenue breakdown by market, according to (Nvidia Corp., 2021) IR page, as of recent FY2020, is represented in the graph below.
Graph 2 Revenue breakdown by market
Source: reported financial statement
The market that brings the most revenue to the company is Gaming, which is represented by the Company’s video gaming cards, or GPUs. This is followed by data center products, which are gaining traction globally, with the growth of the SaaS, cloud services demand.
3.4 Profitability analysis
The sustainable and improving profitability is the strongest side of the Company, which can be viewed in the margins on several levels. To better observe the development, I will make the historical trend readily available to be visualized in a chart. I will be using gross margin, operating margin, and profit margin.
The margin ratios’ definitions, I have derived from (Martin Fridson & Fernando Alvarez 2011) book, which provides the basic formulas for calculating them, as followed:
Gross margin = (Sales – Cost of goods sold) ÷ Sales Operating margin = Operating income ÷ Sales,
or a more detailed formula
49.9%
38.0%
6.1%2.9%3.1%
Gaming Data center Visualizations Auto OEM & Other
15
Operating margin = (Net income + Income taxes + Interest Expense – Interest income – Other income) ÷ Sales
Net margin = Net income ÷ Sales
In our case, “Sales” are interchangeable with “Revenues”, “Net margin” with
“Profit margin”, and “Net income” with “Profit”, “Earnings after-tax”, respectively.
According to (Friedlob & Schleifer, 2002), other income can be defined as costs related to atypical events (i.e. non-recurring income).
The margins development trend for the whole decade can be easily observed. The gross margin increased from 40 % to 62 %, by 22 percentage points (hereinafter as
“p.p.”). The Company has made big changes and investments to achieve such profitability levels. The profit margins have increased from 7 % to 26 %, or an 18.8 p.p. change, which is almost a fourfold change in profitability. The average historical gross margin and profit margins are 56 % and 19 % respectively.
Graph 3 Nvidia historical margin levels
Source: proprietary calculations based on reported financial statements
Considering the high level of competitiveness in the semiconductor sector, these margins are indicative of a real moat the Company is possessing.
By looking at the chart it can be readily seen that the operating and profit margins are almost overlapping, which leads to a conclusion that whatever is in the income
40%
51% 55% 56% 60% 62% 62%
7%
15% 11% 12%
24%
31%
35%
26%
0%
10%
20%
30%
40%
50%
60%
70%
2009 2011 2013 2015 2017 2019 2021
Gross margin Operating margin Profit margin
16
statement between operating and the bottom line does not make for any significant numbers.
By looking again at the more comprehensive formula of operating profit, and making the unknown variable the net income, we can see what are the impacting items in the income statement. In my specific case with Nvidia, I concluded that interest expenses and tax expenses for the Company do not play a significant role in the bottom line formation (i.e. profit or earnings after-tax). I could argue that the Company is tax-efficient and is not highly indebted, a reason why the interest expenses are not a burden for the Company – this will be discussed in more detail in the upcoming chapters.
One more thing to notice here is the fact of the operating margin being lower than the profit margin in one of the followed fiscal years (FY2018). That happened because there was a tax benefit the Company has received from the US government due to the
“Tax Cuts and Jobs Act of 2017”.
3.5 Company’s R&D analysis
As I have already mentioned several times, Nvidia has made extensive investments and entered new markets. A quick analysis of its research and development (hereinafter as “R&D”) costs would be worthwhile and relevant. I have included the historical reported R&D costs in the graph below and the values that represent the R&D expenditure relative to revenue, also known as “R&D intensity”.
Graph 4 Nvidia historical R&D expense
Source: proprietary calculations based on reported financial statements
15%
20%
25%
30%
35%
500 $ 1 000 $ 1 500 $ 2 000 $ 2 500 $ 3 000 $ 3 500 $ 4 000 $ 4 500 $
2009 2011 2013 2015 2017 2019 2021
R&D costs, in million $
R&D - left axis R&D as % of revenue - right axis
17
As seen in the graph above the R&D expenditures are in a clear uptrend, which was of 0.8 billion $ for the FY2010 and 3.9 billion $, as of FY2020. That is almost a fourfold increase, which is impressive, although at the same time I assume it to be a requirement to remain competitive within the industry.
In terms of relativeness, the R&D costs fluctuated somewhat between 20 % and 30 % of revenue. It can be said that the Company, on average, had one-quarter of its revenues directed to the R&D cost, or more precisely 24.8 %.
As a matter of interest, I have calculated the cumulative R&D expenditures from FY2010 until FY2020 and came up to a value of 19.4 billion $. So this is how much the Company has cumulatively spent over 10 years on R&D. If the key that keeps Nvidia a leader in the industry is the R&D expenditure, then it can be understood how much spending in the R&D has to be allocated yearly roughly 1.9 billion $.
According to (Skillicorn, 2019) article, which analyzed the topic of R&D expenditures for the top 1000 companies worldwide for the year of 2018, It can be seen that Nvidia in terms of R&D intensity is way above the top 25 companies, which count for 8.86 % R&D expenditures to sales.
3.6 Balance sheet analysis
In this chapter, I will be analyzing in detail the Company’s balance sheet. It contains a breakdown of asset structure, financing structure or capital structure, activity ratios, and an interpretation of their historical development. The mentioned aspects of analysis will be accompanied by short-term liquidity, long-term liquidity, and solvency analysis.
18
In this chapter I will do provide as well a brief historical overview of the Company’s balance sheet in the tables below.
Table 3 Nvidia historical brief balance sheet statements - assets Assets (in million $)
Fiscal Year 2010 2012 2014 2016 2018 2020
C&CE 665 $ 733 $ 497 $ 1 766 $ 782 $ 847 $ Marketable securities 1 825 $ 2 995 $ 4 126 $ 5 032 $ 6 640 $ 10 714 $ Account receivables, net 349 $ 454 $ 474 $ 826 $ 1 424 $ 2 429 $ Inventories 346 $ 412 $ 483 $ 794 $ 1 575 $ 1 826 $ Other current assets 42 $ 181 $ 133 $ 118 $ 136 $ 239 $ P&PE, net 569 $ 576 $ 557 $ 521 $ 1 404 $ 2 149 $ Goodwill 370 $ 641 $ 618 $ 618 $ 618 $ 4 193 $ Intangible assets, net 289 $ 313 $ 222 $ 104 $ 45 $ 2 737 $ Other non-current assets 41 $ 107 $ 91 $ 62 $ 668 $ 3 657 $ Total assets 4 495 $ 6 412 $ 7 201 $ 9 841 $ 13 292 $ 28 791 $ Source: Nvidia’s reported financial statements
Table 4 Nvidia historical brief balance sheet statements - liabilities & equity
Liabilities and shareholders' equity (in million $)
Fiscal Year 2010 2012 2014 2016 2018 2020
Accounts payables 286 $ 356 $ 293 $ 485 $ 511 $ 1 201 $
Accrued and other current
liabilities 657 $ 620 $ 603 $ 507 $ 818 $ 1 725 $
Convertible short-term debt - - - 796 $ - 999 $
Long-term debt $ $ 1 384 $ 1 983 $ 1 988 $ 5 964 $
Other long-term liabilities $ 589 $ 489 $ 271 $ 633 $ 1 375 $
Other non-current liabilities 371 $ 19 $ 14 $ 37 $ $ 634 $
Total shareholders' equity 3 181 $ 4 828 $ 4 418 $ 5 762 $ 9 342 $ 16 893 $ Total liabilities and shareholders'
equity 4 495 $ 6 412 $ 7 201 $ 9 841 $ 13 292 $ 28 791 $
Source: Nvidia’s reported financial statements
Total assets grew over the 11 years by an impressive 541%, or a CAGR of 18.4
%, calculated using the following formula:
(reported assets FY2020 ÷ reported assets FY2010) ( (1 ÷ 11) – 1 ) × 100 (%)
19
3.6.1 Asset structure
By asset structure, I mean how much does the selected item from the balance sheet accounts for total assets in percent (so-called “vertical analysis”). As an example, for the FY2020, “Intangibles” made 14.6 % of total assets, which is calculated simply, as the selected item value from the balance sheet, divided by the total asset value of the respective FY and multiplied by 100(%).
The graph below illustrates the historical asset structure of the Company. The items altogether from each column, in each year, make up 100 %, of the value of the total asset.
Graph 5 Nvidia historical asset structure
Source: proprietary calculations based on Nvidia reported financial statements
I used the following rule for sorting the items - the top item is the least liquid, while the bottom item is the most liquid.
The “other current assets” value is calculated as the difference between total current assets and selected items of the current assets. The same rule applies to the calculation of the “other non-current assets” value.
55% 56% 58% 64% 64% 68% 69%
63% 56% 63%
40%
8% 6% 6%
5% 7% 6% 8%
7%
12%
6%
6%
9% 8% 10%
8% 8% 8% 10%
12% 12% 10%
9%
13% 10% 9% 8% 8% 6%
5% 9% 11% 10%
7%
8% 12% 10% 9% 9% 8% 6% 5% 5% 4%
15%
6% 6% 5% 4% 3% 2%
10%
3% 5% 7%
13%
2010 C&CE, Marketable securities2011 2012 2013 2014 2015 2016Inventory2017 2018 2019 2020
Other current assets P&PE, net
Goodwill Intangibles
Other non-current assets
20
The most liquid assets of the Company, which include “cash, cash equivalents”
(or abbreviated as “C&CE”), and “marketable securities” (e.g. US treasuries), on average, accounted for 60 % of total assets. In the most recent reported quarter, the share of these items has fallen to 44 %. The sudden decrease was offset by the growth of “intangibles” and “goodwill”. I might explain this as investments made by the Company in the form of acquiring smaller companies, technologies, etc.
Overall, I would say that the Company has been historically well positioned in terms of liquidity, even though during the latest quarter the indicator of short-term liquidity fell below the historical average.
From the perspective of non-current assets, it can be seen that the Company does rely on “tangible assets”, on average, as much as 9 % of total assets. I assume that such a number might be a reason for the fact that the Company outsources most of its physical production, thus not having the producing assets on their balance sheet.
Moreover, the intangibles and goodwill combined always were higher than tangibles, especially in the latest reported period.
This change in the balance sheet structure that hag “intangibles”, “goodwill”
altogether suddenly increase, is due to the acquisition of the company of new targets.
Moreover, it should be noticed that the increase of those items has dragged the most liquid assets down as well, obviously due to a need of financing the acquisitions.
Based on the analysis above, I can conclude that the Company has a strong asset structure (i.e. liquid), and does not rely heavily on tangible assets (i.e. invests in intangible assets and acquires companies that result in growth). This might, as well, be an indication and proof that the Company is a so-called “growth company” that does not rely on tangible assets. One more reason for that would be the fact that the company has a strategy of acquiring, to maintain the growth.
3.6.2 Activity ratios
In this part, I will be focusing on the historical activity ratios of the Company or how efficiently the Company uses its assets and to some extent assess its short-term liquidity.
Firstly, let me introduce the formulas that I will be using to calculate the activity ratios of inventory, account receivables, account payables, and total assets.
21 According to (Friedlob & Schleifer, 2002)
Inventory turnover ratio = cost of revenue ÷ average inventory Accounts receivables turnover ratio = sales ÷ accounts receivable
Assets turnover ratio = sales ÷ total assets According to (Brodersen & Pysh, 2014)
Accounts payable turnover ratio = cost of revenue ÷ accounts payable In the chart below, the right axis relates only to the total assets turnover ratio as it has the lowest values. I can visually see that the total assets turnover has been historically contained between 1 and 0.5. The best years for which the asset turnover was the highest was for the FY2017 and FY2018, thereafter suffering a drop.
Graph 6 Nvidia historical turnover ratios (times)
Source: proprietary calculations based on reported financial statements
The inventory turnover ratio has been slowly decreasing over the years from almost 6 to 3, with a slight bounce in the latest reported period. The Company, as of the most recent reported period, sold its inventory 4.5 times, compared to 5.7 times in 2011. The historical change, overall, is negative for the Company, but in my opinion bearable.
Let me now analyze the account payables and receivables altogether and calculate their activity ratios, in days. That being calculated as the number of days in a year (365), divided by the respective turnover ratio value.
- 0.2 0.4 0.6 0.8 1.0 1.2
- 2.0 4.0 6.0 8.0 10.0 12.0 14.0
2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
Accounts payable turnover (times) Accounts receivable turnover (times) Inventory turnover (times) Total assets turnover (times)
22
So here, historically I can observe a very curious pattern. The average number of days it takes for the Company to pay its suppliers and the average days it takes the customers to pay the Company, has historically converged. As of the latest reported period, receivables turnover was 58.2 days, and payables slightly longer 59.4 days. So the Company has almost a zero trading deficit in the short term. I would assess this neutrally because it has both negative, and positive consequences.
The Company, historically, has improved its average payables period, while the receivables, on average, did the exact opposite. The accounts receivable turnover period has almost doubled since FY2011. The increase is a worrying sign. However, I think that it should be a worrying sign if the increase of the average period started from values, for instance, bigger than 40 days, and reaching an average value of 80 days or even more, which is a bad sign already.
Graph 7 Nvidia historical turnover ratios (days)
Source: proprietary calculations based on reported financial statements
3.6.3 Long, and short term liquidity
This chapter will include the analysis of the Company’s short-term liquidity. For that purpose, I will be calculating the absolute value of net working capital, and the commonly used liquidity ratios of different levels.
The formulas for ratios, as defined in (Friedlob & Schleifer, 2002) are as followed:
Net working capital (“NWK”) = total current assets – total current liabilities Current ratio (“CR”) = total current assets ÷ total current liabilities
Quick ratio (“QR”) = total quick assets ÷ total current liabilities
20.0 30.0 40.0 50.0 60.0 70.0
2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
Accounts payable turnover (days) Accounts receivable turnover (days)
23
Cash ratio = (cash + short investments) ÷ total current liabilities Thereafter, I have considered the following rule:
Current assets = accounts receivable + inventory - accounts payable Quick assets = cash + short investments + receivables
By having defined the method of calculating the ratios and value for NWK, I have therefore introduced them on the graph below.
Graph 8 Nvidia historical short-term liquidity
Source: proprietary calculations based on reported financial statements
The first thing, which comes to the attention is the sharp drop in liquidity ratios and NWK in FY2015. Regarding the NWK (the values displayed on the right side of the axis), I can see that there is a long-term, stable, growing upward trend.
The NWK has increased roughly 6 times over the 11 years. That is related to the growth of the Company itself, which requires bigger working capital.
A very good sign, in my opinion, is that over the long followed period, the Company has never had any liquidity ratios below 2. Even the cash ratio, which is the strictest liquidity ratio, has always stood above that mark. That means high short-term liquidity, which has been growing over the following period, except for FY2015.
I can also observe that since FY2017 the difference among the three different liquidity ratios has widened. I could explain that, by saying that items that were not significant before FY2017 like “Prepaid expensive”, “Accrued, and other current liabilities” have been increasing. One more point, which relates to the chapter, where
$ 2 000 $ 4 000 $ 6 000 $ 8 000 $ 10 000 $ 12 000 $ 14 000 $
- 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 Net working capital Current ratio Quick ratio Cash ratio
24
I described the activity ratios, the “Inventory” items have been increasing, thus causing the difference between the ratios to widen.
Concerning FY2015, the sharp change in liquidity was due to the appearance in the current liabilities of “Convertible short-term debt”, which has immediately lowered the NWK and the liquidity ratios. Considering the fact, that the Company is a healthy revenue generator, it was able to extinguish that debt within 3 years period, and returning to the normalized path of its longer-term uptrend in short-term liquidity, which I assume will be sustained in the near future.
3.6.4 Capital structure
Total shareholders’ equity grew over the same 11 years period by 431% or a 18.2 % CAGR. The CAGR value was calculated as:
(reported equity FY2020 ÷ reported equity FY2010) (1 ÷ 11) – 1) × 100 (%) Now let me turn to the opposite side of the balance sheet, which shows the structure of the Company’s capital, or how are the assets are financed.
Graph 9 Nvidia historical financing structure
Source: proprietary calculations based on reported financial statements
I observed that Company’s non-current liabilities tend to grow. This is not a very good sign, since this is putting more pressure on equity’s book value. Meanwhile, the
71% 75% 75%
61% 61% 61% 59% 66% 70% 70%
59%
8% 9% 9%
25% 26%
7%
23%
23% 20% 19%
28%
21% 17% 15% 13% 12%
32%
18% 10% 10% 10% 14%
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 Equity Non-current liabilities Current liabilities
25
current liabilities had been steady and account for 15% on average, the non-current liabilities and equity, which are both long-term financing options, are tending to be equal. Historically they have never been equal, but as one might notice, there is an emerging trend, which would imply that both values will be equal in the near future.
In other words, the Company’s debt, which matures in one year or more, would equally finance the assets as equity.
It should be a worrying sign when a company’s long-term debt increases.
However, I think the increase for Nvidia specifically, might be due to the low-interest rates environment and Company’s high credit rating. Therefore it is a “cost-free”
financing option for the Company, comparing to equity raising, which in the current market conditions is much more costly, due to the higher equity market returns. In addition to that, an equity financing method would dilute the equity holder’s value and oppose the Company’s policy on shares buyback, which I will briefly analyze later.
In order to analyze whether the long-term debt component of non-current liabilities is increasing, I have looked up the absolute values for the non-current liabilities items as of the most recent FY2020 (all in million $)
5 964 - long-term debt
634 - long-term operating lease liabilities
1 375 - other long-term liabilities
Indeed, the long-term debt has increased from zero in FY2010 to almost 6 billion $ during the 11 years. This is the debt burden that the Company has accumulated so far over the years. I assume that in a scenario of higher interest rates, the Company might face problems due to this financing structure. Interestingly enough, the debt has increased the most in the most recent FY2020, from 1 991 million $ in FY2019 to 5 964 million $. For curiosity, I have tried to imply the interest rate paid on the Company’s debt in 2020, by taking the amount of interest paid in FY2020 and dividing it by the average values of long-term debt for FY2019 and FY2020. As a result, I have obtained 4.63%. It is a rough estimation of course since these are just book values. I assume that considering the market prices of the Company’s debt, the yield would be lower. For comparison, the 10 years US treasury average yield (the risk-free rates for the US dollar) in 2020 was 0.89 %. In my opinion, the “credit spread” is small enough, especially considering the increasing debt levels
26
of the Company. Although, it might be all the consequences of the low-interest rates environment as already mentioned, and perhaps the long-term credit rating of the Company, which is “A”, according to Fitch (Fitch Ratings Agency, 2021) , as of January 2021.
Moreover, if taking into account the interest income the company does obtain the yields of the debt based on book values would be even lower of 3.2 %, so the credit spread would be 2.31 %.
3.6.5 Solvency analysis
In this chapter, I will look at the Company’s solvency. Before going further, I will introduce the simple ratios which describe the Company’s solvency condition, as per (Brodersen & Pysh, 2014), which described the preferred method of the most well- known long-term investor Warren Buffet.
The “Debt” value here is used to describe the long-term debt, which the Company has in its balance sheet. ”Liabilities” represent the total “non-current liabilities” of the Company.
From the chart below, it can be seen that historically the liabilities financed the Company in the range of 20 % to 50 % of total assets. The Liabilities-to-Assets graph is more smoothed than the other and does not show any sharp increases in debt levels.
A more worrying sign for me are the other two ratios, which have increased in value. As I have already mentioned in my previous chapter, where I analyzed the financing structure, I stated that there is a trend of increasing debt levels, which can be reaffirmed below
Graph 10 Nvidia historical solvency ratios
Source: proprietary calculations based on reported financial statements 41%
34% 33%
63% 63% 65% 71%
50%
42% 42%
70%
0%
20%
40%
60%
80%
2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 Debt-to-Equity Liabilities-to-Assets Liabilities-to-Equity
27
The “Long term debt” represents roughly 50 % of “Equity”, up from 10 % in FY2010. In my opinion, this should be a worrying sign for the Company. However, I would rather attribute this to a long-term liquidity issue than a solvency issue. Despite this, I would remind you that the Company has an impressive revenue growth rate, strong margins, and sustainable cash flows. All of which favors the Company to finance itself at low-interest rates.
One more factor, which might be causing this increase, could be the preparation for a potential acquisition, which is financed through debt.
3.6.6 Shares buyback analysis
In this subchapter, I will briefly analyze Company’s buybacks. The item in the balance sheet that helps me to analyze is the “Treasury stock, at cost”.
Treasury stock, at cost, had an average YoY change of 928 million $, which means that the Company had on average spent 928 million $ for shares buyback.
However, this number does not tell much. In order to get a better understanding of the shares buyback effect, I have computed the average for the annual ratio between the amount spent on shares buyback and the net income. The average annual result is an impressive number of 69 %.
In my opinion, this number sends us a very optimistic and good sign for investors, since this method represents an alternative way for the Company by which it decreases the number of shares outstanding in the market (i.e. driving scarcity), thus increasing the Company’s value per share. As opposed to the method used by more non-growth, or conservative companies, which pays dividends, this method brings value back to investors, but at the same time giving the discretion to the Company of when to release the capital, retain. Moreover, shares buybacks are more tax-efficient than dividends, but this topic is not in the scope of this paper. And even more, the shares buybacks, which drive the value of the shares up, are convenient for the company in case it plans to raise capital through shares issuance, since the market price of the shares are higher, and the amount of shares required to issue is lower.
On the other hand, shares buyback might have an illusionary effect on EPS. With the Company having decreasing net income per share, it can manipulate the number by buying back the shares – reducing the shares outstanding and increasing the EPS
28
indicator. However, this is not the case for Nvidia, since the Company has had historically sustainable, and healthy earnings.
3.7 Capital efficiency
The two factors that drive a company’s value are growth and return on the capital it is employing. In this chapter I will be analyzing the Company’s capital efficiency on different levels, namely, return on (total) assets, return on equity, and return on invested capital (hereinafter referred to as following “ROA”, “ROE”, “ROIC”).
I will be calculating these ratios as following:
ROA = (net income) ÷ average (total) assets ROE = (net income) ÷ average shareholders’ equity
ROIC = NOPAT ÷ average invested capital
The average values used for calculating the ratios will be based on the current year and the preceding year (e.g. for FY2015 the denominators will use the FY2015 and FY2014 book values).
In my calculations, the value of NOPAT, or “net operating profit after tax”
equals to EBIT, or “Earnings before interest and taxes”, multiplied by (1 – “Effective tax rate”). The effective tax rate was calculated as Taxes divided by EBT for the respective FY. The value of EBIT is adjusted to non-recurring items (in my case - restructuring costs).
In the ROIC formula, the denominator (or “invested capital”) can be generally calculated by using 2 methods that generate the same result. I used the method, where I deducted "non-interest-bearing liabilities (or short-term liabilities) from total assets, and afterward, I deducted the value of excess cash equivalents which include both cash and short-term marketable securities. I assumed that the Company’s total cash & cash equivalents are non-operating, or in excess.
29
The ROIC is used for assessing companies as equity investors & creditors, since it shows what “operating income after tax”, in relative terms, is available to both equity holders and interest-bearing debt holders.
Graph 11 Nvidia historical capital efficiency ratios
Source: proprietary calculations based on reported financial statements
From FY2015 until FY2017 the Company has attained incredible ROIC. This was mainly due to the high demand for their core product in the crypto industry during the period. However, starting with FY2018, the ROIC has started to drop, returning to historical averages. Even with historically average values, the company has a high ROIC.
According to (Gurufocus, 2021) the Company had a WACC of 8.78 %, as of FY2020 that is far lower than the ROIC value. That means the Company is by far an economic value creator.
44%
34%
26%
38% 40%
98%
121%
101%
58%
47%
16% 13% 9% 14% 14%
33%
46% 49%
30%
12% 9% 6% 9% 8%
19%
29% 34%
18% 19%
2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
ROIC ROE ROA
30
3.8 Cash flow analysis
In this part, I will analyze the Company’s cash flow statement. I will illustrate the cash flows in the graph below. The values are in million $.
Graph 12 Nvidia historical cash flows
Source: proprietary calculations based on reported financial statements
The negative values of cash flows mean that the cash was used, and the positive cash flow values mean the cash was provided.
In the latest FY2020, the “Cash flow from investing activities” (“ICF”), has reached a big negative number of - 19.675 billion $. This data point was an outlier, and the chart scale was set in a way to keep the whole chart easier to view.
One of the most impressive aspects of the Company can be seen in the graph above and is related to the sustainable growth of the cash flow from operating activities (“OCF”). It is something worth highlighting since most companies simply are not able to attain such great results as Nvidia in this regard. The company has an ever-growing and sustainable average yearly growth rate of 31 % in its OCF over the followed period. In my opinion, this is one of the brightest sides of the company.
488 $ 676 $ 909 $ 824 $ 835 $ 1 175 $ 1 672 $
3 502 $3 743 $ 4 761 $
5 582 $
- 5 000 $ - 3 000 $ - 1 000 $ 1 000 $ 3 000 $ 5 000 $ 7 000 $
2010 2012 2014 2016 2018 2020
OCF ICF CFF
31
The ICF, and the “cash flow from financing activities” (“CFF”) were relatively stable, except for the periods between FY2017 and FY2020. During those periods, the ICF, and CFF were volatile mainly due to the conversion operations of the Company’s short-term liquid assets into cash and the opposite, or the maturing of those treasury bills. The fluctuations were caused, as well, by acquisition costs, and by the costs incurred for the tax payments related to the Restricted Stock Units – a type of remuneration by which the employees are entitled to a specific number of shares that are taxed at the source (the Company).
During the followed period, except for the latest FY2020, the Company had an average yearly free cash flow (OCF – ICF) of 1.686 billion $. That alone does not provide too much information. So, in order to have a better understanding of “earnings quality”, calculated the ratio of (OCF ÷ Net income), which resulted in yearly average of 144 %. In my opinion, that is a high quality of earnings.
By doing the same calculations but with (Free cash flow ÷ Net income) I have obtained an average yearly value of 33.2%. In my opinion that is a decent indicator, which states that one-third of the Company’s net income, remains after deducting all the cash used on necessary capital expenditures, acquisitions, etc.
3.9 Peer group analysis
One of the most important and practical components of financial analysis, which gives the best perspective on any company being analyzed is peer group analysis (“PGA”). In order to have a PGA of high quality, it is necessary to define and carefully pick the candidates that are the closest in terms of their products, market, operations to the company which is being analyzed. Moreover, it is important to choose the right basis of comparison, in order to illustrate the relative strengths, and or weaknesses.
In my thesis, I have decided to choose the peer group based on the following criteria, valid as of April 1, 2021
sector and industry – technology and semiconductors
location – US-based
market capitalization
I am fully aware that our Company may not be considered direct peer to the following companies, however, these criteria, in my opinion, are the most appropriate since it involves companies that are producing semiconductors or hardware and have
32
full exposure to the same market, even though at different supply-chain levels and customers’ needs.
For this purpose, I have used a stock screener feature that is being offered by a website “finviz.com” that offers financial-related services and helped me to filter the companies.
The result was a large list of companies which I ordered by their market capitalization and selected the first 10, their stock ticker, company name, and their market cap in billion (“B”) $
1. “NVDA”, Nvidia, 323 B$
2. “INTC”, Intel, 249 B$
3. “QCOM”, Qualcomm, 144 B$
4. “AVGO”, Broadcom Inc, 144 B$
5. “TXN”, Texas Instruments, 165 B$
6. “AMD”, Advanced Micro Devices, 94 B$
7. “MU”, Micron Technology, 94 B$
8. “ADI”, Analog Devices, 55 B$
9. “MCHP”, Microchip Technology, 40 B$
10. “XLNX”, Xilinx, 30 B$
From the final list of peers, which will serve for the analysis, I would like to note that most of them except for AMD, are not direct competitors, even though there are no better candidates, in my opinion, that would be suitable for the peer group analysis.
Nvidia is a very different Company from what it was even 5 years ago because it has undertaken new paths like AI, cloud computing, etc. And today, it is a very different company that hardly can be matched to any, since it is operating in different niches.
However, there are tangible points for both the Company and the selected peers, a reason why the peer group analysis remains relevant.
For the same reason, I have decided to make the comparison based only on the current period, not historical. It is of more value to understand how the Company has changed itself historically, but the comparison to its peers as of only today. Where necessary,
I will be using average historical values for specific peer(s) with more skewed data, or just excluding the outlier(s).
33
3.9.1 P/E, Forward P/E, P/B, P/S
Let me start with the most known relative valuation ratios that will be illustrated in the following graph.
Graph 13 PGA - relative value ratios
Source: data fetched from finviz.com
All the peers’ market price per share (P), are valid as of November 23, 2020.
The “forward P/E” calculates the P/E ratio, where the earnings per share are expected rather than historical. In some way, it factors in the expected growth in the earnings of the company and their respective P/E ratio, thus giving a better view on relative valuation.
By looking at the ratios presented above, it can be seen that Nvidia is valued by the market relatively higher than the average peer. One exception is AMD, which trades cheaper on a P/E basis and more expensive on a P/B basis. Considering the fact that AMD is the closest peer to our Company, if it was to be chosen between the two as investment, I would choose NVDA. For these two companies, it can be concluded that their valuations are relatively high. The market value of Nvidia is high due to either market’s future earnings expectations, or just due to their high-quality business and strong financial condition.
85.9 119.0 54.4 29.8 45.9 31.8 72.5 56.1 27.0 9.0
22.5 12.0 11.0 10.6 9.3 7.0 6.8 6.4 3.4 2.4
21.2 26.1 13.3 17.3 4.3 26.7 6.6 6.2 1.8 2.6
35.85 13.55 16.01 26.15 16.38 9.91 31.09 23.21 20.71 37.41
N V D A * I N T C A V G O T X N Q C O M M U A M D A D I M C H P X L N X P/E P/S P/B Fwd P/E
34
3.9.2 ROA, ROE
For the following graph, I have excluded QCOM and TXN, because their ROE and ROA values were outliers in the data set.
Graph 14 PGA - capital efficiency
Source: data fetched from finviz.com
The companies with the highest values of both ROA and ROE are AMD, NVDA, INTC, and XLNX. The leading company is AMD, reaching the highest ROA and ROE values, that beat the peers by far in both return on total assets, and equity
The company, however, is doing well within the peer group considering the average ROA of 11%, and average ROE of 20.6%.
Based on the data presented in the graph above I can conclude that the Company, is relatively efficient at generating profits from total assets and equity value, even though it is being beaten by its closest peer by a considerable extent.
28%
17%
14%
12%
5% 7% 6%
2%
43%
29%
27% 26%
15%
12%
8% 6%
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
AMD NVDA INTC XLNX AVGO ADI MU MCHP
ROA ROE
35
3.9.3 Gross, and profit margin
In terms of profitability, most of the companies have high gross margins, however, if we look at the profit margins, the picture gets different.
Graph 15 PGA - profitability margins
Source: data fetched from finviz.com
Nvidia does not have the highest gross margin among its peers, although higher than the average value. The leading companies in terms of gross margin are XLNX, ADI, TXN, followed by NVDA with a difference of roughly 7 p.p. to the leader.
When looking at the profit margin, the leading companies are TXN, and INTC, followed by NVDA with a difference of 10 p.p. to the leader.
In both cases, NVDA has a higher than average margin, proving again that the company is doing well with regards to profitability on different levels.
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
AMD
NVDA*
AVGO
MCHP
XLNX ADI
QCOM TXN
MU
INTC
Avg. GM Gross M Avg. PM Profit M
