How many people really understand what they’re buying, especially when it comes to highly specialized hardware companies? Most NVidia investors seem to be relying on a vague idea of how the company should thrive “in the future”, as their GPUs are ostensibly used for Artificial Intelligence, Cloud, holograms, etc. Having been shocked by how this company is represented in the media, I decided to lay out how this business works, doing my part to fight for reality. With what’s been going on in markets, I don’t like my chances but here goes:
Let’s start with… How does NVDA make money?
NVDA is in the business of semiconductor design. As a simplified image in your head, you can imagine this as designing very detailed and elaborate posters. Their engineers create circuit patterns for printing onto semiconductor wafers. NVDA then pays a semiconductor foundry (the printer – generally TSMC) to create chips with those patterns on them.
Simply put, NVDA’s profits represent the difference between the price at which they can sell those chips, less the cost of printing, and less the cost of paying their engineers to design them.
Notably, after the foundry prints the chips, NVDA also has to pay (I say pay, but really it is more like “sell at a discount to”) their “add-in board” (AIB) partners to stick the chips onto printed circuit boards (what you might imagine as green things with a bunch of capacitors on them). That leads to the final form in which buyers experience the GPU. What is a GPU?
NVDA designs chips called GPUs (Graphical Processing Units). Initially, GPUs were used for the rapid processing and creation of images, but their use cases have expanded over time. You may be familiar with the CPU (Central Processing Unit). CPUs sit at the core of a computer system, doing most of the calculation, taking orders from the operating system (e.g. Windows, Linux), etc. AMD and Intel make CPUs. GPUs assist the CPU with certain tasks. You can think of the CPU as having a few giant very powerful engines. The GPU has a lot of small much less powerful engines. Sometimes you have to do a lot of really simple tasks that don’t require powerful engines to complete. Here, the act of engaging the powerful engines is a waste of time, as you end up spending most of your time revving them up and revving them down. In that scenario, it helps the CPU to hand that task over to the GPU in order to “accelerate” the completion of the task. The GPU only revs up a small engine for each task, and is able to rev up all the small engines simultaneously to knock out a large number of these simple tasks at the same time. Remember the GPU has lots of engines. The GPU also has an edge in interfacing a lot with memory but let’s not get too technical. Who uses NVDA’s GPUs?
There are two main broad end markets for NVDA’s GPUs – Gaming and Professional. Let’s dig into each one: The Gaming Market:
A Bit of Ancient History (Skip if impatient
GPUs were first heavily used for gaming in arcades. They then made their way to consoles, and finally PCs. NVDA started out in the PC phase of GPU gaming usage. They weren’t the first company in the space, but they made several good moves that ultimately led to a very strong market position. Firstly, they focused on selling into OEMs – guys like the equivalent of today’s DELL/HP/Lenovo – , which allowed a small company to get access to a big market without having to create a lot of relationships. Secondly, they focused on the design aspect of the GPU, and relied on their Asian supply chain to print the chip, to package the chip and to install in on a printed circuit board – the Asian supply chain ended up being the best in semis. But the insight that really let NVDA dominate was noticing that some GPU manufacturers were focusing on keeping hardware-accelerated Transform and Lighting as a Professional GPU feature. As a start-up, with no professional GPU business to disrupt, NVidia decided their best ticket into the big leagues was blowing up the market by including this professional grade feature into their gaming product. It worked – and this was a real masterstroke – the visual and performance improvements were extraordinary. 3DFX, the initial leader in PC gaming GPUs, was vanquished, and importantly it happened when funding markets shut down with the tech bubble bursting and after 3DFX made some large ill-advised acquisitions. Consequently 3DFX, went from hero to zero, and NVDA bought them for a pittance out of bankruptcy, acquiring the best IP portfolio in the industry. Some more Modern History
This is what NVDA’s pure gaming card revenue looks like over time – NVDA only really broke these out in 2005 (note by pure, this means ex-Tegra revenues):
So what is the history here? Well, back in the late 90s when GPUs were first invented, they were required
to play any 3D game. As discussed in the early history above, NVDA landed a hit product to start with early and got a strong burst of growth: revenues of 160M in 1998 went to 1900M in 2002. But then NVDA ran into strong competition from ATI (later purchased and currently owned by AMD). While NVDA’s sales struggled to stay flat from 2002 to 2004, ATI’s doubled from 1Bn to 2Bn. NVDA’s next major win came in 2006, with the 8000 series. ATI was late with a competing product, and NVDA’s sales skyrocketed – as can be seen in the graph above. With ATI being acquired by AMD they were unfocused for some time, and NVDA was able to keep their lead for an extended period. Sales slowed in 2008/2009 but that was due to the GFC – people don’t buy expensive GPU hardware in recessions.
And then we got to 2010 and the tide changed. Growth in desktop PCs ended. Here is a chart from Statista:
This resulted in two negative secular trends for Nvidia. Firstly, with the decline in popularity of desktop PCs, growth in gaming GPUs faded as well (below is a chart from Jon Peddie). Note that NVDA sells discrete GPUs, aka DT (Desktop) Discrete. Integrated GPUs are mainly made by Intel (these sit on the motherboard or with the CPU).
You can see from the chart above that discrete desktop GPU sales are fading faster than integrated GPU sales. This is the other secular trend hurting NVDA’s gaming business. Integrated GPUs are getting better and better, taking over a wider range of tasks that were previously the domain of the discrete GPU. Surprisingly, the most popular eSports game of recent times – Fortnite – only requires Intel HD 4000 graphics – an Integrated GPU from 2012!
So at this point you might go back to NVDA’s gaming sales, and ask the question: What happened in 2015? How is NVDA overcoming these secular trends?
The answer consists of a few parts.Firstly, AMD dropped the ball in 2015. As you can see in this chart, sourced from 3DCenter, AMD market share was halved in 2015, due to a particularly poor product line-up:
Following this, NVDA came out with Pascal in 2016 – a very powerful offering in the mid to high end part of the GPU market. At the same time, AMD was focusing on rebuilding and had no compelling mid or high end offerings. AMD mainly focused on maintaining scale in the very low end. Following that came 2017 and 2018: AMD’s offering was still very poor at the time, but cryptomining drove demand for GPUs to new levels, and AMD’s GPUs were more compelling from a price-performance standpoint for crypto mining initially, perversely leading to AMD gaining share. NVDA quickly remedied that by improving their drivers to better mine crypto, regaining their relative positioning, and profiting in a big way from the crypto boom. Supply that was calibrated to meet gaming demand collided with cryptomining demand and Average Selling Prices of GPUs shot through the roof. Cryptominers bought top of the line GPUs aggressively.
A good way to see changes in crypto demand for GPUs is the mining profitability of Ethereum:
This leads us to where we are today. 2019 saw gaming revenues drop for NVDA. Where are they likely to head?
The secular trends of falling desktop sales along with falling discrete GPU sales have reasserted themselves, as per the Jon Peddie research above. Cryptomining profitability has collapsed.
AMD has come out with a new architecture, NAVI, and the 5700XT – the first Iteration, competes effectively with NVDA in the mid-high end space on a price/performance basis. This is the first real competition from AMD since 2014.
NVDA can see all these trends, and they tried to respond. Firstly, with volumes clearly declining, and likely with a glut of second-hand GPUs that can make their way to gamers over time from the crypto space, NVDA decided to pursue a price over volume strategy. They released their most expensive set of GPUs by far in the latest Turing series. They added a new feature, Ray Tracing, by leveraging the Tensor Cores they had created for Professional uses, hoping to use that as justification for higher prices (more on this in the section on Professional GPUs). Unfortunately for NVDA, gamers have responded quite poorly to Ray Tracing – it caused performance issues, had poor support, poor adoption, and the visual improvements in most cases are not particularly noticeable or relevant.
The last recession led to gaming revenues falling 30%, despite NVDA being in a very strong position at the time vis-à-vis AMD – this time around their position is quickly slipping and it appears that the recession is going to be bigger. Additionally, the shift away from discrete GPUs in gaming continues.
To make matters worse for NVDA, AMD won the slots in both the New Xbox and the New PlayStation, coming out later this year. The performance of just the AMD GPU in those consoles looks to be competitive with NVidia products that currently retail for more than the entire console is likely to cost. Consider that usually you have to pair that NVidia GPU with a bunch of other expensive hardware. The pricing and margin impact of this console cycle on NVDA is likely to be very substantially negative.
It would be prudent to assume a greater than 30% fall in gaming revenues from the very elevated 2019 levels, with likely secular decline to follow. The Professional Market:
A Bit of Ancient History (again, skip if impatient)
As it turns out, graphical accelerators were first used in the Professional market, long before they were employed for Gaming purposes. The big leader in the space was a company called Silicon Graphics, who sold workstations with custom silicon optimised for graphical processing. Their sales were only $25Mn in 1985, but by 1997 they were doing 3.6Bn in revenue – truly exponential growth. Unfortunately for them, from that point on, discrete GPUs took over, and their highly engineered, customised workstations looked exorbitantly expensive in comparison. Sales sank to 500mn by 2006 and, with no profits in sight, they ended up filing for bankruptcy in 2009. Competition is harsh in the semiconductor industry.
Initially, the Professional market centred on visualisation and design, but it has changed over time. There were a lot of players and lot of nuance, but I am going to focus on more recent times, as they are more relevant to NVidia. Some More Modern History
NVDA’s Professional business started after its gaming business, but we don’t have revenue disclosures that show exactly when it became relevant. This is what we do have – going back to 2005:
In the beginning, Professional revenues were focused on the 3D visualisation end of the spectrum, with initial sales going into workstations that were edging out the customised builds made by Silicon Graphics. Fairly quickly, however, GPUs added more and more functionality and started to turn into general parallel data processors rather than being solely optimised towards graphical processing.
As this change took place, people in scientific computing noticed, and started using GPUs to accelerate scientific workloads that involve very parallel computation, such as matrix manipulation. This started at the workstation level, but by 2007 NVDA decided to make a new line-up of Tesla series cards specifically suited to scientific computing. The professional segment now have several points of focus:
- GPUs used in workstations for things such as CAD graphical processing (Quadro Line)
- GPUs used in workstations for computational workloads such as running engineering simulations (Quadro Line)
- GPUs used in workstations for machine learning applications (Quadro line.. but can use gaming cards as well for this)
- GPUs used by enterprise customers for high performance computing (such as modelling oil wells) (Tesla Line)
- GPUs used by enterprise customers for machine learning projects (Tesla Line)
- GPUs used by hyperscalers (mostly for machine learning projects) (Tesla Line)
In more recent times, given the expansion of the Tesla line, NVDA has broken up reporting into Professional Visualisation (Quadro Line) and Datacenter (Tesla Line). Here are the revenue splits since that reporting started:
It is worth stopping here and thinking about the huge increase in sales delivered by the Tesla line. The reason for this huge boom is the sudden increase in interest in numerical techniques for machine learning. Let’s go on a brief detour here to understand what machine learning is, because a lot of people want to hype it but not many want to tell you what it actually is. I have the misfortune of being very familiar with the industry, which prevented me from buying into the hype. Oops – sometimes it really sucks being educated. What is Machine Learning?
At a very high level, machine learning is all about trying to get some sort of insight out of data. Most of the core techniques used in machine learning were developed a long time ago, in the 1950s and 1960s. The most common machine learning technique, which most people have heard of and may be vaguely familiar with, is called regression analysis. Regression analysis involves fitting a line through a bunch of datapoints. The most common type of regression analysis is called “Ordinary Least Squares” OLS regression, and that type of regression has a “closed form” solution, which means that there is a very simple calculation you can do to fit an OLS regression line to data.
As it happens, fitting a line through points is not only easy to do, it also tends to be the main machine learning technique that people want to use, because it is very intuitive. You can make good sense of what the data is telling you and can understand the machine learning model you are using. Obviously, regression analysis doesn’t require a GPU!
However, there is another consideration in machine learning: if you want to use a regression model, you still need a human to select the data that you want to fit the line through. Also, sometimes the relationship doesn’t look like a line, but rather it might look like a curve. In this case, you need a human to “transform” the data before you fit a line through it in order to make the relationship linear.
So people had another idea here: what if instead of getting a person to select the right data to analyse, and the right model to apply, you could just get a computer to do that? Of course the problem with that is that computers are really stupid. They have no preconceived notion of what data to use or what relationship would make sense, so what they do is TRY EVERYTHING! And everything involves trying a hell of a lot of stuff. And trying a hell of a lot of stuff, most of which is useless garbage, involves a huge amount of computation. People tried this for a while through to the 1980s, decided it was useless, and dropped it… until recently.
What changed? Well we have more data now, and we have a lot more computing power, so we figured lets have another go at it. As it happens, the premier technique for trying a hell of a lot of stuff (99.999% of which is garbage you throw away) is called “Deep Learning”. Deep learning is SUPER computationally intensive, and that computation happens to involve a lot of matrix multiplication. And guess what just happens to have been doing a lot of matrix multiplication? GPUs!
Here is a chart that, for obvious reasons, lines up extremely well with the boom in Tesla GPU sales:
Now we need to realise a few things here. Deep Learning is not some magic silver bullet. There are specific applications where it has proven very useful – primarily areas that have a very large number of very weak relationships between bits of data that sum up into strong relationships. An example of ones of those is Google Translate. On the other hand, in most analytical tasks, it is most useful to have an intuitive understanding of the data and to fit a simple and sensible model to it that is explainable. Deep learning models are not explainable in an intuitive manner. This is not only because they are complicated, but also because their scattershot technique of trying everything leaves a huge amount of garbage inside the model that cancels itself out when calculating the answer, but it is hard to see how it cancels itself out when stepping through it.
Given the quantum of hype on Deep learning and the space in general, many companies are using “Deep Learning”, “Machine Learning” and “AI” as marketing. Not many companies are actually generating significant amounts of tangible value from Deep Learning. Back to the Competitive Picture For the Tesla Segment
So NVDA happened to be in the right place at the right time to benefit from the Deep Learning hype. They happened to have a product ready to go and were able to charge a pretty penny for their product. But what happens as we proceed from here?
Firstly, it looks like the hype from Deep Learning has crested, which is not great from a future demand perspective. Not only that, but we really went from people having no GPUs, to people having GPUs. The next phase is people upgrading their old GPUs. It is much harder to sell an upgrade than to make the first sale.
Not only that, but GPUs are not the ideal manifestation of silicon for Deep Learning. NVDA themselves effectively admitted that with their latest iteration in the Datacentre, called Ampere. High Performance Computing, which was the initial use case for Tesla GPUs, was historically all about double precision floating point calculations (FP64). High precision calculations are required for simulations in aerospace/oil & gas/automotive.
NVDA basically sacrificed HPC and shifted further towards Deep Learning with Ampere, announced last Thursday. The FP64 performance of the A100 (the latest Ampere chip) increased a fairly pedestrian 24% from the V100, increasing from 7.8 to 9.7 TF. Not a surprise that NVDA lost El Capitan to AMD, given this shift away from a focus on HPC. Instead, NVDA jacked up their Tensor Cores (i.e. not the GPU cores) and focused very heavily on FP16 computation (a lot less precise than FP64). As it turns out, FP16 is precise enough for Deep Learning, and NVDA recognises that. The future industry standard is likely to be BFloat 16 – the format pioneered by Google, who lead in Deep Learning. Ampere now does 312 TF of BF16, which compares to the 420 TF of Google’s TPU V3 – Google’s Machine Learning specific processor. Not quite up to the 2018 board from Google, but getting better – if they cut out all of the Cuda cores and GPU functionality maybe they could get up to Google’s spec.
And indeed this is the problem for NVDA: when you make a GPU it has a large number of different use cases, and you provide a single product that meets all of these different use cases. That is a very hard thing to do, and explains why it has been difficult for competitors to muscle into the GPU space. On the other hand, when you are making a device that does one thing, such as deep learning, it is a much simpler thing to do. Google managed to do it with no GPU experience and is still ahead of NVDA. It is likely that Intel will be able to enter this space successfully, as they have widely signalled with the Xe.
There is of course the other large negative driver for Deep Learning, and that is the recession we are now in. Demand for GPU instances on Amazon has collapsed across the board, as evidenced by the fall in pricing. The below graph shows one example: this data is for renting out a single Tesla V100 GPU on AWS, which isthe typical thing to do in an early exploratory phase for a Deep Learning model:
With Deep Learning not delivering near-term tangible results, it is the first thing being cut. On their most recent conference call, IBM noted weakness in their cognitive division (AI), and noted weaker sales of their power servers, which is the line that houses Enterprise GPU servers at IBM. Facebook cancelled their AI residencies for this year, and Google pushed theirs out. Even if NVDA can put in a good quarter due to their new product rollout (Ampere), the future is rapidly becoming a very stormy place. For the Quadro segment
The Quadro segment has been a cash cow for a long time, generating dependable sales and solid margins. AMD just decided to rock the boat a bit. Sensing NVDA’s focus on Deep Learning, AMD seems to be focusing on HPC – the Radeon VII announced recently with a price point of $1899 takes aim at NVDAs most expensive Quadro, the GV100, priced at $8999. It does 6.5 TFLOPS of FP64 Double precision, whereas the GV100 does 7.4 – talk about shaking up a quiet segment. Pulling things together
Let’s go back to what NVidia fundamentally does – paying their engineers to design chips, getting TSMC to print those chips, and getting board partners in Taiwan to turn them into the final product.
We have seen how a confluence of several pieces of extremely good fortune lined up to increase NVidia’s sales and profits tremendously: first on the Gaming side, weak competition from AMD until 2014, coupled with a great product in form of Pascal in 2016, followed by a huge crypto driven boom in 2017 and 2018, and on the Professional side, a sudden and unexpected increase in interest in Deep Learning driving Tesla demand from 2017-2019 sky high.
It is worth noting what these transient factors have done to margins. When unexpected good things happen to a chip company, sales go up a lot, but there are no costs associated with those sales. Strong demand means that you can sell each chip for a higher price, but no additional design work is required, and you still pay the printer, TSMC, the same amount of money. Consequently NVDA’s margins have gone up substantially: well above their 11.9% long term average to hit a peak of 33.2%, and more recently 26.5%:
The question is, what would be a sensible margin going forward? Obviously 33% operating margin would attract a wall of competition and get competed away, which is why they can only be temporary. However, NVidia has shifted to having a greater proportion of its sales coming from non-OEM, and has a greater proportion of its sales coming from Professional rather than gaming. As such, maybe one can be generous and say NVDA can earn an 18% average operating margin over the next cycle. We can sense check these margins, using Intel. Intel has a long term average EBIT margin of about 25%. Intel happens to actually print the chips as well, so they collect a bigger fraction of the final product that they sell. NVDA, since it only does the design aspect, can’t earn a higher EBIT margin than Intel on average over the long term.
Tesla sales have likely gone too far and will moderate from here – perhaps down to a still more than respectable $2bn per year. Gaming resumes the long-term slide in discrete GPUs, which will likely be replaced by integrated GPUs to a greater and greater extent over time. But let’s be generous and say it maintains $3.5 Bn Per year for the add in board, and let’s assume we keep getting $750mn odd of Nintendo Switch revenues(despite that product being past peak of cycle, with Nintendo themselves forecasting a sales decline). Let’s assume AMD struggles to make progress in Quadro, despite undercutting NVDA on price by 75%, with continued revenues at $1200. Add on the other 1.2Bn of Automotive, OEM and IP (I am not even counting the fact that car sales have collapsed and Automotive is likely to be down big), and we would end up with revenues of $8.65 Bn, at an average operating margin of 20% through the cycle that would have $1.75Bn of operating earnings power, and if I say that the recent Mellanox acquisition manages to earn enough to pay for all the interest on NVDAs debt, and I assume a tax rate of 15% we would have around $1.5Bn in Net income.
This company currently has a market capitalisation of $209 Bn. It blows my mind that it trades on 139x what I consider to be fairly generous earnings – earnings that NVidia never even got close to seeing before the confluence of good luck hit them. But what really stuns me is the fact that investors are actually willing to extrapolate this chain of unlikely and positive events into the future.
Shockingly, Intel has a market cap of 245Bn, only 40Bn more than NVDA, but Intel’s sales and profits are 7x higher. And while Intel is facing competition from AMD, it is much more likely to hold onto those sales and profits than NVDA is. These are absolutely stunning valuation disparities.
If I didn’t see NVDA’s price, and I started from first principles and tried to calculate a prudent price for the company I would have estimated a$1.5Bn normalised profit, maybe on a 20x multiple giving them the benefit of the doubt despite heading into a huge recession, and considering the fact that there is not much debt and the company is very well run. That would give you a market cap of $30Bn, and a share price of $49. And it is currently $339. Wow. Obviously I’m short here!
I was just alerted that my post from 7 years ago had a broken link. https://rbcpa.com//wp-content/uploads/2016/12/Notes_To_Margin_of_Safety.pdf
I posted my entire notes, quite long, and I think the link would provide an easier view. Notes To The Book “Margin Of Safety” Author: Seth Klarman 1991 Prepared by: Ronald R. Redfield, CPA, PFS
According to www.wikipedia.com
"Margin of Safety – Risk-Averse Value Investing Strategies for the Thoughtful Investor" is a name of a book written by Seth A. Klarman, a successful value investor and President of the Baupost Group, an investment firm in Boston. This book is no longer published and sometimes can be found on eBay for more than $1000 (some consider it a collectible item). These notes are hardly all encompassing. These are notes I would find helpful for me, as a money manager. I do not mention Klarman’s important premise of looking at investments as “fractional ownerships.” I don’t mention things like that in these notes, as I am already tuned into those concepts, and do not need a reminder. Hence a reader of these notes, should read the book on their own, and get their own information from it. I found this book at several libraries. One awsome library I went to was the New York Public Library for Science, Business and Industry. http://www.nypl.org/research/sibl/index.html
Throughout this paper you will see items in “quote marks.” The quotes exclusively represent direct quotes of Seth Klarman, from the book. As I read this book, and through completion, I felt fortunate that I have been following most of his philosophies for many years. I am not comparing myself to Klarman, not at all. How could I ever compare myself to the greats of Klarman, Buffett, Whitman etal?
What I did experience via this reading was a confirmation of my style and discipline. This book really put together and confirmed to me, so many of the philosophies and methods which I have been using for many years. These notes are a means for me to look back, and feel my roots every so often. At times in these notes, I have added sections which I have found appropriate in my workings. Introduction
“This book alone will not turn anyone into a successful value investor.
Value investing requires a great deal of hard work, unusually strict discipline
and a long-term investment horizon.”
“This book is a blueprint that, if carefully followed, offers a good possibility
of investment successes with limited risk.”
Understand why things work. Memorizing formulas give the appearance of
competence. Klarman describes the book as one about “thinking about
I interpret much of the introduction of the book, as to not actively buy and
sell investments, but to demonstrate an “ability to make long-term
investment decisions based on business fundamentals.” As I completed the
book, I realize that Klarman does not embrace the long term approach in the
same fashion I do. Yet, the key is to always determine if value still exists.
Value is factored in with tax costs and other costs.
Fight the crowd. I think what Klarman is saying is that it is warm and fuzzy
in the middle of crowds. You do not need to be warm and fuzzy with
Stay unemotional in business and investing!
Study the behavior of investors and speculators. Their actions “often
inadvertently result in the creation of opportunities for value investors.”
“The most beneficial time to be a value investor is when the market is
falling.” “Value investors invest with a margin of safety that protects from
large losses in declining markets.” I have only begun the book, but am
curious as to how any value investor could have stayed out of the way of
1973 –1974 bear market. Some would argue that Buffett exited the business
during this period. Yet, it is my understanding, and I could be wrong, that
Berkshire shares took a big drop in that period. Also, Buffett referred his
investors who were leaving the partnership to Sequoia Fund. Sequoia Fund
is a long term value investment mutual fund. They also had a horrendous
time during the 1973 –1974 massacre.
“Mark Twain said that there are two times in a man’s life when he should
not speculate: when he can’t afford it and when he can.”
“Investors in a stock expect to profit in at least one of three possible ways:
a. From free cash flow generated by the underlying business, which
will eventually be reflected in a higher share price or distributed as
b. From an increase in the multiple that investors are willing to pay
for the underlying business as reflected in a higher share price.
c. Or by narrowing of the gap between share price and underlying
“Speculators are obsessed with predicting – guessing the direction of
“Value investors pay attention to financial reality in making their investment
He discusses what could happen if investors lost favor with liquid treasuries,
and if indeed they became illiquid. All investors could run for the door at
“Investing is serious business, not entertainment.”
Understand the difference between an investment and a collectible. An
investment is one, which will eventually be able to produce cash flow.
“Successful investors tend to be unemotional, allowing the greed of others to
play into their hands. By having confidence in their own analysis and
judgment, they respond to market forces not with blind emotion but with
He discusses Mr. Market. He mentions when a price of a stock declines
with no apparent reason, most investors become concerned. They worry that
there is information out there, which they are not privy to. Heck, I am going
through this now with a position that is thinly traded, and sometimes I think
I am the only purchaser out there. He describes how the investor begins to
second-guess him or herself. He mentions it is easy to panic and just sell.
He goes onto to write, “Yet, if the security were truly a bargain when it was
purchased, the rationale course of action would be to take advantage of this
even better bargain and buy more.”
Don’t confuse the company’s performance in the stock market with the real
performance of the underlying business.
“Think for yourself and don’t let the market direct you.”
“Security prices sometimes fluctuate, not based on any apparent changes in
reality, but on changes in investor perception.” This could be helpful in my
research of the 1973 – 1974 period. As I study that era, it looks as though
price earnings ratios contracted for no real apparent reason. Many think that
the price of oil and interest rates sky rocketed, but according to my research,
that was not until later in the decade.
He discusses the good and bad of Wall Street. He identifies how Wall Street
is slanted towards the bullish side. The reason being that bullishness
generates fees via offerings, 401k’s, floating of debt, etc. etc. One of the
sections is titled, “Financial Market Innovations Are Good for Wall Street
But Bad for Clients.” As I read this, I was wondering if the “pay option
mortgages,” which are being offered by many lenders, are one of these
products. These negative amortization and adjustable mortgages have been
around for 25 years. Yet, they have not proliferated the marketplace in the
past as much as they have the last several years. Lenders such as
Countrywide, GoldenWest Financial and First Federal Financial have been
using these riskier mortgages as a typical type of loan in 2005 and 2006.
“Investors must recognize that the early success of an innovation is not a
reliable indicator of its ultimate merit.” “Although the benefits are apparent
from the start, it takes longer for the problems to surface.” “What appears
to be new and improved today may prove to be flawed or even fallacious
“The eventual market saturation of Wall Street fads coincides with a cooling
of investor enthusiasm. When a particular sector is in vogue, success is a
self-fulfilling prophecy. As buyers bid up prices, they help to justify their
original enthusiasm. When prices peak and start to decline, however, the
downward movement can also become self-fulfilling. Not only do buyers
stop buying, they actually become sellers, aggravating the oversupply
problem that marks the peak of every fad.”
He later writes about investment fads. “All market fads come to an end.”
He clarifies, “It is only fair to note that it is not easy to distinguish an
investment fad from a real business trend.”
"You probably would not choose to dine at a restaurant whose chef always
ate elsewhere. You should be no more satisfied with a money manager who
does not eat his or her own cooking." Just to reiterate, I do eat my own
cooking, and I don’t “dine out” when it comes to investing.
“An investor’s time is required both to monitor the current holdings and to
investigate potential new investments. Since most money managers are
always looking for additional assets to manage, however, they spend
considerable time meeting with prospective clients in addition to
handholding current clientele. It is ironic that all clients, Present and
potential, would probably be financially better off if none of them spent time
with money managers, but a free-rider problem exists in that each client
feels justified in requesting periodic meetings. No single meeting places an
intolerable burden on a money manager’s time; cumulatively, however, the
hours diverted to marketing can take a toll on investment results.”
“The largest thrift owners of junk bonds – Columbia Savings and Loan,
CenTrust Savings, Imperial Savings and Loan, Lincoln Savings and Loan
and Far West Financial, were either insolvent of on the brink of insolvency
by the end of 1990. Most of these institutions had grown rapidly through
brokered deposits for the sole purpose of investing the proceeds in junk
bonds and other risky assets.”
I personally suspect that the same will be said of the aggressive mortgage
lenders of 2005 – 2006. I have looked back at my files of 1st quarter 1980
Value Line for a few of these companies mentioned above. Here are some
notes on one of the companies I found.
Far West Financial: Rated C++ for financial strength. In 1979 it was
selling for 5/% of book value. “The yield-cost spread is under pressure.”
“Lending is likely to decline sharply in 1980.” “Far West’s earnings are
likely to sink 30 – 35% in 1980. Reasons: The deteriorating margin between
yield on earning assets and the cost of money, less loan fee income…” Keep
in mind that the stock price rose around 400% from 1974 – 1979. From
1968 – 1972 the P/E ratio was in a range from 11 –17. From 1973 through
1979 the P/E ratio was in a range from 3.3 – 8.1. It would be interesting for
me to look at the 1990 – 1992 Value Lines of the same companies. A Value Investment Philosophy:
“One of the recurrent themes of this book is that the future is unpredictable.”
“The river may overflow its banks only once or twice in a century, but you
still buy flood insurance.” “Investors must be prepared for any eventuality.”
He describes that an investor looking for a specific return over time, does
not make that goal achievable. “Targeting investment returns leads investors
to focus on potential upside rather on downside risk.” “Rather than targeting
a desired rate of return, even an eminently reasonable one, investors should
target risk.” Value Investing: The Importance of a Margin of Safety”
“Value investing is the discipline of buying securities at a significant
discount from their current underlying values and holding them until more of
their value is realized. The element of the bargain is the key to the process.”
“The greatest challenge for value investors is maintaining the required
discipline. Being a value investor usually means standing apart from the
crowd, challenging conventional wisdom, and opposing the prevailing
investment winds. It can be a lonely undertaking. A value investor may
experience poor, even horrendous, performance compared with that of other
investors or the market as a whole during prolonged periods of market
“Value investors are students of the game; they learn from every pitch, those
at which they swing and those they let pass by. They are not influenced by
the way others are performing; they are motivated only by their own results.
He discusses that value investors have “infinite patience.”
He discusses that value investors will not invest in companies that they don’t
understand. He discusses how value investors typically will not own
technology companies for this reason. Warren Buffett has stated this as the
reason as to why he does not own any technology companies. As a side
note, I do believe that at some point, Berkshire will take a sizable position in
Microsoft ($24.31 5/1/06). Klarman mentions that many also shun
commercial banks and property and casualty companies. The reasons being
that they have unanalyzable assets. Keep in mind that Berkshire Hathaway
(Warren Buffett is the majority shareholder) is basically in the property and
“For a value investor a pitch must not only be in the strike zone, it must be
in his “sweet spot.”” “Above all, investors must always avoid swinging at
He goes onto discuss that determining value is not a science. A competent
investor cannot have all the facts, know all the answers or all the questions,
and most investments are dependent on outcomes that cannot be foreseen.
“Value investing can work very well in an inflationary environment.” I
wonder if the inverse is true? Are we in a soon to be deflationary
environment for real estate? I think so. Sure enough he discusses
deflationary environments. He explains how deflation is “a dagger to the
heart of value investing.” He explains that it is hardly fun for any type of
investor. He explains that value investors should worry about declining
business values. Yet, here is what he said value investors should do in this
a. “Investors can not predict when business values will rise or fall,
valuation should always be performed conservatively, giving
considerable weight to worst-case liquidation value and other
b. Investors fearing deflation could demand a greater discount than
usual. “Probably let more pitches go by.”
c. Deflation should give greater importance to the investment time
“A margin of safety is achieved when securities are purchased at prices
sufficiently below underlying value to allow for human error, bad luck, or
extreme volatility in a complex, unpredictable and rapidly changing world.”
“The problem with intangible assets, I believe, is that they hold little or no
margin of safety.” He describes how tangible assets might have alternate
uses, hence providing a margin of safety. He does explain how Buffett
recognizes the value of intangibles.
“Investors should pay attention not only to whether but also to why current
holdings are undervalued.” He explains to remember the reason you bought
the investment, and if that no longer holds true, then sell the investment.
He tells the reader to look for catalysts, which might assist in adding value.
He looks for companies with good management and insider ownership
(“personal financial stake in the business.”)
“Diversify your holdings and hedge when it is financially attractive to do
He explains that adversity and uncertainty create opportunity.
“A market downturn is the true test of an investment philosophy.”
“Value investing is, in effect, predicated on the proposition the efficientmarket (EMT) hypothesis is frequently wrong.” He explains that market
pricing is more efficient with larger capitalization companies.
“Beware of Value Pretenders”
This means, watch out for the misuse of value investing. He explains that
these pretenders came about via the successes of Michael Price, Buffett,
Max Heine and the Sequoia Fund. He labels these people as value
chameleons, and states that they are failing to achieve a margin of safety for
their clients. He claims these investors suffered substantial losses in 1990. I
find this section difficult. For one, the book was published in 1991,
certainly not a long enough time to comment on investments of 1990. Also,
he doesn’t mention the broad based declines of 1973 – 1974
“Value investing is simple to understand but difficult to implement.” “The
hard part is discipline, patience and judgment.” Wait for the fat pitch.
“At the Root of a Value Investment Philosophy”
Value investors look for absolute performance, not relative performance.
They look more long term. They are willing to hold cash reserves when no
bargains are available. Value investors focus on risk as well as returns. He
discusses that the greater the risk, does not necessarily mean the greater the
return. He feels that risk erodes returns because of losses. Price creates
return, not risk.
He defines risk as, “ both the probability and the potential of loss.” An
investor can counteract risk by diversification, hedging (when appropriate)
and invest with a margin of safety.
He eloquently discusses the following, “The trick of successful investors is
to sell when they want to, not when they have to. Investors who may need
to sell should not own marketable securities other than U.S. Treasury Bills.”
Warning, warning , warning. Eye opener next. “The most important
determinant of whether investors will incur opportunity cost is whether or
not part of their portfolios are held in cash.” “Maintaining moderate cash
balances or owning securities that periodically throw off appreciable cash is
likely to reduce the number of foregone opportunities.”
“The primary goal of value investors is to avoid losing money.” He
describes the 3 elements of a value-investment strategy.
a. A bottoms up approach, searching via fundamental analysis.
b. Absolute performance strategy.
c. Pay attention to risk. “The Art of Business Valuation”
He explains that NPV and IRR are great tools for summarizing data. He
explains they can be misleading unless the flows are contractually
determined, and when all payments are received when due. He talks about
the adage, “garbage in, garbage out.” As a side note, Milford Blonsky, CPA
during the 1970’s through the mid 1990’s, taught me that with frequency.
Klarman believes that investments have a range of values, and not a precise
He discusses 3 tools of business valuation”
a. Net Present Value (NPV) analysis. “NPV is the discounted
value of all future cash flows that the business is expected to generate.
He describes the importance of avoiding market comparables, for
obvious reasons. Use this method when earnings are reasonably
predictable and a discount rate can be chosen. This is often a guessing
game. Things can go wrong, things change. Even management can’t
predict changes. “An irresolvable contradiction exists: to perform
present value analysis, you must predict the future, yet the future is
reliably predictable.” He explains that this should be dealt with using
He discusses choosing a discount rate. He states, “A discount rate is, in
effect, the rate of interest that would make man investor indifferent between
present and future dollars.” He mentions that there is no single correct
discount rate and there is no precise way to choose one. He explains that
some investors use a generic round number, like 10%. He claims it is an
easy round number, but not necessarily the best choice. He emphasizes to be
conservative when choosing the discount rate. The less the risk of the
investment, the less the time frame, the less the discount rate should be. He
explains, “Depending on the timing and magnitude of the cash flows, even
modest differences in the discount rate can have a considerable impact on
the present-value calculation.” Of course discount rates are changed by
changing interest rates. He discusses how investing when interest rates are
unusually low, could cause inflated share prices, and that one must be
careful in making long term investments.
Klarman discusses using various DCF and NPV scenarios. He also
emphasizes one should discount earnings or cash flows as opposed to
dividends, since not all companies pay dividends. Of course, one wants to
understand the quality of the earnings and their reoccurring nature.
b. Analyze liquidation value. You need to understand what would
be an orderly liquidation versus fire sale liquidation. Klarman
quotes Graham’s “net net working capital.” Net working capital =
Current Assets – Current Liabilities. Net Net working capital =
Net Working Capital – all long-term liabilities. Keep in mind that
operating losses deplete working capital. Klarman reminds us to
look at off balance sheet liabilities, such as under-funded pension
c. Estimate the price of the company, or its subsidiaries considered
separately, as it would trade on the stock market. This method is
less reliable than the other 2 and should be used as a yardstick.
Private Market Value (PMV) does give an analyzer some rules of
thumb. When using PMV one needs to understand the garbage in,
garbage out concept, as well as the use of relevant and
conservative assumptions. One has to be wary of certain periods
of excesses when using this method. Look at historic multiples. I
am reminded of some recent research I have been working on in
regards to 1973 – 1974. Utility companies were selling for over
18X earnings, when they typically sold for much lower multiples.
I believe this was the case in 1929 as well. Klarman mentioned
television companies, which historically sold for 10X pre-tax cash
flow, but in the late 80’s were selling for 13 to 15X pre-tax cash
flow. “Investors relying on conservative historical standards of
valuation in determining PMV will benefit from a true margin of
safety, while others’ margin of safety blows with the financial
winds.” He suggests when you use PMV to determine what you
would pay for the business, not what others would pay to own
them. “At most, PMV should be used as one of several inputs in
the valuation process and not the exclusive final arbiter of value.”
I think that Klarman mentions that all tools should be used, and not to give
to great a value to any one tool or procedure of valuation. NPV has the
greatest weight in typical situations. Yet an analyst has to know when to
apply each tool, and when a specific tool might not be relevant. He
mentions that a conglomerate when being valued might have a variety of
methods for the different business components. He suggests, “Err on the
side of conservatism.”
Klarman quotes Soros from “The Alchemy of Finance.” “Fundamental
analysis seeks to establish how underlying values are reflected in stock
prices, whereas the theory of reflexivity shows how stock prices can
influence underlying values. (Pg. 51 1987 ed)”
Klarman mentions that the theory of reflexivity makes the point that a stock
price can significantly influence the value of a business. Klarman states,
“Investors must not lose sight of this possibility.” I am reminded of Enron
when reading this. Their business fell apart because they no longer were
able to use their stock price as currency. Soon covenants were violated
because of falling stock prices. Mix that difficult ingredient with fraud, and
you have a fine recipe for disaster. How many companies today are reliant
on continual liquidity from the equity or bond markets?
He discussed a valuation from 1991 of Esco. He indicated that the “working
capital / Sales ratio” was worthwhile to look at. He included a discount rate
of 12% for first 5 years of valuation, followed by 15%. He mentioned that
these higher rates indicated “uncertainty” in themselves. He stressed that
investors should consider other valuation scenarios and not just NPV. This
was all outlined above, but it was cool to see in a real time approach. He
discussed that PMV was not useful, as there were no comparables. He
indicated that a spin-off approach was helpful, as Esco previously
purchased a competitor (Hazeltine). He mentioned that the Hazeltine
acquisition, although much smaller than Esco, showed Esco to be severely
undervalued. He indicated that liquidation value would not be useful,
because defense companies could not be easily liquidated. He did look at a
gradual liquidation, as ongoing contracts could be run to completion. He did
use Stock market valuation as a guide. He noticed that the company was
selling for a small fraction of tangible assets. He called this a very low level,
considering positive cash flow and a viable company. He couldn’t identify
the exact worth of Esco, but he could identify that it was selling for well
below intrinsic value. He looked at all worst-case scenarios, and still
couldn’t pierce the current market price. He claimed the price was based on
“disaster.” He also noticed insider purchasing in the open market.
Klarman discussed that management could manipulate earnings, and that
one had to be wary of using earnings in valuation. He mentioned that
managements are well aware that investors price companies based on growth
rates. He hinted that one needs to look at quality of earnings, and the need
to interpret cash costs versus non-cash costs. Basically, indicating a
normalization of earnings process. “…It is important to remember that the
numbers are not an end in themselves. Rather they are a means to
understanding what is really happening in a company.”
He discusses that book value is not very useful as a valuation yardstick.
Book Value provides limited information (like earnings) to investors. It
should only be considered as one component of thorough analysis.
“The Challenge of Finding Attractive Investments”
If you see a company selling for what you consider to be a very inexpensive
price, ask yourself, “What is wrong with this company?” This reminds me
of Charles Munger, who advises investors to “invert, always invert.”
Klarman mentions, “A bargain should be inspected and re-inspected for
possible flaws.” He indicates possible flaws might be the existence of
contingent liabilities or maybe the introduction of a superior product by a
competitor. Interestingly enough, in the late 90’s, we noticed that Lucent
products were being replaced by those of the competition. We can’t blame
the entire loss of wealth on Lucent inferiority at the time, as the entire sector
followed Lucent’s wipeout at a later date. There were both industry and
company specific issues that were haunting Lucent at the time.
Klarman advises to look for industry constraints in creating investment
opportunities. He cited that institutions frowned upon arbitrage plays, and
that certain companies within an industry were punished without merit. He
mentions that many institutions cannot hold low-priced securities, and that in
itself can create opportunity. He also cites year-end tax selling, which
creates opportunities for value investors.
“Value investing by its very nature is contrarian.” He explains how value
investors are typically initially wrong, since they go against the crowd, and
the crowd is the one pushing up the stock price. He discusses how the value
investor for a period of time (and sometimes a long time at that) will likely
suffer “paper losses.” He hinted that contrarian positions could work well in
over-valued situations, where the crowd has bid up prices. Profits can be
claimed from short positions.
He claims that no matter how extensive your research, no matter how
diligent and smart you are, the diligence has shortcomings. For one, “some
information is always elusive,” hence you need to live with incomplete
information. Knowing all the facts does not always lead to profit. He cites
the “80/20 rule.” This means that the first 80% of the research is gathered in
the first 20% of the time spent finding that research. He discusses that
business information is not always made available, and it is also
“perishable.” “High uncertainty is frequently accompanied by low prices.
By the time uncertainty is resolved, prices are likely to have risen.” He hints
that you can make decisions quicker, without all of the information, and take
advantage of the time others are looking and delving into the same
information. This extra time can cause the late and thorough investor to lose
their margin of safety.
Klarman discusses to watch what the insiders are doing. “The motivation of
company management can be a very important force in determining the
outcome of an investment.” He concludes the chapter with this quote:
“Investment research is the process of reducing large piles of information to
manageable ones, distilling the investment wheat from the chaff. There is,
needless to say, a lot of chaff and very little wheat. The research process
itself, like the factory of a manufacturing company, produces no profits. The
profits materialize later, often much later, when the undervaluation identified
during the research process is first translated into portfolio decisions and
then eventually recognized by the market.” He goes onto discuss that the
research today, will provide the fruits of tomorrow. He explains that an
investment program will not succeed if “high quality research is not
performed on a continuing basis.”
Klarman discussed investing in complex securities. His theme being, if the
security is hard to understand and time consuming, many of the analysts and
institutions will shy away from it. He identifies this as “fertile ground” for
The goal of a spin-off, according to Klarman is for the former parent
company to create greater value as a whole by spinning off businesses that
aren’t necessarily in their strategic plans. Klarman finds opportunity
because of the complexity (see above) and the time lag of data flow. I don’t
know in 2006 if this is still the case, but Klarman mentions there is a 2 to 3
month lag of data flow to the computer databases. I have owned several
spin-offs and have ultimately sold them, as they were too small for the pie,
or just not followed by my research. As I think back, I think quite a few of
these spin-offs did fairly well. One example would be Freescale. As I look
at the Freescale chart, it looks like it went from around 18 two years ago, to
around 33 today. Ahh, this topic alone, enabled the book to provide
potential value to my future net worth.
Look for Net Operating Losses as a potential benefit. He describes the
beauty of investing in bankrupt companies is the complexity of the analysis.
This complexity, as described often in his book, leads to potential
opportunity, as many investors shy away from the complex analysis.
Pending a bankruptcy, costs get leaner and more focused, cash builds up and
compounds with interest. This cash buildup can simplify the process of
reorganization, because all agree on the value of cash.
Michael Price and his 3 stages of Bankruptcy:
a. Immediately after bankruptcy. This is the most uncertain stage,
but also one of the greatest opportunities. Liabilities are not
evident, there is turmoil, financial statements are late or
unavailable and the underlying business may not have stabilized.
The debtor’s securities are also in disarray. This is accompanied
by forced selling at any price.
b. The second stage is the negotiation of a reorganization plan.
Klarman mentions that by this time, many analysts have pored
over the financials and the company. Much more is known about
the debtor, uncertainty is not as acute, but certainly still exists.
Prices will reflect this available information.
c. The third stage is the finalization of the reorganization and the
debtor’s emergence from bankruptcy. He claims this stage takes 3
months to a year. Klarman mentions that this last stage most
closely resembles a risk-arbitrage investment.
“When properly implemented, troubled-company investing may entail less
risk than traditional investing, yet offer significantly higher returns. When
badly done, the results of investing can be disastrous…” He emphasizes that
the market is illiquid and traders take advantage of unsophisticated investors.
“Caution is the order of the day for the ordinary investor.”
Klarman mentions to use the same investment valuation techniques you
would use for a solvent company. He suggests that the analyst look to see if
the companies are intentionally “uglifying” their financial statements. He
cites the example of expensing rather than capitalizing certain expenses.
The analyst needs to look at off-balance sheet arrangements. He cites
examples as real estate and over-funded pension plans.
Klarman discusses the investor should typically shy away from investing in
common stock of bankrupt companies. He mentions there is an occasional
home run, but he states, “as a rule investors should avoid the common stock
of bankrupt entities at virtually any price; the risks are great and the returns
are very uncertain.” He discusses one ploy of buying the bonds and shorting
the stock. He used an example of Bank Of New England (BNE). He
mentioned that BNE bonds were selling at 10 from 70, whereas the stockstill carried a large market capitalization.
He concludes the bankruptcy section by stressing that this type of investing
is sophisticated and highly specialized. The competition in finding these
securities is savvy, experienced and hard-nosed. When this area becomes
popular, be extra careful, as most of the money made is based on the
uneconomic behavior of investors.
Portfolio Management and Trading
“All investors must come to terms with the relentless continuity of the
He mentions the need for liquidity in investments. A portfolio manager can
buy a stock and subsequently find out he or she made an error, or that a
competitor has a stronger product. With that said, the portfolio manager can
typically sell that situation. If the investment was in an annuity or limited
partnership, the liquidity is pierced and the change of strategy cannot be
economically deployed. “When investors do not demand compensation for
bearing illiquidity, they almost always come to regret it.”
He discusses that liquidity is not of great importance in managing a longterm oriented portfolio. Most portfolios should contain a balance of
liquidity, which can quickly be turned into cash. Unexpected liquidity needs
do occur. The longer the duration of illiquidity, should demand a greater
form of compensation for the liquidity sacrifice. The cost of illiquidity
should be very high. “Liquidity can be illusory.” Watch out for situations
that are liquid one day, and illiquid the next. He claims this can happen in
“Investing is in some ways an endless process of managing liquidity.”
When a portfolio is in cash only, the risk of loss is non-existent. The same
goes for the lack of gain when fully invested in cash. Klarman mentions,
“The tension between earning a high return, on the one hand, and avoiding
risk, on the other, can run high. This is a difficult task.
“Portfolio management requires paying attention to the portfolio as a whole,
taking into account diversification, possible hedging strategies, and the
management of portfolio cash flow.” He discusses that portfolio
management is a further means of risk reduction for investors.
He suggests that, as few as ten to fifteen different holdings should be suffice
for diversification. He does mention, “My view is that an investor is better
off knowing a lot about a few investments than knowing only a little about
each of a great many holdings.” He mentions that diversification is
“potentially a Trojan horse.” “Diversification, after all, is not how many
different things you own, but how different the things you do own are in the
risks they entail.”
In regards to trading Klarman stated, “The single most crucial factor in
trading is the developing the appropriate reaction to price fluctuations.
Investors must learn to resist fear, the tendency to panic, when prices are
falling, and greed, the tendency to become overly enthusiastic when prices
“Leverage is neither necessary nor appropriate for most investors.” How do you evaluate a money manager?
a. “Personal interviews are absolutely essential.”
b. “Do they eat their own cooking?” He feels this is the most
important question of an advisor. When an advisor does not invest
in his or her own preaching, Klarman refers to it as “eating out.”
You want the advisor to act in a “parallel” fashion to his or her
c. “Are all clients treated equally?”
d. Examine the investor’s track record during different periods of
varying amounts of assets managed. How has the advisor
performed as his or her assets have grown? If assets are shrinking,
try to examine the reason.
e. Examine the investment philosophy. Does the advisor worry
about absolute returns, about what can go wrong, or is the advisor
worried about relative performance?
f. Does advisor have constraining rules? Examples of this could be
the requirement to always be fully invested.
g. Thoroughly analyze the past investment performance. How long a
track record is there? Was it achieved in one or more market
h. How did the clients do in falling markets?
i. Have the returns been steady over time, or have they been
j. Was the track record from a steady pace, or just a couple of
k. Is the manager still using the same philosophy that he or she has
l. Has the manager produced good long-term results despite having
excess cash and cash equivalents in the portfolio allocation? This
could indicate a low risk approach.
m. Were the investments in the underlying portfolio themselves
particularly risky, such as shares of highly leveraged companies?
Conversely, did the portfolio manager reduce risk via hedging,
diversification and senior securities?
n. Make sure you are personally compatible with the advisor. Make
sure you are comfortable with the investment approach.
o. After you hire the manager, monitor them on an ongoing basis.
The issues that were addressed prior to hiring should be used after
He finishes the book with these words. “I recommend that you adopt a
value-investment philosophy and either find an investment professional with
a record of value-investment success or commit the requisite time and
attention to investing on your own.”
Ronald R. Redfield CPA, PFS
May 3, 2006
Each day, millions of trades are made in a currency exchange market called Forex. The word "Forex" directly stems off of the beginning of two words - "foreign" and "exchange". Unlike other trading systems such as the stock market, Forex does not involve the trading of any goods, physical or representative. Instead, Forex operates through buying, selling, and trading between the currencies of various economies from around the world. Because the Forex market is truly a global trading system, trades are made 24 hours a day, five days a week. In addition, Forex is not bound by any one control agency, which means that Forex is the only true free market economic trading system available today. By leaving the exchange rates out of any one group's hands, it is much more difficult to even attempt to manipulate or corner the currency market. With all of the advantages associated with the Forex system, and the global range of participation, the Forex market is the largest market in the entire world. Anywhere between 1 trillion and 1.5 trillion equivalent United States dollars are traded on the Forex market each and every day. submitted by
Forex operates mainly on the concept of "free-floating" currencies; this can be explained best as currencies that are not backed by specific materials such as gold or silver. Prior to 1971, a market such as Forex would not work because of the international "Bretton Woods" agreement. This agreement stipulated that all involved economies would strive to hold the value of their currencies close to the value of the US dollar, which in turn was held to the value of gold. In 1971, the Bretton Woods agreement was abandoned. The United States had run a huge deficit during the Vietnam Conflict, and began printing out more paper currency than they could back with gold, resulting in a relatively high level of inflation. By 1976, every major currency worldwide had left the system established under the Bretton Woods agreement, and had changed into a free-floating system of currency. This free-floating system meant that each country's currency could have vastly different values that fluctuated based on how the country's economy was faring at that time.
Because each currency fluctuates independently, it is possible to make a profit from the changes in currency value. For example, 1 Euro used to be worth about 0.86 US dollars. Shortly thereafter, 1 Euro was worth about 1.08 US dollars. Those who bought Euros at 86 cents and sold them at 1.08 US dollars were able to make 22 cents profit off of each Euro - this could equate to hundreds of millions in profits for those who were deeply rooted in the Euro. Everything in the Forex market is hanging on the exchange rate of various currencies. Sadly, very few people realize that the exchange rates they see on the news and read about in the newspapers each day could possibly be able to work towards profits on their behalf, even if they were just to make a small investment. The Euro and the US dollar are probably the two most well-known currencies that are used in the Forex market, and therefore they are two of the most widely traded in the Forex market. In addition to the two "kings of currency", there are a few other currencies that have fairly strong reputation for Forex trading. The Australian Dollar, the Japanese Yen, the Canadian Dollar, and the New Zealand Dollar are all staple currencies used by established Forex traders. However, it is important to note that on most Forex services, you won't see the full name of a currency written out. Each currency has it's own symbol, just as companies involved in the stock market have their own symbol based off of the name of their company. Some of the important currency symbols to know are:
USD - United States Dollar
EUR - The Euro
CAD - The Canadian Dollar
AUD - The Australian Dollar
JPY - The Japanese Yen
NZD - The New Zealand Dollar
Although the symbols may be confusing at first, you'll get used to them after a while. Remember that each currency's symbol is logically formed from the name of the currency, usually in some form of acronym. With a little practice, you'll be able to determine most currency codes without even having to look them up.
Some of the richest people in the world have Forex as a large part of their investment portfolio. Warren Buffet, the world's richest man, has over $20 Billion invested in various currencies on the Forex market. His revenue portfolio usually includes well over one-hundred million dollars in profit from Forex trades each quartile. George Soros is another big name in the field of currency trading - it is believed that he made over $1 billion in profit from a single day of trading in 1992! Although those types of trades are very rare, he was still able to amass over $7 Billion from three decades of trading on the Forex market. The strategy of George Soros also goes to show that you don't have to be too risky to make profits on Forex - his conservative strategy involves withdrawing large portions of his profits from the market, even when the trend of his various investments seems to still be correlating upward.
Thankfully, you don't have to invest millions of dollars to make a profit on Forex. Many people have recorded their success with initial investments of anywhere from $10,000 to as little as $100 for an initial investment. This wide range of economic requirements makes Forex an attractive venue for trading among all classes, from those well entrenched in the lower rungs of the middle class, all the way up to the richest people alive on the planet. For those on the lower end of the spectrum, access to the Forex market is a fairly recent innovation. Within the past decades, various companies began offering a system that is friendlier to the average person, allowing the smaller initial investments and greater flexibility that is seen in the market today. Now, no matter what economic position you are in, you can get started. Although it's possible to jump right in and start investing, it's best that you make sure you have a better understanding of the ins and outs of Forex trading before you get started.
The world of Forex is one that can be both profitable and exciting, but in order to make Forex work for you it is important that you know how the system works. Like most lucrative activities, to become a Forex pro you need a lot of practice. There are many websites that offer exactly this, the simulated practice of Foreign Exchange.
The services provided by online practice sites differ from site to site, so it is always a good idea to make sure you know all of the details of the site you are about to use. For example, there are several online brokers who will offer a practice account for a period of several weeks, then terminate it and start you on a live account, which means you may end up using your own money before you are ready to. It's always a good idea to find a site that offers an unlimited practice account. Having a practice account allows you to learn the ways of the trade with no risk at all. Continuing to use the practice account while you use a live account is also a beneficial tool for even the most seasoned Forex traders. The use of a no risk practice account enables you to try out new trading strategies and tread into unknown waters. If the strategy works, you know that you can now implement that strategy into your real account. If the strategy fails, you know to refrain from the use of that strategy without the loss of any actual money.
Of course, simply using a no risk account won't get you anywhere. In order to make money with Forex, you need to put your own money in. Obviously, it would be ridiculous to travel to other countries to purchase and sell different currencies, so there are many websites that you can use to digitally trade your money. Almost all online brokerage systems have different features to offer you so you have to do the research to find out which site you wish to create an account with. All brokers will require specific information of you to create your account. The information they will need from you includes information required to communicate with you, including your name, mailing address, telephone number, e-mail address. They also require information needed to identify who you are, including your Social Security number, Passport number or Tax Identification number. It is required by law that they have this information, so they can prevent fraudulent trading. They may also collect various personal information when you open an account, including gender, birth date, occupation, and employment status.
Now that you have practiced trading currency and set up your live account, it is time to truly enter this profitable yet risky world. To make money with Forex, you do need to have money to begin with. It is possible to trade with very small amounts of money, but this will also lead to very small profits. As is with many other exchange systems, high payouts will only come with high risks. You can't expect to start getting millions as soon as you put money in to the market, but you can't expect to make any money at all if you don't put in at least a 3-digit value.
As most Forex brokers will warn you, you can loose money in the foreign exchange market, so don't put your life savings into any one trade. Always trade with money that you'd be able to survive without. This will ensure that if you get a bad trade and loose a lot of money, you wont end up on the streets, and you'll be able to make a comeback in the future.
So how does trading currency work? Logically, trades always come in pairs. For example, a common trade would be the United States Dollar to the Japanese Yen. This is expressed as USD/JPY. The way to quote a trade is kind of tricky, but with practice it becomes as natural as reading your native language. In a Forex quote, the first currency in the list (IE: USD in USD/JPY) is the base currency, and in the quote the base is always one. This means if (hypothetically of course) One USD was worth Two JPY, that the quote would be expressed as 1/2.
When trading in Forex, we use pips. Pip is an acronym for "percentage in point". A pip a certain decimal place in a number compared to the same decimal place in another number. Using pips, we track the gains and losses of a currencies value compared to another's. Let's take a look at an example. Say a value is written as 1.0001/1.0004. This would indicate a 3-pip spread, because of the 3 number difference in the fourth decimal place. Almost all currency pairs go to the fourth decimal place. The only currency pair that doesn't is that of the USD/JPY, and it goes to the second decimal place. For example, a USD/JPY quote with a 3-point spread would look like this: 1.01/1.04.
A very common aspect to the foreign exchange is leverage. Leverage trading, also known as trading on margin, is a way to amplify the amount of money you are making. When you use leverage trading, you borrow a certain amount of money from your broker and use that to make your transaction. This allows you to trade with more money then you are actually spending, meaning you can make higher profits than you would normally be able to make.
There are risks associated with leverage trading. If you increase the amount of money you are using, if a trade goes bad, then you'll loose more money than you'd usually loose. The risks are worth it though, because a big win on margin means a huge payout. As mentioned before, it is definitely a wise idea to try out leverage trading on your practice account before you use it excessively on your live account, so you can get a feel for the way it works.
Now that you're an expert on the way Forex trading works there are some things about foreign exchange that you should know. Forex is just like the stock market in that there are many benefits and risks, but if you are going to invest your time and personal money into this system, you should be fully aware of all of the factors that may change your decision to invest in the currency market.
Generally speaking, Forex is a difficult subject to opinionate on, because of the different factors that may alter the currency over the years. "Supply and demand" is a major issue affecting the Forex organization, because the world is in constant variable to change, one significant product being oil. Usually the currency of all the nations around the globe is described as a huge "melting pot", because of the fact that all of the interchanging controversy, political affairs, national disputes, and possibly war conflicts, all mixed together as a whole, altering the nature of Forex every second! Although problems such as supply and demand, and the whole "melting pot" issue, there are a numerous amount of pros to Forex; one being benefited profit from long term stock. Because of the positive aspects of Forex, the percentage of the use of electronic trading in the FX market (shortened from Foreign Exchange) increased by 7% from 2005 to 2008. Despite the controversial realm of Forex, it is still recognized today by many, and is still popular amongst many of the nations in the world.
Of all the organizations that recognize Forex, most of them practice fiscal policy, and monetary policy. Both policies are dependent on the nation's outlook on economics, and their standards set. The government's budget deficits, or surpluses against the country, is widely affected by the country's economic status of trade, and may critically inflict the nation's currency. Another factor for the nation's deficit spending is what the nation already has, in terms of necessities for the citizens, and the society. The more the country already has, prior to trade, the greater the budget for other demands from the people, such as technology, innovations in existing products, etc. Although a country may have an abundance in necessities, greed may hinder the nation's economic status, by changing government official's wants, to want "unnecessary" products, therefore ruining or "wasting" the country's money. This negative trend may lead to the country's doom, and hurt the Forex's reputation for positive change. There are some countries which hold more of a product (such as oil stated above), the Middle East dominating that sector in the circle of trade; Since the Middle East suffers much poverty, as a result of deficit spending, and lack of other resources, they demand for a higher price in oil, to maintain their economic status. This process is known as the "flights to quality", and is practiced by many countries, wanting to survive in the trading network that exists today. Interest rate, and leveraged financing, is due to the inflations that occur in many parts of the world from one point to another. Inflations wear down purchasing abilities, causing the currency to fall with it. In some cases, a country may observe the trends that it takes, and beforehand, take action to avoid any mishaps that had been experienced before. Sometimes, the country will buy more of a product, or sell more of a product, otherwise known as "overbought" or "oversold". This may aid in the country's future, or devastatingly hurt the country, because of lack of thought, as a result of fraud logic. "What started out as a market for professionals is now attracting traders from all over the world and of all experience levels" is part of a letter of the chairman of Forex, and it is completely true. There is even a 30-day trial for Forex online if anyone interested in Forex wants to learn more about the company. Although affected by leveraged financing, interest rate, and causing an increase or decrease in exchange rate risks, Forex can be a great way for quick profits and integrated economy for the country. In investing in stocks that are most likely to be successful for a long period of time, and researching these companies for more reference and background that you need to know, Forex can aid in these fields. In the Forex market of different levels of access, the inter-bank market composed of the largest investment bank firm, which contains "spreads", which are divided into bid, and ask prices. Large amounts of transactions, with large amounts traded, and requesting a small amount of difference is known as a better spread, which is preferred by many investors.
In comparison to the Stock Market, the Forex organization is just as stable, and safe, if the users on it are aware, and decently knowledgeable about the topic. The Stock Market Crash in 1929 was a result of lack of thinking, because of the extremely cheap shares, replacing the shares originally costing thousands of dollars. When the Stock Market crashed, and the New Deal was proposed by Franklin D. Roosevelt, leveraged finance was present, and utilized to stabilize the economy at the time. The United States was extremely wealthy and prosperous in the 20s (prior to the depression), and had not realized what could happen as a result of carelessness in spending. This is a result of deficit spending, and how it could damage a society, in less than a decade! When joining Forex, keep in mind that with the possible positive outcomes, and negative ones, there are obstacles that must be faced to become successful.
As a result of many catastrophic events, such as the Great Depression that occurred in the United States, people investing in the Forex organization keep in mind of the dangers, and rewards that may come upon them in a certain point in time. With more work and consideration outputted by a person, or organization in the Forex program will there be more signs of prosperity as a result. In relation to individuals such as Warren Buffet and George Soros, they have become successful through experience, and determination through many programs, and research, for security purposes. Reserving some of the most riches people in the world, to others that are just test driving it to discover its potential for them, Forex is a broad topic that experiences different people everyday. Forex may not help everyone that invests in it, but if enough outputted effort is amplified in attempts to better the economy, it is most definitely something that any person should experience first-hand.
Floating-rate notes The reset margin is the difference between the interest rate of a security and the index on which the security's interest rate is based. Fixed Income Trading Strategy CME Clearing confirms that its existing collateral policy includes acceptance of floating rate U.S. government agencies for performance bond requirements, including floating rate notes anchored to the Secured Overnight Financing Rate (“SOFR”). For the full text of this advisory, please click here. Floating rate notes can also be issued with a step up rate in the event that it is not called (repaid early or there is a trigger event such as a credit rating downgrade. How FRNs work – an example. Commonwealth Bank issued two bonds, one fixed and the other floating on 12 July 2016. Floating rate tranche Volume: A$1.8bn Interest rate: 3m Floating Rate Note (FRN) On July 31, 2013, the U.S. Treasury published amendments to its marketable securities auction rules to accommodate the auction and issuance of a Floating Rate Note (FRN). These securities complement Treasury’s other marketable securities: Treasury bills, notes, bonds, and inflation-protected securities (TIPS). In January 2014, the U.S. Treasury Department made its first sale of Floating Rate Notes (FRNs), securities whose coupon rates vary over time depending on the course of short-term rates. Now that a few years have passed, we have enough data to analyze dealer trading and positioning in FRNs. In this post, we assess the level of trading and positioning, concentration across issues, and auction
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