There have been several questions about the calculation of RBP probability. I encourage readers to review the white paper authored by Professor Bjorn Jorgensen of Columbia University which describes this process in detail. It is available here.

There are several characteristics of the Required Business Performance (RBP) methodology that I find especially interesting.  One is the potential of the RBP probability to revolutionize the way investors look at the risk of a stock.

An axiom of finance theory has traditionally held that risk and return are directly (and linearly) related, and that to expose oneself to the possibility of greater returns means to also expose himself to the possibility of greater losses.  I would like to challenge that notion, because when we define risk as one minus the RBP probability, this need not be the case. 

The higher a company’s RBP probability, the more likely it is that management will produce the results need to maintain the current stock price.  Likewise, the higher a company’s RBP risk (or one minus the RBP probability), the more likely it is that management will fail to produce the necessary results.  Since we have defined risk in this way, greater RBP risk simply implies greater downside exposure.  This exposure is not necessarily offset by collateral upside exposure. So by investing in the highest RBP probability stocks, we have effectively captured the upside potential of a stock while evading the downside risk.  This is how RBP investing is able to reduce risk in general.

Traditionalists will likely to resist this notion because, for several decades now, we have defined risk under the assumption that it is the volatility of returns, not the returns themselves, that define risk.  This doctrine has been taught in business schools since the original professors developed the Capital Asset Pricing Model (CAPM) in the mid-1960s.  The key variable in CAPM, beta, is defined as the covariance of the stock with the market scaled by the variance of the market.  In layman terms this simply means that a stock is as risky as it is more volatile than the market.

There is only one problem.  This model does not help us predict returns whatsoever.  In fact, a paper written in 1992 by the two most prominent finance academics declared in so many words, that “Beta is dead.”  They attempted to save beta and CAPM by adding new variables to the model other than volatility, but even this three-factor model did a weak job at best.  The beauty of CAPM is its simplicity, and it is certainly convenient to be able to quantify a stock’s “risk” so easily.  But allow me to explain why I believe beta fails to describe risk as the individual investor should be concerned.

Most individual investors are in the market for the long-term.  As one them myself, I can say that I am not terribly concerned what types of wild swings my stocks take provided they end higher three, five or ten years from now.  Moreover, I actually kind of like the upswings – it is the downswings that bother me.  Am I alone?  Nonetheless, if a stock has a beta of two, it is deemed risky.  I really don’t care if the stock has a beta of two or twenty, as long as the company behind the stock is improving and I have no immediate need to liquidate my position.

For years I resolved that there was no better way to quantify risk than beta.  Not because beta was at all useful, but just because risk is such indistinct concept to try to distill into a number.  But then along came RBP probability.  After spending some time ruminating about how it is calculated, it began to make perfect sense to me.

RBP probability is the logical way to measure risk because it describes the likelihood that I will lose money.  That, and only that, is what I see as true risk.  Volatility doesn’t translate to risk, in my opinion, simply because the possibility of making money is not something I seek to avoid.

So what does all this mean for the relationship between risk and return, perhaps the most fundamental concept in all of investing?  Simple.  It eliminates it.  We can actually avoid exposure to negative returns while maintaining our exposure to positive returns.  Thus, there is no necessary relationship between risk (as interpreted as the likelihood of losing) and expected return.  In fact, by reducing RBP risk we can actually expect higher returns.

Now, needless to say, many traditionalists and financial theorists will quickly object to this notion since it contradicts such an essential assumption of their strategies.  I can’t blame them - Wall Street is steeped in tradition. However measuring risk by the variance of potential payoffs is not universal, even in other financial settings.  Take the insurance industry for example, where actuaries assess risk by first measuring the probability of an event happening based on historic record.  Or perhaps the gambling markets, where the “odds” of a gamble describe the probability of winning, not necessarily the amount won.

This is a philosophical discussion, but one investors should devote some time to.   My primary hope is that investors will keep an open mind about the issue, because surely many will be reluctant to embrace this new methodology only because it is so revolutionary.

Apple has been a favorite company among technophiles in recent years because of its innovation and exciting new products.  Tech traders, similarly, love to watch Apple’s stock for the economic benefits those products can bring, none of which are readily predictable except in the very near term.  With Apple’s stock now flirting with the highs it set last year, it ought to be worthwhile to take a look at this company.  But what I would like to do, in this inaugural “Can-It-Be-Done” blog posting, is to take a look at Apple from the RBP Investing perspective, rather than that with which most readers are likely familiar.

The RBP Investing approach to stock analysis is different from the customary approach used on Wall Street.  For instance, last week an analyst upgraded Apple Inc. to “Outperform” and set a price target of $235.  This implies that at its current price of around $187, Apple is a buy.  The analyst went on to explain that this price was determined by multiplying his own earnings estimates by the middle of the multiple range in which the company has traded in recent years.

Nearly every analyst I am aware of publishing regular reports on specific stocks will describe his conclusion in this way.  And oftentimes the price target is nothing more than the product of a subjectively chosen earnings multiple and earnings estimates the analyst calculates from various operational considerations.

There is nothing particularly wrong with this approach, I just think there is a better way.  For one thing, a detailed discounted cash flow (DCF) analysis is often neglected in analyst reports.  Since DCF is the only legitimate way to value a stock, an assertion I argued here, any report failing to integrate it is dubious, in my opinion.  More importantly, though, the standard analyst report is simply too opaque.  That is, we don’t really know why $235 is an appropriate price, other than the fact that it is the analyst’s dictum. The RBP Investing approach, however, makes all such prices completely transparent.

Were this analyst to use the RBP Investing approach, instead of setting a price target and suggesting a trading decision, he might say

 “Apple’s RBP Probability is currently 81%.  This implies there is an 81% chance that, in the coming quarter, management will produce the results the stock market is collectively expecting.  Should management do so, we can expect a positive price reaction.  Among companies in the Technology Hardware and Equipment Sector, Apple ranks relatively high, as the average company in this sector has an RBP Probability of 63%.”

But this probability alone does not tell us exactly what management’s performance need be.  So the analyst might go on to discuss Apple’s Required Business Performance (RBP).

“At Apple’s current price of $185, the stock market collectively is expecting the company to sell approximately 56.5 million iPods in the coming twelve months, 9 million iPhones, 6.5 million portable computers and 3.7 million desktops.”

This is a far more transparent way for the individual to assess a stock and overcomes the two most troublesome assumptions he must make when taking an analyst’s advice.  These are a) that the operational analysis is robust enough to make the analyst’s earnings estimates accurate and b) that the earnings multiple chosen is appropriate.

Instead of taking for granted that a certain individual has made the right predictions, we use the information we already know for certain – the stock price – to help us make the decision ourselves.  We know exactly what an RBP Probability of 81% means, because we know what the RBP behind it is.  We don’t try to speculate about where the stock is going.  Rather, we try to assess the risk that the stock will go down.

So the question has become, can it be done?  Can Apple indeed sell 56.7 million iPods, 9 million iPhones, 6.6 million portable computers and 3.7 million desktops in the next twelve months?  All the RBP numbers I mention above are current as of May 30, 2008, but not being an expert in this stock or this sector, I hesitate to answer the question myself.  And so I will leave that to the readership of this blog.  What do you think?

This is a blog about an exciting new way to approach the stock market.  I hope that you, the reader, find it to be an interesting and engaging experience as we help the investment community learn about the Required Business Performance (RBP) methodology.  I also hope to a launch a conversation about specific stocks and how we can use RBP to analyze them.

RBP is a conceptually simple metric.  It represents what results a company must post in the future – what performance management must produce – lest the stock be implicitly overvalued.   Every stock price has in it an enormous amount of information.  The RBP method simply uses that information to infer what the market expects of the company.  Once we know what the market expects, it becomes a much easier task to judge whether the stock price is reasonable.  This is the premise of the RBP methodology. 

While the idea of using market expectations to make investment decisions is nothing new, using them in the way the RBP investor uses them truly is.  The typical sell-side analyst, for example, might claim “We expect ABC Corp to earn $3 per share next year, and have therefore established a price target of $43.”  That is, the buy/sell/hold decision to be made depends on what the analyst deems to be an appropriate price based on that analyst’s expectations for future performance.  Using the RBP approach, however, the decision is made based on what the stock’s current price implies about the expectations of the entire market, not just a single analyst.

Transparent Value takes the RBP analysis a step further when it calculates Required Business Performance Probability, or RBPP (pronounced R-B-double-P).  After inferring what the market expects of the company’s future performance, Transparent Value uses historical performance to judge the probability that these expectations are met.  RBPP is the risk-adjusted likelihood, expressed as a percentage, that the company will meet its required business performance.

The RBPP is the focus of the Dow Jones RBP Index Series, another area for discussion I hope to cultivate on this blog.  Index investing has grown enormously in popularity recently and with that growth has come change.  The Dow Jones RBP indexes are part of a new breed of indexes that challenge traditional assumptions used in index creation such as value-weighting.  This too, I hope, should spark conversation amongst readers.

The products and methodology created by Transparent Value are very exciting and, in my estimation, have the potential to fundamentally change the way investors look at the markets.  I am excited to be a part of this revolution and I hope this blog plays an important part in it. 

The market prices stocks continuously.  In doing so, it offers small shares of ownership of each business for sale at a particular price.  What many investors fail to consider, however, is that in pricing a stock the market is also providing investors information on what it, the market, expects of the company’s operations.  Clearly, the higher a businessperson’s expectations for company operations, the more inclined he will be to purchase shares of it.  But how do his expectations differ from those of the market – those implied by the market price of the stock?  Should he forego a purchase of shares since his high expectations are matched by equally high expectations implied by the stock price?

To help him answer these questions, the RBP methodology uses the same type of discounted cash flow (DCF) valuation model pervasive in financial analysis.  But instead making strong assumptions about growth and solving for the value of the stock, it uses the market price of the stock as an input.  The result of this reverse DCF (RDCF) analysis, rather than being the value of the stock, is the rate of growth of the company’s free cash flow in the next ten years.  That is, we know or can assume the other variables in the valuation model;  the market cap of the company or enterprise value, the cost of capital or discount rate, the prior year’s free cash flow, and the terminal free cash flow growth rate.   We simply seek to infer what the market’s expectations for free cash flow growth are.

The Process:

First we adjust the market cap of the company for certain items to give us an “enterprise value,” a metric often considered to be a more accurate substitute for simple market cap.  This step includes adding all long term liabilities (interest bearing debt and capitalized leases), preferred stock and unconsolidated subsidiaries, while subtracting cash and cash equivalents.  This is the basic input of the RDCF process.

Of course to solve for our first stage free cash flow growth rate we must make other assumptions.  We use CAPM to estimate the cost of capital and make appropriate assumptions about the long-term terminal growth rate.  With all this information, we can calculate the first stage FCF growth rate.  But we still haven’t found the actual required business performance.  This comes next. 

After the first stage free cash flow growth rate pops out of the model, we first calculate the revenue associated with our free cash flow growth and then decompose it in to revenue components.   Here more assumptions are needed, but are made logically and consistently.   They will be things like profit margins, capital expenditures and working capital expenditures.  The assumptions are made by analysts who consider historical values as well as publicly available information regarding planned capital expenditures.  This is an analytical – and crucial – process.

I might add at this point in my explanation that the Transparent Value team is a highly educated and well trained group of analysts.  Each of them gives careful consideration to the assumptions necessary to complete the calculation of a company’s RBP and the results of their analyses are subject to a stringent sixteen-point quality assurance program.  Indeed, the process takes a great deal of time and requires a large team to accurately calculate the RBP of the many companies currently under analysis.  Today, Transparent Value tracks the RBP of more than 1300 different companies and employs more than one hundred analysts to do so.

After determining the future revenue implied by the stock price, we can now decompose this revenue in to the components specific the company’s business model.  For example, after we know the future revenue implied by Apple Inc.’s stock price, we can use publicly available information about sources of that company’s revenue to determine how many iPods and iPhones the market expects to be sold.  This is the most granular level of financial analysis, and also the most understandable one. 

I hope it is now clear how we transform the price of a stock – a number that often seems to have been generated magically and which can change mysteriously – into a useful description of what investors collectively expect of the company it represents.  Knowing that Apple stock currently costs $135 tells us very little, but knowing that this implies it will sell 58 million iPods is very informative.  This process makes that mysterious $135 price tag transparent.  Alas, the investor can understand equity prices like never before.  

The discounting of future cash flows to arrive at the intrinsic value of an asset has a fundamental place in finance theory, yet many laypersons (and even some professionals) are simply not familiar with it.  Discounted cash flow (DCF) analysis is also crucial to understanding the RBP methodology, so I would like to begin this blog by familiarizing those unfamiliar.

Investing can be defined both completely and rather succinctly at the same time.  It is the outlay of money today with the expectation of collecting more money at some point in the future.  That is all there is to it.  What makes this assertion complicated is the great deal of uncertainty inherent in any such outlay.  In the case of investing in stocks the investment process is extremely complicated due to the uncertain nature of the ultimate payoff a stock will produce.

But other investment vehicles are far less complicated, yet can be valued the same way.  To that end, a good understanding of simpler investments can help to explain the process of investing in stocks.  Take for instance a 30-year U.S. Treasury bond, and assume for simplicity we purchase it on the day of issue at face value.  When we purchase the bond we have “invested” an amount equal to the face value because we expect to, over the next thirty years, collect a sum of money greater than that face value.

Since we have defined investment by assuming we will collect more money in the future than we paid initially, we can value that investment by summing up all that money we collect in the future.  Of course, we would much rather collect that money sooner rather than later, so we must account for this in our valuation too.  This brings me to the most elementary axiom in all of finance:  Money today is worth more than the same amount at some time in the future.  We call this phenomenon the “time value” of money.

The time value of money affects our valuation of an asset because we will assign different weights to each cash flow depending on when it is received.  Said differently, we “discount” the later cash flows to account for when they are collected.  This is all there is to discounted cash flow (DCF) analysis.  Just add up all the discounted values of the future cash flows and – voila – we have a value for our asset.

Now let us get back to our 30-year T-bond.  The value of that bond is simply equal to the sum of the discounted value of the interest and principal payments it will make over the thirty years.  But by how much do we discount those later payments?  The answer is simple yet vague.  We discount them by our opportunity cost – the rate of interest we could have otherwise earned ourselves had we done something different with our cash rather than investing it in the bond.   If we could have taken an equivalent amount of risk by purchasing a similar bond and earned 8% interest, then 8% is our “discount rate.”  The formula we would apply to each payment, then, is:  Payment/(1+r)^n  , where “r” is our discount rate and “n” represents the number of years until the payment is made.  After applying this formula, we have a “present value” for the payment.

Once we have added up the present values of all the payments we have a value for our bond.  Quite simple, I must say.  Well, valuing a stock is an intellectually similar exercise, just much less precise.  Since stocks don’t make reliable, pre-determined coupon payments like bonds, we must find an alternative, economically analogous “payment.”  For a variety of reasons I will discuss in a later post, free cash flow is the relevant “payment” in stock valuation.  Thus, when we value a stock, we add up the present value of all the company’s future free cash flows.  But a variety of complications will make this difficult. 

First, unlike a bond, a stock has an infinite life, and thus an infinitely long stream of cash flows to value.  Second, the free cash flow the company will produce, unlike the predictable coupon payments of a bond, will change from one period to the next.  Third, the discount rate that is most appropriate is a topic of debate, and not nearly as unambiguous as that used in bond valuation.  Fourth and finally, we simply do not know what the company’s free cash flow will be in the future.