Is My Weighted Average Cost of Capital WACC - y?

There are a lot of places where we can get the basic formula for a firm's Weighted Average Cost of Capital (often abbreviated as WACC).

Once we have calculated this figure, it can be employed in a number of settings - investment valuation, performance evaluation, industry comparison, etc.

Yet what is often not easy to find are the issues that arise during this employment - either nuances present in its calculation or the traps that can occur if we rotely employ it thereafter.

What Is Capital Structure?

We use the term "Capital Structure" to refer to the variety of instruments the firm has used to finance itself - short-term debt, long-term debt, preferred equity, common stock, options, warrants, etc.

These items are on the right side of the balance sheet. The left side of the balance sheet has assets. If we net the liabilities of items that are not investments (i.e. providers of these funds do not expect a return, such as Accounts Payable), then our balance sheet will show how these assets have been financed by the firm (see "How to Calculate ROIC" for an example of this netting).

Figure A

Capital Structure

Our balance sheet will provide information like that shown in Figure A - it tells us what classes of assets the firm has and what instruments have been used to finance them.

The money the firm has received for each of these financial instruments comes from investors. In this context we define investors as those seeking a return for the funds they have provided. Banks and bond holders require interest, preferred equity holders require dividends, and common stock holders may require dividends and want to sell their shares at a higher price than what they paid for them.

Each of these investors has a different expectation about what they will receive. For example, a short-term debt investor will generally expect a lower interest rate than a long-term debt investor.

These "return expectations" are in large part driven by the market. We'd all love to see the stock we own quadruple in value over the next year, but it would be unrealistic to expect this result.

Opportunity Cost

The fact that an investor's expected return is driven by the market is due to the concept of opportunity cost.

Opportunity cost reflects the fact that we cannot have everything, and in order to get something we must give up something else. For a personal example, if we decide to go to the movies tonight, then we are not going to play soccer, have a long leisurely dinner, practice guitar, etc. during that time instead.

Financially, if we invest ♢ 10 (for new readers, the symbol ♢ stands for Treasury Cafe Monetary Units, or TCMU's, freely exchangable into any currency at any rate of your choosing) in X, then we cannot invest it in Y.

Thus Y "sets the bar" for X. If we would expect to make 10% per year investing in Y, then we need to do slightly better to choose X instead - perhaps 10.000001%.

The caveat on this is that the cost of capital is evaluated against investments with the same level of risk. We do not evaluate X against Z if Z is a "risk free" instrument and X is a risky one.

Weighted Average Cost of Capital I

So far we have established that a firm has a capital structure, made up of a number of financial instruments, and that each of these instruments has a cost of capital associated with it.

Figure B

Weighted Average Cost of Capital Formula

The Weighted Average Cost of Capital is the proportional sum of the different instrument's in our firm's capital structure's cost.

Generically, absent other factors, it can be computed using the formula in Figure B.

Note that the formula in Figure B is hardly ever used in practice for the simple reason that, absent other factors, the weighted average cost of capital for the different financial instruments must equal the cost of capital of the firm as if it were funded with only equity. This is the Nobel prize winning Modigliani - Miller theorem.

For example, let's say that Joe's Agricultural Empire, LLC is in a business where the level of that risk is priced at 10% in the market. In other words, assets with the same level of risk are going for 10%, and therefore investor's require a similar rate of return for Joe's.

Suppose that Joe's produces ♢ 10 of cash flow for investors per year, and is expected to do so forever. We can use the dividend discount formula to calculate the equity value of Joe's at ♢ 100 (10/0.1).

Now imagine that we issue a financial instrument that's worth 50% of the value for Joe's, and the market prices the risk of this security at 8%. Why does the market price this differently? Because the risk characteristics of this security are different than the underlying assets.

It could be that it has a priority claim on the cash flow, meaning these investors get paid first, before the equity investors, so in the year's where the expected cash flow of ♢ 10 is not met, they get a bigger slice of the pie. Or it could be that the payout to these investors is protected from some of the risks Joe's faces, such as market prices (perhaps for a cost input or revenue generating factor).

Figure C

Weighted Average Cost of Capital Formula

Again using the dividend discount formula, after using algebra to rearrange it, the cash flow to these investors is ♢ 4 (4/.08 = 50, which is 50% of the value as stipulated).

The key point for the pricing is that, for the market to price this instrument differently, there needs to be a reason for it related to risk. If the opportunity cost for this instrument is 8%, this instrument has a different risk characteristic than Joe's as a whole to make it that way.

The equity investors will get the remaining ♢ 6 of the expected cash flow, and the value of their investment is ♢ 50 (half the firm's value as stipulated), so their opportunity cost is now 12%. Figure C shows the calculations for this example.

Again, the reason the equity is priced differently is related to risk. Recall that some of the risks for the new instrument's investors was 'taken off the table', resulting in their pricing the new instrument at 8%. Yet, the remaining risk does not go away. It therefore is now disproportionately borne by the equity holder. Thus, higher level of risk, higher level of return required.

We now have a capital structure of 2 instruments, one at 8% and one at 12%, each representing 50% of the firm value. The weighted average cost of capital is 10% (50% * 8% + 50% * 12%), the same as before!

This leads to the Modigliani-Miller conclusion: how the firm is financed does not matter! We can think of it like squishing a balloon - if one part is less the other part becomes more. The volume of air in the balloon is the same, it is merely distributed differently. The same for the risks in the firm and how they are shared by investors.

The key takeaway from this is one of simple common sense: there is no such thing as a free lunch.

Weighted Average Cost of Capital II

The natural question to ask after this exercise is "why bother"? If the parts equal the whole, why bother breaking it down into parts when all that happens is that we get back to the same place? If financing doesn't really matter, let's keep it simple.

The key phrase from the last section is "absent other factors". There are other factors.

The biggest of these is taxes. Because interest is a deductible business expense, financing all of a sudden can drive value through the creation of the so-called "Tax Shield".

Figure D

Weighted Average Cost of Capital Formula

Figure D shows the value of the two components shown in Figure C with the addition of the interest expense deductibility. The example uses 40% as the assumed tax rate. Ultimately, financing with 50% debt adds about ♢ 13 of value to the firm through this deductibility.

Notice that the final capital structure is no longer 50% for both of the securities - the one is worth more than the other.

We can get back to 50% if we iterated through the valuation a few times. Set debt at 50% of ♢ 113, see how close we get to 50% with the new tax shield, adjust, and repeat again and again.

Figure E

Weighted Average Cost of Capital Formula

The other way this problem is solved is to modify our Weigted Average Cost of Capital equation to that shown in Figure E.

In this figure we have added a second term to the formula to deal with instruments that generate tax shields. If an instrument does not generate tax shields, it is evaluated by the first term in the equation. If it does, it is evaluated by the second term.

Figure F

WACC Example Calulation

We can now go back to our Joe's Agricultural Empire LLC example. Figure F shows that by using our new formula, we calculate a weighted average cost of capital of 8.4%. Using this rate in our dividend valuation model, we arrive at a value of a little more than ♢ 119 for Joe's.

The beauty of the WACC approach is that we have captured the fact of tax shield generation in the denominator through the (1-t) term, so in the numerator we use the cash flow from the example before (called "unlevered" because they do not account for debt). We do not have to go through the effort of modeling the cash flows of all the various instruments in order to value the company, the WACC has done this all for us!

Simplicity has its benefits!

And it also has its drawbacks.

Problems with WACC

Using the Weighted Average Cost of Capital makes a number of assumptions.

Figure G

Term Structure Trap

Given the term structure in the upper portion, the payments in the first column of the lower portion are discounted in two ways, the first using the term structure and the second using the Year 3 debt rate. This results in an error of slightly more than 4% in valuation.

First, it assumes that rates are constant through the period we are considering. This is hardly ever the case in reality. Interest rates generally exhibit a "term structure", they vary depending on how long the debt will be outstanding. If we are going to pay off debt in 1 year, this rate is almost always lower than if we are going to wait 30 years to pay it off.

The general approach most take is to use the debt rate that reflects the length of time we are considering. If we need to use our WACC to value a 10-year payment stream, we will use the 10-year debt rate. If its 20 years, we will use a 20 year rate, and so on.

Figure G shows an example of this shortcut and how it results in a mis-valuation of the payments. We use the 3-year debt rate to value 3 years worth of cash flows. Because the cash flows are "lumpy" (not the same in every year), the valuation of them are driven more by the shorter term rates than the 3 year rates.

The solution to the above would be to use the actual term structure, weighted in accordance with the cash flows being evaluated by the WACC. Yet this can be difficult to do. Most companies do not have enough debt outstanding to establish a term structure on their own. In addition, there are points in the "term structure" spectrum which are more liquid than others - generally maturity related, such as 5 years, 10 years 20 years - which can impact pricing. There is less activity off these cycles, so if we have a 13 year cash flow stream it can be difficult to establish a term structure.

Awareness of this dynamic can be critical. If a company has used the WACC calculation to establish a "hurdle rate", which is the rate at which all investments will be evaluated, and has used long term debt rates to do so, then the business unit manager who has a 1-year project may be at a disadvantage, as their hurdle rate would be much lower had the WACC been calculated according to their shorter time horizon. This places the firm in a position where they will reject short term projects that would have in fact added value to undertake.

A second issue is the underlying assumption that the capital structure is constant throughout the term. Because we have calculated the value of tax shields and placed this cost of capital into the WACC, when this rate is used to discount cash flows the capital structure making up the WACC is assumed to be in place at that point in time.

So if we have a 13 year project we are valuing using our WACC, we are assuming that the capital structure (say the 50-50 in our Joe's eample earlier) is in place the entire time.

This again diverges from reality for a number of reasons.

First, capital structure is fluid, yet not generally thought of in that way. When we want to compare our capital structure to others, or earlier periods in our history, we generally use the balance sheet to obtain these numbers. The balance sheet is a "snapshot in time" portrayal of the assets and liabilities of the firm on a certain date. Yet, the assets and liabilities at a quarter end (the time usually for which balance sheets are prepared) may bear a different relation to the assets and liabilities in mid-month.

Figure H

Debt Capitalization Comparison

Second, a lot of the debt companies issue have "bullet" maturities, meaning all the principal is due at the end of the debt term in one lump sum payment. This will lead to the capital structure being uneven.

Figure H shows the debt percentage of a project's capital structure for an amortizing debt instrument and a bullet debt instrument. The bullet debt instrument is consistently higher than 50% of the capital structure for all years except for the first.

Figure's I and J show the detail behind this example. Note that for the amortizing debt case in Figure I, the respective internal rates of return (IRR) for both the debt and equity match their cost of capital as used in the WACC formula. In Figure J, they do not.

Figure I

Financed With Amortizing Debt

Cost of capital assumptions in the top left. Valuation of the cash flows using this are in the top right. The distribution of the cash flows for return on capital and return of capital are in the middle left portion. The distribution of cash flows for the debt and equity portions are on the right. An internal rate of return comparison is on the bottom left.

Figure J

Financed With Bullet Debt

Cost of capital assumptions in the top left. Valuation of the cash flows using this are in the top right. The distribution of the cash flows for return on capital and return of capital are in the middle left portion. The distribution of cash flows for the debt and equity portions are on the right. An internal rate of return comparison is on the bottom left.

Figure K

Perpetuity Financing

The Figure I and Figure J comparison highlights the fact that risk is impacted by how the debt payments are structured. In Figure I, the debt is amortized in proportion to the value 'consumed' by the project during that period of time. In Figure J, it all comes due at the end of the project, which means that equity holders have received their returns earlier, and actually have to contribute amounts in the final year to pay off the debt. This places the debt holders in a much more risky position than the ones in Figure I.

Figure K shows the case when the cash flows to be valued will go on forever (known as a perpetuity). In this instance, we can value the cash flows using the WACC or separately as debt and equity and arrive at the same value. This occurs because we have not violated the constant capital structure condition.

Another common problem occurs when we need to analyze a new project or investment. Since the WACC is driven by opportunity cost, our new project or investment will require a different WACC if the risk level is different than our other assets.

Going back to our Joe's example, we have a WACC of 8.4%. Let's say the company is evaluating whether it should buy some trucks to transport all their products around. Using the WACC calculated earlier will not be appropriate, because that was based on the opportunity cost of the agriculture business, not the trucking business. Owning and operating a fleet of trucks has an entirely different risk profile, and therefore requires a different WACC.

A shortcut often used is to use the face value of debt as a proxy for the market value. This is due to the fact that market values of debt can be difficult to determine. Debt securities are not traded everyday, and there is no end of the day ticker to establish value.

Sometimes face value is a 'good enough' approximation, but sometimes it is not. In Figure K, our WACC was established on 8% debt. If interest rates have gone down to 6% since that debt was issued, it will now be worth ♢ 79.37 rather than ♢ 59.52, a 33% difference!

What You Can Do

While the WACC calculation, as shown through these examples, has its fair share of warts, it nevertheless still has benefits.

It's a useful data point if taken in moderation - estimating our Weighted Average Cost of Capital provides a metric for us to refer to when valuing projects and opportunities, or for evaluating performance. This is better than nothing. The thing we need to remember is that it is not a 'be all, end all' calculation, but one piece of information among many.

Triangulate the WACC - calculating our WACC using different assumptions (changing the debt terms for instance) gives us a sense of the range of the measure. So while we may not be entirely confident that our 'true' cost of capital is 8.46731%, we may establish that it is likely to be somewhere between 8% and 10%. Another way we might establish a range is to calculate it for other firms that are similar to ours.

Key Takeaways

The Weighted Average Cost of Capital is commonly used to value a series of cash flows. However, it is prone to error because the underlying assumptions often do not match reality and/or the shortcuts applied in practice distort its value. Because of this, one should consider this calculation to be an approximation or indication rather than an absolutely correct value.

You May Also Like

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Resources

Excel Spreadsheet Used in this Post

Questions

::When was the last time you applied the WACC in an analysis?

::How many of the assumptions and shortcuts mentioned have you seen practiced?

::What other factors cause imprecision in the WACC calculation?

Add to the discussion with your thoughts, comments, questions and feedback! Please share Treasury Café with others. Thank you!

Why Your Cash Flow Forecast Will Always Be Wrong

Some folks sensed a "negative tone" on my part in our last Treasury Cafe post, "Answer These Questions For A Better Cash Flow Forecast", believing that I advocated an approach that would not require a lot of time, effort and attention.

In a sense, this perception has its merits - I am somewhat cautious about the forecasting process for a number of reasons, but that is by no means the whole story. However, if that is what appears closest to the surface, let's start from there and work our way forward.

Why is it that our cash flow forecasts will always be wrong?

The main objective of the cash flow forecasting process is to provide us a glimpse into the future...and therein lies the biggest problem.

Nobody can predict the future!...for a number of reasons.

Reasons #1 to #3 - Random Events Occur All the Time

Mother Nature delivers her fair share of unexpected windfalls and dissapointments to a business. Had we been forecasting in January, 2011 the cash flow generation of our Japanese business operations for the year would have been wildly off due to the earthquake and tsunami that occurred two months later. Conversely, the cash flow from sales forecast for our Chicago snowblower division would have been understated 4 years in a row (assuming we used average snowfall) from 2006-2010 .

Social factors are another potentially significant contributor to randomness. Imagine being a member of the hapless cash management staff at Abercrombie & Fitch at the beginning of this year, watching the fallout from our CEO's remarks wreak havoc on our cash inflows from sales estimates! Or, suppose we were Paula Deen's cash manager forecasting licensing and advertising revenue about 3 months ago. Would the remainder of this year be anywhere close to our forecast?

Economic and Market Conditions also contribute to uncertainty. Interest rate forecasts we made in the Summer of 2008 would be off by double or triple amounts come that Fall due to the onset of the "Great Recession". And less than a year before that, many would be stuck with investments in Auction Rate Securities because the auctions were failing and investors could not 'cash out' of their investments as planned. The market had never seen something of this magnitude ever in its history.

Reasons #4 to #5 - We Think Like Human Beings

Daniel Kahneman, the Nobel Prize winning scientist credited with a significant role in the development of Behavioral Economics, reports on numerous studies of human behavior which shows that we are quite likely to either overestimate or underestimate the liklihood of low-probability events (original paper here).

In addition, our human forecasting process gives weight, often at the sub-conscious, outside-of-awareness-level-of-thinking, to some events while entirely excluding others (called the "Availability Hueristic"). A lot of our thought processes exist on a "what you see is all there is" basis, with the result being that if we're able to quickly call something to mind we focus on it, and if we aren't able to call something to mind we ignore it. Thus, we individually and collectively possess a stong bias that makes it extremely difficult for us to be 'comprehensive'.

Reason #6 - Model Estimation Error

Statistical models, including those frequently encountered in forecasting such as regression or time-series analysis, if well-constructed will have an error rate that approximates the normal curve. If this is the case, then we can expect about 5% of our estimates to be greater than two standard deviations from the actual values.

In other words, on average 1 day out of 20 our estimation is going to be significantly over or under, even if we have a great statistical process.

Reason #7 - Low Payoff

If it is possible for some people to predict the future, it is quite unlikely they are toiling away day by day in a Corporate Finance group. They are much more likely to be sipping their Pina Coladas on a beach at your favorite tropical island resort after making their fortunes at the race track or in the financial markets.

Reason #8 - The Costs of Accuracy

In our last post, "Answer These Questions For A Better Cash Flow Forecast", we noted that cash forecasting involves a cost / benefit tradeoff. If we want a more precise forecast we are going to have to pay for it, in terms of money, time and attention.

To see how this works, let's consider a simple example. Let's say that customer payments is a line item in our 30-day forecast, and let's further suppose that these estimates come from our sales area, who are the folks in closest contact with the customer.

Over the past year, which is approximiately 2,000 working hours (250 working days x 8 hours per day), let's say that our 2-person sales team generated $10 Million in revenue. This amounts to a revenue generation rate of about $2,500 per hour.

For the sake of improved accuracy, let's further suppose that we implement a new requirement on the sales staff to provide us with collections information that has been validated with their customer's personnel.

Joe, one of our salespeople, knows that Company A's most recent invoice is due in a week. The invoice is for $10,000. He calls over to his AP contact in order to confirm the payment date only to discover they are out of the office. After many calls to others at Company A - going from a contact in purchasing to a manager in purchasing to the office of the CFO back down to the AP manager, who places him on hold for 10 minutes while they find out who has been assigned responsibility for the invoice in question, etc., we finally arrive at the fact that the invoice has been scheduled to be paid 2 days later than originally anticipated.

By the time the exercise has been completed, Joe has spent 2 hours on this task.

Assuming Joe would have achieved the average revenue generation rate during that time, we have forgone $5,000 in additional revenue in order to be 2 days more precise in our cash forecasting accuracy. For the $10,000, let's say that the knowledge of its timing allows us to invest or avoid additional borrowing at an incremental rate of 1% (note: we're being generous with that number given today's rates!). Our total return for those 2 days is a whopping $0.55 (10000 * 1% * 2 / 360)!

Spending $5,000 to earn $0.55 is not a successful business recipe!

Reason #9 - There is No Way to Know When You're Right or Wrong

Suppose I tell you that there is 50% chance of rain tomorrow, and tomorrow it rains. Was I right in my forecast?

What if it did not rain? Was I right in my forecast then?

Unfortunately, there is no way to really know. When Mother Nature "rolled the dice" to determine today's weather and came up "rain", we do not know if those dice reflected a 1% chance of rain, or a 10% chance, or a 50% chance, or a 90% chance, or a 99.99% chance. We only know that it either rained or did not rain. Since we do not know the "probabilities of Mother Nature's dice throw", we cannot calibrate our model against it.

As Taleb points out in The Black Swan "You see what comes out, not the script that produces events, the generator of history."

What we would like to learn as we develop a track record is "oh, it rained today so I see that it should have been a 60% chance rather than 50%". Unfortunately, we only know that it rained.

The process of separating the outcome from a forecast's validity is difficult for many to grasp - "hey, if it rains the forecast that predicted rain was a 'good forecast'". Statistical methods rely on the 'law of large numbers'. If we roll a die and come up with a 3, we need to roll it many more times to understand that a 3 comes up 1/6 of the time, as does 1,2,4,5 and 6. If we 'forecast' a 3 and a 3 is rolled, it is not a 'good call', it is lucky.

Let's take an extreme example to emphasize the point. If your child picks up a 6-shooter loaded with 5 bullets, makes a deal with your neighbor that if they 'win' they get $1 million, put the gun to their head and pull the trigger, and survive, would you call that a "good decision"? After all, they are now $1 million richer. Taking foolish gambles are not sound forecasts even when they happen to payoff. This example illustrates that you cannot base an assessment of a decision's or prediction's quality based upon the single outcome that resulted. And because tomorrow is another day, all we are ever going to get is a single data point.

What Can We Do?

Given this litany of reasons, should we abandon the cash forecasting process?

Of course not!

As we discussed in "Answer These Questions for a Better Cash Flow Forecast", we need some assessment of our future in order to manage our liquidity, financial strategy, metrics, and potential options.

So how to reconcile the fact that we need to forecast even in the face of knowing that it will be wrong?

Encourage Ownership

I can remember a conference session where the speaker emphasized that we should "hold people accountable" for the forecasting process.

In the corporate world, "holding people accountable" is generally a euphamism for "hit your objective....or else", with the "or else" being something along the lines of no bonus, becoming manager of the firm's Siberian operations, getting fired, or some other drastic form of punishment.

The problem with using this "stick" approach, as Daniel Pink discusses in his book Drive (see here for a synopsis by Checkside HR), is that it actually hinders productive, creative, collaborative problem-solving, which are exactly the forces that will make a cash-flow forecast better!

Instead, generate a sense of ownership utilizing people's intrinsic motivation instincts (what Pink calls "Management 3.0"). This can be done through regular team interaction focused on three things: 1) objective review of prior forecasts, 2) open discussion of upcoming forecasts, and 3) illustration of the organizational consequences of both.

As an example, we sit down with our forecast stakeholders and discuss the most recent prior forecast. Without allocating blame, and avoiding a scolding tone, we neutrally comment on where variances have occurred, explore the processes that led to the original forecast, and brainstorm potential methods that might realistically be deployed. We further note that because of these variances on one day we had to arrange emergency, 'late in the day' funding (which is much more expensive), thereby costing the company x.

Or, as future forecasts are developed, we can identify some of the organizational actions that will occur based on it - financing plans, timing strategies, etc. As the consequences are understood, areas where attention may not have been focussed can become apparent. "Oh, I see that extending the term is x amount more costly, perhaps the timing of this large payment can be accelerated".

Be Open-Minded

Given that there are at least nine reasons why the forecast will always be wrong, approach the process with an open, 'willingness to learn' mind set rather than an 'assignment of blame' exercise. Given the many forces outside of their control, it is unreasonable to expect forecast perfection, and those who appear to do so will be resisted and lose respect.

The more information and insight we can gather, the better able we will be to develop the best forecast process possible (even though it will be wrong). The means to open the information spigot is to make conversations and discussions positive experiences, exemplary of respect for each participant's contributions and input.

People will 'clam up' if they sense that a witch-hunt is going on, and will no longer consider themselves stakeholders in the game.

Focus on the Drivers in Order to Learn

Most forecast numbers, at their root, are generated from a Price-Volume relationship. A cash inflow estimate may relate to revenue (i.e. units sold times price), or accounts receivable collections (number in the 'bucket' times payout percentage), or something similar.

Assessing variance between forecast and actual along the driver lines allows us to develop insights. Is our forecast off because of volume reasons or price reasons?

Future actions can be determined based on this type of analysis. If volume is up, what are the market factors that made it so this month, and are they likely to continue or 'revert to the mean'? If payout percentage has dipped, what additional organizational resources would it take to get that figure back up to where we had originally planned?

Maintain a Number of Scenarios

We have established that our cash forecast will always be wrong for at least nine reasons. Practically speaking, we must be willing to consider a number of alternative environments we may be operating in during the future.

Given the critical nature of cash, we cannot use the 'expectations approach' often described in the textbooks. For example, using this approach, if our forecast has a 95% chance of being "off" by as much as 100,000 and a 5% chance of it being 1,000,000, then expectation theory would tell us to hold 145,000 each day.

Unfortunately, this doesn't help us at all!

For 95% of the time, rather than holding 100,000 in "cushion" we would be holding 145,000, thereby increasing the cost of maintaining adequate liquidity during these times.

However, for the 5% of the time where it is 1,000,000, the fact that we have 145,000 isn't going to mean anything significant, since we still won't have enough to cover the error, so we end up bankrupt all the same even though we had calculated this expectation event. We might as well have just held 100,000.

Instead, we need to have contingency plans in place for a number of different events. Is there an alternate funding source we can develop to help us deal with those 5% days, while on the others need only cushion the 100,000?

Or, can we operate as if the 1,000,000 will always occur while maintaining normal practices? This is sometimes possible.

Rather than catalog a long list of events, the impact is inevitably a time-frame issue such as "what is our 'late in the day' capacity?" or "what is our 'liquidity constrained daily market' capacity?"

For example, assume we are a firm issuing commercial paper (CP) to fund its day to day cash needs. In normal markets we can issue 100 million with no problem, while on 'liquidity event' days we can only issue 10 million. Using our cash-flow forecast, we can issue CP in such a way that our daily issuance requirements are no more than 10 million. By using this type of strategy, we have taken the impact of market shocks (due to whatever the nine reasons we know will eventually occur!) 'off the table'.

Of course, market events are not the only source of randomness, so we may need to add other contingency plans for other types of situations that may occur. The result is that we end up with a "playbook" that contains a number of activities and strategies that allow us to "sleep easy" even when the inevitible forecast errors show up, no matter the reason.

Key takeaway

The world is unpredictable enough such that the best laid plans get laid to waste, and so it goes with our cash flow forecast. However, the process is useful even if it is not going to ever be perfect. In order to maximize this usefulness, we need to encourage "collaborative ownership", establish contingency plans, and go through the evaluation exercises in order to derive actionable insights, identify trends, and remain 'on top' of the situation.

You May Also Be Interested In:

Answer These Questions For A Better Cash Flow Forecast

Working Capital Primer: How Is It That This Capital Works?

Cash Conversion Cycle - A Good Measure?

Questions

::What other reasons have I overlooked that will cause a cash flow forecast to be wrong?

::What types of forecast contingency plans do you have in place?

::What process steps have you undertaken that make the process more productive?

Add to the discussion with your thoughts, comments, questions and feedback! Please share Treasury Café with others. Thank you!

You’re Not Diversified Enough for a Reason

The discussion of Apple’s dividend decision resulted in the exploration of factors that occur in real-life that deviate from the Perfect Capital Market Assumptions of financial theory, and how these impact our Financial Strategy.

The final item under this set of assumptions is Absence of Transaction Costs. This is a deceptively simple assumption, yet holds a large amount of implications.

Diversification is Key

One of the most basic principles of investing is to diversify your portfolio - having too many eggs in one basket increases your risk. Sure, if you invested 100% of your money in Google or Apple back in the day you may have hit a home run, but only in hindsight do we know that these were the correct picks.

The investment is made before you know the outcome. There were a lot of people who thought Webvan was the next Amazon, and you would have no money left if you had put 100% into that.

The “eggs in one basket” investment strategy will ultimately leave you hungry almost all of the time.

Theory Says….

Going to the other extreme, a lot of the highly regarded (Nobel Prize winning even) academic theories such as the Capital Asset Pricing Model assume that the investor is invested in the entire market.

So let’s pretend for a minute that the entire market is comprised of only 100 stocks spread out throughout the world. Furthermore, each of these stocks currently trades for $100. Finally assume that we have $10,000 to invest.

Figure A

If there were no transaction costs, investing in each and every stock is not an issue, and we would own 1 share of each firm in the market (100 x 100 = 10,000 : what we have available to invest).

Now let’s assume a stock trade costs $9.95 per trade. Figure A shows how much we actually have invested in the market after paying for the trade, and we can see that the fewer stocks we own the more we have invested, since we have made fewer trades that we had to pay for.

Therefore, because of transaction costs, we will tend towards holding smaller, more concentrated, less diversified (and therefore riskier) portfolios than we otherwise would.

In the Mind of the Investor

Because we have paid something to own the stock, we also experience the fact we begin our investment with a loss! We buy one share of stock for $100, it costs us $109.95. The price needs to go up by almost 10% just for us to break even on the purchase! But that’s not all, since we would still have a loss if we sold it at that point. If we count the buy event and the sell event together (a “round-trip” in trader talk), our stock needs to go up by 20% just to break even!

Of course, if we buy 100 shares instead of 1 share, these percentages are a lot smaller, so again there is an incentive to concentrate investments in fewer securities so we can spread that $9.95 over as many shares as possible.

But there is also a psychological element. The field of Behavioral Finance is a study in and of itself, but one of the things that has come from that field is that our losses hurt us much more than our gains help us. More pain is caused by a $10 loss than the pleasure of a $10 gain.

What happens then is that people hold on to their losers longer than they should in the hopes that the stock will rebound, thereby alleviating all that pain from loss.

With transaction costs, we begin the investment in this painful loss position (remember in the example above we have something worth $100 that cost us $109.95), and we will therefore have a tendency to hold on to this investment longer than we ought.

Conclusion – transaction costs result in investors holding on to investments longer than they should.

Tipping Points

Transaction costs also impact our trading strategy given our expectations of the investment.

Let’s say that we own a stock that will pay out $10 next year, and we have a discount rate of 12% and expect growth of 2% per year. We will value this at $100 using the Dividend Discount Formula, and everyone else in the market is of the same view.

Now the market hears some positive economic news that raises their growth expectations to 2.5%. Because of this, the stock price will rise to $105.26.

We, however, do not believe this economic news and consequently now own a stock we think is overvalued. Because we want to sell high and buy low, our desire now is to sell this stock. However, if we were to sell we would incur the $9.95 cost and we would recoup only $95.31. We are better off holding onto the stock even though it is overvalued.

The change in growth expectations needed to result in a net outflow of $100 given the $9.95 transaction cost is 2.9%. Thus, until the discrepancy between the market’s expectations and ours is great enough, we will not be able to make a transaction that keeps us whole with respect to our value expectations.

Conclusion – transaction costs make immediate reaction less likely, until the gap between the market’s expectations and the individual investor’s is great enough to attain a “tipping point”.

Steps We Can Take

Transaction costs are unavoidable. As an organization, if we are going to acquire or merge with another firm there will be fees we pay to investment bankers, lawyers, accountants, consultants, and others.

Given that transaction costs will occur, our organization’s decisions and behavior may differ from what is “theoretically correct” for valid reasons. However, we also do not want to be led into decision traps (e.g. holding onto losers too long, remaining too concentrated in a line of business) that we can avoid. To that end, we can take the following steps:

Know Your Cost of Capital – as discussed in earlier posts about the Capital Asset Pricing Model, the cost of capital is a “fuzzy” number. The cost of capital we choose to use has a range associated with it. Erring on the high side of that range will allow some absorbing of transaction cost impact without a whole lot of additional work.

Some prefer to model transaction costs explicitly and then apply the cost of capital to the post transaction cost cash flows. This approach is technically incorrect, as the derivation of the cost of capital did not include these items (e.g. it was calculated on pre-transaction cost returns).

Establish Diversification Targets – In order to protect against the tendency to hold fewer investments in the portfolio, a qualitative assessment (using strategic tools) combined with a non-transaction-cost-influenced quantitative assessment can be performed in order to establish targets. By doing this, it changes the perspective of the later analysis as it is not anchored initially on the transaction costs, and they can be layered in and assessed independently.

Establish Exit Targets During a Pre-Mortem – By assessing the conditions and economic signposts under which a divestiture or sale is warranted at the time of the investment initiation, we can establish a more objective target at the onset that will not be influenced later by transaction costs-du-jour. This will help us avoid holding onto investments too long or waiting for a “tipping point”.

Key Takeaways

The presence of transaction costs incents the firm to invest in fewer activities, diversify less, and remain invested longer than traditional theory suggests. By performing up-front analysis of our investments at the time we are embarking upon them, we can mitigate the impacts of some of the decision traps that may be caused later.

Questions

·         What examples of negative decisions caused by transaction costs have you experienced or witnessed?

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Five Things You Can Do To Counteract Irrational Bias

Are financial markets filled with rational investors? Before we even begin to look at the evidence, we know intuitively that this cannot be the case - the dot com boom and bust, the financial crisis of 2008, and Dutch tulips are but a few examples of the tendency to form bubbles that subsequently pop.

What are the implications for our dividend and financial strategy given that Perfect Capital Market Assumption #4 – Rational Investors and Markets – does not hold in the real world?

People are People

The reason that the Rational Investors and Markets assumption does not hold is simply the fact that all participants have one thing in common – they’re people!

And as people we are all subject to very human foibles (from a believer in economic rationalism, anyways) – acting on emotion, deciding based on our “gut”, honoring relationships, loyalty, tapping into our primordial instincts, etc. There is a long list of cognitive bias that we are subject to.

There is Safety in Numbers – and Risk!

One of our human traits is the herd instinct. We congregate into families, tribes and communities. We identify with various collectives of people – our city, our church, our profession, our company, our country. Hermits living in the woods are viewed as strange, abnormal folks.

A lot of the bubble-and-burst activity is tied to this tendency. Our friends buy tech stocks, talk about them at parties, and we call up our broker and order them the next day. Or our analyst buddies at XYZ are bullish on a stock, we become bullish too, which makes it easier to share a drink with them after work.

Yet, as Warren Buffet says - “Be Fearful When Others Are Greedy and Greedy When Others Are Fearful”. This quote points out the need to be the contrarian when it comes to financial markets. If you follow the herd you wind up running over the property value cliff, the dot com cliff, and the Dutch Tulip cliff.

The fact is, you need to run away from the herd in order to succeed.

Companies are People Too!

Companies are but an aggregation of people, and thus the same traits define them to some extent. Many companies exhibit the same irrationality that applies to individuals.

If your firm spends its time courting sell-side and buy-side analysts, it will end up thinking like these folks and seeking to deploy strategies that will satisfy this stakeholder group. Positive NPV? Not when the analysts are focused on Earnings Per Share (EPS)!

Another example is the timing of share repurchases. Research by McKinsey shows that companies on average are much more prone to buying near the top than the bottom. This is likely a combination of the overconfidence bias coupled with the social reinforcement firms receive from their analysts.

Five Things You Can Do to Counteract Irrational Bias

As an organization with the ability to harness the hearts and minds of our many constituents, we are in a position where we can counter-act the human tendency toward irrationality. How can we accomplish this?

Encourage alternative viewpoints through the culture – there are those within your firm that are able to articulate an alternative view of the facts quite different than the accepted norm. In order for these folks to come forward, a culture of awareness, tolerance, and acceptance are required. See here for additional information.

Encourage discovery through formalized process – the Catholic Church anoints a “Devil’s Advocate’ when it comes to determining sainthood. The role of this person is to present the strongest case possible that sainthood is not warranted. This role can be adapted to the strategic planning process and the capital investment allocation process. The key element is ‘immunity’ to those who play this role. See here for additional information.

Perform Introspective Activities – entrepreneurs are sometimes known for their “shoot from the hip”, “decide on the go” style. In order to avoid bias, however, there needs to be a capacity to reflect objectively on behavior without remaining anchored in the heat of the moment. See here for additional information.

Conduct a ‘Pre-Mortem’ – as part of a project planning or group implementation effort, participants can be asked to provide a ‘pre-mortem’ assessment of the effort. This is a twist on the “what do you want on your tombstone” exercise. However, rather than focus on the mission in life, members are asked to provide insight as to how things went wrong in the effort that ultimately made it unsuccessful. See here for additional information.

Learn How to Generate Feedback without the Herd – part of our tendency to follow the herd is that it provides immediate feedback - “They go left, I go left, therefore I am doing something correctly.” Develop benchmarks that are “Herd Independent”. Create your goals in the “vacuum of continuous improvement”. For example: “I know I did x with y this past year, so I am going to shoot for x with z (z being less than y) this coming year”. See here for additional information.

Key Takeaways

The tendency of human nature is irrational. It takes a lot of organizational initiative, structure, and willpower to overcome this, and for this reason organizations rarely attain this standard. This provides us with a golden opportunity.

Questions

·         What suggestions do you have for activities and processes that will enable an organization to overcome basic human irrationality?

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Costs of Financial Distress and Financial Strategy

Continuing on in our series about perfect capital market assumptions and what occurs when we confront reality, with this post we turn towards the concept of “Financial Distress”, #3 on our list.

The previous topics we have looked at – Perfect Information and Taxes – have had relatively straightforward implications when we have examined reality’s divergence from the perfect capital market assumptions. This is not the case when it comes to Financial Distress.

What is “Financial Distress”?

Financial Distress is not very easily defined - ask five people what it means and you will likely get five different answers. We can take a point of view that varies along a wide continuum, from limited scope to broad.

At one end (the “strict view”), it is the costs of going into bankruptcy – legal fees, court fees, etc. It is not the loss of stock value, etc., but literally just the cost associated with the event. At the other (the “expanded view”), if one can only afford a Fiat rather than a Ferrari this can be construed as “distress” by some.

Fundamentally, what these extremes have in common is the fact that there are not sufficient funds available to make necessary expenditures (the key word being “necessary”, and this is subjectively defined).

Bankruptcy

Bankruptcy events are the most obvious financial distress situations. In some cases bankruptcy results the reorganization of the firm, after which time it “emerges” in a transformed state. Often this occurs with losses to former debt and equity holders. In other situations bankruptcy results the cessation of the entity as a going concern and ultimately results in that entity’s liquidation.

Figure A

Theoretically, the cost of financial distress in the bankruptcy situation can be calculated. Simply add up the additional costs of filing for bankruptcy (legal fees, court fees, etc.), along with the losses to debt and equity holders, and multiply this times the probability of the firm going bankrupt (Figure A).

While Great in Theory…

Practically speaking, this is not so simple. How does one determine the probability of bankruptcy?

The major ratings agencies, Moodys and Standard and Poor’s, have a wealth of historical data on default frequency and losses given default for securities that they provide ratings for (I have not linked this as they require a subscription). This data can be useful for some purposes, such as pricing rated debt.

However, this is not the full universe of companies. The local corner coffee shop or your Uncle John’s farm are probably not rated by either ratings agency. In statistical speak, the ratings agency data are not a representative sample, and therefore we cannot confidently draw conclusions from this data for every type of firm.

Financial Distress Can Be So Much More

Even if we had representative data, using an “expanded view” of financial distress leads us to other costs that are not captured in that calculation.

Let us say that we are shareholders in Farmco. Last year, Farmco generated ²10 in cash (the symbol ² representing Treasury Café Monetary Units, or TCMU’s). Let’s further say that Farmco has a dividend of ²8 per year. This indicates that Farmco retains ²2 per year. As discussed in our initial Financial Strategy post, we expect that Farmco invests these funds at our cost of capital, which for the sake of this example we say is 10%.

In the farming business, one can increase crop yields by installing drainage tile in areas that have higher than normal wetness. This wetness may come about due to the slope of the field, the elevation of the field relative to its neighbors, waterways, etc.

If we could install drainage tile on Farmco’s eligible sites, we could generate an additional ²1 per year due to the incrementally higher yield. If we have a 10% cost of capital, we would be willing to make this investment so long as it did not require more than ²10 (using the Dividend Discount Model and assuming the investment lasts forever).



Figure B

However, due to the fact that Perfect Capital Market Assumption #1 (perfect information by all participants) does not hold, we are able to make this investment for ²5 instead, which means this investment will yield 20%, a significant premium to our 10% requirement.

Figure B shows the result of this on the value of Farmco (an increase of slightly more than ²3 from the base value calculated in our last post) under the fully retained cash condition.  

However, due to Farmco’s dividend policy, it only has ²2 available to make this investment. If it chooses to cut its dividend, as we discussed in Apple’s Dividend – A Good Financial Strategy?, this will provide a negative signal to the market, offsetting part or all of the additional return this investment opportunity presents.

Figure C

By funding internally but delaying part of the investment until year 1 and year 2 when it has the funds, Farmco executes the investment opportunity and realizes the value, but on a delayed basis. This impacts its ultimate return, due to the time value of money, by about ²0.35. The delay in activity and subsequent valuation are shown in Figure C.

Income and investment opportunities that are delayed or forgone are also, in the broad view, costs of financial distress.

Yet the Costs of Financial Distress Remain a Mystery

The big problem, however, is that fact that these factors are never objectively known or able to be quantified precisely ahead of time. In fact, shareholder’s likely will never know. After year 1 Farmco will probably not say “we had ²5 in investment opportunity at 20% and only did ²2”, rather it will state “we made great investments this year, and remain expectant that, through our business development efforts, we are confident that other similar opportunities may present themselves in the future”. This is a very difficult statement to infer costs of financial distress from.

The fact that the true costs of financial distress cannot be measured, let alone determined, makes this cost a very “theoretical” exercise, which does not lend itself well to organizational decision-making processes. These are usually attuned to “hard” numbers rather than theoretical ones, yet the fact remains that opportunities were not taken and shareholder value suffered as a result.

Key Takeaways

Costs of Financial Distress are great in theory, and can be used to explain events that occur in financial management of organizations and in the markets. Costs of Financial Distress are real, even if they cannot be measured. Because of this, they may not always be taken sufficiently into account.

Questions

·         What examples do you have of the Costs of Financial Distress?

Add to the discussion with your thoughts, comments, questions and feedback! Please share Treasury Café with others. Thank you!