Monkey Business, John Rolfe and Peter Troob

An intense book. I'd call it 'fair warning' for those of us thinking of 'swinging through the wall street jungle' as the tag line suggests. It's a collection of sordid stories about the life of investment bankers from Harvard and Wharton. A good read even if you have little interest in banking.

This book focuses on the life cycle of an associate (what I'm hoping to become when I finish my MBA). It outlines all the details, starting from recruitment for the summer internship at DLJ right up until the moment they decide to leave the investment banking world.

A timely read for those of us also writing our CFAs with great aspirations. Get a preview about what you are potentially getting into. No surprises.

Sent from my BlackBerry device on the Rogers Wireless Network

Posting Shortfall

I apologize for my regular readers who were expecting CFA related posts for the past three days on this blog, only to be disappointed.

This weekend, I received an offer for an internship in New York city with an equities research firm and I've been busy sorting out which visa status I need to undertake so I've been busy with calls to various sponsorship agencies like SWAP USA, CDS and AIPT as well as the US Consulate and CBP.

Also, OSAP recently underwent an upgrade and opened yesterday, but the traffic was so bad, I got booted from the system for 24h (if you read my post on BCP, you'd understand why I was a little annoyed). I just finished my student loan application through OSAP and am now waiting for final approval for my government loan.

Also, there was a 'Meet the Dean' session at Rotman as well as a free lance consulting project meeting that I had to take care of Monday evening. I have been reviewing, but I covered most of the interesting topics and am now working on topics which I'm having particular trouble with (so I can't pretend to have any sort of expertise in posting the solutions here).

However, if I do encounter interesting topics which would make good posts, I'll take a break from answering questions and put up a post here.

2 Week Hiatus

I will be going on a two week hiatus in preparation for the CFA Examination on Saturday June 6th, 2009.

However, I will continue to post on Amongst the Stars, my Investment Blog, with a focus on CFA level I examination related topics and concepts.

Wish me luck!

Financial Ratios, pt 4 - Profitability Ratios

[ Financial Ratios, Part: 1 - 2 - 3 - 4 ]

Profitability ratios are probably the most universally understood ratio because of their direct impact on the bottom line as well as they encompass the idea of adding and creating value (the foundation of the capitalist structure). They describe the financial efficiency of an organization as well as provide a basis for valuation ratios such as PE ratios.

Return on Sales
Return on sales margins use revenue in the denominator. By looking at the operations process, company management can determine their profitability at different stages.

Gross Profit Margin = Gross profit / revenue
Net Profit Margin = Net income / Revenue

Return on Investment

Return on Assets (ROA) = Net Income / Average Total Assets
Return on Equity (ROE) = Net Income / Average Total Equity

The two major components of DuPont Analysis, these two ratios summarize some of the most fundamentally important concepts in investing. How much have I put in, and how much am I getting out? Higher ROAs and ROEs are the target of any good security. The only downside to extremely high ROAs or ROEs is that the earnings are usually volatile (risk. Or in other words, something that looks too good to be true, usually is).

[ Financial Ratios, Part: 1 - 2 - 3 - 4 ]

Financial Ratios, pt 3 - Solvency Ratios

[ Financial Ratios, Part: 1 - 2 - 3 - 4 ]

Solvency ratios are similar to liquidity ratios except that they focus on the long term ability of the firm to meet it's debt obligations. As a result, by looking at solvency ratios, you can determine leverage, coverage, etc.

Because solvency looks at the broadest measures of financial position, the terms which most often appear in solvency ratios are the bottom lines of balance sheets (Assets, Debt and Equity). Recall the fundamental accounting principle that

Assets = Liabilities + Equity

Basic Solvency Ratios:

Debt-to-Assets = Debt / Assets
Debt-to-Equity = Debt / Equity

Financial Leverage of Assets (FLA):

Financial Leverage = Assets / Equity

A critical part of DuPont Analysis, Financial Leverage also identifies the overall riskiness of the company (higher leverage = higher risk) and directly affects return on equity (ROE). Financial leverage is the cornerstone of financial investing and can turn a "good deal into a great deal".

Note that FLA can be determined from D/E.
FLA = A/E
= ((D+E) / E)
= E/E + D/E
= 1 + D/E

Interest Coverage:

Interest Coverage = EBIT / Interest Payments

Interest Coverage describes your ability to make interest payments. If this is less than 1 this is a *DISASTER*. It means that not only do you have enough money to make your interest payments, but you can't even begin to consider paying down your principle let alone think about profits. This also implies that your principle will grow (interest not immediately paid off becomes part of the new principle amount). I would expect any company with an interest coverage ratio of less than one is quickly and unceremoniously headed for bankruptcy.

By that very token, I would suggest that this ratio isn't actually very useful except to tell you how much trouble you are in (at a time when it's too late BTW). Since the numerator is EBIT (which is directly related to net income and retained earnings), you generally want this number as sustainably high as possible) so unlike some of the previous ratios, there is very little downside to having exorbitantly high interest coverage ratios.

Fixed Charge Coverage

Fixed Charge Coverage = [EBIT + lease payments] / [Interest + lease payments]

Similar to the idea of the interest coverage ratio, the fixed charge ratio takes into account lease payments. It is a little more all encompassing in that it also considers lease payments (not considered discretionary).

[ Financial Ratios, Part: 1 - 2 - 3 - 4 ]

Financial Ratios, pt 2 - Liquidity Ratios

[ Financial Ratios, Part: 1 - 2 - 3 - 4 ]

Liquidity ratios are very important ratios which describe the company's ability to meet its short term obligations. Liquidity shortfalls (liquidity ratios of less than 1) indicate cash flow problems and may require the company to acquire short term financing on short notice (usually the larger and more urgent the need for "convenient" cash, the more expensive the financing).

The three most common liquidity ratios are the Current ratio, Quick ratio and Cash ratio (increasingly conservative ratios). These ratios are also related to the activity ratios we had previously discussed.

In each of the ratios the denominator is the current liabilities.

Current Ratio

Current Ratio = Current Assets / Current Liabilities

Probably the easiest to calculate (seeing as Current Assets is a line item in a Balance Sheet). It is the broadest liquidity ratio, including all current assets. As a result it is also the least conservative.

Quick Ratio

Quick Ratio = [Cash + Equivalents + Receivables] / Current Liabilities

While Current Ratio takes into consideration all of your assets, what if you determine that your inventory is not liquid enough (not enough turn over) to be able to contribute to your liquidity (maybe you sell large products infrequently - looking at your inventory turn over should give you an idea). By removing inventory from consideration as relatively illiquid, the quick ratio is a more conservative measure of liquidity.

Cash Ratio

Cash Ratio = [Cash + Equivalents] / Current Liabilities

The most conservative of all ratios is the cash ratio. It literally assumes that all your receivables go into default (doesn't include them in the numerator) and is very much a "bird in the hand is better than two in the bush" measure of liquidity. A company with a cash ratio of 1 or higher has a very low likelihood of short term cash flow issues as they can cover all their liabilities with cash.

While having a high liquidity ratio is generally good, having TOO high a liquidity ratio can be just as bad. How is that? Because it means that you are inefficiently using your capital. A company which has good asset turn over and few default accounts would be foolish to have a Cash Ratio of 1. Having liquidity is another form of safety, and following the golden rule of investing: the more risk you can reasonably assume, the more return you can expect.

[Example] A company has a Current ratio of 2, a Quick ratio of 0.9 and a Cash ratio of 0.8. If the company is about to order more supplies to create more inventory, what is the net effect on each ratio?

[Solution] First, assuming that the value of the supplies (AP a current liability) is equal to the increase in inventory (Inv a current asset), the net affect will be as follows:

• For a ratio containing inventory in the numerator, the ratio will approach 1 (numerator and denominator increase at an equal rate, but are still weighted with previous values).
• For a ratio NOT containing inventory in the numerator, the ratio will decrease in size (denominator increases)

This means that:

1. The Current ratio, which contains inventory, but is greater than 1, will get smaller (closer to 1).
2. The Quick ratio, which contains inventory, but is smaller than 1, will get larger (closer to 1).
3. The Cash ratio, which does NOT contain inventory, will get smaller.

[ Financial Ratios, Part: 1 - 2 - 3 - 4 ]

Financial Ratios, pt 1 - Activity Ratios

[ Financial Ratios, Part: 1 - 2 - 3 - 4 ]

An important component of financial statement analysis is comparisons based on financial ratios. Financial ratios normalize information against size and provide a baseline for comparison with previous years as well as competitors. While comparing two financial ratios may seem meaningless on the surface, comparing two numbers from the past or with a competitor can give information about direction and relative performance.

As with any mathematical ratio, you have a numerator and a denominator. Each financial ratio contains different items in the numerator and denominator and are therefore subject to certain bias or able to describe different aspects. Again, ratios describe interesting relationships when near the value of 1, meaning the numerator is higher than the denominator (for ratios such as coverages etc).

This post will focus on Activity (Operational) financial ratios. These are ratios that measure the efficiency of operations (payables, receivables, inventory, COGS etc).

I had written a post previously about cash flow as the life blood of business in my management consulting blog which deals with the basics of cash flow as well as some queuing theory.

Inventory Ratios

Inventory Turnover = COGS / Average Inv

Inventory turnover describes how many times over an inventory is sold. A high inventory turnover probably indicates that your product moves well, or (in a more negative sense) that you aren't stocking enough and possibly losing out on sales because of stock outs.

Days of Inventory on hand (DOH) =
Number of days in period (usually 365) / Inventory Turnover

DOH is a measure of how long your inventory is sitting idle in storehouses or distribution centers before being sold off (converted) in accounts receivable.

Receivables Ratios

Receivables Turnover = Revenue / Average Receivables

In a parallel train of thought as inventory turn over, receivable turnover is a measure of how much value is sitting in revenue relative to AR. As a collelery to the previous concepts:

Days of Sales Outstanding (DSO) =
Number of days in period (usually 365) / Receivables Turnovers

This describes how long revenues are accrued before being collected on average during the operating year.

Payables Ratios:

Payables Turnover = Purchases from Suppliers / Average Payables

Number of days payable =
Number of days in period (usually 365) / Receivables Turnovers

You'll note the pattern where the you can subsititue either the word 'inventory', 'receivables' or 'payables' using the same formulas to see different relations. In this case, how long it takes for you to pay your suppliers.

[ Financial Ratios, Part: 1 - 2 - 3 - 4 ]

Business Continuity Series, pt 5 - Implementing the Plan

Once all the homework has been done understanding the relationships and inter-dependencies and once the plan has been put together, it's time to test and implement the plan.

At this stage there is a tricky conundrum. On one hand, in order to do a realistic test, planned outages are required for live services to ensure that systems will be resilient in the manner anticipated (reducing the shock of discovering additional failures during an actual disaster). However, deliberately causing outages is the last resort of any service provider.

Even in the best conditions, where service consumers are notified in advance with a long lead times and everything goes according to plan it is usually heavily orchestrated event that consumes many non-revenue generating resources.

Testing the plan should attempt to avoid being disruptive. As with any change management procedure, downtime should be kept to a minimum and attempts should be made to reduce the impact on live customers (usually translating into "off-peak testing", coming in late on a Saturday night or early Sunday morning).

The shutdown of highly technical and regulated services like nuclear power plants usually requires all hands on deck at the most ungodly hours of the night (colleagues of mine working with in nuclear power remind me that their credo is "Never forget that you work in a very unforgiving industry").

In this stage, often managers and professionals discover more inter-dependencies implying that their plans are either incomplete or not as robust as they had anticipated. This is where GAP analysis comes into play to further develop the plans.

Even in the event of an ideal and perfect implementation of a BCP plan, there is still the requirement of ongoing vigilance. This is because that as the environment changes, certain assumptions which become obsolete suddenly cause vulnerabilities to appear in the system. At this point, BCP projects evolve into on-going BCP maintenance programs.

Weighted Averages

Another recurring mathematical theme in the CFA is the weighted average (probably because it is so universally useful). It appears in portfolio management, expected returns, WACC, indexing etc. It essentially takes the components of a group, takes the proportional weight of each and determines the value of the aggregate. Example:

S = (wα x vα) + (wε x vε) + (wρ x vρ) + ...
Where w is the weight of of each component expressed as a percentage of the whole and v is the value of each component.

For portfolio management, each component is an individual security's expected rate of return.

[Example] A portfolio is make of three stocks A, B and C. A has an expected return of 8% and makes up 20% of the portfolio. B has an expected return of 10% and makes up half of the portfolio. Finally C has a return of 12%. What is the expected return of the portfolio?

[Solution] E (Rp) = wA x E (RA) + wB x E (RB) + wC x E (RC)
= 8% x 20% + 10% + 50% + 12% x 30%
= 1.6% + 5% + 3.6
= 10.2%

For weighted average cost of capital (WACC), each component (debt, mezz and equity financing) of cost is weighted by proportion again:
[Example] A company issues bonds with at a cost of 4% which accounts for half of their capital. The required rate of return for their projects is 9% and they have an issue of preferred shares out for of 6%. They have twice as many common shares issued as preferred. If their tax rate is 30%, what is their WACC? Assuming that preferred shares are treated as debt, what is their total financial leverage ratio?

[Solution] Note in this case: we = 2wp and wd = 50%
wd = 50% = 100% - wp - we
wp = 16.7%
we = 33.3%

WACC = wd x kd x (1 - tax rate) + wp x kp + we x ke
= 50% x 4% x (1 - 30%) + 16.7% x 6% + 33.3% x 9%
= 1.2 + 1% + 3%
= 5.2%

Financial Leverage of Assets (FLA) = A / E
On a percentage basis:
A = wd + wp + we = 100%
FLA = 100% / 33.3%
= 3

[Example] An market weighted index is composed of three stocks A, B and C. A is worth $50 and composes 50% of the index. B is worth $10 and is 30% of the index. If C increases in value by 15%, what is the increase in the index?

[Solution] Initial Index = 100%
Final Index = 50% + 30% + 20% x (1.15) = 103%

The index increases by 3%

Dividend Discount Model, Fundamentals and Supernormal Growth

The Dividend Discount Model (DDM) is a recurring theme in the CFA because of its importance in determining equity value by using required rates of return, growth patterns and dividend payouts. Before we get to the formula, let's review the underlying assumptions:

• The required rate of return is used for discounting at k
• The dividends, Div, grow at rate, g
  
• You use the upcoming payment, not the current payment (Div1 = Div0 * (1+g)).

So using the idea of geometric series and replacing the appropriate terms, we get:

• The first term (a) is Div1 / (1 + k) (the first dividend discounted to today's dollars)
  
• The rate of growth of each term, (r) is [(1 + g) / (1 +k)] - each year the dividend grows by g, but is discounted by k
• The value of the series, S, is the price of the asset, P
  

Therefore, using the summation formula for a geometric series:

P = [Div1 / (1+ k)] / [1 - ((1 + g)/ (1 + k)]
Expanding and simplifiying the denominator
= [Div1 / (1 + k)] / [(1 + k - 1 - g) / (1 +k)]
= Div1 / [k - g]

And this is how the formula for the DDM is derived from first principles.

Now based on this, how can we determine the price of an asset which experiences supernormal dividend growth during a period of it's life?

[Example] A start up business experiences a g of 25% per year dividend growth for three years before returning to a regular 9% per year growth pattern (g in both cases). The dividend is currently $3 and the discount rate is 12%. What is the price of the asset using DDM?

Immediately, it is obvious that a DCF is needed, but with the dividend model changing mid way, what strategy should be used? First calculate the last dividend payment of the super normal growth period: Div3 = $3 x (1.25) ^ 3 = $5.86. At year 3, the terminal value of the asset using the DDM is:

P = Div1 / [k-g]
= ($5.86 x 1.09) / (12% - 9%)
= $212.89

However, recall that this terminal value is in Year 3 dollars. Now as of today, your future cash flows are [$3.75, $4.68, $5.85 + $212.89].

Using a DCF with discount rate of 12%, the NPV of this asset is $162.77. For an asset currently only paying out $3, this might seem high, but the effect of the supernormal growth so early in the assets life dramatically affects the value of subsequent cash flows.

Geometric Sequences and Series

A popular mathematical concept which recurs in finance is the idea of an infinite geometric sequence. Any term Un in a geometric sequence is defined as follows:

Un+1 = Un * r

The parameters to define any sequence is the first term (denoted as 'a') as well as the ratio between terms (denoted as 'r'). So an infinite geometric sequence is [a, ar, ar^2, ar^3, ...]

A geometric sequence value converges to a finite value IFF r is less than 1 as n approaches ∞. Therefore, the sequence can be summed to create a series (the addition of all terms) which is denoted as 'S'.

By definition:

S = a + ar + ar^2 + ar^3 + ...
rS = ar + ar^2 = ar^3 + ar^4 + ...
(1 - r)S = a
∴S = a / [1 - r]

Does this look familiar? It's the underlying math for many assumptions in finance including discounting growing cash flows such as the Dividend Discount Model or some other perpetuity.

An annuity (a perpetuity with a termination point) can be calculated as the subtraction of the value from 0 to infinity to the value at termination, n, to infinity (at which point the numerator of the equation for S would be (ar^n).

Annuity = [a - ar^n] / [1 - r]
= a (1 - r^n) / [1 - r]

This formula is useful for computing the value of coupons in a bond (which terminates at maturity) or securities which pay dividends are sold, called or otherwise terminated.

Business Continuity Series, pt 4 - Building a BCP Plan

Before you can build a plan you need to understand what value you are deriving out of the system. Unfortunately, in the real world, Business Continuity Program planning is constrained by resource allocation like any other project, so understanding the value derived from the program. It is possible to quantifying the problem by understanding:

• Frequency of outages
• Average duration of outage
• Time value of outage
• Value of data lost
• Opportunity cost of capital investment in plan
  

Total cost of outages = Frequency x Duration x Time Value

This basic consideration will give you a foundation for justifying budgeting more or less funds into your Business Continuity Program.

When you've arrived at a stage where you need to begin to start choosing a strategy, there are several categories for recovery strategies, each with an escalating financial and resource commitment and proportional recovery / resiliency benefit:

• Passive-Passive - Cold solution. New equipment may need to be ordered at the time of the event. Capital on-hand 'just-in-case'. Can be improved with planning (better use of capital). Essentially a "do nothing" solution. Probably manifests as a paper plan only with no physically available resources.
  
• Active-Passive - Warm redundant systems - Literally: Turn-key or push button solutions. There is equipment ready but it is not currently in use. It is on hand and can be activated on short notice. This is usually because of technology or financial limitations.
  
• Active-Active - Traffic is load balanced across multiple systems. Disrupted systems are by-passed and traffic is routed to different machines. Usually minor disruptions pass unnoticed. Only catastrophic events knocking out the entire system are noticed by users. The main concerns of an Active-Active system are costs and capacity. Problems generally only become visible when enough modules are knocked out such that the system is over capacity.
  

As usual, better plans usually cost more resources, however sometimes there are non-zero sum gains to be had. For instance, a Passive-Passive solution might be to have $5M allocated in the budget as "contingency" in the event of a disaster. Perhaps rather than have $5M budgeted as "contingency" you can employ $1M in capital expenditures to build resiliency into your processes. Although this investment will depreciate over time, it could potentially be better than keeping the capital idle and the economic loss of the internal rate of return (IRR) of $5M.

Also, systems which are heavily used or mission critical will require more active plans. For instance, if Google or 911 suffered any downtime, people would notice.

When putting together a plan there are other important considerations. For instance, is the a correlation between risk factors and support infrastructure? What is the geographical distance between my redundant systems and what is the possibility of a single event knocking out both my systems? Understanding and process mapping all interdependency is paramount in any BCP endeavour.

Before you think it is too unlikely, recall the power outage in the summer of 2003 which knocked out power for the Ontario and North East USA. If you located redundant system for Toronto was in New York (or vice versa) thinking that locating in a different country was enough insulation and redundancy, this event showed that it sometimes isn't enough.

Asset Pricing Models, Pt 3 - SML

Asset Pricing Models [ 1 - 2 - 3 ]

The Security Market Line (SML) uses CAPM to determine if securities are relatively over or under valued as compared to the market portfolio.

The SML is a graph where the Y axis is expected return, E(R), and the X axis is systematic risk, β. The two points used to construct the line are when β = 0 at RFR and β = 1 at E (R mkt). The line is extended beyond β=1 and individual securities are superimposed as a scatter plot on the graph.
This line represents portfolios which are appropriately valued given their systematic risk relative to the market portfolio. Therefore, portfolios or securities that lie above the line have excessive returns (are undervalued) and securities that lie below the line have under performing returns (not enough returns for the given systematic risk, overvalued).

Notice in the example above:
Security A, Above SML, excess returns, undervalued - Decision: Buy
Security B, Below SML, underperforming returns, overvalued - Decision: Sell
Security C, At SML, equilibrium returns, appropriately valued - Decision: Hold

Using the SML helps identify securities which are mispriced so that the appropriate action can be taken.

Asset Pricing Models [ 1 - 2 - 3 ]

Asset Pricing Models, Pt 2 - CAPM

Asset Pricing Models [ 1 - 2 - 3 ]

The Capital Asset Pricing Model (CAPM) is a familiar term for finance analysts and CFA candidates. It is a model which helps approximate the required rate of return for a given investment portfolio based on it's systematic risk (unsystematic risk is assumed to be diversified away).

CAPM: E(R) = RFR + β(Market Premium)
Market Premium = E(R mkt) - RFR
∴E(R) = RFR + β [E(R mkt) - RFR]

Beta, β, describes the systematic risk and is equal to 1 at the market portfolio. Beta of stocks are described as systematic risk relative to the market portfolio.

While this is a fairly simple result, the implications are quite important. The expected return determines the cost of equity as well as the required rate of return. It also helps identify if stocks are over / under valued when we use the Security Market Line (next post).

Asset Pricing Models [ 1 - 2 - 3 ]

Asset Pricing Models, Pt 1 - CML

Asset Pricing Models [ 1 - 2 - 3 ]

One thing that I initially found confusing was the Capital Market Line (CML) and the Security Market Line (SML). At first glance, they seem to be identical graphs, but let's take a closer look at each while understanding what each is used for.

The Capital Market Line starts of with a scatter plot of all securities with the Y axis being expected return, E(R), and the X axis being standard deviation of return. After calculating the correlations and creating a variety of different portfolios, another scatter plot is super imposed onto the graph. At this point, it should naturally become obvious that there is a curved relationship between the maximum expected return for any given standard deviation (starting with economies of scope and increasing utility to a point of diminishing returns). The curve describing the upper bound of this scatter plot is called the efficient frontier.

Then, on the Y axis itself (the point of no standard deviation, no risk) we have the risk free asset which earns returns at the risk free rate (RFR) typically denoted by US Treasury securities.

The CML is created by creating a line between RFR and the point on the curve for which the CML is tangential. The reason for this is that at any given point on the CML, movement up or down the line will result in a change in the Safety First Ratio (marginal utility of risk, since we are using RFR as the basis for comparison) and therefore the utility is maximized at the point where the CML touches the efficient frontier (in theory this should happen only once). Below is the completed graph:

Because the efficient market portfolio (EMP) represents the optimal mix of securities, the optimal positions based on risk (assuming lending and borrowing at RFR) is any position along the CML. Positions with standard deviations below the EMP are lending positions (being short the EMP and long the RFA). Positions beyond the EMP are borrowing positions (being long the EMP and short the RFA). Basically, it's adjusting your risk tolerance by leveraging or deleveraging the EMP.

Asset Pricing Models [ 1 - 2 - 3 ]

Sharpe and Safety First Ratios - Maximizing Investment Utility

I've often quoted the Sharpe ratio as a good metric to use in investments. This is because it mathematically calculates the marginal utility of different investment vehicles. Let's look at the underlying formula:

Sharpe Ratio = Excess return / risk = [R p - RFR] / σ p

Where:

• R p is the expected return on the portfolio
• RFR is the risk free rate
• σ p is the standard deviation of the portfolio

The Safety First Ratio is a special case of the Sharpe Ratio. For any given security, rather than use the RFR, some minimum required rate of return is substituted instead. This is often used in scenarios where an investor would like to make a minimum return but also capture the most utility possible.

Safety First Ratio = [R p - R min] / σ p

Where R min is the minimum required rate of return (constant cor comparison across securities).

Note that both of these measures have units of return (as a percentage) over standard deviation. Also note that Sharpe Ratio will always be higher than Safety First-Ratio for any given individual security (it doesn't make sense to get a return less than the risk free rate).

If you hold R min constant across all securities and Sharpe is always greater than Safety first, the security with the highest Sharpe ratio will always have a highest Safety First as well for any and all R min.

The highest Safety first, however, does not necessarily imply the highest Sharpe (depending on the R min). In this case, it is better to chose the one with the highest R p. Example:

Two Portfolios
RFR = 1%
R min = 4%
Portfolio A
E(R) = 10
σ = 6
Sharpe = [10% - 1%] / 6 = 1.5
Safety First = [10% - 4%] / 6 = 1

Portfolio B
E(R) = 6
σ = 2
Sharpe = [6% - 1%] / 2 = 2.5
Safety First = [6% - 4%] / 2 = 1

In this case, the two securities have the same Safety First Ratio, but security B has a higher Sharpe Ratio.

Business Continuity Series, pt 3 - Service metrics - What are your goals?

Although we try our best to avoid failures with methodologies and goals like six sigma (the idea that output from processes should be contained within six standard deviations or approximately 3.4 failures per million) there are still some failures which need to be dealt with.

In the event of a system failure, there are two key metrics which are a good indicator of resiliency: Recovery Point Objective (RPO) and Recovery Time Objective (RTO).

RPO refers to the amount of assets lost which can be quickly recoverable. For instance, an RPO of 24 hours for a database server means that if there is a failure (server crash, hard drive failure, building burns down) then the data that is restored is at most 24 hours old (or in other words, all data created in the last 24 hours is lost as a worst case scenario). RPO describes how current the information in your back up from auxiliary sources is.

RTO refers to the amount of time the process /service unavailability (time til service resumes). An RTO of 48 hours for cable television means that if a cable TV signal is disrupted (damaged line, transmitter failure, etc) that it will take the cable company 48 hours to restore service to your house.

The counter balance to achieving excellent RPOs and RTO's is cost. Generally speaking, the less latency for RPO and the less delay for RTO required, the more exponentially costly the solution (inversely proportional relationship).

Using a project management framework, the RTO of system system recovery is based on the critical path of recovering services (which in turn is heavily dependent on the system module with the longest RTO). And without a proper context most data will be useless so the weakest RPO in the system usually reflects the RPO of the system in general (a series relationship).

Email Example: A consultant backups their email every month locally on their laptop and their office mail server experiences an outage for 3 hours. The RPO in this scenario is one month (all the emails on their laptop) and the RTO is however long it takes the IT staff to restore email service (3 hours).

Bonds, Not Risk Free

A common misconception (although probably not any more with all the bankruptcy going on recently) is that bonds are "safe". While it is true that they are "safer" than their comparable equities (debt has senior claims in bankruptcy, but tends to be cut down proportionally with junior tranches in restructuring), they are not perfectly "safe" (the only investment considered safe are US Treasuries which are considered to be default free and used as a proxy for the risk free rate, RFR).

So what are the different forms of risk that investors need to be aware of when making investment decisions in fixed income securities?

• Interest rate risk. As interest rates in the market move down (up), price goes up (down).
• Inflation risk. The risk of unexpected inflation which affects the real interest rate for a given nominal interest rate.
  
• Reinvestment risk. For bonds with coupons, if interest rates decline, than the interest earned from coupon payments will also decline (yield to maturity, YTM, assumes that all cash flows are invested at the same rate).
  
• Prepayment risk. A variation of interest rate and reinvestment risk. If rates fall, borrowers will prepay their obligations and investors will reinvest at the lower rate.
• Credit risk. The risk of an event having an adverse affect on the issuers credit rating (thereby reflecting a change in the credit spread). This could be the company defaulting on an obligation (bankruptcy) or having an issue downgraded.
  
• Liquidity risk. If a security is not actively traded, there is will be a transaction premium to sell the bond (a higher yield will be required).
• Volatility risk. The risk for fixed-income securities that have embedded options. Changes in volatility affect the value of the embedded options and therefore the nominal yield spread and bond price.
  
• Call risk. If the bond has a call option, there is a risk that the bond will be called, limiting the value (price) of the bond.
• Exchange-rate risk. For bonds issued in foreign currency, movement in either currency relative to the other will affect the value of the bond (as it does with equities in foreign markets)
• Sovereign risk. The risk that a foreign countries government takes actions or is affected by events which adversely affect the value of the bond.

Understanding the risks inherent in a bond's structure allows bond portfolio managers to construct positions which have predictably less volatility while maximizing returns.

Bonds with Options

Before we start, let's take a look at the basic principles behind bonds. A bond's yield is dependent on to major factors, the coupon rate (payments made semi-annually unless otherwise specified, analogous to interest payments) and the face value (analogous to repayment of principle). The combination of these two factors determines the yield to maturity (YTM) which is analogous to IRR in NPV and DCF (your calculator can actually use the same function to compute both as the math is identical). The relationships between these components are fairly intuitive and predictable (ceteris paribus):

• The higher the coupon, the higher the yield
• The higher the face value relative to the present value, the higher the yield
• The higher the yield, the lower the present value (and vise versa, Price and yield have an inverse relationship)
  

Note during this discussion that many of the mechanics relating to the treatment of options as they relate to equities also apply in the world of bonds as it relates to the value of the option. However, just to reiterate and clarify, let's look at each class of bond option seperately.

Callable Bonds
A callable option allows the borrower to pay the lender a specified amount to exit the bond agreement (benefits the borrower at a lower interest rate). This effectively acts as a ceiling price for the bond:

1. If the yield drops,
   
2. the cost of borrowing goes down, and
   
3. the price of the bond goes up.
4. If it passes the ceiling, the borrower will call the bond and issue a new bond at the lower rate.

This puts a cap on the maximum value of the bond.

Notice that the call option always benefits the lender, and this flexibility is paid for by issuing the bond at a lower price than an otherwise comparable straight bond at any given price. The nominal spread is always larger to account for the option. An option adjusted spread (OAS) is often approximated to understand the performance of the bond, excluding the option.

Putable Bonds
A putable bond option allows the lender to take a specified amount to exit the bond (benefits the lender at a higher interest rate). This acts as a price floor for the bond.

1. If the yield rises,
   
2. the cost of borrowing goes up, and
   
3. the price of the bond goes down.
4. If it passes the floor, the lender will put the bond and buy a new issue at the higher rate.

The price of a putable bond is always greater than a straight bond at any price point because of the inclusion of the put option (benefiting the lender).

Bond Duration, Quantifying Yield Sensitivity

One concept which I find surprisingly and needlessly confusing is the idea of bond duration. I say surprisingly because most people would associate the word duration with time, however, in this context, it relates to the approximate sensitivity of a bond's price change in dollars given a change in yield.

Aside from that, the math involved is actually quite simple. The formula for Duration is:

Duration = - % Change in Bond Price / Yield Change in %

Dollar Duration is the special case where the change in yield is 1oo basis points (100 bps = 1%).

The duration is the relationship between price and yield as shown below:
Note that like elasticity which is done in percentages, the average bond price is used to calculate the duration so that a more accurate value can be produced for a yield change on either side of the average (rate shock increase or decrease).

However, also note that due to the convexity of the yield curve, duration's approximation of sensitivity under compensates for the sensitivity. In calculus terms, duration is merely an approximation (based on first principles) of the slope of the curve (derivative).

LIFO and FIFO: Fundamentals of Accounting

The CFA curriculum focuses on LIFO versus FIFO accounting in some of their questions and I just wanted to review the reasons for some of the relationships and differences between these two accounting methods by looking at the underlying accounting principles.

First some basics. Why would you choose one method over another? LIFO provides a more accurate picture of profitability, especially if prices are increasing rapidly and / or you have high asset turnover. It paints a more realistic picture regarding your margins. However, from an accounting perspective, FIFO makes sense because it matches the revenue earned with the products created.

Often, questions are based in scenarios of rising prices (as this is usually the case due to inflation). If questions are framed in a scenario with declining prices, the relative relationships are reversed. Let's look at two graphs, both with increasing prices and each using a different accounting method (LIFO versus FIFO):
This is a neat visual aid for understanding the relationships between the two accounting methods during rising prices. In LIFO, the most recently produced units are sold first, therefore the COGS is the area under the right side of the graph whereas the Inventory is the area under the left side. This is reversed in FIFO, where the COGS is on the left and Inventory is on the right. Also notice that in a time of rising prices, COGS will be higher in LIFO (selling the expensive stuff first) versus FIFO (selling the previously made cheaper stuff first).

In an unusual scenario of declining prices, you can use the same tool to understand the relationships:

In this case, the relationships are reversed. With declining prices, FIFO has smaller inventory and higher COGS while LIFO has larger inventory and smaller COGS.

In LIFO accounting the last products created are the first ones to be sold (Last In First Out). To understand what happens in a scenario with rising prices we'll take a step by step look at what happens at each stage of the financial statement:

1. the most expensive products are sold first (therefore COGS goes up relative to FIFO)
2. there is less profit (EBITDA, EBIT, EBT, EAT are all lower)
3. there is less tax is payed
4. net income (retained earnings) is lower
   
5. the ending inventory is lower relative to FIFO (you sold the "expensive" products and kept the "cheaper" products in inventory)
6. implies lower working capital
7. with the same amount of cash coming in but lower taxes paid the result on cash flow is actually higher in LIFO than FIFO (deferring taxes paid by "keeping profits" in inventory).

Again notice that in a scenario of declining prices, the relationships are reversed.

Note that switching from one accounting method to another produces side effects which can potentially allow management to mislead unsuspecting analysts. The argument for using LIFO, especially in scenarios with rising prices (like oil) is that it can provide a more realistic picture of future profitability. However, once using LIFO, liquidating the LIFO reserve will allow management to report artificially high profits (one time selling of assets usually resulting from reduced production - "selling the cheap stuff"). Each accounting method has its pitfalls for those who are not vigilant.

Investment Decisions - NPV versus IRR

An important concept in corporate finance is the idea of cash flow. Based on a given investment decision, what will my increase in cash flows be as a result? There are two important metrics which are used to determine the value of an investment decision, and that is the net present value (NPV) as well as the Internal Rate of Return (IRR).

Net Present Value looks at the current value of all expected cash flows by using a discounted cash flow (DCF) model for a given discount rate (the firm's stated required rate of return) and is measured in dollars (or whatever currency the investment is made in). A higher NPV is preferable.

Internal Rate of Return is the rate of return earned on the investment. Another way to look at it is to consider it the discount rate for which the NPV is zero. A higher IRR is preferable.

Often, for two different investment decisions, NPV and IRR will give the same investment decision (Project A has higher NPV and IRR than Project B), but this is not always the case. For example, with uneven cash flows and different initial investment outlays, it is possible to get a seemingly conflicting decision. So what do you do?

If you have enough money to do both projects, you do both (assuming the NPV is positive, you would never do a project with a negative expected NPV). If the projects are mutually exclusive, you take the project with the highest NPV (most valuable at the end of the day).

What else can you learn from the NPV and IRR profiles of two projects? Look at the graph below:
Since NPV varies based on different discount rates, the graph shows how the NPV moves for each project as the discount rate used changes. There are four discount rates of interest. The first is a discount rate of 0, which is the NPV of all cash flows assuming no discounting. The next is the cross over rate which is the discount rate at which the NPV of Projects A & B are equally valuable. Then we have NPV of Projects A & B at 0 at IRR A & B respectively.

Notice that as the discount rate moves, your investment decision (assuming Projects A & B are mutually exclusive) changes. For example, between undiscounted cash flows and the cross over rate, the NPV for Project A is higher. Between the Cross over rate to IRR A (and up to IRR B) the NPV for Project B is higher.

What else can we see from this graph? The undiscounted cash flows of Project A are higher, but as the discount rate increases, the NPV of B becomes larger. You can infer that based on this relationship, Project A probably has larger cash flows relative to its initial investment, however, they occur at a later date (and are therefore more sensitive to discounting) whereas B probably has cash flows occurring relatively sooner.

Business Continuity Series, pt 2 - Parallel versus Serial Failure and Resiliency

Before we can delve into the world of business continuity, we need to understand the underlying logic of systems design and the probability mechanics of describing failure. Taking a systems approach to redundancy planning, let's look at the mathematics behind failure probabilities of parallel systems and systems in series.

First let's look at a system in series:
The system above contains three modules in series, each with an 80% success rate. Each is independent of the others. The success rate of the system is the probability union of all three modules, in other words, in order for this system to work, you must traverse all three modules. The probability of success is as follows:

Success = 80% x 80% x 80% = 51.2%

Look familiar? It should. This is the exact same model I used for my post about the failure of communication between organizational levels and why smart people say stupid things with CEO's being on the left and mid-level managers on the right.

Note that even though each individual module has a fairly high success rate (80%) each incremental and potential failure compounds the overall success of the system. In series, all modules have to work in order for the system to work. This means that a system in series is vulnerable to single points of failure. If there is one point which goes down in the process, the whole system shuts down.

In human resources planning or even individual career development, being irreplaceable is identical to being a single point of failure.

Next let's look at a system in parallel:
The assumptions here is that each module is interchangeable with any other. That is to say that if one system fails, the other systems will pick up the slack. Here each module is fairly mediocre with a 60% success rate (or a 40% failure rate). However, for the system to fail, all three modules have to fail simultaneously. The probability of that happening is the union of all the failures:

Failure = 40% x 40% x 40% = 6.4%
Success = 1 - Failure = 93.6%

Notice that even while each individual component is not of particularly good quality, when they work together to ensure success they collectively cover for each other in the event of individual failures.

This model is analogous to electrical circuits (and the idea of resistance and conductance):

• Modules are equivalent to resisters (from the perspective of conductance). Where conductance is a process channel.
• Electrical current is work done.
• Voltage differential potential work waiting to be done.
  

Remember, that formulas for electrical are analogous to fluid mechanics (if you come from a chemical or mechanical engineering background and feel more comfortable with those terms).

• Modules are pipes
• Water flow is work done
• Pressure is potential work

With all these analogies, there are also problems associated with capacity. Although an individual failure might not disrupt a system with parallel components, if the system as a whole is operating at 90% capacity, the loss of one third of it's capacity is also a serious problem (system over capacity) and this will manifest in a variety of ways:

• Unstable queue growth (work is coming in faster than you can process it)
• Large (and growing) delay times (backlog)
  
• Mechanical failures / server crashes / employee sickness (overworked)

In the next section, we will look at the goals of continuity planning, how to set goals and understand how to measure performance in an environment where an anticipated failure has occurred.

Options Review, Pt 5 - Options Strategies

[Options Review Series 1 - 2 - 3 - 4 - 5]

One of the reasons why I enjoy options strategies so much is that it is a relatively clear cut way of showing how derivatives can be repackaged to create new instruments. What do I mean? For example, looking at the six different positions listed (Long Underlying, Short Underlying, Long Call, Short Call, Long Put, Short Put) you can see that there are a variety of different profiles which can be created.

Two which the CFA Level I exam seems to like to focus on are Protective Puts and Covered Calls. What are they? Let's look at Protective Puts first:

Protective Put
A Protective Put is someone who wants unlimited upside potential with some downside protection. This is a strategy which allows the portfolio to appreciate, but also protect against some downside if the asset loses value.

Protective Put = Long Underlying + Long Put

Conceptually, it's owning a stock with the option to sell it if the price gets too low. Sound great right (unlimited upside with no downside)? What's the catch?

Like all options, assuming (or removing) risk upfront also comes with an upfront cost. That is to say the catch is that there is an immediate downside in the form of the premium placed on the Long Put.

Consider this position the equivalent of gambling insurance (like in Black Jack when the dealer shows an Ace). If you buy the insurance and the dealer shows a 10 or face card, you max your loss out at your insurance, but if not, you can still get upside. [Odds actually state that you shouldn't use insurance, but perhaps gambling itself is a flawed analogy with negative expected returns.]

Protective Put = Long Underlying + Long Put = Long Call

You'll notice that if you add a Long Underlying with a Long Put, the profile of the new "Protective Put" position is identical to a Long Call. Below the excise price, the gains of the Long Put are offset by the losses of the Long Underlying. Above the excise price, the Long Put is worthless and the Long Underlying appreciates.

Covered Call
So what is a covered call? A covered call is someone who wants to write a call option (Short Call), but also wants to have stock on hand (be "covered") in case that call is executed in-the-money. Think of it as writing a call option with insurance.

Covered Call = Short Call + Long Underlying

What does the profile look like? Well below the excise price, the call is worthless and the underlying is losing value. Above the excise price, the call appreciates in value as fast as the underlying to cancel each other out.

This translates into limited upside and unlimited downside. Seems like a pretty raw deal. So why would anyone enter this position? Again, the answer is the premium. By assuming unlimited downside risk with a capped break-even upside profile, the incentive comes in the form of an upfront fee (the premium).

Covered Call = Short Call + Long Underlying = Short Put

Resolution:
The point I would like to highlight here is that with these six pieces, you can construct (or reconstruct) any profile position you would like. Below are the most obvious examples (in synthetic positions, Long and Short bond positions are assumed to have a face value at the excise price in order to balance the profiles by generating value related to X at expiration):

• Synthetic Long Call: Long Put + Long Underlying + Short Bond
  
• Synthetic Long Put: Long Call + Short Underlying + Long Bond
• Synthetic Long Underlying: Long Call + Long Bond + Short Put
• Synthetic Long Bond: Long Put + Long Underlying + Short Call

Note that all counter party (reversed) positions can be determined if all the positions of which they are composed are reversed (ex. Synthetic Short Call: Short Put + Short Underlying + Long Bond).

Since each option profile is constructed using simple arithmetic, they are commutative and associative. Therefore reversing each component position will reflect a reversing of the portfolio of options as a whole.

[Options Review Series 1 - 2 - 3 - 4 - 5]

Options Review, Pt 4 - Put Options

[Options Review Series 1 - 2 - 3 - 4 - 5]

Now let's look at Put Options. Put options are the options to "put" (sell) options in the market at a given price. They become more valuable as the stock drops (If you have the right to sell something at X even though it's only worth St) and the value is (X - St). It has similar features to short selling (Short the Underlying Asset) but it's value is capped at X (limited upside potential).

If the market price goes above X, the put option is worthless (why use a put to sell an asset at a price lower than what you can get for it in the market?). So for any price above X, the value is zero. For each dollar below the strike price, the intrinsic value goes up a dollar.

The profit profile for a long put position is as follows:

Long Put Profit = (X - St) - Call Premium, while X > St
- Call Premium, otherwise

Break Even point, St when Long Put Profit = 0
St = X - Call Premium

Note, whenever you are Long the option (regardless of what type of option), you pay the premium because you gain "flexibility" to exercise the option. If you are ever short an option you take the premium to assume the risk that the counter party will execute the option when it's "in-the-money".

Now the profile of a Short Put:

Short Put Profit = Call Premium - (X - St), while X > St
Call Premium, otherwise

Break Even point, St when Short Put Profit = 0
St = X - Call Premium

[Options Review Series 1 - 2 - 3 - 4 - 5]

Options Review, Pt 3 - Call Options

[Options Review Series 1 - 2 - 3 - 4 - 5]

Next, let's look at the intrinsic value of call options (St - X). I choose calls over puts because they have similar profit characteristics to longs with "downside protection". A call option is the option to "call" (purchase) a stock at a given price (the Excise price, X).

If the market price of the underlying asset is less than X, the call option is worthless (why use a call to buy an asset at a price higher than what you can get it for in the market?). So for any price below X, the value is zero. For each dollar beyond the strike price, the intrinsic value goes up a dollar.

In a Long Call position, the holder pays the premium to the counter party so therefore the entire graph shifts down by the amount of the premium.

It's profit profile for a long position is as follows:

Long Call Profit = (St - X) - Call Premium, while St > X
- Call Premium, otherwise

Break Even point, St when Long Call Profit = 0
St = X + Call Premium

Now let's look at the short call position. Remember that between any two opposite positions (Long and Short) the graph is reflected against the X-axis (reflecting a zero-sum game profit between two parties - you can't make something from nothing).

So inversely, being short a call means that you get the call premium, but can lose money if the market price goes up. And the profile is as follows:

Short Call Profit = Call Premium - (St - X), while St > X
Call Premium, otherwise

Break Even point, St when Short Call Profit = 0
St = X + Call Premium

A few quick notes:
Notice that a premium is required so that both Long and Short positions have both a profit and loss scenario. If either position doesn't have a profit scenario, then no party will not enter into that position. However, the profit scenario of one becomes the loss scenario of another.

The Break Even point is the same for Long and Short positions (no one comes out on top).

[Options Review Series 1 - 2 - 3 - 4 - 5]

Options Review, Pt 2 - Fundamentals

[Options Review Series 1 - 2 - 3 - 4 - 5]

Next let's look at Options. They are instruments which give you the flexibility ("option") to undertake an action if you feel it is beneficial.

The value of options are composed of two components, the intrinsic value and the time value.

Intrinsic value is the easiest to understand. It is the difference in value between the excise price and the current market price. If you option allows you to execute the option at price X, and the market price for the underlying asset is St, there is a intrinsic profit / loss potential of (St-X) and profit or loss would depend on which side of the transaction you are on (long or short). More on this later. Options have special words for profit or loss based on the intrinsic value. If the holder of an option (the Long position) earns a profit based on the current position of the option (St - X), the option is said to be "in-the-money". If the opposite is true, the option is said to be "out-of-the-money".

Regarding time value of options, there are generally two types of options. American and European. Here are some key points:

• American options can be exercised at anytime.
  
• European stocks can only be exercised at expiration.
  
• The flexibility of American style options makes them more attractive and therefore equal to or more valuable under every circumstance than their European counterparts. This is a tip for removing incorrect answers in the CFA exam.
  
• The time value of an option is always greater than zero.
• Time value of an option increases as the stock volatility increases (options are protection against volatility)
  

Option Value = Intrinsic Value + Time Value

Note that even if Intrinsic Value drops to zero, the Time Value must always be positive therefore the Option Value must always be positive. If by expiration, an option is not used, it expires and becomes worthless. The lowest possible price allowable for an option is 0. It cannot become negative.

While options sound fantastic (they always have positive value) don't forget that an upfront premium is needed to purchase the option. As we will see in the next post, this creates more balanced (and realistic) scenarios for profit and loss.

[Options Review Series 1 - 2 - 3 - 4 - 5]

Options Review, Pt 1 - Underlying Asset

[Options Review Series 1 - 2 - 3 - 4 - 5]

While it would appear to be a misnomer for the inaugural post to start with underlying asset, I wanted to show a few graphs and tools related to movement in the underlying asset in today's posts about derivatives to build a foundation on which to describe other option based derivatives. Using the tools and short graphs presented in today's series, there should not be any learning outcome statement (LOS) on the CFA Level I exam relating to options based derivatives which can't be tackled.

Let's start with the position most people are familiar with: Being Long the underlying asset (buying something).
Obviously, as the value (St) goes up, so does the value of the asset. And if St is greater than S0 (purchase price), then you've made a profit. If it goes down below S0, you've taken a loss.

Long Underlying Asset Profit = St - S0

Now let's look at short selling. Short selling is the exact opposite of being long the underlying asset. In short selling, you borrow the stock from a broker, sell it on the open market, and repurchase it later in the hopes that the price will drop (rather than go up).

Short Underlying Asset Profit = S0 - St

A few interesting notes about short selling. Unlike being long a security which technically involves only two parties (yourself and the market), being short also includes the broker who lends you the stock. In being short a stock, all dividends paid by the stock while you hold it need to be paid by you to the broker. It's as if the broker still has it (they own it even if they don't currently hold it).

Interestingly, if you add the two graphs together, (Long Underlying Asset and Short Underlying Asset) there is no profit. The profit area under one graph cancels the loss area of the other. That is to say, the profit in the Long is the loss of the Short and visa versa.

Now capitalists being what they are, there is a fee which is associated with incentive for the broker for you to perform this action, but this is outside the scope of CFA Level I.

Also note that shorting is only permitted on "upticks" or flat prices where the previous tick was an uptick. What does this mean? Consider the following 5 prices in order: [52, 51, 53, 53, 50]

Short selling is not permitted on the:

• 2nd tick (a downtick from 52 to 51)
• last tick (a downtick from 53 to 50)

Short selling is permitted on the:

• 3rd tick (an uptick from 51 to 53)
• 4th tick (a flat tick at 53, preceded by an uptick from 51 to 53)

I did wonder, however, if you had an uptick followed by a series of flat ticks if you were still able to short sell. I would assume the answer is yes, since the underlying reason is to prevent short sellers from aggressively depressing the stock price, but this is also outside of the CFA Level I curriculum.

[Options Review Series 1 - 2 - 3 - 4 - 5]

Business Continuity Series, pt 1 - Overview

Business continuity was an extremely hot topic during 9/11 as well as with current worries about avian and swine flu. The question posed is this: "How resilient are your business process to disruptions"? Whether that be a building fire, a crashed server or the loss of key personnel due to illness, companies need to know the inter-dependency of related systems as well as the redundancies (or lack thereof).

The next series will look at the math and mechanics of business resiliency planning

• Part 1. Overview (This post)
• Part 2. Parallel versus Serial Failure and Resiliency
• Part 3. Service metrics - What are your goals?
  
• Part 4. Building a BCP Plan
• Part 5. Implementing the Plan

What is important is to differentiate between fear mongering and understanding real business risks associated with the operating environment and taking appropriate steps to mitigate them efficiently and effectively.

The material that will be covered in this series is a combination of engineering statistics principles coupled with business continuity planning as described by the Disaster Recovery Institute (DRI) as part of the Associate and Certified Business Continuity Professional level certifications (ABCP and CBCP respectively).

Home Stretch - CFA Exam on June 6th

With the CFA exam officially less than 3 weeks away, I'm going to intensify my posts and focus more on CFA related topics and concepts. I'm going to aim for 2 or 3 shorter posts a day, each focusing on a typical CFA style question I've encountered which highlights an interesting investment topic.

Afterwards, I will resume a more broad range of discussion topics (including current events), but will generally try to keep my blogging on focus for the upcoming examination.

Cash Flow Analysis, pt 5 - FCFE

[Cash Flow Analysis Series 1 CFO - 2 CFI - 3 CFF - 4 FCFF - 5 FCFE]

The second free cash flow methodology is Free Cash Flow to Equity (FCFE). This represents the cash that is available for distribution to owners. This is very important in determining the liquidity of a company in the short term as well as understanding the efficient use of cash in a company (no cash "idling").

Free Cash Flow to Equity is calculated as:

FCFE = CFO - FCInv + Net Borrowing - Net Debt Repayment

You'll notice there are some key differences between FCFE and FCFF.

First is the exclusion of interest expense effect (Interest Expense x (1 - Tax Rate)) and the addition of net borrowing and net debt repayment. The common thread between these items is that they are related to changes in net debt and related expenditures.

[Cash Flow Analysis Series 1 CFO - 2 CFI - 3 CFF - 4 FCFF - 5 FCFE]

Gap Analysis and Integrative Thinking

Gap analysis is a framework enabling a management team to evaluation actual performance with its potential. At its core are two questions: "Where are we?" and "Where do we want to be?". In game theory, this manifests as potential non-zero sum gains and in economics manifests as working within the potential frontier curve (both describing inefficient processes).

Gap analysis is a logical step following common size analysis and other forms of bench marking. It helps identify the causes of performance shortfalls and areas for improvement.

Many managers who are familiar with ISO 9000 for quality management (which implements a Plan, Do, Check, Act (PDCA) framework) will notice it has many similar characteristics and goals to GAP analysis applied recursively.

Sometimes gaps are easy to quantify: Our competitors computer model has 20% more computing power. Other times it is not: Our brand equity is weak relative to comparable fashion designers.

Understanding the factors that produce these distances is the first step in bridging them. The initial steps of an integrative thinking framework also has similar characteristics in using Salience, Causality, Architecture and Resolution to move from problem to solution.

Cash Flow Analysis, pt 4 - FCFF

[Cash Flow Analysis Series 1 CFO - 2 CFI - 3 CFF - 4 FCFF - 5 FCFE]

Free cash flow is the excess of operating cash flow above capital expenditures. There are two methods using free cash flow which are used for determining free cash flow. Today, we look at Free Cash Flow to Firm (FCFF)

FCFF is the discretionary cash that's available for the firm's investors and creditors (debt holders) after accounting for the necessary investments in working and fixed capital have been made. Using methods similar to the direct and indirect method, it can be determined using either net income (NI) or cash flow from operations (CFO) as a starting point. Using net income as a starting point:

FCFF = NI + non-cash charges + (Interest Expense x (1 - tax rate)) - FCInv (capital investment / expenditure) - WCInv (working capital investment / expenditure)

• Non-cash charges include items such as depreciation and amortization
• Interest Expense x (1 - tax rate) is the equivalent to tax sheltering provided by debt (related to the cost of debt).
• FCInv is NOT CFI. CFI also includes *discretionary* uses of cash which are NOT included in FCFF. What are "discretionary" uses of cash? In this context, cash inflows from investing (selling off PPE) is considered discretionary. Note that FCInv is only Cap Ex!
  

Note that CFO is NI after including the effects non-cash expenditures and working capital investment. Therefore, using cash flow from operations (CFO) as the starting point:

FCFF = CFO + (Interest Expense x (1 - tax rate)) - net capital expenditure

It is essentially the cash flow that describes how much cash is available to the firm can use to cover its obligations and therefore is a good measure of solvency.

[Cash Flow Analysis Series 1 CFO - 2 CFI - 3 CFF - 4 FCFF - 5 FCFE]

Changing the Model - Newspapers as Not-for-profit

The death of newspapers has been an interesting topic in the news lately (notice that I couldn't find a newspaper with the article... Only another blog), and I included them in a previous post on my investment blog about the decline and bailout of the financial and automotive industries.

However, we have heard some interesting discussion about possible solutions. One in particular which I thought was rather insightful was the idea of making newspapers into not-for-profit entities. This idea comes from Jefferson's fundamental idea:

"The basis of our governments being the opinion of the people, the very first object should be to keep that right; and were it left to me to decide whether we should have a government without newspapers or newspapers without a government, I should not hesitate a moment to prefer the latter." ~Thomas Jefferson

While a good idea there are some serious considerations:

• Government bailout (and part ownership) of media has some potentially devastating Orwellian consequences (in the extreme, think 1984) due to conflict of interest.
  
• Newspapers and media should be considered a public service as the dissemination of information is of paramount importance to the operation of a free society. (Even right wing conservative supply side economists must agree that free flowing information is a major component of the assumptions in economic theory).
  
• Not-for-profit does not imply no revenue streams. Depending on the government definitions and regulations regarding NPOs, certain fees (to a cap) are excluded from taxation (sales revenue below a certain number, membership dues, etc).
• A broken business model is a broken business model. There will be no tax to pay if there is no profit to begin with. And there will soon be no profit with declining revenue.
  
• Using Profitability Analysis, there needs to be fundamental cost cutting in the way of distribution methods as well as a look at the advertising revenue streams (the bulk of the revenue is from advertising rather than subscription fees).
  

While a bit of fantasy, this strip from LICD highlights the drastic change in models required:

Sohmer has already received a great deal of criticism for the "practicality" of his idea, but I think what is highlighted is the dramatic nature needed to implement the change. As previously discussed, the newspaper industry finds itself in a crisis change situation.