Service Management Field Trip – Thessaloniki

Yesterday marked the last day of in person contact with our project sponsors. They have sent us some preliminary information to analyze and signed off on the project scope and definition. All that remains now is for us to do our analysis and provide our report. That coupled with the completion of our individual assignments will tie up the end of this course.

Shown above: View of Aristotelous Square from the Orizontes rooftop restaurant in Electra Palace Hotel Thessaloniki.

This has been a unique experience, to hear from the mouths of people who live here their opinion on a very timely topic: globalization, competitiveness and the structure of a nation’s (Greece’s) economy. Our professors did a lecture on Monday talking about the characteristics of the Greek economy, breaking down GDP components and telling a story about Greece’s economic focus and structure over the past 5 years as a backdrop for the current conditions the country is facing. They also prescribed a logical recipe for what would be needed to turn the Greek economy around and the challenges involved. These sentiments were echoed by many of the project sponsors who participated as many of them were looking to boost their competitiveness and engage the other economies of the world.

Today, I’ll be spending most of my time wrapping up all remaining loose academic ends in the hope of leaving nothing unfinished for my return to Toronto.

Emerging Markets - China

We just completed our final presentation in the Emerging Markets class taught by Linda Yueh at LBS. Our group chose China, and we did a cross section of important business factors and how they affect investment decisions and mechanisms into the country. While the presentation was performed by myself and my classmate Tim, the other team members contributed greatly to the material and their preparation was reflective in the cohesive and comprehensive story we presented. It was easy to present the highly refined material to create an investment thesis branching across a broad range of industries and tell a story about how specific companies would benefit or be hindered by government regulations and financial market mechanisms.

Tim did a great job going into the details of the domestic business environment with some personal anecdotes from some of our team members’ recent trip to China. JEMBAs (aka January intake Executive MBAs) at LBS are required to a week intensive in a foreign country and three of our JEMBA team members visited China together.

I think we represented the hard work and analysis of our team well.

YCIF London – First Conference Call

Today the YCIF in London hosted its first conference call. The speaker was Mr. Carlos Leitao, Chief Economist and Strategist at Laurentian Bank of Canada. He gave some great insight into the outlook of the Canadian economy by providing some colour as to the major macro indicators and the story of what was going on behind the key performance metrics.

I'm looking forward to the next conference call which is slated for Wednesday of next week. The topic will be the European state of the economy for 2011.

Bid / Ask Curves

At the break in behavioural finance, I was speaking to a prop trader about the mechanics of the market. This reminded me of my short trading exercise in the Rotman Finance Lab with the Trading Simulation software.

In microeconomics, we discuss demand curves and how they are based on individuals with different levels of willingness to pay. So as the price increases due to a supply curve shift right (less supply), the quantity demanded decreases.

In markets, this is a little more transparent if you look at the bid / ask lists. These lists show the prices and volumes people are willing to buy and sell for. The other unique thing about the capital markets, is that there is actually a set number of securities (assuming that banks do not issue or buyback securities in the short term, supply is price inelastic based on total float) and that investors can be both buyers and sellers (short term suppliers and consumers) of securities. Actually, a better way to put it would be they can either hold or release securities (demand based relationship).

If their intrinsic value (IV) of a stock is above the current market price, they will buy the stock. If their IV is less than market, then they will sell. And in an exchange market, that is exactly the case (orders, unless removed before execution, are commitments to buy or sell at the stated price).

Shown here is an illustration of a “complete” market. This assumes that everyone’s IVs are included, that there are no hidden orders and that people’s opinions won’t change with the market price (a snapshot by nature). The current ask price is $8.00 and the bid is $7.75. As people’s sentiments change (or new investors are introduced into the market), orders to buy are satisfied at $8.00 and orders to sell are satisfied at $7.75. If all the potential sellers at $8.00 are taken up, then people can only buy the stock at $8.25 and the stock price goes up. Note that the differential between bid and ask is a proxy for market liquidity, as the lower the transaction fee to enter and exit a position the lower the cost of trading the security.

Also note that the steepness of the curve is a good proxy for potential volatility as well. Because if the slope of the curve is steep over a variety of prices, it means that the market doesn’t necessarily agree on the price. And if a few people cross the line from one side to another, the price can change quickly and dramatically (shown below):

[Rotman] 5 Great Speakers at Rotman

[Rotman Series: 1, 2, 3, 4, 5]

Jaime is a part-time student in the MBA program at Rotman. He has worked in the sports media industry since 2002 and is currently Manager, Digital Media for the Canadian Football League. He and I went to the Latin America study tour in May last year. He was gracious enough to do a write up for me on his favourite guest speakers which follows:

By Jaime Stein

One of the first things you notice when you obtain an e-mail account at the Rotman School of Management is the sheer volume of e-mails from a guy named Steve. At first it can be overwhelming, but if utilized wisely, it can be your ticket to an exclusive roster of speakers. Steve and his team are the masterminds behind the A-list speakers that regularly visit the Rotman School.

The hardest choice I have to make each week is which speakers I will NOT listen to. This is a good problem to have because choice is always welcome when working full time and attending school part time. I simply don’t have the time to listen to every speaker that passes through Rotman. However, in almost three years, I have been privileged to listen to close to 100 guest speakers.

Most of the speakers that I have seen have delivered outstanding talks, but for the purpose of this blog I present five of the best speakers I have listened to during my time at the Rotman School:

1. Paul Martin – Former Prime Minister of Canada

Imagine you are in your second semester of a three-year MBA degree and you are studying Macroeconomics. A large focus of the course stems around Canada’s macroeconomic policies during the 1980s and 1990s; specifically the country’s battle with debt and inflation. One day you find out that the man behind the plan to battle inflation will be speaking at your school. That would be like a young basketball player having the opportunity to shoot hoops with Michael Jordan and ask him for tips.

Fortunately for our macro class, Mr. Martin came to speak at the Rotman School one morning and for about an hour took us through his plan that brought Canada back from the brink in the mid-‘90s. Following his talk he took time to speak to each of us and share some more personal insights and war stories from his time as both Finance Minister and Prime Minister. This was one of the great days at school that left me wanting to explore a subject further.

2. Isadore Sharp – Founder, Chairman and CEO of Four Seasons Hotels and Resorts

One of the main selling points of the Rotman School is its focus on Integrative Thinking – the theory coined by the current Dean, Roger Martin. In one of his books on Integrative Thinking (The Opposable Mind), Martin focuses on the story of Isadore Sharp and his path to building the greatest luxury brand of hotels in the world. In many of our classes we study the Four Seasons Model for customer service and other best-in-class management techniques. We were fortunate to have Mr. Sharp visit the Rotman School and explain firsthand how he went from one Four Seasons hotel in 1961 in Toronto to operating a chain of approximately 100 properties worldwide.

For anyone with an ounce of entrepreneurial spirit this was a motivating discussion. You could see the passion, courage and drive that Mr. Sharp possessed to launch his vision and stay true to it along the way. Any successful company will create a competitive advantage – however, these are eventually replicated by the competition over time. When people are your competitive advantage, it becomes truly sustainable as Mr. Sharp has proven. While other hotels provide outstanding service, none of been able to match the formula created by the Four Seasons.

3. Rahaf Harfoush – Digital Strategist and Author

It was November 27, 2008 when Ms. Harfoush spoke (for the first time, I believe) at the Rotman School. There was lots of hype surrounding her talk that day because Barak Obama had recently been elected President of the United States and Ms. Harfoush was a part of his wildly successful digital media campaign. I also remember this talk vividly, because it was one day later on November 28, 2008 that I joined Twitter. A lot in my personal and professional life has changed since that defining moment – all for the better.

The topic of conversation at Rotman that day was, “Applying Barack Obama’s Social Media Strategy to Your Brand’s Communications Needs” and it was Ms. Harfoush’s talk that became the inspiration for a lot of what we have done at the Canadian Football League over the past two seasons in the social media realm. To me, this is what an MBA program is about – an exchange of ideas to help stoke peoples’ imagination and potential. I’m glad I made time to attend her talk that day.

4. Michael Lee-Chin – Founder and Chairman of Portland Holdings Inc.

In October, 2009 I attended the Rotman School MBA Leadership Conference in downtown Toronto. It was a star-studded event with speakers like George Butterfield, Co-President of Butterfield & Robinson, Beth Comstock the CMO for GE, Don Morrison, COO of Research in Motion, Robert Deluce the CEO of Porter Airlines and Michael Lee-Chin, the Founder and Chairman of Portland Holdings.

Mr. Lee-Chin is one of the most engaging speakers I have had the pleasure to listen to in person. Mr. Lee-Chin spoke for about an hour on a variety of subjects including how to create wealth. He focused on a small number of blue chip businesses with long-term growth potential. But he was adamant that you know and understand where you are investing your money. One quote from Mr. Lee-Chin that sticks with me is, “If you don’t understand what you own, are you investing or speculating?” This is important advice that too many people continue to ignore this day and age.

5. Jay Hennick – Founder and CEO of FirstService

Mr. Hennick spoke to our class recently at the Rotman School. He runs FirstService, a company that provides services in commercial real estate, residential property management and property services and generates about US $2 billion in annualized revenue. Mr. Hennick told us his amazing story of how he achieved his current standing atop a multi-national company. He got his start with a company he ran as a tenth grader that brought in an income of $200,000. Yes, you read that correctly – he was in grade 10.

His key message was focused on people management; what he believed was the differentiating factor for the success of his current company. His “Partnership Philosophy” states that impact players must have more than a salary and bonus invested in the business; they must have an equity stake. His company focuses on aligning employees’ interest with shareholders in building long-term value. This was both fascinating and eye opening for most students who believe this is hard to do in a company of 18,000+. Yet FirstService continues to succeed. Listening to Mr. Hennick and his passion for success was rewarding.

As you can see, there are some overarching themes from these speakers such as focusing on people and establishing long-term strategies. But ultimately, each of these speakers is among the leaders in their field and that is why I feel fortunate to have spent the past three years at the Rotman School. The access to these great minds alone was worth the price of admission – well almost!

Flight of Fancy: What If...? A Market for Bid Points

One common theme I've heard is that MBA's are often upset when they don't get all the elective courses that they want. While I certainly can't complain, it brings up an interesting question: "What if someone like me was able to sell their bid points? What would I get for them? And how would you value them?"

For example, my course choices weren’t very restrictive, I got 500 points to bid on four courses, most of which I could have gotten with a zero bid. Whereas, Mr(s). Ambitious was trying to take TMP and Value Investing while going on Exchange (physically impossible, Value Investing is a year long course and Exchange means you are physically gone). If there existed a mechanism (and therefore a market) for me to transfer my points for a price, what would I get for them? What should they be worth? Clearly, there is currently some "market inefficiency" as we are both unsatisfied: Mr(s). Ambitious because they didn't get all the courses they wanted [net deficiency] and me because I didn't realize the full value of my bid points because I had more than I could use - [net surplus].

Well let’s make some assumptions:

• Rotman tuition is C$35k per year (let’s not include first year as it’s common, or you can adjust the value of points accordingly if you feel second year courses are more / less important)
• You take 10 elective courses in your second year
• You are given 1000 points with which to bid

A “book value” of the points would simply be C$35k / 1000 points or about $35 per point.

But keep in mind that when something is inherently useful, especially in a scenario where a few points margin can mean the difference between getting the course you really want versus having to settle for a less popular course, there can potentially be bidding wars from “oversubscription” (points trade at a multiple above their book value) especially if they were in limited supply.

While people are paying C$70+k to go to school, for a marginal $35 x 100 points (a rough approximation of the average points allocated per student / course) or $3500 you can get any course you want (including the highly coveted TMP and Value Investing – which includes a trip to visit Warren Buffet – one of the reasons why this course is so wildly popular).

If you could some how do it, you could see how much additional probability you have of getting into the classes you wanted and put a dollar value on how badly you wanted to be in that class (regression analysis), you can determine a price you’d be willing to pay to attend that class. For example: Would there be a correlation between the number of points you consumed to get into classes of your choice against your overall earning power once out of university (thinking along the lines of DCF to value bid points like common shares).

And also imagine if this market had a “market maker”. For example, the PSO will (create and) sell you points for a certain value (either regulated and pre-determined or floating with the market). Students could liquidate their points at market value and get money back or buy points of the market to be more competitive for course selection and the school could potentially get revenue from selling points.

And since you have a market with underlying assets, imagine if you created financial instruments for those assets (shorts, puts, and calls for bid points, futures).

And imagine if other schools had market systems (I’m told that bidding systems are not uncommon at other MBA schools), you could trade between these. Or even other programs!

Of course, these points would inherently have an “expiry” as to their value (you wouldn’t want to be holding (take delivery of) 5000 MIT Engineering points if you were going to Stanford Law School).

There are some interesting implications. For instance, a new ranking system for schools where the relative value of a course is determined by the market value (determined by students taking courses there) in real time with comparisons to year over year values. Example: Would an engineering calculus class go for more at Waterloo or Toronto? Could you couple this with flexibility between schools (accreditation programs) which allow students to take equivalent courses at other schools and what do you get?

It would be a more sophisticated and real-time version of tuition regulated by the market. Taken to the extreme, here is another idea: drop the original tuition completely and have students buy bid points for classes. And then what if you were able to connect this market to actual financial markets? An S&P Index of Undergraduate studies to benchmark the valuation of your individual class’ performance.

Another thought: If the value of courses in a particular faculty started to "overheat" would that be a leading indicator of oversupply of labour in a particular industry in 4 years time?

Bidding Strategy - The Mechanics

So I've been lucky enough to receive all the classes I want in all the sections I want and it turns out that LBS doesn't use a "bidding" system per say (classes awarded based on listed "preference" - an ordinal system).

A few people were asking about how my bidding formula works and while it's hardly perfect, I figured I'd put up some of the details just for laughs (or a least as building blocks for someone who plans on taking this model to the next level). It uses only public information available to all students at the time of bidding.

In this model, each course bid is determined by three factors. The first is the inital base and most people will choose one of two initial bases: Last year's minimum bid or last year's median bid (depending on how competitive the class is).

After determining the appropriate bases for your five courses, the remaining points (“the Remainder”) can be divided amongst your courses to make your bids more competitive. But like all dilemmas in bidding, you want to assign just enough points so that you get the courses you want, but not so much that you jeopardize your chances of getting the other courses. So how do you do it?

I propose that the two major factors you should look at are what I call:

1. The Ballot factor (anticipated) (x% of the Remainder, or “X-Factor”)
2. The Historic factor (backward-looking) ([100% - x%] of the Remainder, or the “Y-Factor”)

Where x% is the weight of value of your Ballot factor versus your Historical factor (In other words: how much you believe your Ballot Factor represents real bidding behaviour versus historical).

Ballot Factor:

This factor accounts for the number of people who say they will take the course. A few notes:

• People don’t always bid for the courses they ballot for
• Use the numbers as guidance to see if the course is oversubscribed
• Calculate the expected utilization capacity = total number of students balloting for any course in that section / total class capacity
• Square the utilization capacity to create an “intensity factor”
• Total all the factors and express each factor as a percentage of the total
• Multiply the percentages by the X-Factor
• The result is each individual courses’ Ballot Factor offset

Example:

• 2 classes have a capacity of 40 people each
• You have 200 points allocated to Ballot Factor
• 20 people bid on Class A (fairly certain everyone who bids will get in… There is even a chance that a 0 point bid could win) has utilization 50% and Ballot “intensity factor” of .25
• Class B has 60 bidders has utilization 150% (red flag: guarantee that not everyone will get in) and it’s “intensity factor” is 2.25.
• Class A’s weight is .25/(.25+2.25) = 10%
• Class B’s weight is 2.25 /(.25+2.25) = 90%
• Class A’s Ballot factor offset is 10% * 200 points = 20 points (a non-zero bid with decent margin, you'll probably get in)
• Class B’s Ballot factor offset is 90% * 200 points = 180 points (a strong bid, considering an average of 100)

This model tries to account for the fact that only very high bids will win the competative class, but you also don't want to low ball Class A incase a few stray bids appear from people who take the class last minute (obviously, the less people who originally bid on the class, the less you have to worry about dark horse bidders).

Note that it is 9x because at least 20 people are guaranteed to not get in the class. Classes that are oversubscribed will have intensity factors much higher than 1 with much heavier weights and undersubscribed much lower than 1 with much lower weights. This accounts for the premium on variation and intensity due to the number of bids in a competitive environment. Note that in this pure form, this is a best effort bidding mechanism with the scaling of points to consume all remaining points.

Historical Factor:

Another way to try to guess what the bidding will look like is to use the historical bidding as guidance for the variation of bids (were the bids tight or across a broad range?) One indicator of that is the minimum and median bid. If you make some HUGE assumptions, you can use these two points to create a normal curve with standard deviations. Since the mechanics of this are taught in stats in first quarter, I won’t bore my readers with a poor facsimile of Prof. Krass’ lecture.

Even if you don’t technically know the actual distribution of the curve, you can also use Chebyshev's inequality to position yourself within a certain percentile (also looking at the expected capacity utilization of the class based on your previous calculations). How? Here’s a hint (shown above): the bidding percentiles (% of students bidding that are not successful being admitted into the class) should be the same as the bid oversubscription capacity (again, huge assumptions) to provide the number of standard deviations. Combine this fact with the distance from the median to the minimum should provide a clue as to size of a standard deviation. Note that using this method, you may not (probably won't) have enough points to guarantee getting into the courses you want (unless like me, you probably have a surplus of points or are taking unpopular courses), but it is probably one of the best mechanical methods for balancing aggresive bidding with conserving points as well as building a view for what the bidding landscape looks like. In practical terms, at this point you can use a best effort model similar to the one shown above using the Y-Factor.

Also, I’ve deliberately left out methodology for mechanically scaling up courses based on your individual preferences (ie rating courses from 1 to 10 and incorporating that into your bidding strategy). Also, there are huge economic implications for bidding strategy considering that the involved parties do communicate with each other and affect the bidding levels of courses (ie Friends talk to each other about how they plan to bid). Signalling, game theory and strategy all come into play.

While not perfect, this model will give you some perspective into what a reasonable, very mechanically inclined bid would be. Admittedly, while I built this model, I did do some “emotional” adjustments to my bids (there was one course where I wanted to work with my friends on their team, so I wanted to be CERTAIN that I got the course). Like anything done on a computer, it’s just a tool.

Disclaimer: Like anything on this blog, this model does not guarantee any degree of success. This post is intended as a conversation / pensive reflection piece only. It is possible for you to use this model and not get ANY courses you want. For instance, it is physically impossible to get both Top Management Perspective AND Value Investing because both courses usually require exceptionally high bids. Note that by definition, there will be some people who don't get the courses they want. The more you want to be certain that you are in one course, the less certain that you will be in another (almost like the Heisenberg uncertainty principle). For better or worse, it is a zero-sum game.

Also, more importantly, I've been told that it's all a wash and at the end of the day, after the drop and add periods are over, most people get the courses they want anyways.

Purchasing Power Parity

Another example of exchange rate theory is the Purchasing Power Parity (PPP) condition. This model is similar to IRP in that it assumes that when purchasing commodities across borders that the same real price should be used regardless of currency.

For example.

• A widget costs $150 USD in the US
• The same widget costs £100 in the UK

What is the implicit FX rate between US dollars and pounds?

Well, you should be able to buy the same widget with either $150 USD or £100, so the implicit exchange rate (assuming PPP holds) is:

= $150 / £100

= $1.5 / £

Obviously, there are some HUGE assumptions required for this theory to hold. Minimal or zero transaction costs (including transportation, cross border tarrifs etc). In practice, it is probably more realistic to say that there is a threshold for which arbitrage probably won't happen in PPP because of the real costs incurred to handle transactions.

Also to be more accurate, rather than just use a "widget" it would be more appropriate to use a basket of goods to reflect a more broad use of the currency.

Interest Rate Parity Condition

The Interest Rate Parity condition that is in the CFA and discussed in our Global Managerial Perspective (GMP) class talks about.

Long story short, it says: Regardless of what financial mechanisms are used, two countries which are considered to be default free should generate the same real returns for the same period.

For example:
Today:

• You hold $1 USD
• The FX rate is 100 yen per USD
• The Japanse Bonds are yielding 5%

A year from now:

• FX rate is expected to be 103 yen per USD

What does IRP imply the interest rate on the US bond should be?

This can be graphically represented by:


The blue path shows how $1 USD is convered to Japanese Yen, held in a bond, and converted back at the new exchange rate back into USD. IRP states that whether this route is taken or if the USD is just held in a US bond (Red path) should make no difference. It should result in the same amount otherwise there is an arbitrage opportunity.

This is the solution. Note that the US bond rate is reverse engineered from the information given such that the end result produced in the red path is the same as the blue path.

You also note that there is a relationship which is defined by IRP. That is:

Japanese Bond Rate = US Bond Rate + [Appreciation / Depreciation of Foreign Exchange Rate]

Notice that this framework can have a blank in any one cell which can be derived using algebra if the other cells are filled in.

George Soros - Breaking the Bank

We were discussing the notorious story of George Soros' shorting of the UK pound in our GMP class this morning.

The story begins with the UK joining Europe's Exchange Rate Mechanism (ERM), not exactly fixed but had a policy where the currencies were staying within an exchange rate band. This simultaneously existed with a carry trade scenario where the German government was offering a higher interest rate than the British Government so people were borrowing in pounds and lending in DMs.

George Soros foresaw the opportunity where people who were participating in carry trades with the British pound created an opportunity for currency deprectiation. He sold off all his positions and then proceeded to short the position. This aggressive "attack" position resulted in many other fund managers dumping pound denominated assets. On the "Black Wednesday", the Bank of England tried to fight back by raising interest rates up to as high as 15% that day, but it wasn't enough.

Also, this is compounded by the required draw of the UK's foreign reserves (another avenue to defend against currency depretiation) to prop up the currency would have resulted in a significant depletion which would not have benefited nor saved the currency (essentially paying out the speculators).

This reminds me of the scenario I experienced in the finance trading lab where I could see the ask list depleting very quickly (low number of orders). The Interest Rate Parity condition only holds if you have a player who is large enough to hold the position of the currency. In a scenario (often repeated in other markets) where people put a currency (or any financial instrument) under siege, it makes it difficult for players to hold their positions as they take massive losses.

Eventually, as the story concludes, the epilogue is that the UK bank decided to let go and allow the currency to depreciate. George Soros also made a reported $1B USD.

Exchange Rates - Currencies as Investment Instruments

Oddly, in my Global Managerial Perspective (an international economics course), we were discussing exchange rates and the professor brought up nominal and real exchange rates (nothing new really), but also introduced the idea of using a weighted average of currency exchange rates as a bench mark for appreciation. There are two neat ideas which I took away from this:

The first is that when currencies appreciate relative to one another (on a bi-lateral basis) it is often hard to tell what is happening. For example, the Canadian dollar flirting with parity to the US dollar in the last few years. Is this a result of the US recession and lack of confidence in their dollar? Or the fact that Canadian Exports are in high demand and driving up our dollar value? Or both? In putting together a weighted average of exchange rates against your currency, you can tell on a more clear individual basis if your currency is appreciating against your "basket", a proxy for global currencies and real Purchasing Power Parity growth.

The second idea is that this weighted average looks an awful lot like an index. Much of the language above encompasses the idea that it behaves like a portfolio of financial instruments. Having said that, I recognize that things like CAPM probably wouldn't work (considering that currencies are not return generating instrumentns) so a regression of gains over time from the currency to the "index" would probably be meaningless. In the same way that commodities (although they are assets - items that store value) are not investment assets in the same way other financial instruments are because they don't generate return.

As the CFA material mentions, the only real way to receive gains from non-income generating instruments (commodities and currencies) is to rebalance after a change in price of the underlying asset.

Integrative Thinking Practium - Agent Based Modeling

At the beginning of the course I was a bit confused. At first I thought I didn't really understand what was happening. And then our class today started by describing a model of sand falling on a table. I was further confused as to how this was in any way related to business.

With a few changes in our frame of mind, "sand falling on a table" became a metaphor (or analogy?) for customer arrivals at a business. Pile height became analogous to company capacity constraints and pile location became geographic properties of companies.

Suddenly, we actually had a working model for the growth of an industry into equilibrium which encompassed such ideas as customer movement from one business to another. With a few more tweaks, the model was even able to show the decline of an industry (and death of underperforming companies).

I think my favourite part of this class was that it showed us in a very intuitive way how the models of our business work in more practical sense which are based in math, but don't require formulas.

I do apologize for my explanation as I don't feel it truly does justice to the class, but it encorporated topics we had learned in economics, operations management, managerial accounting, strategy I and II (Prof Ryall even made references to Anita McGahan's research).

Gravity as a Analogy to Globalization

Our professor just used one of the most clever analogies for international trade I've ever seen. It's surprising how much the physics of gravity can model relationships involving size and proximity.

The formula for the physics of gravity is:

Force = Gravitational Constant x Mass 1 x Mass 2 / Distance ^ 2

In this analogy:

• Force -> Strength of trade relationship
• Gravitational Constant -> Trade coefficient <-- trade barriers / regulations / tarrifs?
• Mass 1 -> Size (GDP as proxy?) of country 1
• Mass 2 -> Size (GDP as proxy?) of country 2
• Distance -> Distance

Our professor, Blum, took it a step further and did a logarithmic deconstructed the formula to further show how changing different values of each variable (pulling different strings) results in intuitive changes in the relationship. For example: Decreasing distance between countries increases. He even quotes his research (2004). This is his criticism of the idea that the world is truly "flat".

Imagine the game theory implications also. If you could use this relationship to predict how countries would trade and grow, you could build a model with multiple components (countries) to see how they'd develop.

So... It turns out that when Roger Martin tells us that Rotman has a world class research faculty which impacts the material we learn in our classes, he certainly wasn't lying.

Managerial Accounting / Operations - Capacity Management

One interesting topic which has surfaced in our introductory classes of Managerial Accounting (this morning) and Operations (yesterday) is the idea of capacity management. This is a topic I've been very interested in for a variety of reasons, particularly focusing on the idea of stock-outs and capacity planning.

For example, the ideal scenario is to create *just enough* inventory to satisfy's the period's needs. Creating any more (assuming a perishable good) results in inflated costs related to waste and/or inventory carrying costs. Creating any less results in lost revenue related to stock-outs.

However, in real life, it is unrealistic to assume perfect inventory planning all the time, so chances are there will be some days with over stock and some days with stock-outs.

The basic formula for profit is: Profit = Revenue - Costs

and

Profit Margin = Marginal Revenue - Marginal Cost or Marginal Revenue - Variable Cost

We know that we will incur some sort of inefficiency or uncertainty cost in the form of over / under stocking as mentioned above. However, the idea is to minimize this "capacity cost" we have to understand how operations affect these costs. For example:

A bakery sells donuts for $1.00. Donuts cost 10c to make. Therefore, over-stocking results in a cost of 10c per donut due to wastage. However, stock-outs cost $1.00 per donut due to lost sales. Therefore there is a 10 to 1 cost per unit on either side of the ideal capacity target. Let's say on any given day, the average sales is approximately 1000 donuts.

To minimize the cost side of the profit equation, we have to look at the probability of capacity distributions above and below the target.

Let's make a HUGE assumption (for simplicity) and say that there is a uniform distribution about the target (not normal, but uniform). Let's say there is a 10% chance of the actual daily sales being:

1. 950
2. 960
3. 970
4. 980
5. 990
6. 1000
7. 1010
8. 1020
9. 1030
10. 1040

How many donuts should the bakery produce?

I would propose that you should overlay the capacity with the associated cost of capacity management. What do I mean? If you produced 1000 donuts and you only sold 950, you're capacity related costs would be amount of capacity variance x cost per unit of variance. Generally this would be expressed as:

Capacity Related Cost = Capacity Variance x Cost per unit of Variance

So in this case:

Capacity Related Cost = 1000-950 x (10c)

=$5.00

What about baking 1000 donuts and then selling all 1000, but having an additional 20 donut customers who go unserved? Then:

Capacity Related Cost = 1000-1020 x ($0.90)

= $20.00

Notice that for a smaller number of donuts not sold, there is a much larger effect on Capacity Related Costs. This is a reflection on the profit margin (profit from one lost sale = marginal revenue - variable cost). That is to say, it is much worse to not sell 1 donut rather than have 10 donuts go stale.

To optimize planning (create a capacity level which will optimize profits) it would make sense to minimize the Capacity Related Costs. Since we have the probabilities of the capacity distribution and the associated costs with under production, what target capacity creates the minimal expected capacity related cost? Below is a chart outlining the capacity related costs for given target and actual production levels.

You'll notice that the optimal production level is actually 1040 or 1030. This sort of makes sense as the costs for missed sales are so high. Generally, because of the structure of the model, there are two major factors affecting the end result for capacity planning:

• Volatility and variablity of demand
• Profit margin (difference between cost of wastage and cost of lost sales)

Global Management Perspective and the Start of Q4

Today we started Q4 with Global Management Perspective. It promises to be an interesting class. Prof. Blum was a guest speaker at our Latin America class (he's Brazilian) and gave us his perspective on the interesting developments in that part of the world, focusing on Brazil, Argentina and Chile.

I think Prof. Blum gave a very fair and balanced perspective of globalization. While most capitalists would tout the praises of globalization and competition, he gave what I think is a fair criticism of globalization along with his description of the underlying economics. The key take away summarized (in my humble opinion):

"Globalization will create more wealth, but does not guarantee that it will be
distributed evenly."

It is NOT a zero sum game - I noticed that this is especially prevalent anywhere "efficiency" is involved. Advocates of globalization will often quote "comparative advantage" as one of the primary benefits of globalization even negating the benefits of size. For instance:

Country A (a larger country) can create:

• Computers at a rate of 50 per year
• Bread at a rate of 100 per year
• or any linear combination of the two (Computers are worth 2 bread)

Country B can create:

• Computers at a rate of 10 per year
• Bread at a rate of 30 per year
• or any linear combination of the two (Computers are worth 3 bread)

Country B is much better at creating bread than computers, so using it's comparative advantage it should create bread and trade with Country A for the computers it needs. Even though Country A can "out-manufacture" Country B in any category because of it's size, Country B can more efficiently create certain goods which it can trade with Country A.

It is fairly undisputed that globalization utilizes comparative advantage to increase the total wealth of all countries involved. However, as was brought up by our professor, this does not account for distribution of wealth. Regulations and other mechanisms are needed to ensure income equity. His comment was that criticism on this line against the WTO and globalization in general was certainly valid, whereas criticsm citing globalization as not wealth creating was economically falacious.

It's like in our strategy class when we talked about "double marginalization" where in vertical integration, two companies (as seperate entities) will optimize their cost and pricing structure in order to maximize their individual profits. However, from a more macro view, there is the potential for companies to gain synergies by vertical integration and earn margins that are optimal from a more wholistic view (which makes the case for the acquisition of a supplier or distribution channel by a company).

Rotman Q3 Exams - Prefaced by Canada vs USA

The Canada / US Men's Hockey is on the TV in the atrium and if you aren't watching it here, chances are you are probably watching it somewhere anyways.

However, exam week for Q3 will be starting next week with Econ on Monday, Strategy (a monster 5 hour exam) on Tuesday and Finance on Thursday. Also, the final leadership paper will be due on Friday at midnight.

March break will be the week after and already people have made plans to visit exotic warm locations like Cuba or Cancun or have decided to go for skiing: Tremblant, Tahoe.

Money and GDP Multipliers

I love geometric series. It describes so many natural phenomena especially as it relates to finance and economics. For example:

GDP mutiplier and Marginal Propensity to Consume (Save)
Marginal Propensity to Consume (MPC) is for every additional dollar of income, how much will people spend. Marginal Propensity to Save (MPS) is the opposite: for every additional dollar of after tax income how much will people save. By definition:

$1 = MPC + MPS

Different cultures will have different MPC and MPS. Americans are notorious for having high MPC (bordering on higher than $1, using financial instruments like credit cards and lines of credit to boost short term liquidity). Japanese are stereotypically savers in contrast.

However, let's assume a culture with MPC of 40%.

1. A spends $100 on B.
2. B receives $100 and spends $40 (40% of $100) on C.
3. C receives $40 and spends $16 on D.
4. D spends $6.40 on E etc. and the process continues.

Look familiar? It should. This pattern can be described as an infinite geometric series (the same formula which is used to described a perpetuity for DCF evaluation).

For a GDP multiplier, the initial amount is $1 by definition. The "discount rate" or rate of decay is related to the MPC. Recall (Using the same math trick for geometric series):

GDP Multiplier = $1 + $1 x MPC + $1 x MPC^2 + ...
MPC x GDP Multiplier = $1 x MPC + $1 x MPC^2 +...
(1 - MPC) GDP Multiplier = $1
GDP Multiplier = $1 / (1 - MPC)

But recall: $1 = MPC + MPS
MPS = $1 - MPC

Therefore:
GDP Multiplier = $1 / MPS

Money Supply Multiplier and Reserve (Lending) Ratios

This is EXACTLY the same case for Money Supply and Bank Reserves. A bank (by policy or regulation) has a reserve ratio (RR). That is, for every additional $1 in deposits, it keeps a given percentage and lends out the rest. Let's also define lending ratio (LR) as the complement and by definition:

$1 = Reserve Ratio + Lending Ratio

Imagine "the bank" (representing all banks in the economy) has a reserve ratio of 20%.

1. "The Bank" receives a $100 deposit and lends out $80.
2. The $80 it lends out to "the Economy" (representing all depositors and borrowers) takes the $80 and "uses" it and it is redeposited into the Bank.
3. With the new $80 deposit, the Bank lends out $64.
4. The borrower uses it and it is redepositied into the bank.
5. The bank receives $64 and lends out $51.20 etc and the process continues.

Again, this is a pattern described by the same concept and the same formulas apply:

Money Supply Multiplier (MSM) = $1 + $1 x LR + $1 x LR^2 + ...
LR x MSM = $1 x LR + $1 x LR^2 +...
(1 - LR) MSM = $1
MSM = $1 / (1 - LR)

But recall: $1 = RR + LS
RR = $1 - LR

Therefore:
MSM = $1 / RR

Notes:

Some key points about this formula, notice that the multiplier effect is always greater than the initial amount ASSUMING that the reserve (saving) amount is less than the total amount (you don't reserve or save all of it). So when a dollar is spend in the economy (or lent out) the effect on the supply is greater than one.

Also note that for odd values of reserves and saving (aka, American's spending more than a $1 by borrowing), you get a negative MPS and therefore a negative mutliplier which is a non-sense result (in a similar manner as my contest question that Chad got right). Whenever you see non-sense numbers (numbers which tell "stories" that don't make sense) it should always act as a red flag to reinvestigate the initial assumptions of the model.

Integrative Thinking: Dutch Auction - Tender Offer

What an interesting concept. We had briefly touched the idea of Dutch Auctions in microeconomics way back in Q1 which is a bidding strategy whose mechanics are based in the math of economics. Today, we applied this strategy towards share buy-backs in finance.

While it might be easy to pick up shares at the current market price, large orders by corporations to buy-back their shares is much more difficult because the market can't immediately absorb the change in liquidity from the huge jump in temporary demand.

So what to do? What mechanism will work where the company can get the best (a "fair") price for buying back its shares and shareholders can get the best (a "fair") price. The mechanism to use is a Dutch Auction.

Everyone announces their lowest acceptable price and number of shares for sale. The buyer (the company in the case of a buy-back) slowly adds up all the numbers of shares from lowest price to highest price until it accumulates all the stock it wants. It pays out all the share holders at the highest price of the group. This ensures that sellers get AT LEAST their minimum required amount and the buyer (the company) gets all the shares they need at the LOWEST possible price.

This actually happened in practice with Morgan Stanley's Dutch Auction system used for Google's IPO. They used a similar Dutch auction system which neutralized the effect of large companies purchasing stock and allowed smaller investors to also pick up shares.

Also, another lesson from class (something I was wondering about previously) Dividend policies don't really matter. Perhaps, like our capital structure lecture, this only occurs in "perfect" capital markets, but it is something to think about.

In summary: If a company gives out cash, it's beta goes up (because it's mix of "risky" assets has gone up, and it has given out cash which is a "safe" asset). However, on a net position your total holdings is the same. The risk gained / lost by giving out cash doesn't change your total net position.

Commitment - Restrictions for Improved Reward

Wow. What an oxymoron. We had briefly heard about this in game theory in Economics way back in Q1 and now it's coming up again in Q3 in finance.

First in game theory and dominant strategies. Look at the following example of the prisoner's dilemma:

So in the typical fashion, the dominant strategies for both players show that they will end up in the lower right corner with a return of 3 each. This is unfortunate, as there is a potential to get 5 each if they could only credibly commit to Strategy A each. But because of the conditions of the prisoner's dilemma, it's impossible.

To change the parameters of the game, what if it was possible for Player 1 and 2 to commit to impairing their own return matrix? For instance, what if Players 1 and 2 could reduce their returns in the cells AB and BA to 4 instead of 7 (as shown below)? Suddenly, the dominant strategy changes and the end game to a return of 5 each rather than 3.
We achieve a counter intuitive result. By placing restrictions on their own returns, both players can achieve a higher return.

In our finance class today, we talked about a different scenario with similar characteristics. First, an overly simplified example. Because equity holders are only liable for capital at risk (what money they put in), with the effects of leverage, they can increase their upside with a bottom of bankruptcy. This will encourage them to take on projects even if they have a stand-alone negative NPV (but a positive NPV with regards to the equity holder's return and relationship in bankruptcy - equity holders don't lose more money then they put in).

However, the debt holders will require a larger return on their debt to compensate them (make them whole) and offset the risk. This in turn can make projects unattractive and become prohibitive.
However, shareholders can introduce debt covenants in order to restrict the their own flexibility (preventing them from taking on too much risk and inflating their upside) to secure financing and ensure debt holders that they won't have to bear the dead weight loss of projects which fail.
Again, a counter intuitive result: You can do better by restricting your choices.

CFA Level II - Study Begins

I was studying for the CFA Level II on Sunday and I noticed that some of the topics covered in the Equity Analysis portion were items that I was pondering earlier including: alternate method of including the value of risk in DCF, inflation as a reasonable proxy for long term sustainable growth in a GGM or DDM, the constant relationship between ROE, k, PE, Dividend payout / retention, growth rate etc.

I'm very excited to be starting my study for the CFA Level II. Already, I'm learning a lot and getting confirmation and validations on some of the ideas I had pondered earlier as well as correction on some misconceptions.

So far, I'm particularly impressed with the integration of macro economic factors on valuations and approximating growth rates and factor variables in valuations via economic indicators (GDP growth, inflation, CPI etc). I am absolutely fascinated at the interplay and relationships for how different disciplines of study interact and how the mechanics of economics and strategy affect the mechanics of finance. Also, I think that the topics covered are pragmatic and absolutely brilliant in terms of applying theory in practice.