Artistry with Dr. Hilary Austen

Tonight, there was a Rotman panel discussion hosted at the Savoy Hotel in London by our dean, Roger Martin, on “Artistry Unleashed: Pursuing Great Performance in Work and Life” written by Dr. Hilary Austen. They had a great discussion on how our current educational system seems to focus heavily on quantitative knowledge potentially at the expense of qualitative knowledge which, although by definition difficult to measure, plays an important role not just in decision making, but our ability to perform well in different environments.

Vetran integrative thinkers can probably also recognize the concept of model tension between these two ideas and can appreciate that the conversation between the panelists with Roger facilitating lead to interesting perspectives and topics being raised (eg. the role of analytical versus intuitive recognition for diagnosis performed by doctors).

Afterwards, there was a cocktail reception with the opportunity to speak with people connected to the Rotman community in London through a variety of different channels: students like myself, alumni, business partners, patrons of business publications etc.

KKR at LBS - Socially Responsible Private Equity

Just now, we had the inaugural talk for the Socially Responsible Private Equity talk given by Ken Mehlman, KKR's Global Head of Public Affairs. He was the Chairman of the United States Republican Party, campaign manager for President George W. Bush's re-election campaign, and White House Political Director. He was also a classmate of Barack Obama at Harvard Law.

He gave a great talk on how social responsibility is integral to sustainability of a business, especially one with patient capital in PE. One point he made which I thought was particularly poignant seemed to echo the ideas of Integrative Thinking. He said that there are generally two common models with regards to social responsibility:

1. Corporate CSR – Where a company makes contributions to organizations outside of its operations that show it cares.
2. It focuses solely on strong operations and generating business returns to the bottom line without much consideration for social responsibility.

He mentioned that KKR takes a third approach, and that it integrates social responsibility not just at some abstract corporate or portfolio level, but right down to the alignment of its operations to produce. Examples of this would include involving a broader definition of stakeholders versus shareholders such as environmental agencies and unions in determining the best course of action for a company’s future operations and how it should be run.

Besides some of the insightful deal war stories, future PE trends and industry knowledge he shared, he also gave great advice on what he thought it took to be successful which was well received by the crowd.

There were a host of excellent questions asked by the crowd in the Q&A session as well as the cocktail reception following. I’m looking forward to the next event hosted by the PEVC club.

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):

Intuitive Explanation of Bayes’ Rule

One of my favourite math identities is Bayes’ rule. It also occurs quite frequently in Behavioural Econ / Finance as well as integrative thinking because it is such a good (mathematically provable) example of flawed thinking and model construction.

But like any formula, if not understood at an intuitive level (aka memorizing the formula vs rebuilding it from scratch), applying the formula incorrectly will yield meaningless (and potentially misleading) results.

Bayes’ rule states:

P(A\B) = P(B\A) x P(A) / P(B)

On the surface, this formula seems to make no sense: “The probability of A given B is the probability of B given A multiplied by probability of A divided by probability of B.”

However, walking through step by step we first understand that:

P(A\B) = P(A Λ B) / P(B)

This makes sense. The probability of A happening given that B has happened is the area encompassed by A and B (gray) divided by the total universe of probabilities, B (red and gray), because we are told that B “has happened”.

So from here we can also understand that:

P(B\A) = P(A Λ B) / P(A)

Which is simply the same rationale as the one above. However, using algebra, we can see that:

P(A Λ B) = P(B\A) x P(A)

And combining the two formulas, we get the original:

P(A\B) = P(B\A) x P(A) / P(B)

Example provided in class:
Of patients entering a chest clinic:
Event A – Person has cancer
Event B – Person is a smoker

80% of people with cancer are smokers: P(A\B) = 80%

10% of patients have cancer: P(A) = 10%
50% of patients smoke: P(B) = 50%

If you knew someone was a smoker, what is the probability they have cancer?

Solution:

Most people would over estimate the number, due to various incongruities in the probabilities, namely because such a high percentage of patients with cancer are smokers at 80%.

However, the math shows us that P(B\A), the probability of finding cancer given that you know someone is a smoker is (80% x 10%)/50% or 16%. Although it is higher than the average of 10%, is still relatively unlikely that they have cancer relative to what most guesses anticipated.

You'll notice that the answer is heavily affected by the rarity (and relative elasticity) of event A, or the chance that someone has cancer to begin with.

Behavioural Finance and Bounded Rationality

Whether fortunately or unfortunately, human beings do not behave in perfectly economically rational ways which makes them very difficult to predict. Even with our most complex models accounting for a variety of different factors, there is a high degree of volatility not explained by our multifactor regressions and the models they produce.

Behavioural finance (along with it's fraternal twin, behavioural economics) aims to better understand how humans make decisions that are non-optimal in the strict finance / economics definition and don't comply with what academics would have us anticipate as expected behaviour.

While this course is particularly interesting, what did strike me as noteworthy was that a lot of the foundation material for this course is based on the same principals as integrative thinking taught in our FIT class. In fact, it seems as if we've been doing a review of FIT, focusing on how humans make errors in judgment and build sub-optimal mental models based on well documented shortcomings in how we think.

In fact, some of the examples used in the class are lifted from the exact same material presented to us in Q1 of our first year highlighting anchoring effects, neglecting regression to the mean, availability heuristic, rational probabilty assessments, hot hand and gamblers fallacy etc.

[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!

Modeling a Down Payment as a Call Option

There was an interesting idea that came up in our discussion of Islamic Finance that got me thinking. While not directly related to what we were doing, someone mentioned the idea that a down payment was modeled like a call option which I thought was quite clever.

Consider this, you can:

• put down a payment for the right to purchase the asset
• elect to walk away from this right, forfeiting the down payment, or
• pay the *remaining amount* and purchase the asset at the appropriate time

This is very similar to a call option, with only one exception:

Note that in a down payment, you are paying the remaining amount, not the full amount of the asset. So if you were to use a call option to model down payment, you would have to adjust the strike price down by the premium (down payment) because the down payment is applied to the purchase price of the asset.

So imagine that the value of your asset changes after you’ve paid the down payment. If it goes up, you can continue your purchase (and possibly even sell your asset for a profit, assuming its liquid enough) or you can elect not to buy it if you’ve taken a huge bath (maybe even the market value dropped by more than the down payment amount).

Back from the Holiday

Well after a well deserved break, all the students are back.

First years are in their Negotiations class which odd for me as I didn’t do this last year due to the Middle East study tour, but now I see what it was like with the Atrium constantly being flooded by ambitious MBA students trying to get better deals in their exercises. There have also been requests for help with preparing for recruitment week which is coming up next week and some postings already up.

Even second years are at school, many having the clever idea of taking an intensive or two to lighten their final term course load.

Yesterday, we did a presentation for our ICP in Islamic Finance. Arash and I did a presentation on two comparable securities, one conventional and one Islamic and we showed they were strategically and operationally comparable (same industry, business model, enterprise value, capital structure, debt ladder, similar maturity, seniority and economic conditions, but different country and terms) and we analyzed the yield, adjusting for country risk and broke down the spread accounting for liquidity risk, minor maturity differences and increased cost of capital related to Sharia compliant terms.

This material will be used as part of Rotman’s new Executive MBA program class on Islamic Finance. While we aren’t quite finished with our work, the next step being to propose a term sheet for what the conventional financing would look like if it were Sharia compliant, I’m very happy with our progress and the insight we were able to bring into this new product class.

ICP Islamic Finance - "Conventional" Analysis

This morning we had a working session for our ICP - Islamic Finance with some lawyers, a corporate banker and professors. The two teams presented their analysis of the conventional financing structure of the primary security instruments used to finnace our projects. Under this conventional analysis, we looked at the costs of capital and the associated terms related to these types of paper with the intent of understanding the requirements need to make them Sharia compliant.

We also had great explanation from a senior lawyer regarding the structuring and "asset-based" (versus "asset-backed") nature of nominating (rather than selling) assets under a Special Purpose Vehicle (SPV) in order to comply with the necessary requirements of Islamic finance. We had considered the capital gains implications of a sale leaseback transaction, as well as understood how an asset and capital intense infrastucture project would look similar under an adjusted EV to EBITDAR metric regardless of the off-balance sheet financing that may potentially be required.

We have a solid understanding of the work requirements due before our next meeting in early January (before I fly off for London). We also had an opportunity to fire questions back at the professionals in the room in terms to learn what were the appropriate resources for generating comparables for analysis and benchmarking of our theoretical capital structures based on similar Sharia compliant instruments and current market conditions.

Some of the best advice we got:

• Understand the difference between "asset backed" versus "asset based" and how that affects your ability to issue Sharia compliant instruments
• Be aware of tax implications of capital gains/losses in a sale leaseback transaction
• Like any financial security, understand the key characteristics of seniority and expected return for a sukuk issuance and understand market appetite for these structured products

What Makes Rotman Different? A foray into the world of Business Design

In anticipation of our trip to LBS, Geoff and I have been asking ourselves: “What makes Rotman different?” In discussing this idea, one of the key points at the top of the list was business design. This week, I’ve had the pleasure of attending various events over at Design works where members of a university in Singapore are undergoing certification for Business Design.

On Tuesday, Geoff and I attended a working session with Anita McGahan discussing the evolution of demographics across different geographies and the implications for the future of the health care industry around the globe. With our guests present, we learned a great deal about the specific differences in the Singaporean culture and life style and were impressed by the innovation produced by their ambitious programs.


This exercise was particularly enlightening for me, not only because of my previous work as a Wireless Consultant for RIM in the healthcare communication and process optimization space, but also to learn more about the business design process.

Today, I also attended a talk given by my class mate and president of the Business Design club, Jason Huang, at Design Works for our Singaporean guests. He gave a very inspiring speech about the current state of business design at Rotman as well as a road map to the initiatives he and his team are putting into place to further develop the program at Rotman at the academic and extra-curricular levels. I am particularly impressed by his attitude, aiming to be the top club at Rotman. I think he also has demonstrated that he has the will and ability to execute on these new initiatives, launching business design more prominently into the spotlight.

He also had a great point about case competitions where “the idea isn’t just to try to do well, but more importantly to learn” a sentiment which I would like to echo and I think reflects my personal motivation for participating in various case competitions, including those not necessarily related to my chosen profession.

What is Business Design @ Rotman? Find out for yourself by watching the YouTube video below:

Multi-Factor Models – Applying the Lessons Learned from the Numbers

In Finance 1 last year, we were introduced to the idea of multi-factor models (MFM) originally explained by Fama and French as an alternative to the traditional Capital Asset Pricing Model (CAPM) for assessing systematic risk. Additional factors include small versus big (SML) and value versus growth (HML).

In our Business Analysis and Valuation class, we discussed a merger case in which a large company acquired a smaller company. We talked about what would be the best way to approximate beta. The method I used (which was the best method I could conceive, I’d be happy to hear criticism or suggestions otherwise) was to weight the betas by market cap and take an average.

However, there was some discussion about the fact that one entity was much smaller than the other. While we were having a conversation of what that would actually mean, I would suggest a mathematical method for expressing the quantitative effect of size, using FF’s MFM.

1. 1. Express both company’s re as a three factor MFM
   Re1 – RFR = beta1 (Rm – RFR) + betas1 (SMB) + betav1 (HML)
   Re2 – RFR = beta2 (Rm – RFR) + betas2 (SMB) + betav2 (HML)
2. Take the larger company’s size beta and apply it to the smaller entity
   betasnew = betas2
3. Recalculate re for both entities
   Re1new – RFR = beta1 (Rm – RFR) + betasnew (SMB) + betav1 (HML)
   Re2new – RFR = beta2 (Rm – RFR) + betasnew (SMB) + betav2 (HML)
4. Take a weighted average (by market cap) as the expected return of the combined entity

By taking the larger company’s size beta for both, what you are saying is that you expect the smaller company to have the size “characteristics” of the larger entity. I might even be more appropriate to add the size factors (Would that be appropriate? As the MFM is a linear regression, is it appropriate to add these factors?) and use that for new return on equity for each entity as it relates to the combined entity.

betasnew = betas1 + betas2

While there are some significant assumptions which are required for this to work, it is the best solution I can conjure based on information given. I would really appreciate any additional ideas for creating a more robust model.

Islamic Finance - International Consulting Project

A new initative at Rotman (although you wouldn't know it as it has simply exploded this year) is the International Consulting Project. Laura Wood, Director of International Programs, has started a new research type project that engages students to work with professors on international topics. Some countries involved are the G20, Middle East, Israel, Africa and potentially others.

I myself am participating in the Islamic Finance ICP with Walid Hejazi, the professor who leads the Middle East study tour.

Yesterday, we were invited to attend the kick off event for the Islamic Finance EMBA course which will be offered in Jan 2011. The keynote speaker was David Dodge, Senior Advisor, Bennett Jones and former Governor of the Bank of Canada. He spoke about the growing interest in Islamic finance and how there it is common for people to see Shariah compliant instruments as simply "no interest" and how this superficial understanding does not encompass the fundamental rational for the structure of these products.

I am looking forward to working with my four other colleagues on this research project to look at Islamic financial instruments.

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.

Recursive Options? Calling a Call

We've been shown how equity near bankruptcy behaves like a call option in our Finance II class. We've also been told in some of our integrative thinking classes to consider the models for employee (CEO) compensation to reduce the principle-agent costs / issues resulting from the relinquishing of control from capital investment.

My question is this. Consider the following scenario:

A company is struggling. It's Enterprize Value is low (less than debt) making equity intrinsic value essential zero (or negative) trading like an option.

In order to turn the company around and restructure, the company fires it's current CEO and recruits a new one. In order to motivate the new CEO to turn the company around, the CEO is offered stock options (we'll assume unrestricted for now).

What scenario have I just decribed? The securities that the CEO is holding are essentially call options on call options. That is to say the CEO's derivative, the call option, has an underlying asset which also behaves as an option (the equity behaves like a call option).

... Now assume that the stock is a mining company (which behaves like an option relative to the underlying commodity).

I wonder how you would even begin to model how much these options are worth? While valuing options itself are already quite tricky using models like Black Sholes Martin, I wonder what model would be appropriate for a derivative with recursive properties.

Also, as a financial derivatives joke, I overheard one unfortunate soul ask this question: "Are management stock options calls or puts?"

BATNA and Sharpe Ratios in M&A

While I missed the Negotiations class my classmates took for the Middle East Study tour, I was fortunate enough to have taken a Negotiations class at the Analyst Exchange in NYC where they explained concepts like BATNA (Best Alternative to a Negotiated Agreement) in a simulated negotiation environment.

Also, in ITP, we talked about the model for "rational experimentation", that is to say the formula which describes the logic between probability of successful outcomes versus the risk and initial investment required (looks suspiciously similar to an NPV calculation because it uses the same mathematical components with probability of success superimposed on the cash flow, similar to how the CFA teaches to account for risk).

With my last post on M&A and splitting synergies with the target's share holders, this got me thinking about what would be "rationally" fair in M&A negotiations. I thought about it and decided it might be a good idea to integrate the thoughts from the post below with the idea of a Sharpe Ratio (or more exactly, Roy’s Safety First Criterion – where we use a “minimum return” rather than risk free rate).

S = (E[R] - Rf) / sigma

Where:

• E[R] is the expected return of the project
• Rf is the risk free rate (or in Roy's SFC, minimum return)
• sigma is the standard deviation of the investment

Obviously, there are some of the same undertones that we have learned from CML or CAPM. While I was thinking about Synergies and Premiums analysis of an M&A deal, it struck me that while there is some "risk" in the total Synergies achievable, the Premium is paid in advance and essentially risk free. Immediately, some of the same terminology which was used in the previous post suddenly rung a bell with regards to the Sharpe Ratio (from CFA Level I).

I would propose that the Sharpe ratio calculation can be used in an analogous manner for an M&A deal with synergies. For example:

• Expected Returns --> Synergies
• Risk Free Rate --> Premium
• Sigma --> some sort of volatility related to success of M&A deals to achieve expected returns

In fact, you can take this a step further and get:

• Synergies / EV as a proxy for M&A incremental ROA
• Premium / EV as a proxy for M&A minimum return

S = (Synergies – Premium) / (EV * sigma)

The formula would then calculate something very similar to marginal excess ROA or value creation per unit risk by the deal. Besides helping you understand your BATNA, this metric might also help you select acquisition targets from a financial perspective.

The Acumen

I've been exceptionally busy the last few weeks. Even though I've decided to place a moratorium on competitions, I’ve still found myself overwhelmed with the MBA and the CFA Level II material. One thing I’ve been trying to keep track of in my posts is the absolutely brilliant ideas I’m encountering, whether in the Rotman MBA or CFA Level II.

But lately, my ability to post and get work done has drastically dropped off. And I would like to think it’s not because I’ve gotten lazy, but rather because there is so much brilliant and interesting stuff going on that I can’t post it all.

And I think that is exactly the case. Example? ITP, a course that had many of us scratching our heads in the beginning has suddenly burst forth with ‘light bulbs’. For example, not too long ago, I was complaining about how “past performance does [NOT] predict future behaviour” in some cases but not others. For example, individuals (as social science will tell you) are predictable (past performance DOES predict future behavior) but this is not so in finance and capital market instruments (good luck buying a stock based on it’s past behaviour hoping for gains).

And ITP has taken this exact point and, in our latest team assignment, asked us to investigate why this is. How “predictable” individuals (with their behaviour well defined) in a group produce slightly unexpected results. And the effect this has on our perception of what we learn in finance classes as it relates to theoretical concepts (CAPM comes to mind at the top of this list, but is closely accompanied by the idea of bubbles and crashes in the stock market, a very timely topic).

You can imagine that I am very excited. Suddenly, I am being given the vocabulary to describe in practical terms what we’ve been taught in textbooks. One of the reasons why I came to the MBA program was to help me structure my thoughts so that I could package them and deliver them to someone in a more digestible format.

While I was fortunate to have known many brilliant minds at McMaster Engineering, in my work life, I felt like I wanted to further develop my business skills to speak the same language as my colleagues and be able to use descriptors outside of the Engineering dictionary so we could understand each other, work together and accomplish amazing things. It was one of my goals coming into Rotman: I thought I was pretty clever. But I wanted to develop my business acumen.

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).

Business Design Competition - 3rd Place

I spent to better part of yesterday afternoon and this morning participating in the Business Design Competition. Our team was composed of myself, Yan, Mark, Justin and Xinxin. It was an interesting challenge. We were introduced to the business design process and given an open problem and carte blanche to find an appropriate solution.

We had a great team dynamic and every member contributed according to their strengths. At the end, I think we all learned something new, picked up more skills and experience which we can certainly apply to other aspects of our business careers.

The competition was judged by several industry professionals including a strong showing from Monitor Consulting.

After the first round presentation, when we discovered that we had made it to the second round, I think our group took the criticism of the judges very well. Even before our ranking was announced, I had told my team that I was exceptionally happy with the improvement we had made as a group in refining our presentation skills on the fly.

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.