Capital Markets Theory asynchronous lecture

Finance 4335 will not meet in person tomorrow, Tuesday, March 19, due to ongoing health-related issues in my family.  Therefore, tomorrow’s “Capital Markets Theory” lecture will be delivered asynchronously.  This lecture explores capital market theory, transitioning from our previous (Thursday, March 14) portfolio theory lecture.  As in last week’s asynchronous lectures, class participation credit will be awarded to students who write and upload a lecture synopsis to Canvas.

Capital market theory examines the equilibrium pricing of individual securities, a concept better known as the capital asset pricing model (CAPM). This session mainly draws upon the lecture note  “Portfolio and Capital Market Theory,” the linked for which also appears under item 10 on the course website’s lecture notes page. Toward the lecture’s end, I discuss the Capital Market Theory Class Problem, available at http://fin4335.garven.com/spring2024/capmktproblem.pdf.

This lecture is available for viewing at https://mediaspace.baylor.edu/media/Capital+Market+Theory+Lecture+%28March+19%2C+2024%29/1_pkvgnk98.

Video Lecture Synopsis

A couple of students from Finance 4335 have reached out inquiring about the contents of a synopsis. A synopsis should encapsulate a condensed overview of the lecture. Within your overview, enumerate the subjects discussed and outline the significant principles connected to these subjects, which you learned from the video lecture. It should also be concise; no more than a page or two.

I have decided to extend the deadline for this particular assignment from 5 pm to 11:59 pm today. Additionally, you have the option to resubmit your synopsis once if you choose to do so.

This week, Finance 4335 will proceed asynchronously!

Because of health-related issues in my family, our Finance 4335 class will not meet in person next week and will proceed asynchronously on March 12th and 14th. We will continue as planned, concluding our discussion of the Asymmetric Information topic on March 12th and beginning the Portfolio Theory topic on March 14th.

I’ve uploaded lectures for both of these dates: “Asymmetric Information and Adverse Selection” on March 12th and “Portfolio Theory” on March 14th. Since Finance 4335 will not meet in person this week, I expect everyone to watch and report on both lectures online. To earn attendance and participation credits, watch both lectures and submit synopses for each in PDF format via Canvas. The synopsis for the March 12th lecture is due at 5 pm on March 13th, and the synopsis for the March 14th lecture is due at 5 pm on March 15th. I have created two separate assignments for your lecture synopses that can be found on the course Assignments page on Canvas.

I will also be available for virtual (Zoom) office hours on Tuesday, March 12, and Thursday, March 14, from 3:30-4:30 p.m. To meet with me, type “officehours.garven.com” in the address field of your device’s web browser.  If you like, you can also make an appointment on MW by typing “appointment.garven.com” in the address field of your device’s web browser.

Here are the links for the March 12 and March 14 lectures:

March 12 (Asymmetric Information and Adverse Selection): https://mediaspace.baylor.edu/media/Finance+4335+-+Asymmetric+Information+and+Adverse+Selection+lecture/1_d8mdxvhh

March 14 (Portfolio Theory): https://mediaspace.baylor.edu/media/Portfolio+Theory+Lecture%2C+March+14%2C+2024/1_gbm0vhlg

Tomorrow: 2024 Collegiate Day of Prayer

Did you know Baylor University is hosting the 2024 Collegiate Day of Prayer? All Baylor students are encouraged to come together tomorrow (February 29) at 7 p.m. for the worship and prayer service in Waco Hall. The Hankamer School of Business will also have Foster Room 143/144 reserved tomorrow from 8 a.m.-5 p.m., with stations for prayer guidance for students, faculty, and staff.

For more information, visit baylor.edu/dayofprayer.

Midterm 1 and Current Course Grades in Finance 4335

I have uploaded the midterm 1 grades, along with current attendance/participation, quiz, problem set, and Finance 4335 course grades, to Canvas.

As stated in the course syllabus, final numeric course grades will be determined according to the following equation:

Final Course Numeric Grade =.10(Attendance and Participation) +.10(Quizzes) +.20(Problem Sets) + Max{.20(Midterm Exam 1) +.20(Midterm Exam 2) +.20(Final Exam),.20(Midterm Exam 1) +.40(Final Exam),.20(Midterm Exam 2) +.40(Final Exam)}

As I noted in my January 29th blog posting entitled “Finance 4335 Grades on Canvas”, as the spring semester progresses and I continue to collect grades in the attendance, quiz, problem set, and exam categories, then the course grade listed on Canvas will dynamically incorporate that information on a timely basis for each student.  Now that we have Midterm 1 Exam grades, the course equation that I am now using (until Midterm 2) is:

Course Numeric Grade after Midterm 1 = (.10(Attendance and Participation) +.10(Quizzes) +.20(Problem Sets) +.20(Midterm 1))/.6

Here are the current grade statistics, broken down by grade category, for the 31 students enrolled in Finance 4335 this semester:

Although actual letter grades won’t be assigned until after the final exam, hypothetically, you can determine where your course letter grade currently stands by comparing it with the course letter grade schedule in the course syllabus.

If you are disappointed by your performance to date in Finance 4335, keep in mind that the final exam grade automatically double counts in place of a lower midterm exam grade. If both midterm exam grades are lower than the final exam grade, the final exam grade replaces the lower of the two midterm exam grades.

If any of you would like to have a chat with me specifically about your performance on Midterm 1, or generally about your grades in Finance 4335, then by all means, stop by my office (Foster 320.39) 3:30-4:30 pm TR, or set up a Zoom appointment with me.

WSJ Page 1: The Small University Endowment That Is Beating the Ivy League

From WSJ: “The more than $200 million Paul and Alejandra Foster Pavilion at Baylor University opened in January, with proceeds from the endowment helping to fund its construction.

WSJ (2/14/2024) Page 1 story about Baylor’s 2 billion dollar endowment, and how it is managed…

https://www.wsj.com/finance/investing/the-small-university-endowment-that-is-beating-the-ivy-leagues-8ce37cf1?st=ncxhvwphm1vrrx8&reflink=desktopwebshare_permalink

An important clarification of the logical principles behind the stochastic dominance model

On problem set 4, part D, most of you had no apparent difficulty in correctly establishing that the sum of the differences between the cumulative distribution (CDF) for risk 2 and the CDF for risk 1 is positive.   However, many of you drew the wrong conclusion, claiming that since the sum of differences between F({W_{2,s}}) and F({W_{1,s}}) came out to a positive number, it followed that risk 2 second order stochastically dominates risk 1.  Actually, this result implies the opposite; i.e., that risk 1 second order stochastically dominates 2. This blog posting aims to clarify everyone’s understanding of the logic behind the stochastic dominance model.

The one-page exam formula sheet includes section 4, which explains that risk i dominates risk j, in both the first and second cases when 1) the cumulative distribution function (CDF) of the ith risk is either less than or equal to the CDF of the jth risk for all states (first order dominance), or 2) the sum of the differences between the jth risk CDF and the ith risk CDF for all states is positive (second order dominance):

While the math behind first and second order stochastic dominance is summarized in my optional reading entitled “Technical Note on Stochastic Dominance and Expected Utility”, the intuition for first and second order stochastic dominance can be seen in the figures featured on pages 9 and 12 of my Decision-Making under Risk and Uncertainty, part 4 lecture note.

In the above figure from page 9 of my Decision-Making under Risk and Uncertainty, part 4 lecture note, the G risk has 50% of a $0 payoff, and 25% each of a $10 payoff and a $100 payoff.  The F risk involves removing 25 percentage points off the $0 payoff and adding 25 percentage points extra to the $100 payoff, and both F and G have a 25% probability of $10 payoffs.  Graphically, this ensures that F first order stochastically dominates G; i.e., G(Ws) is greater than or equal to F(Ws) for all s, which also implies that EF[U(W)] > EG[U(W)]. Intuitively, the picture which gets rendered by this analysis shows that most of the probability mass of the stochastically dominant risk (in this case, F) lies below the probability mass of the stochastically dominated risk (in this case, G). Furthermore, since risk F first order stochastically dominates risk G, risk F also second order stochastically dominates risk G because G(Ws) – F(Ws) > 0 for $0 and $10 payoffs, and G(Ws) – F(Ws) = 0 for the $100 payoff.

Next consider the figure from page 12 of my Decision-Making under Risk and Uncertainty, part 4 lecture note:

Here, G(Ws) – F(Ws) > 0 for payoffs ranging from 1-5, G(Ws) – F(Ws) < 0 for payoffs ranging from 5-8, and G(Ws) – F(Ws) = 0 payoffs ranging from 8-12.  Thus, there is no first order dominance.  However, since the positive difference between G(Ws) – F(Ws) for payoffs ranging from 1-5 exceeds the negative difference between G(Ws) – F(Ws) for payoffs ranging from 5-8, the sum of G(Ws) – F(Ws) over the entire range of payoffs comes out positive.  Thus, risk F second order stochastically dominates risk G, which also implies that EF[U(W)] > EG[U(W)].