Syllabus (FIN 332) Fundamentals of Investments

SUNY POLYTECHNIC INSTITUTE

SCHOOL OF BUSINESS ADMINISTRATION

Instructor: Matt Brigida, Ph.D.

Office: Donovan 1277

Online Office Hours: On request.

Email: matthew.brigida@sunypoly.edu

Class Location: Online.

Class Day/Time: Asynchronous

Optional Text: Investments by Bodie, Kane, and Marcus, 8th edition (or later), ISBN: 0077261453

The Investments text is optional, and all the material is available with appropriate prompts to an LLM. That said, I recommend you pick up some edition of the text. You can often find a used copy online for less than $10, and in this case it is well worth the money.

Supplementary/Optional Materials:

Description

An introductory survey of the fundamental principles of investment management. The learning outcomes for this course are summarized below:

Understanding the structure of various capital markets, as well as how and why organizations (ranging from individuals to multinational firms) participate in these markets. Particular importance will be assigned to innovations in market structures (dark pools, ECNs) and their implications for market participants. The student will be able to set up buy and sell orders for various securities, as well as understand the use of leverage inherent in margin accounts and some derivative securities.
To extend previous study on equity and fixed income security valuation. Further, we will introduce and value hybrid securities which have characteristics of both debt and equity (particularly convertible bonds). Valuing the warrant in a convertible bond will also serve as a prelude to derivative securities.
Quantify the interest rate risk in fixed income securities using duration and convexity. Moreover, the student will be able to discuss the allocation of interest rate risk between lender and borrower in fixed rate as compared to adjustable rate securities.
Assess reinvestment risk in fixed income securities and the benefits inherent in the option to prepay.
This course will also introduce exchange-listed derivative securities (futures and options), along with basic hedging and speculation strategies using these securities. Students will also learn about the markets wherein derivatives are traded, and how laws governing these markets may differ from the laws governing the stock markets. A basic introduction to valuing futures on storable commodities, currencies, and interest rates will be afforded. We will then briefly discuss futures on non-storable commodities (particularly electricity). Lastly, using Excel students will apply the Black-Scholes (1973) option pricing model to valuing options on non-dividend paying stock. The assumptions of Black-Scholes (1973) will be discusses along with a non-rigorous introduction to risk neutral pricing (intended to motivate further study).
Students will be able to measure the risk and return of individual securities as well as of a portfolio of multiple risky securities. The effect of forming a portfolio on risk and expected return will be quantified, as well as the resulting implications for forming an efficient portfolio. We will derive the Capital Asset Pricing Model (CAPM) and thereby calculate the expected return for individual securities. A short discussion of the assumptions of the CAPM and the alternative ‘Arbitrage Pricing Theory’ (APT) will conclude.

Course Objectives and Learning Outcomes:

Upon successful completion of the course each student will be able to:

Understand and express factual knowledge, principles and theories in the area of investments,
Exhibit creative problem-solving skills and refined reasoning capabilities in the area of investment selection and management,
Recognize the need for a broad-based, general education as a useful tool to understand the financial markets,
Understand the growing importance of globalization on both the investment process and on security markets,
Show an awareness of the various issues and developments that constantly reshape financial markets and investment choices.

Learning Goals and Objectives

Goal or Objective	Assessed by
Goal 1.0: Demonstrate Business Disciplinary Competence	The exams and homeworks will evaluate both equity and fixed income security valuation.
Goal 3.0 (Objectives 3.1 and 3.2): Communicate Effectively Orally and in Written Form	The presentation of a student created Excel spreadsheet to calculate stock option prices using the Black-Scholes(1973) model
Goal 4.0 Objectives 4.1 and 4.3): Demonstrate Analytical Thinking Skills	Students will learn to value securities by the principle of no-arbitrage. Further, students will discern which derivative securities may be valued by no-arbitrage and which may not
Goal 5.0: Understand Global Issues in the Functional Areas of Business	New exchanges spanning of multiple continents (e.g. NYSE Euronext) will be discussed with particular attention being paid to their effect on the investment landscape.
Goal 6.0 (Objectives 6.1 and 6.3): Demonstrate Effective Use of Technology and Data Analysis	In both homeworks and these project, students will value complex securities using Excel.
Objectives 1.1 (knowledge of a key business discipline), 4.1 (interpretation of evidence), 4.3 (formulation of conclusions), and 6.3 (understanding data analysis)	Students will measure both individual asset and portfolio risk and return. Through analyzing the effect of portfolio construction on risk and return, students will derive the CAPM. After a discussion of the assumptions of the CAPM, students will weigh the model against the APT.

Project 1: Earnings Announcement Event Study

Each student will complete an event study on a U.S. common stock whose ticker begins with the same first letter as the student’s last name. The event is the company’s most recent earnings announcement prior to the start of the semester. If no suitable NYSE or Nasdaq-listed common stock is available for that letter, the student should use the next letter in the last name. If that also fails, the student should contact the instructor for an approved fallback ticker. ETFs, mutual funds, ADRs, preferred shares, and OTC stocks may not be used.

The project has two parts. Part A measures the market’s reaction to a single earnings announcement, and is worth 10 points. Part B repeats that measurement across roughly three years of quarterly announcements and asks whether the size of the earnings surprise explains the size of the reaction, and is also worth 10 points.

Part A: A Single Announcement

The purpose of this part is to measure how the stock reacted to its most recent earnings news. Students must identify the earnings announcement date using the company’s investor relations page, earnings press release, or SEC filing. The event date is defined as the first trading day on which the market could react to the earnings news. If the earnings release was issued before the market opened, that trading day is day 0. If the earnings release was issued after the market closed, the next trading day is day 0.

Students will use daily adjusted closing prices for both the stock and the market benchmark, SPY, to compute returns. Daily stock return is:

\[ R_{i,t} = \frac{P_{i,t}}{P_{i,t-1}} - 1 \]

and daily market return is:

\[ R_{m,t} = \frac{P_{m,t}}{P_{m,t-1}} - 1 \]

where $P_{i,t}$ is the adjusted close for the stock on day $t$, and $P_{m,t}$ is the adjusted close for SPY on day $t$.

Students will calculate abnormal return for each day in the event window using the market-adjusted model:

\[ AR_t = R_{i,t} - R_{m,t} \]

The required event window is [-1, +1], where:

-1 = the trading day before the event
0 = the event day
+1 = the trading day after the event

Students must calculate:

the stock’s return on day -1, day 0, and day +1
SPY’s return on day -1, day 0, and day +1
abnormal return on day -1, day 0, and day +1
the cumulative abnormal return over the three-day window:

\[ CAR[-1,+1] = AR_{-1} + AR_0 + AR_{+1} \]

For Part A, each student must submit:

a spreadsheet showing all calculations
the source for the earnings announcement date
a chart showing either the three abnormal returns or the cumulative abnormal return over the event window
short responses to the following questions:
- Was the market reaction to the earnings announcement positive or negative?
- Was most of the reaction concentrated on day 0, or did it spill over to day -1 or day +1?
- Does the result appear consistent with semi-strong-form market efficiency? Be careful here about what a single observation can and cannot establish — you will return to this question with a larger sample in Part B.

Part B: Multiple Announcements — Do Surprises Explain Returns?

Part A measures the market’s reaction to a single announcement. One observation cannot tell you whether the market is efficient. In Part B you repeat the measurement for every quarterly announcement available for your stock — roughly the last three years, or about 12 quarters.

Go to the Earnings tab of your stock’s Google Finance page. For example, for Nike: https://www.google.com/finance/quote/NKE:NYSE (then select Earnings). For each quarter available, record:

the announcement date
EPS actual, EPS estimate, and EPS surprise (%)
revenue actual, revenue estimate, and revenue surprise (%)

For each announcement, compute $CAR[-1,+1]$ exactly as in Part A, using SPY as the benchmark. You need only download the daily adjusted closes for your stock and for SPY once, covering the full three-year period. Use the announcement date shown as day 0 if the release was before the open, and the next trading day if it was after the close. If you cannot determine the timing for a particular quarter, use the date shown and note that you did so.

Note that with only about twelve observations your fitted relationships will be noisy and your $R^2$ values will likely be low. That is a feature of a small sample, not evidence that you have done something wrong.

Then produce:

a scatter plot of $CAR[-1,+1]$ (vertical axis) against EPS surprise % (horizontal axis), with a fitted line, reporting the slope and $R^2$
the same scatter plot against revenue surprise %
a count of sign agreement: in how many quarters did a positive EPS surprise produce a positive $CAR[-1,+1]$, and in how many did a negative surprise produce a negative $CAR[-1,+1]$?

And short responses to the following:

Which surprise measure — earnings or revenue — lines up better with the market’s reaction? Why might that be?
The slope of your fitted line is the abnormal return associated with a one percentage point earnings surprise. Is that magnitude economically large?
Identify a quarter in which a large positive surprise produced a negative $CAR[-1,+1]$. What could explain this? Consider forward guidance issued in the same release, and the difference between the published analyst consensus and what traders actually expected.
With roughly twelve observations rather than one, what can you now say about semi-strong-form market efficiency that you could not say from Part A alone?

Optional Extension: Post-Earnings Announcement Drift

This extension is not required and is not worth any points. It is here for students who want to see the most interesting result in this area.

Everything above looks at the three days around the announcement. Instead, compute $CAR[+2,+30]$ — the cumulative abnormal return from two trading days after the announcement through thirty trading days after it — and plot it against EPS surprise %. This window begins after the immediate reaction is over, so under semi-strong-form efficiency the surprise should have no power to predict it: the news was public a month earlier.

If you find a positive relationship — stocks with good surprises continuing to outperform for weeks afterward — you have found post-earnings announcement drift, one of the most durable documented anomalies in finance, and a result that cuts against the efficiency conclusion you likely reached in Part B.

Submission and Grading

Submit both parts together in a single spreadsheet, with Part A and Part B on clearly labeled separate sheets, along with your written responses. Include a description of how AI was used in completing the project. This description should cover the project as a whole, and only one is needed for both parts.

A successful project will correctly identify the event date, correctly compute stock returns, market returns, abnormal returns, and $CAR[-1,+1]$ for Part A, and will provide a brief interpretation of the market’s reaction to that announcement. For Part B it will correctly repeat the $CAR[-1,+1]$ calculation across the available quarters, correctly report the surprise data and its source, produce the required scatter plots, and interpret the relationship between surprise size and market reaction.

Project 2: Black-Scholes Option Valuation

Each student will value an exchange-traded stock option using the Black-Scholes (1973) option pricing model, and will compare that value to the option’s market price. Choose a stock whose ticker begins with the same first letter as your last name — the same rule used in Project 1, so you may reuse the stock and the price history you already downloaded. For example, since my last name is Brigida I may choose Boeing (ticker BA). The stock must have exchange-listed options. ETFs, mutual funds, ADRs, preferred shares, and OTC stocks may not be used.

Black-Scholes as we apply it here assumes the stock pays no dividend. If your stock does pay a dividend, use it anyway, but note this in your submission and state which direction the assumption biases your call value.

Part A: Valuing the Option

From your stock’s option chain, select a call option with roughly three months to expiration and a strike near the current stock price. Record:

$S$, the current stock price
$K$, the strike price
$T$, the time to expiration in years (trading days to expiration divided by 252, or calendar days divided by 365 — state which you used)
$r$, the risk-free rate, using the 3-month Treasury bill rate
the current market price of the option (use the midpoint of the bid and ask)

Value the call in Excel using:

\[ C = S N(d_1) - K e^{-rT} N(d_2) \]

where

\[ d_1 = \frac{\ln(S/K) + (r + \sigma^2 / 2)T}{\sigma \sqrt{T}} \qquad d_2 = d_1 - \sigma \sqrt{T} \]

and $N(\cdot)$ is the standard normal cumulative distribution function, which is NORM.S.DIST(x, TRUE) in Excel. Use your historical volatility estimate from Part B as $\sigma$.

Part B: Historical and Implied Volatility

Volatility is the one Black-Scholes input that cannot be looked up. You will estimate it two ways.

Historical volatility. Download at least one year of daily adjusted closing prices for your stock, convert them to daily returns, take the standard deviation of those returns, and annualize it:

\[ \sigma_{annual} = \sigma_{daily} \times \sqrt{252} \]

Implied volatility. Now reverse the problem. Holding $S$, $K$, $T$, and $r$ fixed, find the value of $\sigma$ that makes your Black-Scholes price equal the option’s actual market price. Excel’s Goal Seek or Solver will do this for you.

Report both numbers and answer: which is larger, and what does the difference tell you about what the market expects relative to what the stock has recently done?

Part C: Valuing the Option by Monte Carlo

Value the same option a second way, by simulation. Under the risk-neutral measure the stock price at expiration is

\[ S_T = S \, e^{\left(r - \sigma^2 / 2\right)T + \sigma \sqrt{T} \, Z} \]

where $Z$ is a draw from a standard normal distribution, which is NORM.S.INV(RAND()) in Excel.

Simulate at least 1,000 terminal stock prices. For each, compute the call payoff $\max(S_T - K, 0)$. Average those payoffs and discount the average back at the risk-free rate:

\[ C = e^{-rT} \times \overline{\max(S_T - K, 0)} \]

Compare this to your closed-form answer from Part A. They should be close. Report both, and explain why they agree.

Background on the valuation: https://www.youtube.com/watch?v=HOSf-lk9JOw and https://www.youtube.com/watch?v=vLCXAKzaW5A

Part D: Where Does Your Stock’s Risk Come From?

Using daily returns for your stock and for SPY, estimate the regression

\[ r_s = \alpha + \beta_s r_m + e_s \]

Because $Cov(r_m, e_s) = 0$, the variance of your stock’s return splits cleanly in two:

\[ Var(r_s) = (\beta_s)^2 Var(r_m) + Var(e_s) \]

Here $(\beta_s)^2 Var(r_m)$ is the market’s contribution to your stock’s variance and $Var(e_s)$ is the firm specific contribution. Note that $Var(X)$ denotes the variance of $X$, and is also often written as $\sigma^2_X$.

Report each piece as a proportion of total variance. Which dominates for your stock? Keep this result — you will use $\beta$ again in Project 3.

Submission Requirements

Each student must submit:

a spreadsheet showing all inputs, the Black-Scholes calculation, the volatility estimates, the Monte Carlo simulation, and the regression
the source and retrieval date for every input, including the option quote
a comparison of your Black-Scholes value to the option’s market price, with a short explanation of any difference
short responses to the questions in Parts B, C, and D
a description of how AI was used in completing the project

You should be ready to explain any part of the spreadsheet.

A successful project will correctly implement Black-Scholes in Excel, correctly annualize historical volatility and back out implied volatility, produce a Monte Carlo value that converges on the closed-form value, correctly decompose the stock’s return variance into market and firm specific components, and interpret each result.

Project 3: Portfolio Construction and CAPM Analysis

Each student will construct and evaluate a portfolio of common stocks. The purpose of the project is to measure how diversification affects risk and return, and to relate the portfolio’s expected return to its systematic risk.

Each student will choose four U.S. common stocks. At least three different sectors must be represented in the portfolio. ETFs, mutual funds, ADRs, preferred shares, and OTC stocks may not be used.

Students will use daily adjusted closing prices over the four complete calendar months immediately preceding the month in which this project is due. Check the due date at the end of this syllabus and work out your window before you start. For example, if the project is due in November, your sample period is July 1 through October 31. Every student in a given semester therefore uses the same window. You will also need the closing price on the last trading day before your window begins, since you cannot compute a return for the first day without the prior day’s price.

Students will also use SPY as the market benchmark and the 3-month Treasury bill rate as the risk-free rate.

Students must first calculate daily returns for each stock and for SPY:

\[ R_{i,t} = \frac{P_{i,t}}{P_{i,t-1}} - 1 \]

where $P_{i,t}$ is the adjusted closing price of asset $i$ on day $t$.

Students will then form an equally weighted portfolio, so that each of the four stocks has a portfolio weight of:

\[ w_i = 0.25 \]

The daily return on the portfolio is:

\[ R_{p,t} = \sum_{i=1}^{4} w_i R_{i,t} \]

Students must calculate the following for the portfolio:

average daily return
annualized average return
daily standard deviation
annualized standard deviation

Annualized return should be calculated as:

\[ \bar{R}_{p,ann} = 252 \times \bar{R}_{p,daily} \]

Annualized standard deviation should be calculated as:

\[ \sigma_{p,ann} = \sqrt{252}\,\sigma_{p,daily} \]

Students must then estimate the portfolio’s beta by running the following regression:

\[ R_{p,t} - R_{f,t} = \alpha_p + \beta_p (R_{m,t} - R_{f,t}) + e_t \]

where $R_{p,t}$ is the portfolio return, $R_{m,t}$ is the return on SPY, and $R_{f,t}$ is the daily risk-free rate implied by the 3-month Treasury bill rate.

Using the estimated beta, students must calculate the portfolio’s CAPM expected return:

\[ E(R_p) = R_f + \beta_p \left(E(R_m) - R_f\right) \]

Students must compare the portfolio’s realized annualized return to its CAPM expected return and briefly discuss whether the portfolio outperformed or underperformed what CAPM would predict.

Students must also calculate the Sharpe ratio of the portfolio:

\[ Sharpe = \frac{\bar{R}_p - R_f}{\sigma_p} \]

Each student must submit:

a spreadsheet showing all calculations
a table with the four stocks and their sectors
the portfolio’s annualized return, annualized standard deviation, beta, CAPM expected return, and Sharpe ratio
one chart comparing the cumulative return of the portfolio to SPY over the sample period
short responses to the following questions:
- Did diversification reduce risk relative to the individual stocks?
- Was the portfolio’s realized return above or below its CAPM expected return?
- Would you consider this a strong portfolio for a passive investor? Why or why not?
a description of how AI was used in completing the project.

A successful project will correctly calculate portfolio returns, annualized risk and return, beta, CAPM expected return, and the Sharpe ratio, and will provide a brief interpretation of the portfolio’s performance.

Project 4: Trading Assignments

Trading assignments are here: https://github.com/Matt-Brigida/fin-332-trading-assignments Students will complete each of these during the semester. If you do not make the trades you will receive a 0 for the assignment even if you attempt to answer some of the questions. Don’t wait until the last minute to complete these assignments. Ideally, you should complete these while also completing the other projects.

Market Trading Hours: The stock and option markets are open from 9:30 am to 4pm each non-holiday weekday. Therefore, you must make your trades within these times.

Here is a video on the first 3 trading assignments: https://www.youtube.com/watch?v=uG7l0WaATDs

And a video on shorting stock: https://www.youtube.com/watch?v=bTP19kqiKEk

Questions on Projects

I am happy to answer any specific questions you have. However, often students will post their spreadsheet for me to “review”. I’ll find errors and the student will fix them and then post it again for review. I’ll find more errors, and so forth. What this means is I am doing your work for you, and moreover it encourages shoddy work (why worry about errors when I will catch them?).

So I will answer any specific questions, but will not provide general reviews until you submit your spreadsheet for a grade.

Brokerage Accounts

I will request you paper trading accounts provided by Interactive Brokers. These trading accounts are the exact same as the actual brokerage accounts—except the money isn’t real. You will have access to (and real data from) stock, bond, commodity, and foreign exchange markets. While the data alone is worth a fair amount of money, Interactive Brokers is offering the accounts to us for free. Keep this in mind while following the directions to set up your account customer service will be nonexistent. If you lose your password, or forget your username, etc, you will not have an account for the semester. In this case you will have to use the demo* account. Please pay attention while setting up your account, and write everything down.

*You can also use a demo account. This account will not save your trades, so you will have to take a screenshot of each trade and submit it with your trading assignment. Without screenshots I cannot verify you have made the trades. If you use the account I request for you, then I am able to see your trades without screenshots.

See here example of the data we can pull using our IB accounts (though you won’t need to do this in any of your trading assignments). You may want to think if interesting projects/analyses you can do with access to such data. Also check out the IB Quant Blog. It is a very good resource.

Exam

There will be one multiple-choice exam covering important Investments topics. The exam will be posted early in the course, and you will have until the due date to submit the exam. If you do not submit the exam by the due date you will receive a 0. Because you have over a month to take the exam, I won’t allow late submissions for any reason.

Course Communication

All important/official announcements will either be posted on D2L or emailed to each student’s SUNY Poly email account. All student questions (other than those that contain personal information) should be asked in class or posted to a discussion board. Do not email me questions such as “When is the exam?”. These types of questions should be asked in class (or on a discussion board).

How to send an email

If you do send an email, be sure to include your course number (FIN 332) in the subject line. Also you should send your email from your SUNY email account. Emails from gmail or other similar addresses may not be read. Lastly, make sure you are clear—for example if you are asking why you got a 0 on an assignment, be sure to include which assignment you are referring to.

Missed Classes

If you are not in class you are responsible for figuring out what you missed. I will not email you a summary of what we covered in the class.

Re-Grading Assignments

I normally do not regrade assignments, however if I do so your grade may increase or decrease when regraded.

Grading

Item	Points
Project 1	20
Project 2	20
Project 3	20
Project 4	20
Final Exam	20
Total Points	100

Final grades will be assigned according to the following scale:

90 - 100 A
80 - 89.9 B
70 - 79.9 C
60 - 69.9 D
< 60 F

+/- grades may be assigned at the instructors discretion.

An Important Note on Grading

There is no special consideration if you need a certain grade in this course to graduate. If you require a certain grade in this class to graduate it is your responsibility to earn that grade. Specifically if you receive a D in this course I will not allow you to do extra assignments after the course is complete in exchange for a higher grade.

An Important Note on Late Work

In this course you have plenty of time to take exams and submit assignments. Therefore, late work is not accepted and will receive a 0 grade. Say, for example, you email me on the due date of an assignment or exam and say “I can’t complete the assignment because the power went off at my house/dorm”. You will receive a 0. The takeaway from this is don’t wait until the last day to submit work.

Again, I’ll note the stock market closes at 4pm. So let’s say you wait until 5 pm on the due date of the trading assignments to start working—you will receive a 0 grade because you can’t complete the trades.

A Note on Submitting Assignments

Before you submit an assignment I suggest you take a step back, open the document, and ask yourself can anyone easily understand the answers and how they were generated. This is an important skill a financial analyst must have—the ability to organize a document to efficiently convey information. That is also why I do not provide template for assignment submissions. Constructing a readable document is part of the assignment.

An Important Note on Meetings in 35W Courses

If you signed up for a 35W course this is asynchronous. This is the definition of a 35W course from the SUNY Poly website:

Online course are fully online and are asynchronous and have no meeting time (remotely or in-person). The activities must be completed by the due dates specified by your instructor. Online courses may also have proctored exams. Students will be required to locate their own proctors for the exams.

Depending on the instructor/department, the course may also use webinars to provide office hours, study sessions, presentations, group projects and recorded sessions. Contact the instructor or department for more information. The section number of online synchronous courses end with a “W”

Notice there are no meeting times. If you want to meet by video I will try and set office hours to meet with students, but there is absolutely no guarantee we will be able to meet. If you request a new video on a topic I can usually create one in a timely manner.

If you need to meet with me to take this course however, you should drop the 35W offering and sign up for a in-person or 35S or H offering of FIN 332. One is guaranteed to be offered every other year.

Due Dates

All dates are Fall 2026.

Project 1 Due: Sunday, October 4
Project 2 Due: Sunday, October 25
Project 3 Due: Sunday, November 22
Project 4 Due: Friday, December 11 (the last day of classes — the market closes at 4pm, so do not leave the trades until that afternoon)
Final Exam Due: Friday, December 11

BRTI Tick Data

Below are millisecond data for the Bitcoin Real-Time Index on Jan 3, 2018. The data are pulled via the IB API. With data of this type, you can dicover interesting features of market data—for example, notice the “last trade” is often outside of the bid/offer. This is particularly important to understand when trading illiquid contracts, such as some options. You can left-click your mouse, and drag, to zoom in on subintervals.

Course Syllabus Disclosure Statement Fall 2026

Accommodations for Students with Disabilities:

In compliance with the Americans with Disabilities Act of 1990 and Section 504 of the Rehabilitation Act, SUNY Polytechnic Institute is committed to ensuring comprehensive educational access and accommodations for all registered students seeking access to meet course requirements and fully participate in programs and activities. Students with documented disabilities or medical conditions are encouraged to request these services by registering with the Office of Disability Services. Please request accommodations early in the semester, or as soon as you become registered with Disability Services, so that we have adequate time to arrange your approved academic accommodation/s. Once Disability Services creates your accommodation plan, it is your responsibility to provide me a copy of the accommodation plan.

If you experience any access concerns that may require the need for adaptive or alternate format/presentation of materials, reach out to me or Disability Services right away.

For information related to these services or to schedule an appointment, please contact the Office of Disability Services using the information provided below. The Office of Disability Services can accommodate virtual meeting requests. The website has helpful information, and the link can be found here: https://sunypoly.edu/student-life/diversity-equity-inclusion/disabilities-services/contact-us.html

General Notes (most relate only to in class sections)

The instructor is not involved in any way with your adding and dropping the course. It is the student’s responsibility to abide by all proper procedures and dates.
Attending class, and reading the text is required.
All exams will be closed book.
If you are late for an exam, no extra time will be allotted to you.
There will be no make up exams or extra points assignments.
You will be responsible for any material covered in class that is not in your text.
You should bring your text to class.
You are expected to be on time for class. This is especially important for exam dates.
Disruptive behavior in the classroom will not be tolerated.