In the chapter assigned for this module, the book addressed several catastrophic geologic events: Krakatoa eruptions of 1883 and 1979, Eruption of Mt. Vesuvius in A.D. 79, Hurricane Katrina in 2005, and Indian Ocean Tsunami in 2004. Research another catastrophic geologic event (a volcanic eruption, a large earthquake, a big landslide, etc), and describe it using 10-15 sentences. Be sure you differentiate what makes the event you selected unique and special. Spelling and grammar also count!

Milwaukee Telecom (MT) just paid a dividend (D0) of $2.44 per share; future dividends are expected to grow 3% per year indefinitely. The firm’s stock is not publicly traded but data from comparable firms shows an average beta of 1.28; these firms had average debt-equity ratios of 51 and an average tax rate of 28%. MT has a debt-equity ratio of 82 and a tax rate of 32%. The current yield on 10-year U.S. Treasury bonds is 2.8%, and the expected return on the S&P 500 is 11.6%. What would be the firm’s current cost of common stock?

At the beginning of the semester, you identified the healthcare industry, energy industry, financial industry, or a technology industry and a publicly-traded company to think about as part of your final project or other course work. Some of that analysis begins now.

1. (5pts) For your industry/company what are the major goods and services markets (final products) & factor markets (production inputs and/or intermediate goods and services) that characterize their business?

2. (5pts) Briefly (200 words or less) offer some thoughts about what you feel are the major risks faced in both the final goods market, and the factor markets in which your industry/company participate.

3. (5pts) Look up the definitions of Perfect Competition, Monopoly, Oligopoly and Monopolistic Competition. Based upon what you learn, which of these types of competition and market structure best describe your industry and/or company?

We had two financial crises since 2000, 2000 dot.com bubble, 2008-2009 financial crisis. From FRED website, find the following data from 1995 to 2013, and make a graph. Explain the general trends of each series, and compare them between the two crises.

1. Money supply (M2)
2. Nominal GDP
3. Velocity of Money
4. Consumer Price Index

An economist with a major bank wants to learn, quantitatively, how much spending on luxury goods and services can be explained based on consumers’ perception about the current state of the economy and what do they expect in the near future (6 months ahead).  Consumers, of all income and wealth classes, were surveyed.  Every year, 1500 consumers were interviewed.  The bank having all of the data from the 1500 consumers interviewed every year, computed the average level of consumer confidence (an index ranging from 0 to 100, 100 being absolutely optimistic) and computed the average dollar amount spent on luxuries annually.  Below is the data shown for the last 24 years.

Date                 X                     Y (in thousands of dollars)

1994                79.1                 55.6

1995                79                    54.8

1996                80.2                 55.4

1997                80.5                 55.9

1998                81.2                 56.4

1999                80.8                 57.3

2000                81.2                 57

2001                80.7                 57.5

2002                80.3                 56.9

2003                79.4                 55.8

2004                78.6                 56.1

2005                78.3                 55.7

2006                78.3                 55.7

2007                77.8                 55

2008                77.7                 54.4

2009                77.6                 54

2010                77.6                 56

2011                78.5                 56.7

2012                78.3                 56.3

2013                78.5                 57.2

2014                78.9                 57.8

2015                79.8                 58.7

2016                80.4                 59.3

2017                80.7                 59.9

Question:

1. Construct the linear regression model for the dollar amount spent on luxury goods and services.

The data below is the total spending (in millions of dollars) on drugs and other non-durable products for your assigned state (or DC). You need to convert this data to spending per capita in constant 2019 dollars.

Go to the FRED database at https://fred.stlouisfed.org/

Search for the PCEPI. Change the frequency to annual. Using that price index (this is a national index; there isn't a PCE index for each state), convert the following to 2019Q3 dollars.

Again using the FRED database, find the population for your state. The symbol is usually the two letter abbreviation for the state and POP. New York, for example, would be NYPOP.

Using this information, covert the spending below into spending per capita, in 2019Q3 dollars. Keep in mind that the values below are in millions of dollars and you want your answers in dollars.

Enter your results for every even-numbered year in the answer

Alaska

Use the procedure outlined in Section 11.6.2 on p.262 of textbook and the annual percentage default rate for all rated companies in Table 11.6 on p.259,

a. Estimate the probability of default (PD) and default correlation (ρ) for the period 1970-1993, and for the period 1994-2016 separately.

b. Plot the probability distribution of default rate (similar to Figure 11.6 on p.263) for the time period 1970-1993 and 1994-2016 together on the same graph.

Textbook Risk Management and Financial Institutions, 5th Edition

a)            CEMENCO Stock Return

Find the Average Return and Risk (as measured by Standard Deviation) of CEMENCO since 2000.

b) You have a portfolio consisting of 20 percent CEMENCO stock (β = 0.81), 40 percent of Monrovia Breweries (Club Beer) stock ((β = 1.67). How much market risk does the portfolio have? How does this compare with the general market?

c) Data from the last eight decades for S & P 500 index yield the following statistics: average excess return = 7.9%; Standard Deviation = 23.2%.

(i)To the extent that these averages approximated investor expectations for the period, what must have been the average coefficient of risk aversion? Formula: E (r_m) – r_f = Ā ẟ²_m

(II)If the coefficient of risk aversion were actually 3.5, what risk premium would have been consistent with the market’s historical standard deviation?

d) A portfolio’s return is 12%, its standard deviation is 20% and the risk-free rate is 4%. Which of the following would make the greatest increase in the portfolio’s Sharpe ratio?

An increase of 1% in expected return?

A decrease of 1% in the risk-free rate?

A decrease of 1% in its standard deviation?