Late-mover advantages (or first-mover disadvantages) are not likely to arise when: Multiple Choice

a. Opportunities exist for a blue-ocean strategy to invent a new industry or distinctive market segment that creates altogether new demand.
b. The marketplace is skeptical about the benefits of a new technology or product being pioneered by a first-mover.
c. Technological change is rapid and fast-following rivals find it easy to leapfrog the pioneer with next-generation products of their own.
d. The costs of pioneering are much higher than being a follower and only negligible learning/experience benefits accrue to the pioneer.
e. The pioneer's products are somewhat primitive and are easily bested by late movers.

Your mother's well-diversified portfolio has an expected return of 12.0% and a beta of 1.20. she is in the process of buying 100 shares of safety corp. at $10 a share and adding it to her portfolio. safety has an expected return of 15.0% and a beta of 2.00. the total value of your current portfolio is $9,000. what will the expected return and beta on the portfolio be after the purchase of the safety stock?

Burke enterprises is considering a machine costing $30 billion that will result in initial after-tax cash savings of $3.7 billion at the end of the first year, and these savings will grow at a rate of 2 percent per year for 11 years. after 11 years, the company can sell the parts for $5 billion. burke has a target debt/equity ratio of 1.2, a beta of 1.79. you estimate that the return on the market is 7.5% and t-bills are currently yielding 2.5%. burke has two issuances of bonds outstanding. the first has 200,000 bonds trading at 98% of par, with coupons of 5%, face of $1000, and maturity of 5 years. the second has 500,000 bonds trading at par, with coupons of 7.5%, face of $1000, and maturity of 12 years. kate, the ceo, usually applies an adjustment factor to the discount rate of +2 for such highly innovative projects. should the company take on the project?

True or false: a fitted model with more predictors will necessarily have a lower training set error than a model with fewer predictors.