1. Investments, Tue. May 12, ’09 Big picture for Tue, Wed, Thu: Finish up! Tue: Remarks on Ch. 5. Ch. 6 w/ disagreement over prob’s. Some Ch. 7 w/ options. Wed: More Ch. 7 – first all but Sec 7.9. Hand-back of Hand-In #2. Thu: Words on 7.9. Ch. 8 on advice. The 2008 exam solved. And closing remarks.

2. Chapter 5 recap: -Cases 9, 10: If you already have large exposure to something you should under-represent that in your financial portfolio to achieve diversification. Don’t put you pension savings in your own company. -Case 11: * Investors with long horizons want to over-represent stocks if human capital is safe. * The inability (even for one party) to make strong, binding commitments can hurt everybody. Bankruptcy protection isn’t.

3. Section 5.5: Other outside effects -Taxes. Payments aren’t just “1 - tax rate”. Depend on investor type (private, fund; tax bracket), on dividend/interest vs. capital gain, on the investment vehicle, and “very digitally” on timing. -Home bias. Swedes over-represent Swedish stocks, etc. (Btw: Sweden is good for investigations.) Could be myopia or pure nationalism. But the is “natural diversification” in having income and expenses in same currency. I’m learning the hard way.Sweden is good for investigations

4. Chapter 6: Disagreement over probabilities A main driver investment or: speculation, betting. Active managers remark. Intuition: If I think an asset is over-valued and you think it’s under-valued, then I want to sell and you want to buy. Large effect on our portfolios. Not so large on prices. Or: Prices are averages so the law of large numbers apply. (BTW: Beware of spurious LLN applications.)

5. When Sharpe writes prices reflect information he means something like: -A market-beta relation, e.g. CAPM, holds for individual securities and the market portfolio. I.e. they lie on SML. Individuals’ portfolios scattered (horizontally and vertically). -Not a lot of portfolios above the CML on which the market portfolio lies by def. Individuals’ portfolios (well) below CML.

6. Cases: #14: Setting the stage w/ Hue and Mario #15: Many independent predictions; vox populi. #16: Many are dead-wrong, a few are right. Detectable gains. #17: Wrong & noise (”bias”) vs. right: Harder to see gains. #18: Different prediction accuracies: Quite hard to spot.