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4434Personal Taxes Videos
https://www.merlot.org/merlot/viewMaterial.htm?id=1045263
From the Kahn Academy, Personal Taxes consists of the following 10 short videos:Basics of U.S. Income Tax Rates (1:02)Tax Deduction Introduction (3:30)AMT Overview (3:45)Alternative Minimum Tax (3:55)Estate Tax Introduction (10:47)Tax Brackets and Progressive Taxation (:33)Calculating Federal Taxes and Take Home Pay (6:36)Calculating State Taxes and Take Home Page (6:30)Marriage Penalty (10:05)Married Taxes Clarification (3:40)Wed, 8 Jul 2015 09:59:10 -0700Lecture 12 - Accountability and Greed in Investment Banking
https://www.merlot.org/merlot/viewMaterial.htm?id=986014
This video was recorded at PLSC 270 - Capitalism: Success, Crisis and Reform. Professor Rae explores the creation of incentives and disincentives for individual action. The discussion begins with the Coase Theorem, which outlines three conditions for efficient transactions: 1) clear entitlements to property, 2) transparency, and 3) low transaction costs. Professor Rae then tells the story of a whaling law case from 1881 to highlight the power of incentives and property rights. The conversation then moves to Hernando de Soto's portrayal of the development of property rights in the American West, and then shifts to a discussion of New Haven deeds, property values, and valuation of real estate. The lecture concludes with a discussion of Mory's.Tue, 10 Feb 2015 15:43:50 -0800Lecture 26 - The Leverage Cycle and Crashes
https://www.merlot.org/merlot/viewMaterial.htm?id=985705
This video was recorded at YALE - ECON 251 - Financial Theory. In order to understand the precise predictions of the Leverage Cycle theory, in this last class we explicitly solve two mathematical examples of leverage cycles. We show how supply and demand determine leverage as well as the interest rate, and how impatience and volatility play crucial roles in setting the interest rate and the leverage. Mathematically, the model helps us identify the three key elements of a crisis. First, scary bad news increases uncertainty. Second, leverage collapses. Lastly, the most optimistic people get crushed, so the new marginal buyers are far less sanguine about the economy. The result is that the drop in asset prices is amplified far beyond what any market participant would expect from the news alone. If we want to mitigate the fallout from a crisis, the place to begin is in controlling those three elements. If we want to prevent leverage cycle crashes, we must monitor leverage and regulate it, the same way we monitor and adjust interest rates.Tue, 10 Feb 2015 15:40:13 -0800Lecture 25 - The Leverage Cycle and the Subprime Mortgage Crisis
https://www.merlot.org/merlot/viewMaterial.htm?id=985703
This video was recorded at YALE - ECON 251 - Financial Theory. Standard financial theory left us woefully unprepared for the financial crisis of 2007-09. Something is missing in the theory. In the majority of loans the borrower must agree on an interest rate and also on how much collateral he will put up to guarantee repayment. The standard theory presented in all the textbooks ignores collateral. The next two lectures introduce a theory of the Leverage Cycle, in which default and collateral are endogenously determined. The main implication of the theory is that when collateral requirements get looser and leverage increases, asset prices rise, but then when collateral requirements get tougher and leverage decreases, asset prices fall. This stands in stark contrast to the fundamental value theory of asset pricing we taught so far. We'll look at a number of facts about the subprime mortgage crisis, and see whether the new theory offers convincing explanations.Tue, 10 Feb 2015 15:40:12 -0800Lecture 23 - The Mutual Fund Theorem and Covariance Pricing Theorems
https://www.merlot.org/merlot/viewMaterial.htm?id=985699
This video was recorded at YALE - ECON 251 - Financial Theory. This lecture continues the analysis of the Capital Asset Pricing Model, building up to two key results. One, the Mutual Fund Theorem proved by Tobin, describes the optimal portfolios for agents in the economy. It turns out that every investor should try to maximize the Sharpe ratio of his portfolio, and this is achieved by a combination of money in the bank and money invested in the "market" basket of all existing assets. The market basket can be thought of as one giant index fund or mutual fund. This theorem precisely defines optimal diversification. It led to the extraordinary growth of mutual funds like Vanguard. The second key result of CAPM is called the covariance pricing theorem because it shows that the price of an asset should be its discounted expected payoff less a multiple of its covariance with the market. The riskiness of an asset is therefore measured by its covariance with the market, rather than by its variance. We conclude with the shocking answer to a puzzle posed during the first class, about the relative valuations of a large industrial firm and a risky pharmaceutical start-up.Tue, 10 Feb 2015 15:40:09 -0800Lecture 22 - Risk Aversion and the Capital Asset Pricing Theorem
https://www.merlot.org/merlot/viewMaterial.htm?id=985697
This video was recorded at YALE - ECON 251 - Financial Theory. Until now we have ignored risk aversion. The Bernoulli brothers were the first to suggest a tractable way of representing risk aversion. They pointed out that an explanation of the St. Petersburg paradox might be that people care about expected utility instead of expected income, where utility is some concave function, such as the logarithm. One of the most famous and important models in financial economics is the Capital Asset Pricing Model, which can be derived from the hypothesis that every agent has a (different) quadratic utility. Much of the modern mutual fund industry is based on the implications of this model. The model describes what happens to prices and asset holdings in general equilibrium when the underlying risks can't be hedged in the aggregate. It turns out that the tools we developed in the beginning of this course provide an answer to this question.Tue, 10 Feb 2015 15:40:07 -0800Lecture 21 - Dynamic Hedging and Average Life
https://www.merlot.org/merlot/viewMaterial.htm?id=985695
This video was recorded at YALE - ECON 251 - Financial Theory. This lecture reviews the intuition from the previous class, where the idea of dynamic hedging was introduced. We learn why the crucial idea of dynamic hedging is marking to market: even when there are millions of possible scenarios that could come to pass over time, by hedging a little bit each step of the way, the number of possibilities becomes much more manageable. We conclude the discussion of hedging by introducing a measure for the average life of a bond, and show how traders use this to figure out the appropriate hedge against interest rate movements.Tue, 10 Feb 2015 15:40:06 -0800Lecture 20 - Dynamic Hedging
https://www.merlot.org/merlot/viewMaterial.htm?id=985693
This video was recorded at YALE - ECON 251 - Financial Theory. Suppose you have a perfect model of contingent mortgage prepayments, like the one built in the previous lecture. You are willing to bet on your prepayment forecasts, but not on which way interest rates will move. Hedging lets you mitigate the extra risk, so that you only have to rely on being right about what you know. The trouble with hedging is that there are so many things that can happen over the 30-year life of a mortgage. Even if interest rates can do only two things each year, in 30 years there are over a billion interest rate scenarios. It would seem impossible to hedge against so many contingencies. The principle of dynamic hedging shows that it is enough to hedge yourself against the two things that can happen next year (which is far less onerous), provided that each following year you adjust the hedge to protect against what might occur one year after that. To illustrate the issue we reconsider the World Series problem from a previous lecture. Suppose you know the Yankees have a 60% chance of beating the Dodgers in each game and that you can bet any amount at 60:40 odds on individual games with other bookies. A naive fan is willing to bet on the Dodgers winning the whole Series at even odds. You have a 71% chance of winning a bet against the fan, but bad luck can cause you to lose anyway. What bets on individual games should you make with the bookies to lock in your expected profit from betting against the fan on the whole Series?Tue, 10 Feb 2015 15:40:05 -0800Lecture 19 - History of the Mortgage Market: A Personal Narrative
https://www.merlot.org/merlot/viewMaterial.htm?id=985691
This video was recorded at YALE - ECON 251 - Financial Theory. Professor Geanakoplos explains how, as a mathematical economist, he became interested in the practical world of mortgage securities, and how he became the Head of Fixed Income Securities at Kidder Peabody, and then one of six founding partners of Ellington Capital Management. During that time Kidder Peabody became the biggest issuer of collateralized mortgage obligations, and Ellington became the biggest mortgage hedge fund. He describes securitization and tranching of mortgage pools, the role of investment banks and hedge funds, and the evolution of the prime and subprime mortgage markets. He also discusses agent based models of prepayments in the mortgage market.Tue, 10 Feb 2015 15:40:03 -0800Lecture 18 - Modeling Mortgage Prepayments and Valuing Mortgages
https://www.merlot.org/merlot/viewMaterial.htm?id=985689
This video was recorded at YALE - ECON 251 - Financial Theory. A mortgage involves making a promise, backing it with collateral, and defining a way to dissolve the promise at prearranged terms in case you want to end it by prepaying. The option to prepay, the refinancing option, makes the mortgage much more complicated than a coupon bond, and therefore something that a hedge fund could make money trading. In this lecture we discuss how to build and calibrate a model to forecast prepayments in order to value mortgages. Old fashioned economists still make non-contingent forecasts, like the recent predictions that unemployment would peak at 8%. A model makes contingent forecasts. The old prepayment models fit a curve to historical data estimating how sensitive aggregate prepayments have been to changes in the interest rate. The modern agent based approach to modeling rationalizes behavior at the individual level and allows heterogeneity among individual types. From either kind of model we see that mortgages are very risky securities, even in the absence of default. This raises the question of how investors and banks should hedge them.Tue, 10 Feb 2015 15:40:02 -0800