3Introduction What is a “platform”? By analogy to computing, where a platform is a hardware architecture or set of standards that that allow software applications to run.Platform markets bring together different sides of the market to interact.Many examples: visa payment network, video game systems, online dating sites, iPhone app store, etc.Today, focus on auction platforms: markets such as eBay, Amazon, financial exchanges, withA structured environment for buying and selling goodsOften a very specific set of market rules & institutions.
4Introduction Idea 1: Bigger than the auction itself Auction design: specify the bidding rules, who gets the object(s), and payments to be made.Search/Information: platform markets help buyers and sellers find one another, and allow them to exchange information (e.g. presentation of informaiton on eBay/Amazon).Standards: quality scores, reputations scores, grading of used goods, targeting in online ads.Contract design and enforcement: rules for pricing and exchange and various mechanisms for verifying and enforcing that these rules are followed.
5Introduction Idea 2: Platform creates an ongoing market We’ve been analyzing auctions “one at a time”Platform markets generally involve ongoing exchange, many sales every day, market evolves over time.Platform is setting the rules of the environment, e.g. on eBay the type of ways that sellers can offer stuff to buyers or set prices.Doesn’t always have to be auctions, e.g. Craigslist and eBay have quite different pricing…
6Market design Platform operators have to consider How to attract buyers and sellersHow to match them efficientlyHow to ensure market runs in an orderly fashionHow are the gains from trade sharedHow does the platform make moneyTools for answering these questionsTheoretical models (as in search auction case)Experiments (very common in online markets)Data analysis (platforms get to collect a lot of data)
7Monopoly platforms“Indirect” network effects: more buyers attracts more sellers and vice-versa.Platform may have to decide which side to charge - Does it matter? Why might it matter?Common to charge one side of the market but not the other (e.g. yellow pages, sponsored search, dance clubs, visa?)Platform may have to trade off market efficiency (creating a bigger pie) and profit (taking a bigger slice).Recall our auction design choices in sponsored search.
8Competing platformsNature of competition and effects of competition depend on single vs multi-homing.If one side “single-homes,” platform can charge the other side for “unique access”Can create a lot of competition to attract single-homers, e.g. payments, exclusive contracts.Scale economies may be very importantScale can allow platform to improve its technology (fixed costs amortized over more transactions).Scale effects can also be subtle - sellers like more buyers, but not necessarily more competing sellers!
10eBay and online markets eBay: largest site for e-commerce81,000,000 monthly visitors140,000,000 listings on a given day$8,500,000,000 platform revenueCompetes against Amazon, Craigslist, other online sites, plus many off-line companies.Today: discuss its marketplace design.
11Market + Search Technology Many heterogeneous objects being soldDifferent kinds of sellers and buyersRange from full-time “pros” to casual participants.Ongoing market, sequential sales/closesMultiple pricing mechanismsAuctions, Posted prices (Buy it Now)Buyer searchCatalogs/Browsing, Sophisticated searchFeatured listings, advertising
12Structure of Buyer Search What distinguishes listingsWhat is the good, new/usedWho is the seller, reputation, locationWhat is the sale type: auction, posted price.Some important issuesPrioritize auctions or posted pricesCatalogue vs non-catalog itemsDistinguish sellers, or initially just goodsConflation? Or emphasize diversity?
13Conflation in market design Emphasize diversityTraditional eBay search brought up page of listings, organized by auction ending time.Similar items might look very different – sellers have an incentive to emphasize diversity!Conflation (a la Amazon, eBay more recently)Search for product, product is displayedSellers, and seller distinctions revealed later.What are the trade-offs? Do they depend on the nature of the item and perhaps buyer?
16Listings and Information eBay in principle controls what sellers can communicate to buyersDifferent types of information in listingStandardized information“Free-form” information (photos, videos, text)Some important issueseBay imposes relatively little structure on sellersOnly recently has started to collect “extra” information from sellers – why would you do this?
18Disclosure and Adverse Selection Especially for big-ticket items, buyers may be worried about the quality of the item.There is potential for adverse selection problems.Seller disclosure might mitigate these issues.Greg Lewis (2009) study of eBay motors.Provides empirical evidence by correlating sale prices with amount of information disclosed by sellers.
19The Lemons Problem Three kinds of car: peach, apple, lemon Buyer values: $2500, $1800, $1100Seller values: $2000, $1500, $900Seller knows quality, buyer doesn’tEqual numbers of car types“Akerlof” lemons problemAt market price > $2000, all sellers will sell, but buyer expected value is only $1800… No trade.At market price btwn $1500 and $2000, apples and lemons will be available, but then buyer expected value only $1450At market price btwn $900 and $1500, only lemons will be available, so buyer value is $1100.Market eqm: Lemons trade at btwn $900 and $1100.
20Disclosure If quality can be costlessly disclosed Peach sellers will disclose qualitySo apple sellers will also discloseSo buyers will be able to identify lemons!Then all types of cars will trade…This “unraveling” result is quite strikingDepends on buyers being sophisticatedOr alternatively, on seller competition…What happens if disclosure is costly?
21Costly disclosure Back to our example Suppose disclosure costs $400. Buyer values: $2500, $1800, $1100Seller values: $2000, $1500, $900Suppose disclosure costs $400.Peaches will disclose, sell for $2000-$2100.Apples will not disclose – too expensive!Lemons will trade w/ no disclosure $900-$1100.Costly disclosure can lead to intermediate trade. Doesn’t have to be the best items that trade, but the items where there are large gains from trade!
23Contract/Transaction Design eBay can place structure on the transaction itself, or facilitate transaction in various ways.What is the contract?Seller agrees to provide object as represented.Some “free form” terms and conditionsBuyer pays first, usually no escrow!Trust-based (compare with China eBay)Main issue: safety for buyers…
24Reputation mechanisms Seller reputation helps enforce “contract”Buyers give feedback post transactionSellers also give feedback post transactionParticipants acquire scores – pos. & neg reviewsWhat are the issuesWhat is the incentive to give feedbackRetaliation problemsBolton et al. innovative designsNew programs for “top sellers” – good idea?
25Bolton et al. on Reputation How can you avoid the “retaliation” problem?Don’t let seller give feedbackDon’t let buyer/seller see each other’s feedbackMix of disclosed/non-disclosed feedbackWhat are the trade-offs?Other reputation issuesWhy are the sellers trusted? Why not buyers?Are there other ways to organize the market?Markets turn out to be quite local – trust issues?
26Auction mechanism Ascending auction with proxy bidding Enter “maximum bid” – proxy bids up to maximumObject awarded to standing high bidder at closeHard close: auction ends at a fixed timeSecret reserve – minimum bid usual reserve, but possible an extra “secret” reserve.What are the issues?Sniping (late bids: why does this happen?)Squatting (early bids: why does this happen?)
27Sniping (Roth et al.) Roth and Ockenfels (2002) Sniping observed at “hard close” auctionsSniping doesn’t occur when there is a “soft close”Why would you wait to the last minuteEarly bids might attract attention to a listingEarly bids might signal object was valuableEven if these benefits are small, the costs of delaying to the last minute are also small or zero.Squatting is what you expect if the effects go the other way – early bids “scare off” other bidders.
28Auctions vs Posted Prices eBay has moved toward to posted pricesNow more than half of the platform is pricesWhat are the trade-offs?Auctions: good for price discovery, maybe fun for buyers, perhaps good for unusual or unique items, forces buyers to compete.Prices: good for immediacy, speeds up the market potentially, forces sellers to compete.Why would the market have shifted?
29Market design, broadly What are all these smaller decisions aimed at Attracting participantsEfficient matching of buyers and sellersOrderly and safe transactionsHow could we assess the efficiency of the market? What measures to look at?Number of participants and level of engagement, how easily/quickly buyers and sellers can trade, level of prices, amount of fraud, market structure.
31Today’s Lecture Background on financial exchanges The role of financial exchangesDesirable attributes of an exchangeHistory of these marketsSpecialist markets, OTC markets, exchangesThe move to electronic exchangesMarket design issuesInformation aggregration, large ordersCompeting platforms, transparency, dark pools.
32Public equity markets Focus on markets for public equity Companies issue publicly traded stock.Historically traded on a few large exchangesRecently competition between exchanges and a great deal of innovation in exchange design.Questions to considerWhat are the objectives for a successful market?What designs help achieve these objectives?What is the role of competition between markets?
33Market objectives Objectives for the public equities market Price discovery (prices reflect current information)Fair competition (open access, nondiscrimination)Investor protection and confidenceUS regulates financial markets to achieve these objectives, looking at things such asHow fast are orders executed? How large are spreads? How large is systemic risk (e.g. risk of a complete market shut-down)? Are certain investors being advantaged or disadvantaged? Is there cheating or fraud?
34Desirable market properties LiquidityIn liquid markets, traders can buy or sell large quantities of shares without a large price impact.TransparencyParticipants have information available to them before making a trade (receive a quote, see open offers) and after a trade (see prices, quantities).Price discoveryPrices incorporate and track available information in the market - and do so in a reasonable and efficient way.
35Organization of Markets Historically, equities in US were mainly traded on the floor of the NYSE.NYSE as a “specialist” marketEach stock managed by a specialistSpecialist quotes “bid” and “ask” pricesInvestors, who are physically on the trading floor, trade with the specialist at these pricesSpecialist holds some stock to keep market functioning, but not very large positions.
36Organization of Markets Nasdaq competes with NYSE and was historically an “over the counter” market.Organization of OTC marketsSmall number of “brokers” quote bids/ask to prospective traders, who can trade with any of the brokers.In some OTC markets, executed trades are posted publicly creating a degree of transparency.OTC organization is typical for less “liquid” securities: corporate and municipal bonds, derivatives, etc.
37Organization of markets Equity trading has increasingly moved to electronic order books, including at NYSE.Organization of electronic exchangesTraders submit orders to buy or sellOrders are posted in an electronic “book”If a buy order comes in above a current sell order, the orders are “crossed” and a trade is executed.Different exchanges allow different types of orders (more on this in a minute).
38Organization of markets Many large trades take place “upstairs” - not on the NYSE floor or in a public exchangeOrganization of large tradesOften a bilateral negotiation or by private placement.Example: investor approaches Goldman Sachs to sell a large position. GS either finds a buyer, or buyers, or buys the position itself and then dribbles it out over time.Recently, many electronic exchanges are trying to automate large trades by allowing for more sophisticated types of orders (more later).
39Recent events: 2005-2009 Location of trades In Jan 2005: NYSE accounted for 80% of trading volume in NYSE-listed stocks; by Oct 2009, down to 25%Execution speeds for tradesFalls from 10.1 seconds in 2005, to 0.7 seconds in 2009.Trading volumeFrom 2.1 bn shares/day in 2005 to 5.9 bn in 2009.Average trade sizeFalls from 724 shares in 2005 to 268 shares in 2009
40Current market Trading mostly done on electronic platforms Questions Five large exchanges (transparent)Multiple smaller electronic exchangesInternal or “dark” trading pools (not transparent)QuestionsDoes this fragmentation matter? (Offer to buy and sell must be posted publicly to all exchanges.)Why the proliferation of markets? Should different types of trades be executed in different markets?
41Applying economic theory Price formation and price evolution“Efficient” markets with asymmetric informationModel bid/ask spreads in specialist marketsSearch costs and market frictionsBid/Ask spreads in OTC marketsLarge orders and price impactsDesign of exchanges, and exchange competition.
42Modeling price formation Consider a specialist marketSpecialists offer bid price b (offer to buy) and ask price a.Traders arrive and can buy or sell at these prices.After trading, world ends, stock pays d ~ U[0,1].First consider traders coming to sell…Two types of traders, equally likely to arriveSmart trader: knows d, sells only if b>dDumb trader: doesn’t know d, sells at any b.Specialists don’t know d, but they understand the environment and quote a price that ensure they will just break even on average.
43Bid prices in market Specialist quotes a price b With probability 1/2, dumb trader shows upTrader sells the stock for bSpecialist makes a profit d-bWith probability 1/2, smart trader shows upTrader sells the stock if b>dSpecialist makes a profit (really a loss) d-b
44Specialist marketIf dumb trader arrives, sells for b, specialist gets E[d]=1/2If smart trader arrives, only sells if d<b, I.e. with pr=bbIf d>b, smart trader will not sellIf d>b, smart trader will sell1E[Profit] = (1/2)b - b= - (1/2)bE[Profit] = 0
45E[Profit] = (1/2) * [ 1/2 - b ] + (1/2) * b * (- 1/2* b) = 0 Bid Prices in MarketWhat is the expected profit for specialistIf dumb trader: expected profit is 1/2 - bIf smart trader: expected profit is b * [ -(1/2)b ]Specialist break-even conditionE[Profit] = (1/2) * [ 1/2 - b ] + (1/2) * b * (- 1/2* b) = 0Solving for the competitive bid price1/2 - b = 1/2* b21-2b-b2 =0b = 0.414
46Ask prices in the market Now suppose traders may also show up to buy, and specialist quotes an “ask” price.Two types of buyers, equally likely to arriveSmart traders: know d and buy if d>aDumb traders: don’t know d and buy at any aSpecialists quote an ask price that ensures they will just break even in expectationWill the ask be above or below the bid?
47Ask prices in the market Specialist quotes an ask aWith probability 1/2, dumb trader arrivesBuys at aSpecialist profit is a-dWith probability 1/2, smart trader arrivesBuys if a<d
48Solving for ask prices Specialist expected profit If dumb trader: profit is a-1/2If smart trader: profit is -(1-a)*(1-a)/2.Solving for the break-even ask price2a - 1 = (1-a)2a = 0.586Compare to the bid b = 0.414The “spread” is a-b, here 0.172
49Price Formation & Dynamics Efficient market theoryCurrent prices equal E[Value | Current Info].True in this theory, except an offer to buy or sell convey NEW information.So each “buy” trade raises the price and each “sell” trade lowers the price.Specialists charge a “spread” a>b to protect themselves from private information of the traders.More liquid market means lower spreads, and probably less movement of prices with each trade.
50Competition and Spreads What makes spreads larger or smaller?More informed traders => larger spreadsLess specialist competition => larger spreadsCompetition and spreads?If specialist has no competition, can set a=1,b=0.Trades with probability 1/2, but makes an expected profit of 1/2 on each trade.Extreme example, but can more generally specialist can increase spread and trade only with the dumb money.Competition prevents this by forcing spreads to be narrower - but requires traders to be able to “shop”.
51Theory of Exchanges View exchange as a “double auction” Buyers put in demand curvesSellers put in supply curvesIn “one-shot” case, would collect all offersCompute aggregate demand and supply.Find market clearing price, execute trades.In practice, trading takes places in real timeThis means that orders don’t all come in at once.And trades get executed as the opportunity arisesWhy trade in real time, rather than an auction every hour or day or week?
52Dynamics of the order book Traders put in buy and sell ordersLimit order: offer to buy or sell at some price pMarket order: buy or sell at best offered price.Example of the “order book” w/ limit ordersOrders to buy at 80, 90, 100Order to sell at 110, 120, 130.
53Example130120There is currently no trade to execute b/c best sell offer is 110 and best buy offer is 100.1101009080
54Dynamics of the order book Current order bookOrders to buy at 80, 90, 100Order to sell at 110, 120, 130.Buy order comes in at 120.“Crossed” with the best sell order (110).Updated order bookOrders to sell at 120, 130
59Price impact of large trades What happens if there is a large tradeLarge buy order can “eat up” the supply curveIf there is little “liquidity”, maybe big price impact.Example of order bookBuy orders 80,85,90,95,100Sell orders 105,110,115,120,125,130,135Average of best buy/sell offers: 102.5Buy order for four units at best sell offers =>Buy orders 80, 85, 90, 95, 100Sell orders 125, 130, 135Average of best buy/sell offers: 112.5
60Efficient markets?Theory of efficient markets assumes roughly that p = E[Value| Current Info].If a seller has to liquidate a large holding of stock for reasons that aren’t informative about the value of the company, shouldn’t matter for the price.But in practice, doesn’t always work this way.Example: de-listing of stock from S&PIndex funds all sell on a given day.This is understood well in advance, so no “news”But stock price generally falls and often takes a substantial amount of time to recover!
61Problems for Large Traders Limit orders make it difficult for large traders to get a good price…Example:Buyer and seller each willing to hold two units, but have decreasing marginal values.Buyer has values 35 and 32Seller has values 30 and 25Efficient to trade both unitsBuyer ideally offers 55 for two units.
62Large trades, cont. Example, cont. Buyer values 35 and 32 Seller values 30 and 25If buyer offers 30 and 25, seller can trade one unit at 30 and won’t want to trade a second unit.To get the seller to sell both units, buyer must offer 30 and 30, and spend 60 for 2 units.More profitable to offer 25 for one unit, and make profit 35-25=10, than pay 60 for two units and make profit =7.
63More problems Large traders suffer from “front-running” Example of order bookBuy orders 80,85,90,95,100Sell orders 105,110,115,120,125,130,135Large trader submits buy order for four unitsShould pay 105, 110, 115 and 120 for these units.Front-running strategyFront-runner jumps ahead and submits buy order for 3 units, then offers to sell 3 units at 120.Front-runner buys units at 105, 110, 115, sells at 120Large trader pays 120 for all unitsIt pays to be fast in a financial market!
64Strategies for large trades Large traders try to avoid thisExecute trades slowly, e.g. order one unit (pay 105), then one more unit (pay 110), and so forth.But this slows things down, and seems inefficient.Alternative to take the trade “upstairs”: find a large seller, or pay an intermediary to assemble or liquidate the position slowly.New exchanges try to improve the market design to facilitate large trades…
65Innovations in exchanges “Icebergs” and hidden ordersAllows traders to submit offers that are entered in the order book, but “hidden” from view.Makes it harder for predatory traders to front-run, and can allow large traders flexibility.“Dark pools”Orders submitted to broker (e.g. Goldman Sachs) are “crossed” before being submitted publicly to the exchange.Traders cannot see what is going on in this “dark” exchange, which benefits from seeing the prices and being able to access the liquidity in the public exchanges.Many interesting market design questions around the design of public and dark exchanges…
67Today’s Lecture Securitization and markets for loans How credit markets and securitization workWhy securitization: informational theoriesEconomics of secured credit marketsLeverage theory & Feedback effectsApplication to real estate and secondary marketsThe panic of & market failureHow the market failed, explanations and implicationsAttempts to “restart” and “redesign” these markets
69Consumer Lending Traditional consumer lending (by banks) Bank takes deposits from consumersBank lends the money out to borrowersBank collects payments on loansAs payments come in, can originate new loans.Modern consumer lending (by banks & others)Lender raises money (maybe deposits, but maybe not)Lender originates loans to borrowersLender resells loans to secondary marketCash from loan sales can be used to originate new loans.
70Traditional Lending (in pictures) BorrowersStep 1Step 2$$$Step 0LenderDepositors
71Securitization (in pictures) BorrowersStep 3: $ (via a loan “servicer”)Step 1IOUIOU$Step 2$Trust$Step 0$LenderDepositors$: Step 3Step 2InvestorsInsurersInsurance (CDS)$
72“Securitization” Securitization process Key features of the market Lender sells a “pool” of loans to the trust.Trust sells financial claims on the loan pool.Sale of the claims used to pay the lender.Trust collects loan payments & pays claim holders.Key features of the marketPooling of many loans (rather than resale of single loans)Tranching of pool payments to create securitiesWhy these features? Risk-sharing & information.
73Pooling Pooling can diversify risk Pooling can lower transaction costs Suppose each loan promises $1 but defaults with prob = 0.1So E[Payment]= $0.90, but Pr[Payment = 0] = 0.1.Consider 1% claim on 100 loans with independent defaultE[Payment] = 0.90, but Pr[Payment = 0] = (0.1)100.As the pool gets large, if defaults are really independent, then each fractional investor is likely to get close to $0.90Pooling can lower transaction costsIf each loan sold separately, investors want to inspect each one to cherry-pick the pool => sale process very costly.If loans are pooled, everyone gets a representative claim on the pool & harder to cherry-pick. (Analogy to de Beers!)
74Tranching Consider pool of loans made by bank Loans promise $100, but may deliver as little as $80.Investors think all outcomes btwn 80 and 100 equally likely.Suppose the bank knows what the outcome will be (v).Suppose bank tries to sell the whole poolIf investors offer 100, bank will sell, but E[Ret. to Inv]=90.If investors offer 90, bank will sell if v<90, E[Ret. to Inv]=85In equilibrium investors cannot offer p>80 and break even.So, investors offer 80, and bank only sells if v=80.The market doesn’t work to allow resale.
75Tranching Alternative “tranching” structure From theory to practice Bank sells claim on the first $80 in loan payments, and keeps all additional loan payments.Investors will pay $80 b/c claim is a sure thing.So finance the pool with a combination of debt (sold to investors) and equity (held by the bank).From theory to practiceTypically several tranches, which take losses in order: “junior” tranche is like equity, “senior” more like debt.Key feature: junior tranches are “information sensitive”, but senior tranches are less so --- doesn’t matter if pool will return 80, 85, 90, 95, investors get paid regardless!
76Ratings Agencies Rating agencies (Moody’s, S&P, Fitch) Usually grade corporate debt: AAA,AA,A, etc.Higher grades “safe”, lower more likely to default.Also grade “securitization” proposals: most senior tranches might be AAA, equity tranche maybe B.Concerns about ratings agenciesInvestors relied “blindly” on high ratings, but maybe…Gaming: tranches designed to “just” make the grade.Bad models: underestimated default from falling house prices, or the possibility of mass (correlated) defaults.Focus on probability of default rather than whether defaults would occur in “bad” states of the world (subtle).
77Secured Lending & Collateral What happens when borrowers default?If a loan is unsecured (like a credit card)Lender can try to harass the borrower, but not much else the lender can do to recover value.If a loan is secured (like a mortgage)Lender gets the underlying collateral. So default is less costly for the lender, who can charge a lower interest rate.If collateral is sufficiently valuable, default won’t even occur because if the borrower can’t make payments, she can sell the asset and use the proceeds to pay off the loan.
78Collateral & Feedback effects With secured lending, there can be feedback effects between the credit market and the asset market.Example with housing marketWhen prices are rising, lenders expect that even if they lend a large fraction of the purchase price, the house will become more valuable and so default won’t happen.And if home buyers can borrow a lot and at low rates, they can pay more, so prices go up => positive feedback.When prices are falling, the reverse can happen….Lenders will lend a smaller fraction of the purchase price, buyers have a harder time getting cash, prices fall more….Downward spiral can be exacerbated because borrowers who can’t make payments default and houses are sold at auction increasing supply of houses for sale.
79The Leverage Cycle On the way up… On the way down Asset prices expected to riseLenders offer generous creditBuyers can spend morePrices do rise, and so loans get repaid…On the way downAsset prices expected to fallLenders tighten creditBuyers can’t spend as muchPrices do fall, and so loans don’t get repaid, and so..Additional “forced sales” bring prices down further.
80Housing Bubbles & Crashes Many financial crises triggered by real estateUS Savings and Loan collapse (early 90s)Japanese bank failures in (early 90s)Sweden and Finland bank failures (early 90s)US and other recent problemsWhy real estate (rather than, say, business failures)Owners of real estate tend to be highly levered, as compared to, say, owners of businesses.Maybe why stock market crashes in 1987 and 2001 didn’t trigger broader financial crisis … although these events themselves may have been exacerbated by investor leverage.
81Investor LeverageBuyers of loans in the secondary market also used leverage… sometimes lot of it!In January 2007, it was possible to buy a AAA mortgage-backed security, and borrow 98% of the purchase price.These rates were available, however, only if the investor rolled the loan over every night (in the “repo” market)Feedback and the leverage cycle, again…If a small number of optimistic investors can borrow 50:1, they can have large buying power, and drive up asset prices --- particularly if it is hard to “short” the asset.Once prices start to fall, however, the optimists will be wiped out & credit will tighten, so prices fall a lot --- it’s harder to borrow & optimists are out of the market.This can lead to a crash in the secondary market.
82Feedback & Panics Bank runs - the old-fashioned kind Consumers have deposited money at bank and can come at any time to withdraw. A deposit is like a loan that is rolled over every second.Bank has lent the money out, keeping only a small reserve, so if more than a few investors withdraw, bank can’t pay.If consumers believe the bank has made some bad loans, there can be a race to get money out.Government solution: deposit “insurance”Many bank runs in the 19th century and Great Depression, following which US Gov’t decided to insure deposits.If investors demand their money, and bank can’t pay, govt will. So long as investors are confident in FDIC, no runs.
83Feedback & Panics Bank runs - the modern kind Suppose a financial institutions is borrowing short term (e.g. buying mortgage securities with overnight financing).If investors get nervous, they pull their money, knowing that the gov’t may not be there to “insure” repo loans.Plus, there are some additional twists..If institution is a broker (Lehman, Bear, Morgan Stanley), its customers (e.g. hedge funds), may also run, so franchise value of the institution disappears.Small number of “core” institutions are interdependent: e.g. they may have sold each other insurance, so if bank A fails, and owes money to bank B, bank B may fail.
84Stepping back (macro picture) From , there was a lot of money chasing investment opportunities.Savings glut in China, Middle East, etc.Fed had interest rates low so investors wanted better investments than treasuries.Lots of this money found its way into housing.Home ownership increased from 65% to 69%.House prices increased by XX%.Leverage increased a lot: many new purchases at zero percent down, and home equity loans let homeowners increase size of mortgage relative to house value.Didn’t everyone see problems coming? Why not?
85The panic of 2007… Housing market started to turn: bad loans (esp. subprime from ) began to default,even tranches viewed as “safe” become risky.Everyone realized that investors holding securities based on bad loans were going to take losses.Loss of confidence in shadow banksmany of which were holding these securities,and many of which were reliant on repo financingTriggering feedback effect and panicSlow-motion run/collapse of the repo marketPrices being offered for mortgage-backed securities dropped sharply, making it hard for investors to liquidate position without taking big losses.
86… continuing into 2008 Positions of finacial institutions deteriorated Failure of Bear Stearns in Feb 2008.Takeover of Fannie Mae, Freddie Mac, IndyMac.Collapse of WaMu, Lehmann, AIG, Merrill, Wachovia, etc.Government interventionsInitially, offered loans to replace lost repo financing, and responded in ad hoc way to individual failures.Eventually proposed TARPIdea: buy “bad assets” from the banks, restoring confidenceActual: buy equity shares in the banks, restoring solvency.Plus Fed eventually buys $1+ trillion of mortgage-backed securities essentially taking on the role of lender to prevent further economic collapse, especially in housing.
87Market Design Problems Market for “toxic assets”Once housing prices started to fall, seemingly “safe” securities became risky, market shut down.Why did the market shut down?Asymmetric information? Anticipation of bailout?Could it have been re-started?TARP proposal was for Treasury to buy large quantities of toxic assets.Initially considered a SAA or treasury-style auction.Later considered setting up funds managed by professional investors who would buy in various ways.
88Market Design Problems Market for Credit Default SwapsCDS are insurance contracts that pay off if a given loan (or bond) defaults.Example. I buy a Lehmann bond that promises $1, and pay AIG to insure it. I pay AIG premiums and if the Lehmann defaults, AIG makes me whole.Markets for CDS settlements?When Lehmann goes under, it takes a while to sort our who gets what, but ideally want to “settle” the CDS contracts right away based on value of the bonds. But what is it?Should CDS markets be bilateral or exchange-based?CDS contracts are bilateral - concern is spillover effects and non-transparency. New proposals call for exchanges where parties would trade against the exchange.
89Market Design Problems Funding markets for financial institutionsPart of the problem in the crisis was the heavy reliance on short-term repo financing.Is it possible to have better markets/models for financing financial institutions?Insured deposits? Loans that can be re-paid with stock certificates? Or maybe just limits on leverage?Difficult regulatory problem because gov’t ultimately bears a lot of the risk, but doesn’t want to overly constrain financial institutions.
90Macroeconomics How does the recession link to the crisis? Starting in and accelerating in fall 2008, consumer spending, employment, and investment dropped.Various theories to explain thisHarder for consumers and firms to get creditLoss of consumer confidence and wealthLoss of business confidence, and uncertaintyGovernment creating additional uncertainty…Of course, in 2009, the survivors in the financial markets actually did great …Partly because of gov’t lending them lots of money at cheap rates, and partly because market dislocations created a lot of opportunities…