Platforms and Exchanges

1. Platforms and Exchanges Jon Levin Winter 2010 Economics 136

2. Auction Platforms

3. Introduction • 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, with • A structured environment for buying and selling goods • Often a very specific set of market rules & institutions.

4. Introduction • 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.

5. Introduction • 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…

6. Market design • Platform operators have to consider • How to attract buyers and sellers • How to match them efficiently • How to ensure market runs in an orderly fashion • How are the gains from trade shared • How does the platform make money • Tools for answering these questions • Theoretical models (as in search auction case) • Experiments (very common in online markets) • Data analysis (platforms get to collect a lot of data)

7. Monopoly 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.

8. Competing platforms • Nature 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 important • Scale 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!

9. eBay’s Market Design

10. eBay and online markets • eBay: largest site for e-commerce • 81,000,000 monthly visitors • 140,000,000 listings on a given day • $8,500,000,000 platform revenue • Competes against Amazon, Craigslist, other online sites, plus many off-line companies. • Today: discuss its marketplace design.

11. Market + Search Technology • Many heterogeneous objects being sold • Different kinds of sellers and buyers • Range from full-time “pros” to casual participants. • Ongoing market, sequential sales/closes • Multiple pricing mechanisms • Auctions, Posted prices (Buy it Now) • Buyer search • Catalogs/Browsing, Sophisticated search • Featured listings, advertising

12. Structure of Buyer Search • What distinguishes listings • What is the good, new/used • Who is the seller, reputation, location • What is the sale type: auction, posted price. • Some important issues • Prioritize auctions or posted prices • Catalogue vs non-catalog items • Distinguish sellers, or initially just goods • Conflation? Or emphasize diversity?

13. Conflation in market design • Emphasize diversity • Traditional 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 displayed • Sellers, and seller distinctions revealed later. • What are the trade-offs? Do they depend on the nature of the item and perhaps buyer?

16. Listings and Information • eBay in principle controls what sellers can communicate to buyers • Different types of information in listing • Standardized information • “Free-form” information (photos, videos, text) • Some important issues • eBay imposes relatively little structure on sellers • Only recently has started to collect “extra” information from sellers – why would you do this?

18. Disclosure 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.

19. The Lemons Problem • Three kinds of car: peach, apple, lemon • Buyer values: $2500, $1800, $1100 • Seller values: $2000, $1500, $900 • Seller knows quality, buyer doesn’t • Equal numbers of car types • “Akerlof” lemons problem • At 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 $1450 • At 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.

20. Disclosure • If quality can be costlessly disclosed • Peach sellers will disclose quality • So apple sellers will also disclose • So buyers will be able to identify lemons! • Then all types of cars will trade… • This “unraveling” result is quite striking • Depends on buyers being sophisticated • Or alternatively, on seller competition… • What happens if disclosure is costly?

21. Costly disclosure • Back to our example • Buyer values: $2500, $1800, $1100 • Seller values: $2000, $1500, $900 • Suppose 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!

23. Contract/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 conditions • Buyer pays first, usually no escrow! • Trust-based (compare with China eBay) • Main issue: safety for buyers…

24. Reputation mechanisms • Seller reputation helps enforce “contract” • Buyers give feedback post transaction • Sellers also give feedback post transaction • Participants acquire scores – pos. & neg reviews • What are the issues • What is the incentive to give feedback • Retaliation problems • Bolton et al. innovative designs • New programs for “top sellers” – good idea?

25. Bolton et al. on Reputation • How can you avoid the “retaliation” problem? • Don’t let seller give feedback • Don’t let buyer/seller see each other’s feedback • Mix of disclosed/non-disclosed feedback • What are the trade-offs? • Other reputation issues • Why are the sellers trusted? Why not buyers? • Are there other ways to organize the market? • Markets turn out to be quite local – trust issues?

26. Auction mechanism • Ascending auction with proxy bidding • Enter “maximum bid” – proxy bids up to maximum • Object awarded to standing high bidder at close • Hard close: auction ends at a fixed time • Secret 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?)

27. Sniping (Roth et al.) • Roth and Ockenfels (2002) • Sniping observed at “hard close” auctions • Sniping doesn’t occur when there is a “soft close” • Why would you wait to the last minute • Early bids might attract attention to a listing • Early bids might signal object was valuable • Even 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.

28. Auctions vs Posted Prices • eBay has moved toward to posted prices • Now more than half of the platform is prices • What 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?

29. Market design, broadly • What are all these smaller decisions aimed at • Attracting participants • Efficient matching of buyers and sellers • Orderly and safe transactions • How 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.

30. Financial Exchanges

31. Today’s Lecture • Background on financial exchanges • The role of financial exchanges • Desirable attributes of an exchange • History of these markets • Specialist markets, OTC markets, exchanges • The move to electronic exchanges • Market design issues • Information aggregration, large orders • Competing platforms, transparency, dark pools.

32. Public equity markets • Focus on markets for public equity • Companies issue publicly traded stock. • Historically traded on a few large exchanges • Recently competition between exchanges and a great deal of innovation in exchange design. • Questions to consider • What are the objectives for a successful market? • What designs help achieve these objectives? • What is the role of competition between markets?

33. Market objectives • Objectives for the public equities market • Price discovery (prices reflect current information) • Fair competition (open access, nondiscrimination) • Investor protection and confidence • US regulates financial markets to achieve these objectives, looking at things such as • How 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?

34. Desirable market properties • Liquidity • In liquid markets, traders can buy or sell large quantities of shares without a large price impact. • Transparency • Participants have information available to them before making a trade (receive a quote, see open offers) and after a trade (see prices, quantities). • Price discovery • Prices incorporate and track available information in the market - and do so in a reasonable and efficient way.

35. Organization of Markets • Historically, equities in US were mainly traded on the floor of the NYSE. • NYSE as a “specialist” market • Each stock managed by a specialist • Specialist quotes “bid” and “ask” prices • Investors, who are physically on the trading floor, trade with the specialist at these prices • Specialist holds some stock to keep market functioning, but not very large positions.

36. Organization of Markets • Nasdaq competes with NYSE and was historically an “over the counter” market. • Organization of OTC markets • Small 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.

37. Organization of markets • Equity trading has increasingly moved to electronic order books, including at NYSE. • Organization of electronic exchanges • Traders submit orders to buy or sell • Orders 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).

38. Organization of markets • Many large trades take place “upstairs” - not on the NYSE floor or in a public exchange • Organization of large trades • Often 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).

39. Recent 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 trades • Falls from 10.1 seconds in 2005, to 0.7 seconds in 2009. • Trading volume • From 2.1 bn shares/day in 2005 to 5.9 bn in 2009. • Average trade size • Falls from 724 shares in 2005 to 268 shares in 2009

40. Current market • Trading mostly done on electronic platforms • Five large exchanges (transparent) • Multiple smaller electronic exchanges • Internal or “dark” trading pools (not transparent) • Questions • Does 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?

41. Applying economic theory • Price formation and price evolution • “Efficient” markets with asymmetric information • Model bid/ask spreads in specialist markets • Search costs and market frictions • Bid/Ask spreads in OTC markets • Large orders and price impacts • Design of exchanges, and exchange competition.

42. Modeling price formation • Consider a specialist market • Specialists 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 arrive • Smart trader: knows d, sells only if b>d • Dumb 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.

43. Bid prices in market • Specialist quotes a price b • With probability 1/2, dumb trader shows up • Trader sells the stock for b • Specialist makes a profit d-b • With probability 1/2, smart trader shows up • Trader sells the stock if b>d • Specialist makes a profit (really a loss) d-b

44. Specialist market If dumb trader arrives, sells for b, specialist gets E[d]=1/2 If smart trader arrives, only sells if d<b, I.e. with pr=b If d>b, smart trader will not sell b 0 If d>b, smart trader will sell 1 E[Profit] = (1/2)b - b = - (1/2)b E[Profit] = 0

45. Bid Prices in Market • What is the expected profit for specialist • If dumb trader: expected profit is 1/2 - b • If smart trader: expected profit is b * [ -(1/2)b ] • Specialist break-even condition E[Profit] = (1/2) * [ 1/2 - b ] + (1/2) * b * (- 1/2* b) = 0 • Solving for the competitive bid price 1/2 - b = 1/2* b2 1-2b-b2 =0 b = 0.414

46. Ask 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 arrive • Smart traders: know d and buy if d>a • Dumb traders: don’t know d and buy at any a • Specialists quote an ask price that ensures they will just break even in expectation • Will the ask be above or below the bid?

47. Ask prices in the market • Specialist quotes an ask a • With probability 1/2, dumb trader arrives • Buys at a • Specialist profit is a-d • With probability 1/2, smart trader arrives • Buys if a<d • Specialist profit is a-d

48. Solving for ask prices • Specialist expected profit • If dumb trader: profit is a-1/2 • If smart trader: profit is -(1-a)*(1-a)/2. • Solving for the break-even ask price 2a - 1 = (1-a)2 a = 0.586 • Compare to the bid b = 0.414 • The “spread” is a-b, here 0.172

49. Price Formation & Dynamics • Efficient market theory • Current 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.

50. Competition and Spreads • What makes spreads larger or smaller? • More informed traders => larger spreads • Less specialist competition => larger spreads • Competition 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”.