2 The Institutional View on Markets
2.1 Microeconomic System Framework
2.1.3 Institutions
2.1.3.4 Adjustment Process Rules
The adjustment process rules specify under what conditions messages can be introduced, modified or repudiated along the market process. Hitherto, it was assumed that the allocation and the transfers are determined as a result of the message exchange. However, this view ab-stracts from the fact that message submission can also be subject to some constraints. The space of all adjustment process rules is naturally very huge, taking the many conceivable con-straints30 into consideration. The description is thus reduced to three rule types, which are general enough to capture a fairly complete set of adjustment process rules. Adjustment proc-ess rules consists of the following rules:
• Opening rules: gi
(
t0,...,...)
• Transition rules: gj
(
...,t,...)
• Closing rules: gk
(
...,...,T)
30 The constraints can generally be distinguished into event, time, and state-oriented constraints.
Definition 6: Adjustment Process Rules
The adjustment process rules govern the control of the message flow.
Formally, the adjustment process rules are described as a set G =
(
g1(
t0 t,,T)
,...,gN(
t0 t,,T) )
31.Basically, these adjustment rules specify under what conditions messages can be introduced, modified or repudiated. As previously described, adjustment rules must contain an opening rule, transition rules, and a closing rule. The opening rule determines the condition
(
t0,...,...)
gi , when the message exchange may commence. Transition rules gj
(
...,t,...)
govern the flow of messages, whereas the closing rules gk(
...,...,T)
state the closing conditions.2.1.3.4.1 Opening Rules
Opening rules define the beginning of the message exchange process. This time-period may be fix or dependent on the incidence of an event. Fix opening rules are pretty common in most auction formats. Frequently, the message exchange process commences at a particular time.
Event-triggered opening rules also determine the start of the message exchange process but are less obvious than time-triggered rules.
Example 2.1-13: Opening rule of the German stock exchange
The German stock exchange accepts orders not before 7.30 a.m. At this time the pre-trade phase starts. Buy or sell orders can be entered into the system as a preparation for the sub-sequent trading phase. As this phase merely serves the order management, the agents do not receive any information feedback of the other messages. In the following phase, the messages are matched and executed against each other at a time, heralding the subsequent continuous trading phase.
In contrast to time-dependent rules, suppose the message exchange process only com-mences on the submission of a certain message by one agent. For example, in thin (illiq-uid) markets the submission of bid-messages commences with a request from a buyer or seller. This rule temporarily concentrates the messages at an arbitrary time.
2.1.3.4.2 Transition Rules
The transition rules state the conditions how the sequencing and the exchange are governed.
The following list gives an overview over the most prominent transition rules.
• Internal dominance rules
Dominance rules in general require, newly introduced messages, say bids, to dominate the previous highest bid in some specified form. Internal dominance requires the newly intro-duced bid to dominate the previous bids of the same agent. It is conceivable that internal dominance rules can apply not only to the buying but also to the selling agents. In the case of a double auction both sides – buying and selling side – are allowed submitting bids.
Then, internal dominance rules for both sides are necessary.32 Typically, internal nance rules are either ascending or descending. Ascending (descending) internal domi-nance demands superior bids than the previous ones in terms of a higher (lower) price.
More complex internal dominance rules can also account for multi-dimensional bids, where dominance is more difficult to define (Wurman, Wellman et al. 1998).
31 Usually, the arguments of the adjustment rules are assumed to be common knowledge (for a mathemati-cal treatment of common knowledge see for example (Aumann 1976)), i.e. all agents know them in ad-vance.
32 No restrictions upon own bids are also a dominance rule.
• External dominance rules
External dominance rules require that the newly introduced messages, say bids, do domi-nate the previous highest bid of other agents. For example, in an English auction not only the own highest bid must be surpassed but also the standing highest bid of all agents. The applied concept of external dominance (Wurman, Wellman et al. 2002) is again dependent on the resource that is to be distributed among the agents. Suppose the resource is a stock, implying a discrete and standardized good, respectively. In those cases dominance is often defined by a higher price at constant quantities.33 For a more detailed description of domi-nance rules see for example Wurman, Wellman et. al. (Wurman, Wellman et al. 1998).
Example 2.1-14: External dominance rules
Stock Exchanges usually apply the principle of price-time priority as a dominance rule.
This means that the first dominance criterion is the offered price. In case the price of sev-eral orders is equal, the time when the order was submitted becomes the criterion to de-termine dominance. Since early orders provide the market with additional liquidity, early orders are dominating late orders.
• Activity rules
Activity rules are another intriguing example of transition rules. Basically, activity rules are intended to encourage truthful bidding in every stage of the market process (Milgrom 2000; Wilson 2001). The gist of activity rules is to confront the agents with an “to bid for it or lose it” (DeMartini, Kwasnica et al. 1998) decision at any stage of the process. If the agent fails to meet a certain minimum bid requirement, the agent is excluded from the subsequent market process.
This exclusion reflects the idea of revealed preferences: by posting a bid the agent is partly revealing his preferences. The observed choice represented by the bid (e.g. a price-quantity combination) allows inferring the agent’s utility. This inference can be used to impose bounds on the agent’s subsequent bids (Kreps 1990; Varian 1992). If an agent fails to post a bid inside these bounds, he is excluded from the bidding process. Based on a sin-gle bid, the bounds are not very tight. However, as the bidding process progresses the bounds can become very close together. In this case there is only small or none room for strategic behavior left (Wilson 2001). In summary, activity rules prevent agents from im-proving their messages late in the process withholding information that might have been valuable for the other agents along the process.34
Example 2.1-15: Activity rules of the FCC-Spectrum auction
The Federal Communications Commission (FCC) -Spectrum auction is probably one of the most prominent examples in auction theory. Its design provides an easy version of an activity rule. The activity rule manages the eligibility status of all bidders. A bidder is re-garded eligible, if he either holds the highest bid from the previous round or if he submits a bid which exceeds the previous round's high bid by at least the amount of the minimum bid increment. During the auction every bidder is granted a number of automatic waivers from this activity rule. If the bidder fails to maintain the demanded level of activity, i.e.
uses up all waivers, he loses his eligibility status and is excluded from subsequent bidding rounds (Cramton 1997).
33 Dominance is easy to define if the resources that are to be allocated are perfect substitutes, i.e. standard-ized. If the resources differ in their appearance, i.e. non-standardized, the concept of dominance is more difficult to formalize. Examples can be found under (Che 1993; Branco 1997; Wurman 1999).
34 The success of activity rules in auction design is controversially discussed (Wilson 2001).
• Withdrawal Rules
Withdrawal rules dictate whether the institution permits withdrawals and if so it specifies the time when withdrawals are feasible. As such, the withdrawal rules control the com-mitment with which the messages are released. The more stringent the messages are, the less room is left for strategic behavior. On the other hand, very restrictive withdrawal rules, e.g. no repudiation, remove much of flexibility away from the participating agents.
Suppose the agents realize that their previous message is inappropriate they may not have a chance to revoke it. Usually, the current implementations of withdrawal rules are some-where between those extremes. Revocation is only permitted at a particular time. Fur-thermore, revocation can come along with a penalty, say a fee. The size of this penalty can also vary depending on the time the message was withdrawn (Porter 1999).
Example 2.1-16: Withdrawal Rules
In most of the commercial applications, full commitment is required. As such, withdrawal is usually not possible. For example Moai’s Livestock auction allows no withdrawal rules (c.f. Neumann, Benyoucef et al. 2003). In the FCC auction the high bidders can withdraw their bids. This is, however, coupled with a bid withdrawal penalty (c.f. Cramton 1997).
2.1.3.4.3 Closing Rules
Closing rules indicate the condition under which the message exchange process is ceased.
Principally, there are several different ways to determine the closing of the messaging. Wur-man identifies four common closing policies (WurWur-man 1999):
• Scheduled
Analogous to the opening rules, closing rules can specify a particular time at which the bidding process is stopped. This so-called closing time is normally published in advance.
The fixed-end closing rule is very straightforward. Nonetheless, this rule has recently at-tracted a lot of interest from the economic community, because it may cause a behavior called late bidding.35 Note that processes that are performed in one-shot must have a scheduled end.
Example 2.1-17: Scheduled closing rules
A vivid example of scheduled closing rules associated with late bidding is eBay’s second price auction. The bidder can enter a reservation price, which is posted to a proxy agent.
The proxy agent always bids just one increment above the previous highest bid until the reservation price is reached. This format was intended to encourage early bidding, since it does not incur any detrimental effects. The proxy bidder adjusts the bids according to the actual bidding process. The auction is terminated at a specific point of time, which is pub-lic knowledge.
Despite the fixed closing time, a lot of agents submitted their bids in the last seconds be-fore the auction closes. Such a massive “snipping” behavior suggests that there are not only non-strategic but also strategic reasons. As the more informed bidders are reluctant to reveal their superior knowledge early in the auction, they prefer late bidding, such that the other bidders cannot react on their bids (Roth and Ockenfels 2002).
• Random
Random closing rules refer to the case where the matching and allocation is scheduled at a random time. The ending time is usually following a previously specified distribution.
35 Late bidding behavior does not necessarily occur in any institution embodying scheduled closing rules.
For example activity rules can alleviate the effect of late bidding.
tended to prevent the agents from strategically bidding, the rule is also apt to heal the problems of scheduled closing rules. This is straightforward to explain taking into account that the agents simply do not know the exact closing time. By bidding late the agents run the risk of submitting their bids too late. On the other hand, late bids – which are revealed too early – may still grant the other agents time to react upon the new information before expiration.
Example 2.1-18: Random closing rules
Crossing networks epitomize institutions that embody a random closing schedule as one of their fundamental rules. Crossing networks refer to institutions, which allocate goods, usually stocks, at a so-called crossing price that is derived from another market that trade the same goods. The intuition underlying crossing networks becomes clear, if their pri-mary area of application is closer delineated.
In stock markets, few professional traders36 manage a large share of the total amount of stocks. Accordingly, their trading volume per order can be very large37. The trading size of these “block trades” can, however, induce a negative price effect. This price effect de-notes the difference between the price before the block trade was submitted and the reac-tion of the other traders. One perspicuous explanareac-tion38 refers to the set of private infor-mation. The potential traders may suspect that they have less precise information about the stock and thus run the risk of trading with an agent who has superior information. In order to assure from this risk, the traders demand a recompense from the block trader.
This recompense nicely describes the negative price effect.
Now, crossing networks come into play. They collect buy and sell orders and allocate the stocks at a price that is derived from a reference market. The advantage is that the price is executed at the current price without the negative price effect.39 Taking the size of the blocks into consideration, the block traders are tempted to manipulate the price of the ref-erence market. The random closing rules are designed to discourage this manipulation be-havior. Since the closing time is uncertain, manipulation is getting more costly because more buy or sell orders have to be submitted (Harris 2003).
• Agent inactivity
The case of agent inactivity is another common instance of a closing rule. The message exchange process is terminated if no more messages are placed. On an abstract level, it can be assumed that the absence of new messages is reasoned by the fact that the institu-tion has attained a situainstitu-tion in which the messages converge of to the real preferences of the society. This implies that every agent has had the opportunity to release an updated message. Principally, all agents can bid up to their valuations – if necessary. If all agents forfeit the chance to revise their messages, apparently no agent can improve his situation by placing another message.
Note that agent inactivity can be coupled with a scheduled closing rule. In this case, the closing time is scheduled in advance. Different to pure scheduled closing rules the
36 In the finance literature professional traders are usually called institutional traders. This refers to the fact that these institutions, e.g. banks or insurance companies, are not trading for their own account, but (merely) conduits for someone else, e.g. retail customers. To avoid misunderstanding between institu-tions – understood as the set of rules – and instituinstitu-tions – understood as some sort of companies –, the term “professional traders” is used in the following.
37 Note that a unanimous definition of a block is missing.
38 Theoretically, there are many plausible explanations for this negative effect existing (see for example (Burdett and O'Hara 1987; Holthausen, Leftwich et al. 1987; Ball and Finn 1989).
39 The disadvantage is that only a fraction of the entire block is executed. This market imbalance stems from the fact that the crossing price does not reflect demand and supply situation and hence cannot attain a market clearing.)
sage exchange process is automatically extended on receiving another message. The proc-ess is finally terminated when no further mproc-essages are posted.
Example 2.1-19: Agent inactivity closing rules
Auction Theory offers a comprehensive pool of examples for agent inactivity closing rules. For example, the perhaps most common auction format, the English auction, is often dubbed by the phrase “going, going, …, gone”. This phrase literally depicts the closing rule: The message exchange period stops after the closing has passed and no new mes-sages are transmitted for some minutes.
Furthermore, the example of the English auction also confirms the convergence hypothe-sis. The agent with the highest valuation eventually clinches the deal. Under the strong as-sumptions of the IPV model, the optimal strategy is in deed “bid up to your valuation”.40 In summary, the IPV model imposes a strict corset on the economic environment.
• Agent activity
According to the agent activity closing-rule, the message exchange process is terminated once a pre-specified activity such as bid submission has occurred. For example, if a new bid is submitted that allows execution with a previously issued offer, the transaction is ini-tiated. This example is taken from the continuous double auction, where allocation and price determination is performed whenever it is possible.
Example 2.1-20: Agent inactivity closing rules
The single unit Dutch auction is presumably the easiest agent-inactivity closing rule. Once an agent accepts the current price the auction closes.