Complete market

Résumé

In economics, a complete market (aka Arrow-Debreu market or complete system of markets) is a market with two conditions:

Negligible transaction costs and therefore also perfect information,

Every asset in every possible state of the world has a price.

In such a market, the complete set of possible bets on future states of the world can be constructed with existing assets without friction. Here, goods are state-contingent; that is, a good includes the time and state of the world in which it is consumed. For instance, an umbrella tomorrow if it rains is a distinct good from an umbrella tomorrow if it is clear. The study of complete markets is central to state-preference theory. The theory can be traced to the work of Kenneth Arrow (1964), Gérard Debreu (1959), Arrow & Debreu (1954) and Lionel McKenzie (1954). Arrow and Debreu were awarded the Nobel Memorial Prize in Economics (Arrow in 1972, Debreu in 1983), largely for their work in developing the theory of c

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https://en.wikipedia.org/wiki/Complete_market

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This course provides an overview of the theory of asset pricing and portfolio choice theory following historical developments in the field and putting emphasis on theoretical models that help our understanding of financial decision making and financial markets.

This course provides students with a working knowledge of macroeconomic models that explicitly incorporate financial markets. The goal is to develop a broad and analytical framework for analyzing the interaction of financial decisions, macroeconomic events and policy decisions.

This course aims to give an introduction to the application of machine learning to finance. These techniques gained popularity due to the limitations of traditional financial econometrics methods tackling big data. We will review and compare traditional methods and machine learning algorithms.

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Asset trading volume in infinite-horizon economies with dynamically complete markets and heterogeneous agents: Comment

In a recent paper, Judd et al. [2003. Journal of Finance 58, 2203-2217] study asset trading in a version of the standard Lucas infinite horizon economy with heterogeneous agents. They report the surprising finding that (for generic economies in their class), in equilibrium, there is no trade in (long-lived) assets after the initial date. This note points out that the conclusions of Judd et al. [2003. Journal of Finance 58, 2203-2217] are artifacts of the assumption that asset dividends and individual endowments follow the same stationary finite state Markov process. Without this assumption-and even if asset dividends and aggregate endowments follow the same stationary process-there will necessarily be trade at many histories. © 2006 Elsevier Inc. All rights reserved.

2006

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Prices and Allocations in Dynamically Complete Markets: Experimental Evidence

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Event Risk, Contingent Claims and the Temporal Resolution of Uncertainty

Pierre Collin Dufresne, Julien Hugonnier

We study the pricing and hedging of contingent claims that are subject to Event Risk which we define as rare and unpredictable events whose occurrence may be correlated to, but cannot be hedged perfectly with standard marketed instruments. The super and sub-replication costs of such event sensitive contingent claims (ESCC), in general, provide little guidance for the pricing of these claims. Instead, we study utility based prices of ESCC under two scenarios of resolution of uncertainty for event risk: when the event is continuously monitored or when it is revealed only at the payment date. In both cases, we are able transform the incomplete market optimal portfolio choice problem of an agent endowed with an ESCC into a complete market problem with a state and possibly path dependent utility function. For negative exponential utility, we obtain an explicit representation of the utility based prices under both information resolution scenarios and this in turn leads us to a simple characterization of the early resolution premium. For CRRA utility functions we propose a simple numerical scheme to compute both late and early resolution prices and study the impact of size of the position, wealth and expected return on these prices.

2001

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