Decision Making & Negotiations

Technical analysis, also known as "charting," has been a part of financial practice for many decades, but this discipline has not received the same level of academic scrutiny and acceptance as more traditional approaches such as fundamental analysis. One of the main obstacles is the highly subjective nature of technical analysis — the presence of geometric shapes in historical price charts is often in the eyes of the beholder.

This paper studies implementation in a principal-agent model of adverse selection. We explore ways in which the additional structure of principal-agent models (compared to general implementation models) simplifies the implementation problem. We develop a connection between the single crossing property and monotonicity conditions which are necessary for Nash and Bayesian Nash implementation. We also construct simple implementing mechanisms that rely on the single crossing property and on assumptions about the outcome set frequently made in the principal-agent literature.

This paper describes novel market-based technologies that uniquely establish quantifiable and adjustable limits on the power of attackers, enable verifiable accountability for malicious attacks, and admit systematic and uniform monitoring and detection of attacks. These technologies, incorporated in the MarketNet system, establish a financial economy to regulate the trade and use of access rights in information systems. Resources are instrumented to use currency for access control and monitoring, establishing accountability in their use.

Prior evaluations are frequently challenged and need to be revised. We propose that an important determinant of such revisions is the degree to which the challenge provides an opportunity to compare the target against a competitor. Whenever a challenge offers an opportunity, the information contained in the challene will carry a disproportionate weight in the revised judgments. We call this proposition the comparison-revision hypothesis.

This paper introduces a class of state dependent jump (SDJ) models in which the arrival intensity and jump sizes depend on a given set of state variables, including lagged jumps. With this model, we investigate the structure of jumps to U.S. equity indices, concentrating on the predictability of jumps times if found for all of the indices considered: Standard and Poor's 500 and Mid-Cap, the Russell 1000, 2000, and 3000 indices, the Wilshire 5000 and the Nasdaq 100 (NDX).

Research extending over twenty years in behavioral decision theory has led to the development of two important research streams--mental accounting and reason-based choice. This paper explores recent research on the role of mental accounting and reason-based choice in the construction of consumer preferences. Evidence suggests that the principles of mental accounting often regulate the purchase and consumption of luxuries and that reasons may play an important part in this process.

Affective states of the same valence may have distinct, yet predictable, influences on decision processes. Results from three experiments show that, in gambling decisions, as well as in jobselection decisions, sad individuals are biased in favor of highrisk/high-reward options, whereas anxious individuals are biased in favor of low-risk/low-reward options. We argue that these biases occur because anxiety and sadness convey distinct types of information to the decision-maker and prime different goals.

Stochastic Economic Lot Scheduling Problems (ELSPs) involve settings where several items need to be produced in a common facility with limited capacity, under significant uncertainty regarding demands, unit production times, setup times, or combinations thereof. We consider systems where some products are made-to-stock while another product line is made-to-order. We present a rich and effective class of strategies for which a variety of cost and performance measures can be evaluated and optimized efficiently by analytical methods.