Organisms continuously monitor the stimuli they encounter and the outcome of their actions. To survive in an uncertain world they aim for rewards and try to avoid punishments. Research in neuroscience, ecology, and economics implies that organisms base their decisions in uncertain situations on expected rewards and risk. Neuroscience focuses on reward prediction learning based on reward prediction errors. In contrast, economic studies emphasize risk in addition to expected reward.
\r\n\r\nWe used functional imaging in humans during gambling tasks to understand how the brain represents expected reward and risk. We find that brain activity in subcortical dopaminoceptive structures can be separated, both spatially and temporally, into signals that correlate with (mathematical) expectation of reward, and with reward variance (risk) \u2013 two fundamental parameters in financial decision theory. Our results suggest that the primary function of the dopaminergic system extends beyond its established role in learning, motivation, and salience: it signals different aspects of upcoming stochastic rewards \u2013 expected reward and risk.
\r\n\r\nBased on financial decision theory we then hypothesized neural representations of prediction risk and prediction risk errors. We find that the insula represents both. In analogy with reward representations in subcortical structures, the signals are spatially and temporally differentiated. These findings expand our understanding of the neural basis of decision making under uncertainty by adding prediction risk estimation.
\r\n\r\nFinally, we investigated where and how expected reward and risk are combined into the neural representation of a gamble\u2019s overall value. Using canonical correlation analysis, we find a new predictor that \u2013 contrary to expected utility theory \u2013 adds risk to expected reward. This sum may define a metric of conflict or attention. This metric significantly correlates with activation in the anterior cingulate cortex a structure associated with conflict monitoring.
\r\n\r\nDrawing on financial theories, we show how the brain represents expected reward and risk. Our results suggest that the earlier understanding of decision making under uncertainty needs to be expanded to include (prediction) risk as measured by variance as well as prediction risk errors. Such integration has far-reaching implications, in particular for pathological decision making.
\r\n", "doi": "10.7907/X8G3-B032", "publication_date": "2007", "thesis_type": "phd", "thesis_year": "2007" }, { "id": "thesis:13829", "collection": "thesis", "collection_id": "13829", "cite_using_url": "https://resolver.caltech.edu/CaltechTHESIS:06292020-132308787", "type": "thesis", "title": "Stochastic Bargaining Theory and Order Flow", "author": [ { "family_name": "Kato", "given_name": "Kaoru", "clpid": "Kato-Kaoru" } ], "thesis_advisor": [ { "family_name": "Bossaerts", "given_name": "Peter L.", "orcid": "0000-0003-2308-2603", "clpid": "Bossaerts-P-L" } ], "thesis_committee": [ { "family_name": "Bossaerts", "given_name": "Peter L.", "orcid": "0000-0003-2308-2603", "clpid": "Bossaerts-P-L" }, { "family_name": "Hillion", "given_name": "Pierre", "clpid": "Hillion-Pierre" }, { "family_name": "McKelvey", "given_name": "Richard D.", "clpid": "McKelvey-R-D" }, { "family_name": "Plott", "given_name": "Charles R.", "clpid": "Plott-C-R" } ], "local_group": [ { "literal": "div_hss" } ], "abstract": "This thesis is composed of two parts, each of which reflects our attempt to describe order flow determinants in a bilateral and multilateral trading environment, respectively.
\r\n\r\nIn Part I of this research, we investigate noncooperative bilateral sequential bargaining games in which the value of the asset changes stochastically according to a sequence of perfectly observable time-varying random variables. We attempt to model scientific speculations of the game participants that lead to varied length of bargaining durations. Previous studies, which have focused on the analyses of incomplete information games in interpreting bargaining delays, have shown that such delays are attributed to information asymmetry on asset values among players that results in differences in players' personal valuation of the asset. However, following the viewpoint of the Efficient Market Hypothesis, we assume in our models that there is no uneven assimilation of information of vital importance that affects the asset value once the players are at a negotiating table. Hence, one of the important features of the investigated models is that both players observe identical information regarding the future asset value, and that there is no uncertainty regarding one's opponent's preferences during the bargaining process. Despite the assumption of complete information, we argue that a delay before an agreement under certain conditions is an inevitable consequence of the stochastic component in this model.
\r\n\r\nWe give game theoretic specifications for two types of bargaining games, which we call the Basic game and the Alternative game. The two games differ from each other in their timing of information arrivals with respect to players' actions. We characterize their subgame perfect equilibria that follow our particular behavioral assumptions. Characteristics of the equilibrium outcomes of the two games are compared. We direct special attention to the study of the analytical results in comparison with those of Rubinstein (1982), Osborne and Rubinstein (1990), and Merlo and Wilson (1995). We then give statistical specifications for two types of stochastic bargaining simulations, which are the Autoregressive Binomial Model and the Generalized Wiener Process Model. Comparative statics of several variables and bargaining durations are investigated thoroughly through numerous simulation runs. Subsequently, through our research we clarify the importance of integrating stochastic concepts into the bargaining theory and its applications in search of alternative explanations for various bargaining durations.
\r\n\r\nIn Part II of this research, we provide a set of experimental results in our study of order flow determinants in experimental financial markets with asymmetrically informed human subjects. The markets are organized as computerized double auctions accommodated with an order book that contains a complete set of current limit and market orders and that can be inspected by every market participant at any time during each trading period. Our empirical analysis focuses on the series of actions taken by the subjects that include quote revisions, limit order arrivals, and trades. At first, we report thorough descriptive statistics on the extracted data sets, where we do not assume any particular theory of the market microstructure. Then we show serial dependencies of order flow on the previous event type, the state of the order book, the size of bid-ask spread, and the time intervals. In so doing, we ascertain the significance of the impact of information carried in the order book.
", "doi": "10.7907/5z8b-d658", "publication_date": "1996", "thesis_type": "phd", "thesis_year": "1996" } ]