Features of Financial Returns Modelling Price Volatility Forecasting Standard Deviations The Accuracy of Autocorrelation Estimates Testing the Random Walk Hypothesis Forecasting Trends in Prices Evidence Against the Efficiency of Futures Markets Valuing Options Appendix: A Computer Program for Modelling Financial Time Series.

Modelling Financial Time Series

Investors systematically deviate from rationality when making financial decisions, yet the mechanisms responsible for these deviations have not been identified. Using event-related fMRI, we examined whether anticipatory neural activity would predict optimal and suboptimal choices in a financial decision-making task. We characterized two types of deviations from the optimal investment strategy of a rational risk- neutral agent as risk-seeking mistakes and risk-aversion mistakes. Nucleus accumbens activation preceded risky choices as well as risk- seeking mistakes, while anterior insula activation preceded riskless choices as well as risk-aversion mistakes. These findings suggest that distinct neural circuits linked to anticipatory affect promote different types of financial choices, and indicate that excessive activation of these circuits may lead to investing mistakes. Thus, consideration of anticipatory neural mechanisms may add predictive power to the rational actor model of economic decision-making.

The Neural Basis of Financial Risk Taking

Are Investors Reluctant to Realize Their Losses

/pdf/neuroimaging-and-neuromodulation-approaches-to-study-eating-3vncwg7or8.pdf

Neuroimaging and neuromodulation approaches to study eating behavior and prevent and treat eating disorders and obesity

In the 1990s, Agent-Based Modeling (ABM) began gaining popularity and represents a departure from the more classical simulation approaches. This departure, its recent development and its increasing application by non-traditional simulation disciplines indicates the need to continuously assess the current state of ABM and identify opportunities for improvement. To begin to satisfy this need, we surveyed and collected data from 279 articles from 92 unique publication outlets in which the authors had constructed and analyzed an agent-based model. From this large data set we establish the current practice of ABM in terms of year of publication, field of study, simulation software used, purpose of the simulation, acceptable validation criteria, validation techniques and complete description of the simulation. Based on the current practice we discuss six improvements needed to advance ABM as an analysis tool. These improvements include the development of ABM specific tools that are independent of software, the development of ABM as an independent discipline with a common language that extends across domains, the establishment of expectations for ABM that match their intended purposes, the requirement of complete descriptions of the simulation so others can independently replicate the results, the requirement that all models be completely validated and the development and application of statistical and non-statistical validation techniques specifically for ABM.

A Survey of Agent-Based Modeling Practices (January 1998 to July 2008)

An important challenge of the financial theory in recent years is to construct more sophisticated models which have consistencies with as many financial stylized facts that cannot be explained by traditional models. Recently, psychological studies on decision making under uncertainty which originate in Kahneman and Tversky's research attract a lot of interest as key factors which figure out the financial stylized facts. These psychological results have been applied to the theory of investor's decision making and financial equilibrium modeling. This paper, following these behavioral financial studies, would like to propose an agent-based equilibrium model with prospect theoretical features of investors. Our goal is to point out a possibility that loss-averse feature of investors explains vast number of financial stylized facts and plays a crucial role in price formations of financial markets. Price process which is endogenously generated through our model has consistencies with, not only the equity premium puzzle and the volatility puzzle, but great kurtosis, asymmetry of return distribution, auto-correlation of return volatility, cross-correlation between return volatility and trading volume. Moreover, by using agent-based simulations, the paper also provides a rigorous explanation from the viewpoint of a lack of market liquidity to the size effect, which means that small-sized stocks enjoy excess returns compared to large-sized stocks.

/pdf/an-agent-based-approach-to-financial-stylized-facts-3bbgy86kze.pdf

An agent-based approach to financial stylized facts

This paper indicates that the human product-preference relationship can, using a product selection task, be predicted to an extent on the basis of changes in the oxygenated hemoglobin concentration in the ventromedial prefrontal cortex and that functional near-infrared spectroscopy allows this prediction despite the shallow depth at which brain information is measured. A Bayesian three-layer perceptron was used as a predictive model. Results of this work help to lay the foundations for the concept of utility in economics and marketing theories from the perspective of neuroscience and have important significance from a practical standpoint as well.

Neural representation of preference relationships.

Predicting investment behavior: An augmented reinforcement learning model

Psychological studies on decision-making under uncertainty, which have been inspired by Kahneman and Tversky's study, have attracted considerable interest in financial research as key factors to solve anomalies that cannot be explained by the traditional models. Recently, we proposed an agent-based prospect theoretical model and demonstrated that the loss-aversion feature of investors is capable of explaining a large number of financial stylized facts. This paper aims to extend the previous work to the field of option pricing. Two important anomalies in the field - the implied volatility smile and the skewness premium - will be analyzed. This study can be considered as an attempt to integrate the behavioral financial theory and the option pricing theory by using the agent-based approach.

An Agent-Based Approach to Option Pricing Anomalies

This paper addresses how communication processes among investors affect stock prices formation, especially emerging predictability of stock prices, in financial markets. An agent based model, called the word of mouth model, is introduced for analyzing the problem. This model provides a simple, but sufficiently versatile, description of informational diffusion process and is successful in making lucidly explanation for the predictability of small sized stocks, which is a stylized fact in financial markets but difficult to resolve by traditional models. Our model also provides a rigorous examination of the under reaction hypothesis to informational shocks.

Tadanobu Misawa

Papers

An agent-based approach to financial stylized facts

Neural representation of preference relationships.

Predicting investment behavior: An augmented reinforcement learning model

An Agent-Based Approach to Option Pricing Anomalies

Word of mouth : an agent-based approach to predictability of stock prices