Nonlinear oil price dynamics: a tale of heterogeneous speculators?

While some of the recent surge of oil prices can be attributed to robust global demand at a time of tight production capacities, commentators occasionally also blame the impact of speculators for part of the price pressure. We propose an empirical oil market model with heterogeneous speculators. Whereas trend-extrapolating chartists may tend to destabilize the market, fundamentalists exercise a stabilizing effect on the price dynamics. Using monthly data for WTI oil prices, our STR-GARCH estimates indicate that oil price cycles may indeed emerge due to the nonlinear interplay between different trader types. --oil price dynamics,endogenous bubbles,STR GARCH model

Principal-agent Incentives, Excess Caution, and Market Inefficiency: Evidence From Utility Regulation

Regulators and firms often use incentive schemes to attract skillful agents and to induce them to put forth effort in pursuit of the principals' goals. Incentive schemes that reward skill and effort, however, may also punish agents for adverse outcomes beyond their control. As a result, such schemes may induce inefficient behavior, as agents try to avoid actions that might make it easier to directly associate a bad outcome with their decisions. In this paper, we study how such caution on the part of individual agents may lead to inefficient market outcomes, focusing on the context of natural gas procurement by regulated public utilities. We posit that a regulated natural gas distribution company may, due to regulatory incentives, engage in excessively cautious behavior by foregoing surplus-increasing gas trades that could be seen ex post as having caused supply curtailments to its customers. We derive testable implications of such behavior and show that the theory is supported empirically in ways that cannot be explained by conventional price risk aversion or other explanations. Furthermore, we demonstrate that the reduction in efficient trade caused by the regulatory mechanism is most severe during periods of relatively high demand and low supply, when the benefits of trade would be greatest.

Heterogeneous Agent Models in Economics and Finance, In: Handbook of Computational Economics II: Agent-Based Computational Economics, edited by Leigh Tesfatsion and Ken Judd , Elsevier, Amsterdam 2006, pp.1109-1186.

This chapter surveys work on dynamic heterogeneous agent models (HAMs) in economics and finance. Emphasis is given to simple models that, at least to some extent, are tractable by analytic methods in combination with computational tools. Most of these models are behavioral models with boundedly rational agents using different heuristics or rule of thumb strategies that may not be perfect, but perform reasonably well. Typically these models are highly nonlinear, e.g. due to evolutionary switching between strategies, and exhibit a wide range of dynamical behavior ranging from a unique stable steady state to complex, chaotic dynamics. Aggregation of simple interactions at the micro level may generate sophisticated structure at the macro level. Simple HAMs can explain important observed stylized facts in financial time series, such as excess volatility, high trading volume, temporary bubbles and trend following, sudden crashes and mean reversion, clustered volatility and fat tails in the returns distribution.

Price Stability and Volatility in Markets with Positive and Negative Expectations Feedback: An Experimental Investigation

The evolution of many economic variables is affected by expectations that economic agents have with respect to the future development of these variables. Here we show, by means of laboratory experiments, that market behavior depends to a large extent on how the realized market price responds to an increase in average price expectations. If it responds by decreasing, as in commodity markets, prices converge quickly to their equilibrium value, confirming the rational expectations hypothesis. If the realized price increases after an increase of average expectations, as is typical for financial markets, large fluctuations in realized prices are likely.

Complexity and Endogenous Instability

The global financial crisis proved the critical impact of the gap between individual rationality and group rationality. This gap is not supposed to arise in a Neoclassical world, but it frequently arises in a world as complex as ours. The paper explores how endogenous instability might arise due to such a gap, and what behavioral rules might help to mitigate its impact.fallacy of composition, empathy, n-person prisoner’s dilemma games, n-person zero-sum games, symmetry, the golden rule.

The evolution and dynamics of stocks on the Johannesburg Securities Exchange and their implications for equity investment management

[No subject] This thesis explores the dynamics of the Johannesburg Stock Exchange returns to understand how they impact stock prices. The introductory chapter renders a brief overview of financial markets in general and the Johannesburg Securities Exchange (JSE) in particular. The second chapter employs the fractal analysis technique, a method for estimating the Hurst exponent, to examine the JSE indices. The results suggest that the JSE is fractal in nature, implying a long-term predictability property. The results also indicate a logical system of variation of the Hurst exponent by firm size, market characteristics and sector grouping. The third chapter investigates the economic and political events that affect different market sectors and how they are implicated in the structural dynamics of the JSE. It provides some insights into the degree of sensitivity of different market sectors to positive and negative news. The findings demonstrate transient episodes of nonlinearity that can be attributed to economic events and the state of the market. Chapter 4 looks at the evolution of risk measurement and the distribution of returns on the JSE. There is evidence of fat tails and that the Student t-distribution is a better fit for the JSE returns than the Normal distribution. The Gaussian based Value-at-Risk model also proved to be an ineffective risk measurement tool under high market volatility. In Chapter 5 simulations are used to investigate how different agent interactions affect market dynamics. The results show that it is possible for traders to switch between trading strategies and this evolutionary switching of strategies is dependent on the state of the market. Chapter 6 shows the extent to which endogeneity affects price formation. To explore this relationship, the Poisson Hawkes model, which combines exogenous influences with self-excited dynamics, is employed. Evidence suggests that the level of endogeneity has been increasing rapidly over the past decade. This implies that there is an increasing influence of internal dynamics on price formation. The findings also demonstrate that market crashes are caused by endogenous dynamics and exogenous shocks merely act as catalysts. Chapter 7 presents the hybrid adaptive intelligent model for financial time series prediction. Given evidence of non-linearity, heterogeneous agents and the fractal nature of the JSE market, neural networks, fuzzy logic and fractal theory are combined, to obtain a hybrid adaptive intelligent model. The proposed system outperformed traditional models

Herd Behavior in Financial Markets

This paper provides an overview of the recent theoretical and empirical research on herd behavior in financial markets. It looks at what precisely is meant by herding, the causes of herd behavior, the success of existing studies in identifying the phenomenon, and the effect that herding has on financial markets. Copyright 2001, International Monetary Fund