We apply methods of quantum mechanics for mathematical modeling of price dynamics at the financial market. The Hamiltonian formalism on the price/price-change phase space describes the classicallike evolution of prices. This classical dynamics of prices is determined by ”hard ” conditions (natural resources, industrial production, services and so on). These conditions are mathematically described by the classical financial potential V (q), where q = (q1,...,qn) is the vector of prices of various shares. But the information exchange and market psychology play important (and sometimes determining) role in price dynamics. We propose to describe such behavioral financial factors by using the pilot wave (Bohmian) model of quantum mechanics. The theory of financial behavioral waves takes into account the market psychology. The real trajectories of prices are determined (through the financial analogue of the second Newton law) by two financial potentials: classical-like V (q) (”hard ” market conditions) and quantum-like U(q) (behavioral market conditions).

In this chapter we describe a stock market simulation in which stock market participants use genetic algorithms to gradually improve their trading strategies over time. A variety of experiments show that, under certain conditions, some market participants can make consistent profits over an extended period of time, a finding that might explain the success of some real-world money managers. These experiments suggest a four parameter model of market participants. Each participant can be described along four dimensions: information set, constraint set, algorithm set, and model set. The information set captures what data the participant has access to (e.g., the participant has access to all historical price data). The constraint set describes under what restrictions the participant operates (e.g., the participant can borrow money at 1% above the prime rate). The algorithm set indicates what programs the participant can use (e.g., the participant is restricted to hill-climbing optimization ...

Neural networks are one of the most widely used artificial intelligence methods for financial time series analysis. In this paper we describe the standard application of neural networks and suggest that it has two shortcomings. First, backpropagation search takes place in sum of squared errors space instead of risk-adjusted return space. Second, the standard neural network has difficulty ignoring noise and focusing in on discoverable regularities. Both problems are illustrated with simple examples. We suggest ways of overcoming these problems. 1 Introduction Ever since McCulloch and Pitts [8] published their landmark paper describing a neural calculus, researchers have explored how biologically inspired networks might be employed to solve a wide class of problems. In recent years, Wall Street, in its never ending search for new ways to beat the market, has turned to neural networks as a possible answer. The attention focused on neural networks for financial time series analysis stems ...

A widely held belief in financial economics suggests that stock prices always adequately reflect all available information. Price movements away from fundamentals are assumed to occur only infrequently, if at all. "False" prices are supposed to be corrected by the counter-actions of "rational" investors reestablishing equilibrium. However, empirical evidence of widespread irrationality among investors as well as theoretical insights into the properties of complex systems suggest that this view is too static. In fact, it can be shown that under certain conditions dynamic disequilibria have a considerable probability of being "locked in".

for their numerous and insightful remarks on earlier drafts of this Report. The authors thank professor Michael J. Artis for his excellent assistance with the English language version of the Report. The Report was submitted for publishing in March 2004. Design: Oliwka s.c. Printed by:

The tension in the air is as palpable as a high-stakes prize fight. In one corner, the finance professors — the proponents of stock market efficiency — argue that investors cannot outperform the market over time. In the opposing corner, the practitioners

Levy Institute scholars and conference participants. The purpose of the series is to disseminate ideas to and elicit comments from academics and professionals. The Levy Economics Institute of Bard College, founded in 1986, is a nonprofit, nonpartisan, independently funded research organization devoted to public service. Through scholarship and economic research it generates viable, effective public policy responses to important economic problems that profoundly affect the quality of life in the United States and abroad.

Levy Institute scholars and conference participants. The purpose of the series is to disseminate ideas to and elicit comments from academics and professionals. The Levy Economics Institute of Bard College, founded in 1986, is a nonprofit, nonpartisan, independently funded research organization devoted to public service. Through scholarship and economic research it generates viable, effective public policy responses to important economic problems that profoundly affect the quality of life in the United States and abroad.

currency transactions has the unique distinction of having attracted the ire of a power no less than the U.S. Congress. Introduced by Bob Dole and three other politicians, the "Prohibition on United Nations Taxation Act of 1996 " aimed at preventing UN officials and agencies from developing or promoting the Tobin tax or any other international taxation scheme under a different name. 2 Leaving aside the irony of a country with the greatest arrears in its dues to the UN, telling the international body what it should and should not do, what made the Tobin tax such an unwelcome proposal to the U.S. Congress was, as Raffer (1998) argues, its potential to bolster national autonomy and distribute the tax burden more equally around the globe. Both ran "counter to current tide of liberalization, globalization, and tax reductions for the well-off " (p. 530). Tobin's main reason for proposing his tax was of course more technical in nature. His main concern was to curb currency speculation, which he thought was responsible for the much greater frequency of exchange rate crises around the world since the trend of capital liberalization took hold. In much of the academic criticism on the Tobin tax, the debate concentrated on its feasibility and the "distorting " effects it would have as any tax does on private decisions. 3 Some also cautioned against its potential to detract attention from discussions of more far reaching solutions to the problem of international financial volatility (Taylor and Eatwell 2000, p. 93). But, few if any other than Davidson (1997, 1998) have questioned- on Keynesian grounds- that in theory such a transaction tax would dampen financial volatility and curb

I would like to thank Amit Bhaduri for his helpful comments on an earlier draft of this paper. The Levy Economics Institute Working Paper Collection presents research in progress by Levy Institute scholars and conference participants. The purpose of the series is to disseminate ideas to and elicit comments from academics and professionals. The Levy Economics Institute of Bard College, founded in 1986, is a nonprofit, nonpartisan, independently funded research organization devoted to public service. Through scholarship and economic research it generates viable, effective public policy responses to important economic problems that profoundly affect the quality of life in the United States and abroad.