for helpful comments. We would also like to thank Jeremy Evnine and the discount brokerage house which provided the data necessary for this study. Financial support from the Nasdaq Foundation and the American Association of Individual Investors is gratefully acknowledged.

GARCH-type models have been highly developed since Engle [1982] presented ARCH process 30 years ago. Different kinds of GARCH-type models are applicable to different kinds of research purposes. As documented by many literatures that short-memory processes with level shifts will exhibit properties that make standard tools conclude long-memory is present. Therefore, in this paper, we want to fore...

1. ABSTRACT In this paper I discuss the possibility of replacement of human traders in the world’s stock markets, to be replaced with computer based agents. During a recent trading test competition, carried out by Jeffrey Kephart at IBM's research centre in New York between humans and computer agents, it was found that the latter made on average five to seven percent more profit [Kephart et al....

In this chapter we use particle filtering methods to estimate volatility and examine volatility dynamics for three financial time series during the early part of the current credit crisis. We compare estimates from a pure stochastic volatility model, a stochastic volatility model with jumps and a Garch model to each other and to the market volatilities implied by actual option prices. Our three...

Until its sales of a product materialize, a firm is a “pre-producer” in the market for that product. That firm may may be a new start-up, or it may already sell other products. Firms that do not succeed in generating sales eventually become discouraged and move on to other activities. When this fate befalls a lot of firms, as it recently did in several IT-related businesses, the indistry experi...

We apply a recently developed wavelet based approach to characterize the correlation and scaling properties of non-stationary financial time series. This approach is local in nature and it makes use of wavelets from the Daubechies family for detrending purpose. The built-in variable windows in wavelet transform makes this procedure well suited for the non-stationary data. We analyze daily price...

Stock market analysis is one of the most important and hard problems in finance analysis field. Recently, the usage of intelligent systems for stock market prediction has been widely established. In this paper, a PSO based selective neural network ensemble (PSOSEN) algorithm is proposed, which is used for the Nasdaq-100 index of Nasdaq Stock Market and the S&P CNX NIFTY stock index analysis. In...

This paper considers nonlinear dynamics of quotes issued by Nasdaq dealers. We study the top two ECN’s (Island and Instinet) and the three most active market makers for a sample of twenty stocks traded at Nasdaq. We develop a model that extends the standard linear vector error correction model for price discovery in three different ways. First, quote adjustments are set relative to the inside q...

The Nasdaq fell another ≈ 10% on Friday the 14’th of April 2000 signaling the end of a remarkable speculative high-tech bubble starting in spring 1997. The closing of the Nasdaq at 3321 corresponds to a total loss of over 35% since its all-time high of 5133 on the 10’th of March 2000. Similarities to the speculative bubble preceding the infamous crash of October 1929 are quite striking: The bel...