and Company LLC (GMO) uses mixed-integer-programming (MIP) methods to construct portfolios that are close (in terms of sector and security exposure) to target portfolios, have the same liquidity, turnover, and expected return as the target portfolios, control frictional costs, and do so with fewer distinct stocks and with fewer transactions. It also applies MIP methods to portfolios consisting ...

A developmental co-evolutionary genetic programming approach (PAM DGP) is compared to a standard linear genetic programming (LGP) implementation for trading of stocks in the technology sector. Both interday and intraday data for these stocks were analyzed, where both implementations were found to be impressively robust to market fluctuations while reacting efficiently to opportunities for profi...

In this paper, we develop and test a theoretical model of multi-market trading to explain the differences in the foreign share of trading volume of internationally cross-listed stocks. The model derives an equilibrium which predicts that, under fairly general conditions, the distribution of trading volume across exchanges competing for order flow is related to the correlation of the cross-liste...

Confluence occurs when different trading filters generate signals that point to the same directional move. Using regression analysis, this paper investigates confluence trading signals associated with number preference and price exhaustion, for a sample of Australian stocks. The results show that certain price levels tend to act as psychological barriers, and that price exhaustion signals are a...

We model the distribution of daily stock trading volume using the power law and document a new phenomenon. The power law exponent systematically increases with time suggesting that trading is becoming increasingly concentrated in a subset of stocks. © 2007 Elsevier B.V. All rights reserved.

We used the Support Vector Machines in a classification approach to 'beat the market'. Given the fundamental accounting and price information of stocks trading on the Australian Stock Exchange, we attempt to use SVM to identify stocks that are likely to outperform the market by having exceptional returns. The equally weighted portfolio formed by the stocks selected by SVM has a total return of ...

We study the trading of individual investors using transaction data and identifying buyeror seller-initiated trades. We document four results: (1) Small trade order imbalance correlates well with order imbalance based on trades from retail brokers. (2) Individual investors herd. (3) When measured annually, small trade order imbalance forecasts future returns; stocks heavily bought underperform ...

a r t i c l e i n f o We examine the role of liquidity risk, both as a stock characteristic as well as systematic liquidity risk, in UK mutual fund performance for the first time. We find that on average UK mutual funds are tilted towards liquid stocks (except for small stock funds as might be expected) but that, counter-intuitively, liquidity rather than illiquidity, as a stock characteristic ...

Chart patterns and indicators are popular technical tools for making investment decisions. This article presents a trading strategy combining price movement patterns, candlestick chart patterns, and trading indicators, including Moving Average, Exponential Moving Average, Bollinger Bands, On Balance Volume, Relative Strength Index, Moving Average Convergence Divergence, and Stochastic Oscillato...

We show that a mutual fund’s stock selection skill can be decomposed into additional components that include liquidity-absorbing impatient trading and liquidity provision. We find that past performance predicts future performance better among funds trading in stocks affected more by information events: Past winners earn a risk-adjusted after-fee excess return of 35 basis points per month in the...