in this study, trading patterns and constituents of trading performances of individual and institutional investors have been investigated in a weekly manner, using an auto regressive model and a grinblatt & titman portfolio performance measure spanning 2008-2012. the results show that while individual investors have a herding behavior, institutional investors take contrarian trading strategies....

The paper presents results of computer-assisted portfolio management simulation based on using a DEACascor mathematical model. The model uses the Data Envelopment Analysis (DEA) ratio as a neuron with memory and combines it with Cascade Correlation Neural Network (Cascor) to forecast stock prices. The model is designed for using in high-frequency stock trading. It utilizes ability of DEA to con...

This paper analyzes the relations among firm-level stock option portfolio incentives, investment, and firm value based on a sample of Finnish firms during the time period 1987 – 2000. Utilizing exact and complete information regarding stock option portfolio characteristics, we find some evidence that firm investment is increasing in the incentives to increase stock price (delta) and risk (vega)...

Identification of useful patterns in price movement of a stock in stock market needs tremendous analytical skills and effort. Careful analysis of the available technical indicators will help finding the right timing of trading of a stock to maximize the gains. To help investors manage their portfolios, we propose a tool for clustering and classification of stock market data using an unsupervise...

This article examines the performance of four life-cycle portfolio allocation strategies through stochastic simulation based on observed U.S. asset returns during 1926-2008. Annual worker contributions to retirement savings accounts are based on the actual lifetime earnings histories maintained by the Social Security Administration for 12,871 workers born during 1915-1942. Each strategy's perfo...

Algorithm portfolios represent a strategy of composing multiple heuristic algorithms, each suited to a different class of problems, within a single general solver that will choose the best suited algorithm for each input. This approach recently gained popularity especially for solving combinatoric problems, but optimization applications are still emerging. The COCO platform [6] [5] of the BBOB ...

portfolio selection is considered a critically significant decision, firms have to make. as such, much research has been focused on the selection of a portfolio with a controlled level of risk and high expected return. this paper uses a new definition of risk for portfolio selection whereby risk taking is taken as a curve instead of a specific value. in this paper, a genetic algorithm is presen...

The analysis of risk-return tradeoffs and their practical applications to portfolio analysis paved the way for Modern Portfolio Theory (MPT), which won Harry Markowitz a 1992 Nobel Prize in Economics. A typical approach in measuring a portfolio's expected return is based on the historical returns of the assets included in a portfolio. On the other hand, portfolio risk is usually measured using ...

On June 29, 2010, Taiwan signed an Economic Cooperation Framework Agreement (ECFA) with China as a major step to open markets between Taiwan and China. Thus, the ECFA will contribute by creating a closer relationship between China and Taiwan through economic and market interactions. Co-movements of the world’s national financial market indexes are a popular research topic in the finance literat...

In this paper, a hybrid fuzzy-neural system for Egyptian stock price prediction is proposed. In order to help in choosing the right stock mixture with the highest profit within a certain risk factor, a hybrid fuzzy-neural system is applied to significantly save effort and time of portfolio managers and increase the individual investors’ local market understanding by providing buy and sell signa...