We examine the optimal trading strategy for an investment fund which wishes to maintain assets two assets in fixed proportions, e.g. 60/40 in stocks and bonds. Transactions costs are assumed to be proportional to the amount of each asset traded. We show that the optimal policy specifies a band about the target stock proportion. As long as the actual stock/bond ratio remains inside this band, no...

While a large number of studies have been reported in the literature with reference to the use of Regression model and Artificial Neural Network (ANN) models in predicting stock prices in western countries, the Chinese stock market is much less studied. Note that the latter is growing rapidly, will overtake USA one in 20 30 years time and thus becomes a very important place for investors worldw...

The last decade has witnessed a dramatic increase in both the number and the market share of screen-based trading systems. Electronic trading systems do offer lower operating costs and the possibility of remote access to the market. On the other hand, arguments based on the anonymity of electronic trading systems suggest that adverse selection may be a more severe problem and that, therefore, b...

This study examines various measures of trading costs estimated from highfrequency data, the extent to which these measures can be estimated from daily data, and finally the relation between the daily-based proxies and stock returns (where trading cost is viewed as a characteristic). The high-frequency estimates of trading cost achieve partial agreement. Posted spreads and effective costs are h...

We are the first to evaluate the impact of the trading floor closure on the corresponding efficiency of the stock price formation process on the Toronto Stock Exchange (TSX). Utilizing short-horizon return predictability as an inverse indicator of market efficiency, we demonstrate that while the switch to all electronic trading resulted in higher trading activity and lower trading costs, the in...

This work examines the predictive power of public data by aggregating information from multiple online sources. Our sources include microblogging sites like Twitter, online message boards like Yahoo! Finance, and traditional news articles. The subject of prediction are daily stock price movements from Standard & Poor’s 500 index (S&P 500) during a period from June 2011 to November 2011. To fore...

Stock trading plays an important role for supporting profitable stock investment. In particular, more and more data mining-based technical trading rules have been developed and used in stock trading systems to assist investors with their smart trading decisions. However, many mined trading rules are of no interest to traders and brokers because they are discovered based on statistical significa...

The purpose of this study is to investigate the determinants of stock investors’ intention towards using mobile stock trading. Based on a modified UTAUT (unified theory of acceptance and use of technology) with risk perceptions, a comprehensive research model was proposed. An empirical survey with a valid sample of 329 stock investors was conducted in Taiwan to test the research model. The anal...

This work underlies the poster presented at the XVIII Workshop on Quantitative Finance (QFW2017) in Milano on January 25-27, 2017. We seek a discussion about the most suitable feedback control structure for stock trading under the consideration of proportional transaction costs. Suitability refers to robustness and performance capability. Both are tested by considering different one-step ahead ...

Numerous studies in the finance literature have investigated technical analysis to determine its validity as an investment tool. This study is an attempt to explore whether some forms of technical analysis can predict stock price movement and make excess profits based on certain trading rules in markets with different efficiency level. To avoid using arbitrarily selected 26 trading rules as did...