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The purpose of this paper is to reexamine the value, momentum and size factors employed in the trading strategy originally proposed by Reinganum. Also to enhance our understanding of the impact of these factors over time; to evaluate the effectiveness of these factors; to develop new strategies through a framework presented by Chan et al.; and to investigate the possibility of limiting the number of filters to allow for a larger universe of eligible stocks without hurting performance for both long and short strategies.

Using data from 1970 to 1983, Reinganum developed a profitable trading strategy based on four (or nine) variables to select stocks. First this paper shows why it is increasingly difficult to implement his original trading strategy, then tests his strategy on 23 additional years of data through 2006, and compares it to similar strategies that incorporate straightforward modifications to his filters. The analysis is further extended to a long/short trading strategy similar to that of Chan et al.

Using the Capital Asset Pricing Model, Fama‐French's three‐factor model and Carhart's four‐factor model to evaluate returns following portfolio formation, significant and consistent alphas and portfolio sizes were found.

It is concluded that strategies that mix value, momentum and size filter rules can be developed to produce consistently negative or non‐positive (vs solely positive) alphas.

The paper shows that it is possible to form profitable short‐only and long/short strategies and to increase the number of eligible stocks in the sample despite our modifications to Reinganum's variables. By creating strategies based on mixed filter rules to produce either consistently positive (or negative) risk‐adjusted returns, it can be concluded that slightly different versions of a given filter rule – often much simpler versions – not only enhance return performance but also increase its effectiveness in terms of portfolio size.

The empirical studies have indicated that the information uncertainty is one of the reasons leading to the momentum effect in the stock market. Based on this conclusion, the concept of “information uncertainty” is deepened into the concept hierarchy of “information ambiguity,” the purpose of this paper is to explain the momentum effect in the China’s stock market from information ambiguity.

Based on the information ambiguity, the paper puts forward two hypotheses, portfolio analysis and cross-sectional regression analysis method were used to empirically test these hypothesis based on the weekly data.

The empirical results support the two hypotheses.

Finally, the paper discusses the importance from ambiguity to understand financial anomalies, such as momentum effect.

Since equity markets have a dynamic nature, the purpose of this paper is to investigate the performance of a revision procedure for domestic and international portfolios, and provides an empirical selection strategy for optimal diversification from an American investor's point of view. This paper considers the impact of estimation errors on the optimization processes in financial portfolios.

This paper introduces the concept of portfolio resampling using Monte Carlo method. Statistical inferences methodology is applied to construct the sample acceptance regions and confidence regions for the resampled portfolios needing revision. Tracking error variance minimization (TEVM) problem is used to define the tracking error efficient frontiers (TEEF) referring to Roll (1992). This paper employs a computation method of the periodical after revision return performance level of the dynamic diversification strategies considering the transaction cost.

The main finding is that the global portfolio diversification benefits exist for the domestic investors, in both the mean-variance and tracking error analysis. Through TEEF, the dynamic analysis indicates that domestic dynamic diversification outperforms international major and emerging diversification strategies. Portfolio revision appears to be of no systematic benefit. Depending on the revision of the weights of the assets in the portfolio and the transaction costs, the revision policy can negatively affect the performance of an investment strategy. Considering the transaction costs of portfolios revision, the results of the return performance computation suggest the dominance of the global and the international emerging markets diversification over all other strategies. Finally, an assessment between the return and the cost of the portfolios revision strategy is necessary.

The innovation of this paper is to introduce a new concept of the dynamic portfolio management by considering the transaction costs. This paper investigates the performance of a revision procedure for domestic and international portfolios and provides an empirical selection strategy for optimal diversification. The originality of the idea consists on the application of a new statistical inferences methodology to define portfolios needing revision and the use of the TEVM algorithm to define the tracking error dynamic efficient frontiers.

An event portfolio is a vital part of economic and socio-cultural processes designed around the use of public events in cities and destinations around the world. The purpose of this paper is to suggest a new research framework for comparative studies of diverse event portfolio strategies.

The discussion in this paper is based on a review of the literature and content analysis of event strategies from two New Zealand cities: Auckland and Dunedin.

The paper suggests an empirically tested framework for exploring event portfolios. It entails such dimensions as the event portfolio strategy, event portfolio focus, portfolio objectives and evaluation tools and event portfolio configuration.

This exploratory research provides a comparative analysis of diverse portfolio contexts and offers insights on developing sustainable event strategies while considering diverse local contexts. Core conditions and processes shaping event portfolio design and management are evaluated and strategic factors articulated.

Purpose – This chapter considers the question whether firms can contribute to poverty alleviation through engaging in ‘inclusive business’, thereby linking the macro concept of ‘inclusive growth’ to the micro concept of ‘inclusive business’. A key element in this approach is how to take so-called cross-sector partnerships into account. Partnerships are one way of bundling non-market resources in the internationalisation strategies of multinational enterprises (MNEs).

Design/methodology/approach – This chapter is largely exploratory and primarily aimed at validating a general taxonomy of inclusive business. The creation of a multi-level taxonomy of business models of MNEs towards inclusive business takes into account the role of cross-sector partnership portfolios. The taxonomy makes it possible to come to a first comparison of the strategies of MNEs across national and cultural boundaries, distinguish some patterns and discuss determinants of strategies in which partnerships play a role in the inclusive growth strategies of MNEs.

Findings – A first application of this taxonomy on the business and partnership models adopted by the first 100 Global Fortune companies shows that in general firms still adopt very reactive strategies when integrating inclusive business strategies in their cross-sector partnership portfolios.

Originality/value of chapter – This chapter takes a company-specific level of analysis for the relationship between Foreign Direct Investment and development, which is habitually researched at the macro level of analysis. It documents business models as well as the related cross-sector partnerships. Cross-sector partnership portfolios of companies are not yet researched at any systematic level. They form the meso-level link between micro-level business models and macro-level national development strategies.

The purpose of this paper is to evaluate if there are any momentum patterns in stock and sectoral returns and if they can be explained by the risk factors.

The methodology involves portfolio generation based on company characteristics and short‐term prior return (six to 12 months). The characteristic‐sorted portfolios are then regressed on risk factors using one‐factor (CAPM) and multi‐factor model (Fama French model and four‐factor model involving three Fama French factors and an additional sectoral momentum factor).

The authors find momentum profits in Indian context for prior return portfolios which are stronger for 6‐6 compared to 12‐12 strategies. These momentum profits are larger for some characteristic‐sorted portfolios. Risk models such as CAPM and Fama French model fail to capture momentum profits. In fact, winner portfolios generally comprise large firm and high P/B stocks, thus defying the risk story. Some zero investment momentum‐based trading strategies do provide significant payoffs. The authors also observe momentum profits in sectoral returns. A part of stock momentum profits is captured by sectoral factor, thus implying that it may mainly be an outcome of sectoral momentum.

The findings are pertinent for portfolio managers and investment analysts who are continuously in pursuit of trading strategies that provide extra normal returns. From an academic point of view, the authors suggest that sectoral factor should be used in the multi‐factor framework for explaining asset returns.

The study contributes to the asset pricing and behavioral literature from emerging markets.

This paper investigates how a firm's status moderates the performance of its investment portfolio diversification strategy. We combine the investment diversification literature with the organizational status theory, arguing that status would weaken the benefits of a specialist strategy in their niche industry of investments while strengthening the positive consequences of a generalist strategy across various industries.

We collected our data using the Securities Data Company (SDC) Platinum VentureXpert database. A fixed-effects spline regression analysis for 2,201 US venture capital firms between 1969 and 2016 was used to test for a nonlinear relationship between the level of portfolio diversification and firm performance.

We found that status differences exist in the performance of a specialist strategy but not in that of a generalist strategy. Our results indicate that portfolio specialization in fewer number of industries has little impact on low-status firms, whereas high-status firms suffer significantly lower IPO success rates. In contrast, above-median portfolio diversification was found to be beneficial to both high- and low-status firms.

We specifically identify the impact of status on the performance of investment diversification strategies, an area of research which has received little attention. Further, our findings provide some practical implications for managers making investment decisions between specialist and generalist investment strategies, given their status within the market. Implications for understanding the roles of firm status in portfolio diversification strategies are discussed.

The purpose of this study is to develop an investment strategy designed both to enable student‐managed investment fund (SMIF) students to more quickly build out their portfolio at the beginning of the academic year and to give them some exposure to quantitative approaches to investment management.

This study uses data and software that would be readily available to typical SMIF students to develop both an asset‐allocation model and a security‐selection model that can be described as a long‐flat (or synthetic protective put) equity strategy with a momentum‐based style‐rotation overlay.

Over the time period since the requisite style‐based ETFs began trading, the composite strategy would have outperformed the S&P 500 index during both market downturns and market upturns, providing better than market returns at lower than market levels of risk.

The key innovation of this paper is the development of a quantitative investment strategy tailored specifically to meet both the educational and the portfolio management needs of SMIF students; a secondary innovation is the demonstration of the efficacy of a style‐rotation strategy, in contrast to the more typical sector/industry‐rotation type of strategy.

The purpose of this paper is to present an alternative approach to equity trading that is based on cointegration. If there are long-run equilibria among financial assets, a cointegration-based trading strategy can exploit profitable opportunities by capturing mean-reverting short-run deviations.

First, the author introduces an equity indexing technique to form cointegration tracking portfolios that are able to replicate an index effectively. The author later enhances this tracking methodology in order to construct more complex portfolio-trading strategies that can be approximately market neutral. The author monitors the performance of a wide range of trading strategies under different specifications, and conducts an in-depth sensitivity analysis of the factors that affect the optimal portfolio construction. Several statistical-arbitrage tests are also carried out in order to examine whether the profitability of the cointegration-based trading strategies could indicate a market inefficiency.

The author shows that under certain parameter specifications, an efficient tracking portfolio is able to produce similar patterns in terms of returns and volatility with the market. The author also finds that a successful long-short strategy of two cointegration portfolios can yield an annualized return of more than 8 percent, outperforming the benchmark and also demonstrating insignificant correlation with the market. Even though some cointegration-based pairs-trading strategies can consistently generate significant cumulative profits, yet they do not seem to converge to risk-less arbitrages, and thus the hypothesis of market efficiency cannot be rejected.

The primary contribution of the research lies within the detailed analysis of the factors that affect the tracking-portfolio performance, thus revealing the optimal conditions that can lead to enhanced returns. Results indicate that cointegration can provide the means to successfully reproducing the risk-return profile of a benchmark and to implementing market-neutral strategies with consistent profitability. By testing for statistical arbitrage, the author also provides new evidence regarding the connection between the profit accumulation of cointegration-based pairs-trading strategies and market efficiency.

The relative performance of five popular nonzero-investment strategies, including Size, book-to-market ratios, earnings-to-price (E/P) ratios, cash flow-to-price (CF/P) ratios and dividend-to-price ratios, and their corresponding zero-investment strategies (also known as premiums) are first examined altogether for equally weighted (EW) and value-weighted (VW) methods to check whether a certain strategy (or some strategies) could be recommended to portfolio managers as the best (better) strategy (strategies). The paper aims to discuss these issues.

This paper uses the stochastic dominance (SD) approach, a non-parametric test, to investigate the relative performance among various strategies and help investors search for the best or better strategy (strategies).

The main results show that both the highest E/P and CF/P strategies (and their corresponding premiums) generally produce higher returns than the other three strategies (and their corresponding premiums) through allocating investors’ capital between the risky and risk-free assets for the EW and VW methods, respectively.

This study only examines US stock markets by SD approach, whether the results are consistent with non-US markets still needs further investigation. The findings imply that investors can benefit by investing in the highest E/P or CF/P stocks (or their corresponding premiums) to make more profit or less loss for US stock markets.

First, the SD findings suggest that investors or portfolio managers can allocate their funds between risky and risk-free assets to maximize their profits. Next, the simulation results again prove that the profits of each nonzero-investment or zero-investment strategy for EW portfolios are higher than those of each corresponding strategy for VW portfolios. Finally, the findings imply that portfolio managers or investors can invest in the highest E/P or CF/P stocks (or their corresponding premiums) to make more profit or less loss.

This study first uses an extensive data set (1952-2009) to examine the relative performance of nonzero-investment strategies and their corresponding zero-investment strategies for the five popular indicators altogether for the EW and VW methods with the SD approach for US stock markets. Moreover, the results reveal that the investors or portfolio managers can invest in the highest E/P and/or CF/P portfolios (or their corresponding premiums) to make more profit or less loss.