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The purpose of this study is to investigate the relationship between predictability in return and investment strategy performance. Two measures that characterize investment strategies within a mean‐variance framework, an activity measure and a style measure, are developed and the performance of alternative strategies (e.g. contrarian, momentum, etc.) is examined when risky asset returns are mean reverting.

Returns are assumed to follow a multivariate Ornstein‐Uhlenbeck process, where reversion to a time‐varying mean is governed by an additional variable set, similar to that proposed by Lo and Wang (1995). Depending on its parameterization, this process is capable of producing an autocorrelation pattern consistent with empirical evidence, that is, positive autocorrelation in short‐horizon returns and negative autocorrelation in long‐horizon returns.

The results, for four uninformed investment strategies and assuming that returns are generated by a simple univariate Ornstein‐Uhlenbeck process, show that the unadjusted returns from the contrarian (momentum) strategy are greater than those from the other strategies when the mean reversion parameter, α, is greater than (less than) one. The results are expected, given the relationship between α and the first‐order autocorrelation in returns. The risk level (measured by either the standard deviation of returns or beta) of the contrarian strategy is the lowest at essentially all levels of mean reversion and the risk‐adjusted returns from the contrarian strategy, measured by the both the Sharpe and Treynor ratios, dominate those from the other strategies.

In future research, a number of issues not considered in this study may be investigated. The style measure developed here can be used to determine whether the results obtained hold when an informed, mean‐variance efficient active strategy is employed. In addition, the performance of both the informed and uninformed strategies may be examined under the assumption that the risky return process follows a multivariate Ornstein‐Uhlenbeck process. This work should provide findings that facilitate the separation of fund risk due to dynamic strategies from that due to time‐varying expected returns.

The methodology used here may be easily extended to consider a number of important issues, such as the frequency of portfolio rebalancing, transactions costs, and multiple asset portfolios, that are encountered in practice.

The approach used here provides insight into how predictability affects the relative performance of tactical investment strategies and, thus, may serve as a basis for determining the magnitude and persistence in autocorrelation required for active investment strategies to yield profits significantly different from those of passive strategies. In this sense, this study may have appeal for both academics and investment professionals.

This study aims to investigate whether the zero-investment portfolio strategy generates higher excess returns for all listed companies in the Stock Exchange of Thailand (SET) or ESG100 stocks. The study period is from January 2016 to December 2020, a total of 60 months. The dividend yield is employed for categorizing the stock into value and growth stocks. The strategy of buying value stocks and short-selling growth stocks is then applied. The results show that investing using the zero-investment portfolio strategy can generate higher returns in an investment portfolio that consists of ESG100 stocks than in an investment portfolio that consists of all stocks in the SET. The optimal holding periods for investing in portfolios that consist of stocks in the SET are 6 months, 9 months, and 12 months, and the optimal holding periods for a portfolio that consists of ESG100 stocks is 6 months. To explain excess returns of stocks in the SET, the Fama and French (2015) five-factor model is employed. There is no relation between risk factors and excess returns for the holding period of 6 months and 12 months. However, excess return is found to have a negative relation with the market risk premium factor for a 9-month holding period. The excess returns of ESG100 stocks are also inversely correlated with investment factors for a holding period of 6 months.

Property is a key investment asset class that offers considerable benefits in a mixed-asset portfolio. Previous studies have concluded that property allocation should be within the 10-30 per cent range. However, there seems to be wide variation in theory and practice. Historical Australian superannuation data shows that the level of allocation to property asset class in institutional portfolios has remained constant in recent decades, restricted at 10 per cent or lower. This is seen by many in the property profession as a subjective measure and needs further investigation. The purpose of this paper is to compare the performance of the AU$431 billion industry superannuation funds’ strategic balanced portfolio against ten different passive and active investment strategies.

The analysis used 20 years (1995-2015) of quarterly data covering seven benchmark asset classes, namely: Australian equities, international equities, Australian fixed income, international fixed income, property, cash and alternatives. The 11 different asset allocation models are constructed within the modern portfolio theory framework utilising Australian ten-year bonds as the risk free rate. The Sharpe ratio is used as the key risk-adjusted return performance measure.

The ten different asset allocation models perform as well as the industry fund strategic approach. The empirical results show that there is scope to increase the property allocation level from its current 10-23 per cent. Upon excluding unconstrained strategies, the recommended allocation to property for industry funds is 19 per cent (12 per cent direct and 7 per cent listed). This high allocation is backed by improved risk-adjusted return performance.

The constrained optimal, tactical and dynamic models are limited to asset weight, no short selling and turnover parameters. Other institutional constraints that can be added to the portfolio optimisation problem include transaction costs, taxation, liquidity and tracking error constraints.

The 11 different asset allocation models developed to evaluate the property allocation component in industry superannuation funds portfolio will attract fund managers to explore alternative strategies (passive and active) where risk-adjusted returns can be improved, compared to the common strategic approach with increased allocation to property assets.

The research presents a unique perspective of investigating the optimal allocation to property assets within the context of active investment strategies, such as tactical and dynamic models, whereas previous studies have focused mainly on passive investment strategies. The investigation of these models effectively contributes to the transfer of broader finance and investment market theories and practice to the property discipline.

With the rapid growth of the economy, people have increasingly higher living standards, and although people simply pursued material wealth in the past, they now pay more attention to material quality and safety and environmental protection. This paper discusses the lack of motivation for investing in fresh-keeping technology for agricultural products by individual members of an agricultural supply chain composed of a supplier and a retailer by means of mathematical models and data simulations and discuss the optimal price-invest strategies under different sales models.

First, based on the model of no investment by both sides (NN), this paper considers three models: supplier only (MN), retailer only (NR) and cooperative investment (MR). Then, the authors analyze the influence of consumer price sensitivity and freshness sensitivity on the investment motivation of agricultural products under four models. Subsequently, the paper makes a sensitivity analysis of the optimal strategies under several models, and makes a game analysis of the suppliers and retailers of agricultural products. Finally, we conduct an empirical analysis through specific values.

The results show that (a) when the two sides cooperate, the amount of investment is largest, the freshness of the agricultural products is highest, and the sales volume is greatest; however, when both sides do not invest, the freshness of agricultural products and sales volume are lowest. (b) The price and freshness sensitivity of the consumer have an impact on investment decisions. Greater freshness sensitivity corresponds to a higher investment, higher agricultural product price, greater sales volume, and greater supply chain member income and overall income; however, greater price sensitivity corresponds to a lower investment, lower agricultural product price, lower sales volume, fewer supply chain members and lower overall income. (c) The investment game between the supplier and retailer is not only related to the sensitivity to price and freshness but also to the coordination coefficients of interest. At the same time, the market position of agricultural products should be considered when making decisions. The market share of agricultural products will affect the final game equilibrium and then affect the final benefit of the supply chain and individual members.

These results provide managerial insights for enterprises preparing to invest in agricultural products preservation technology.

At present, the main problem is that member enterprises of agricultural supply chains operate based on their own benefits and are resistant to investing alone to improve the freshness of agricultural products. Instead, they would prefer that other members invest so that they may reap the benefits at no cost. Therefore, the enterprises in each node of the agricultural product supply chain are not motivated enough to invest, and competition and game states are observed among them, and such behavior is definitely not conducive to improving the freshness of agricultural products. However, the current research on agricultural products is more about price, quality and greenness, etc., and there are few studies on agricultural investment. Through the establishment of the model, this paper is expected to provide theoretical suggestions for the supply chain enterprises that plan to invest in agricultural products preservation technology.

The study presents the zero investment strategies based on the pricing impact of real earnings management (REM) on stock returns after taking into account the direction and endogeneity nature of REM.

The authors use standard portfolio methodology and Fama–Macbeth cross-sectional regression to analyze the data for this study. Both upward and downward form of REM has been examined. Accrual earnings management (AEM) has been controlled while examining the association between REM and stock returns.

The findings demonstrate that the REM anomaly exists in the Indian equity market and is consistent under different market conditions and investment horizons. It is robust after controlling for cross-sectional effects and AEM. Our subsequent analysis suggests that a decile-based zero investment portfolio strategy based on REM loadings generates an annual excess return of 17.90%. The presented annual excess return is highest among quantile and mean-based investment strategies. Further, the authors find that REM sorted proposed investment strategies outperform the AEM sorted investment strategies in all spheres.

The findings suggest that investors can form an arbitrage profitable investment strategy by taking a long position in the bottom 10% of negative REM stocks, and a short position in the top 10% of positive REM stocks.

This is the first study that examines the pricing impact of REM on stock returns and provides zero investment strategies by betting against REM.

Foreign direct investment (FDI) from developing economies has increased sharply since the beginning of the 2000s. While most investment flows correspond to firms from large economies, small developing economies have also witnessed the increase of outward investment flows from their domestic companies. The literature on outward FDI (OFDI) from developing economies has focused mainly on large emerging countries, such as China and India. In the case of small developing economies, for which there is scant empirical evidence, firms willing to invest abroad face a different business environment with several barriers such as a small domestic market to achieve economies of scale and a limited supply of specialised resources. In this setting, the purpose of this paper is to examine firm-level strategies and the home-country effects in a small developing economy.

A research case study is conducted through a representative sample of Costa-Rican firms investing abroad. Costa Rica makes a strong case since it stands out among small developing economies investing abroad in terms of both the number of operations and the amount of OFDI.

The main findings are: outward investment is not only for large and mature firms, as medium and small-sized firms are actively investing abroad; most firms pursue a market-seeking strategy; the benefits for the firm and the home country are stronger when companies follow a clear outward investment strategy; and there is a positive relationship between international trade and OFDI.

This paper provides novel empirical evidence to better understand an emerging trend in OFDI: in an increasingly integrated world economy, even SMEs from small developing economies are compelled to internationalise their operations in order to compete successfully.

This study explores company strategies for intangibles. The authors investigate whether it is reasonable for companies to intensify intangibles when the current strategy is not intangible-intensive. The purpose of this paper is to elaborate a theoretical model to describe the strategic decision making in companies.

The authors use the Bellman-equation framework to find the conditions under which a change in strategy for intangibles is reasonable.

The results determine the parameters of returns on intangibles in different strategies, the optimal intangible stock and the influence of external economic shocks. The findings of the study demonstrate that many requirements have to be met to make intangible-intensive strategy beneficial for a company. Moreover negative shocks of crises force a company to postpone a new strategy on intangibles.

This research provides an insight into strategic behavior of companies under uncertainty. The theoretical findings demonstrate under which conditions companies should decide to switch to a strategy more intangible-intensive. This model can be used to empirically test parameters of different investment strategies of companies using structural estimation techniques.

This work contributes to the theory of managerial economics giving closed form solutions for the dynamic optimization of company behavior. The findings also show how this behavior might change when economic crises are faced or expected.

This paper aims to investigate the impact of a firm's marketing strategy on involving customers in new product development. Special attention is to be paid to three facets of a marketing strategy: product differentiation, competitor orientation and brand profiling emphasis.

A survey with quantitative questionnaires was used in the context of relationships between Norwegian suppliers and international buyers.

Two facets of marketing strategy, product differentiation and competitor orientation, positively impact customer involvement. Furthermore, specific investments dedicated to the relationship are also positively related to customer involvement, and customer involvement increases customer profitability.

The study relies on data from the suppliers, and future studies should also include customer data to explore possible effects of the customer's marketing strategy on joint involvement in new product development.

The study shows that managers seeking to involve customers in product development should carefully develop their marketing strategy and build commitment through specific investments.

Previous studies show that firms can benefit from involving customers in new product development. This paper extends knowledge in the field by exploring how different facets of the firm's marketing strategy can increase or decrease the possibilities for involving customers.

The purpose of this paper is to derive an empirical method to identify different types of training strategies of companies based on publicly available company data.

Using a ten‐year panel, the within‐firm retention rate, defined as the average proportion of apprentices staying in a company in relation to all apprenticeship graduates of a company over several years, was analyzed. The within‐firm retention rate is used to identify these companies' training strategies.

It was shown that companies' motivation for apprenticeship training in Germany is not homogeneous: 19 percent of all companies follow a substitution strategy and 44 percent follow an investment strategy. The determinants of the substitution strategy were estimated and, for example, sizeable differences were found between sectors with different skill requirements and between firms' coverage of industrial relations.

The method is well suited to classify substitution‐motivated training firms but it is less precise in identifying the investment motivation. Moreover, very small firms which train only one apprentice need longer panel duration for precise results and therefore the classification results are less precise for very small firms.

The classification can be used to identify determinants of company participation in apprenticeship training and to predict changes in demand for apprentices.

A simple and innovative method of identifying different types of training motivation with publicly available company data was derived, which has so far been possible only with very detailed company‐specific apprenticeship surveys.