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This paper aims to investigate a relatively new anomaly of investment growth and revisits well-known anomalies of size and value. It aims to answer two main research questions. First, can covariance risks (i.e. factor loadings) be excluded from being determining variables that drive return premiums and explain stock returns? Second, from a behavioral finance standpoint, the authors examine whether using firm characteristics is a more practical and accessible approach and also meets the necessary and sufficient conditions to analyze stock returns.

The authors create the investment-growth-based factor (LMH) which is defined as the return difference between low and high investment growth portfolios. The authors then incorporate the LMH factor along with other characteristic-based factors and their loadings into characteristic-balanced portfolio and three-factor model tests.

The authors find that covariance risks on investment growth, size and value are not necessary as determining variables. Instead, they find that behavioral-related firm characteristics of investment growth, size and value are necessary and sufficient as determinants of return premiums and stock returns.

The results have practical and useful implications for investors in their stock portfolio analysis and selection because firm characteristics are relatively more available than covariance risks that need estimation and typically contain measurement errors.

The paper has practical value to investors in their stock portfolio analysis and selection. Methodologically, in contrast to prior studies that do not directly use the investment growth to control for portfolio characteristics, the use of the newly created LMH factor and its loadings allows us to directly and properly test if the investment growth anomaly is related to the investment growth characteristic that is hypothesized to drive return premiums and determine stock returns from behavioral finance perspectives.

The purpose of this paper is to investigate who trade actively in the Malaysian stock market and what determines investors’ active trading decisions.

Using a cross-sectional survey on individual investors, the study identifies active and inactive investors and then, investigates active trading by estimating binary logistic regression.

Active investors in Malaysia are more likely to be male, working in non-finance-related sectors and are more experienced. The likelihood of active trading increases with the number of hours spent on researching investment, very short-term favorable unemployment and economic growth expectations (three-month) and past investment outcomes, whereas this probability decreases with higher cognitive ability and short-term unemployment expectations.

The results imply that regulators may focus on certain groups of investors, based on the result of this study, and provide them training to reduce inactivity in this market. As active trading in response to past investment outcomes indicate rational response, regulators therefore may inform investors to learn about their ability and skill from their prior investment outcome, through educational program. Educational program may also include the role of macroeconomic indicators in active investing decisions.

This is the first study to combine a list of demographic and socio-economic characteristics, investment characteristics, macroeconomic expectations and past investment outcomes together to explain the likelihood of active trading.

Considering the unique characteristics of equity crowdfunding platforms including the removal of stringent structural barriers (e.g. lack of co-location), high visibility and traceability of investor characteristics, large pool of available investors and simplified transaction process, the authors aim to examine how the two most prevalent mechanisms (i.e. homophily and repeated ties) unfold in this context by incorporating the contextual characteristics. The authors theorize an inverted U-shaped relationship between leader-backer similarity and the likelihood of co-investment in a syndicate on equity crowdfunding platforms. In addition, a leader–backer dyad is more likely to form new syndicates if the students have more prior co-investment ties.

The empirical study is based on data from the AngelList syndicate platform and a linear probability model (LPM) with fixed effects is adopted to estimate the syndicate formation.

The authors find that the similarity between a leader and a backer has an inverted U-shaped relationship with the leader and backer's likelihood of co-investment in a syndicate, which is different from the dominant homophily-based tie formation in venture capital (VC) syndicates and other digital platform contexts. Although equity crowdfunding platforms encourage the possibility of exploring new partners, investors are more likely to co-invest with others who have stronger prior ties.

This research theoretically contributes to the scant literature of equity crowdfunding syndicates by contextualizing two most prevalent mechanisms (i.e. homophily and repeated ties) driving tie formation in VC syndicates and digital platforms.

Similar to real estate, infrastructure investments are regarded as providing a good inflation hedge and inflation protection. However, the empirical literature on infrastructure and inflation is scarce. Therefore, the purpose of this paper is to investigate the short- and long-term inflation-hedging characteristics, as well as the inflation protection associated with infrastructure and real estate assets.

Based on a unique data set for direct infrastructure performance, a listed infrastructure index, common direct and listed real estate indices, the authors test for short- and long-term inflation-hedging characteristics of these assets in the USA from 1991-2013. The authors employ the traditional Fama and Schwert (1977) framework, as well as Engle and Granger (1987) co-integration tests. Granger causality tests are further conducted, so as to gain insight into the short-run dynamics. Finally, shortfall risk measures are applied to investigate the inflation protection characteristics of the different assets over increasingly long investment horizons.

The empirical results indicate that in the short run, only direct infrastructure provides a partial hedge against inflation. However, co-integration tests suggest that all series have a long-run co-movement with inflation, implying a long-term hedge. The causality tests reveal reverse unidirectional causality – while real estate asset returns are Granger-caused by inflation, infrastructure asset returns seem to cause inflation. These findings further confirm that both assets represent a distinct asset class. Ultimately, direct infrastructure investments exhibit the most desirable inflation protection characteristics among the set of assets.

This study only presents results based on a composite direct infrastructure index, as no sub-indices for sub-sectors are available yet.

Investors seeking assets that are sensitive to inflation and mitigate inflation risk should consider direct infrastructure investments in their asset allocation strategy.

This is the first study to examine the ability of direct infrastructure to assess inflation risk.

A unit trust is a vehicle by which a large number of investors can pool their varying amounts of money into one trust fund. In return they are issued with “units” in proportion to the fraction of the fund that they own. The fund is then invested, by the managers, on the Stock Exchange. Investors buy units from the managers at what is known as the offer price and can sell them back to the managers at what is known as the bid price. These purchases and sales can be made through direct contact with the managers or via an agent such as a bank, stockbroker, accountant or solicitor.

The purpose of this paper is to decompose and measure the microstructure of property investment returns for Tokyo’s residential property markets in as much detail as possible in comparison with office market.

Using enterprise value data for property investment trust companies composed of share prices available on capital markets, this study proposed a method of estimating property investment returns corresponding to changes in capital markets, and clarified the distortion in capitalization rate that are formed based on property appraisal prices.

The results for residential property showed that as building floor space increased, income and price increased while the discount rate decreased. In particular, a higher return could be obtained from office property than residential property by investing in larger-scale properties. Building age lowered asset price and income for both residential and office property, especially for residential property.

In Japan, investors believe that investment returns are high for properties close to the city centre, relatively new properties and those with large design or floor space. Therefore, this study first measured how asset prices, income and asset price–income ratios that comprise property investment returns change based on differences in these property characteristics. Second, the reliability/distortion of information that can be observed on the property investment market was measured. Furthermore, there was a significant divergence between discount rates and risk premiums formed by asset or space markets versus capital markets.

The differences of discount rate and risk premium formed by asset markets versus capital markets indicate that appraisal prices have biases. Thus, when it comes to property investment decisions, it is essential to make active use not just of property investment returns based on appraisal prices formed by asset markets but also information formed by capital markets.

A greater difference was generated in a shrinking market, suggesting that analysing property returns estimated on asset market information alone could lead to erroneous investment decisions.

This research is the first to use the enterprise value data from real estate investment trust companies composed of share prices available on capital markets for calculating discount rate and risk premium in property market.

The purpose of this paper is to test the hypothesis that investment decision making in the UK direct property market does not conform to the assumption of economic rationality underpinning portfolio theory.

The developing behavioural real estate paradigm is used to challenge the idea that investor “man” is able to perform with economic rationality, specifically with reference to the analysis of the spatial dispersion of the entire UK “investible stock” and “investible locations” against observed spatial patterns of institutional investment. Location quotients are derived, combining different data sets.

Considerably greater variation in institutional property holdings is found across the UK than would be expected given the economic and stock characteristics of local areas. This appears to provide evidence of irrationality (in the strict traditional economic sense) in the behaviour of institutional investors, with possible herding underpinning levels of investment that cannot be explained otherwise.

Over time a lack of distinction has developed between the cause and effect of comparatively low levels of development and institutional property investment across the regions. A critical examination of decision making and behaviour in practice could break this cycle, and could in turn promote regional economic growth.

The entire “population” of observations is used to demonstrate the relationships between economic theory and investor performance exploring, for the first time, stock and local area characteristics.

The purpose of this paper is to define an approach useful to evaluate real estate funds on the specific characteristics of the Italian market and on the basis of international best practices.

The first step is to identify specific factors and portfolio construction choices that could impact directly on the variability of inflows and outflows related to real estate fund. The analysis is realised constructing standard measures of financial and downside risk and identifying a panel model that allows to explain risk measure dynamics on the basis of some investments and portfolio characteristics. Results obtained are tested with an out of sample procedure in order to evaluate the type of misclassification risk related to each model. The second step is to evaluate the impact of debt policy on the risk assumed by a real estate funds. After an analysis of debt sustainability for each real estate unit on the basis of deadlines and amount of flows related to each investment, the study proposed looks directly at the debt policy of listed real estate funds: the analysis is aimed to evaluate the relationship between leverage choice and inflows/outflows variability and the coherence between declared results and expected results for high‐leveraged funds respect to the others.

The results stemming from the use of a real estate database supplied by Beni Stabili Gestioni Società di Gestione del Risparmio showed that the portfolio's construction choice impacts strongly on the variability of results of a real estate fund. The strict linkage between characteristics of debt and type of property makes difficult to evaluate the additional risk related to debt choice but on the basis of Italian market data are possible to point out the higher difficulties for high‐leveraged funds to achieve the result communicated to the market (the so‐called target IRR).

The value added of the paper is to study the relevance of specific risk factors respect to portfolio's ones in the evaluation of risk exposure for a real estate portfolio and the impact of the leverage choices on the variability of inflows and outflows related to the real estate investments.

The purpose of this paper is to indicate trade characteristics of Foreign direct investment (FDI) inflows in China and examine the dynamic interaction between FDI inflows and China’s international trade through empirical analysis.

At first, this paper builds the probability distribution model (Poisson and negative binomial (NB)) to capture the characteristics of spatial distribution of all kinds of FDI firms in Chinese cities and provinces based on count data, so as to indicate the potentials for further introducing FDI inflows in China; Second, this paper investigates the effects of trade on FDI firms inflows based on probability regress model (Binary Logit, Tobit, NB, Poisson, zero inflated negative binomial) and shows how international trade accelerates the different kinds of FDI firms to agglomerate in Eastern, Middle and Western region by the endowments of factors; third, this paper empirically examines the magnitude and characteristics of trade effects generated by FDI inflows by building dynamic panel model based on continuous data.

First, statistical tests of probability distribution model based on count data show that there are characteristics of spatial agglomeration of FDI firms such as manufacture firm, R & D firm, managing and marketing firm and total sectors, which obey NB distribution as whole; Second, this study indicate that FDI inflows have strong positive effects on the international trade in China’s provinces and on China’s regional trade, and that most of foreign firms in China are export oriented being strongly characterized as labor-intensive industries, especially, contributions of FDI to imports are greater than the contributions of FDI to exports in China’s Middle and Western trade, and the growth of FDI trade in China’s trade volume has been strong over the past years; third, the empirical results of models based on count data and continuous data indicate that FDI inflows have significantly positive relationship with international trade, that is, the relationship between FDI and international trade in the case of China is the characteristics with complement and imports substituting relationship.

Because of mixed data set for FDI inflows of processing and assembling trade and production-oriented FDI, efficiency-seeking and knowledge or technology – intensive FDI inflows in the past 36 years, the paper only investigate characteristics of FDI inflows in China before the turning point of financial crisis, but it is important for capturing the whole picture of trade characteristics of FDI inflows in China.

The derived quantitative results imply that there are still greater potentials for further introducing FDI inflows in China, and decision-maker should make policy of introducing FDI inflows which are favorable to supporting innovative activities and economic agglomeration, and preferably encourage efficiency-seeking and export-oriented FDI inflows so as enhance quality and efficiency of economic growth, which are also helpful to accelerate upgrade of Chinese industry and gradually shorten gap of growth among Eastern, Middle and Western region.

FDI inflows in China not only stimulate the remarkable growth of bilateral trade between host country and home country, but also promote the growth of international trade between China and the rest of the world. Thus, policies of bilateral or multilateral free-trade and investment area should be encouraged, which will be also favorable to promote the growth and welfare in all the regions.

This paper demonstrates that spatial distributions of FDI firms in Chinese cities and provinces obey NB probability distribution pattern, and puts forward the methodology of model based on count data and continuous data. Besides, this paper quantitatively indicates trade characteristics of FDI inflows in China as well as the dynamic interaction between FDI inflows and China’s international trade.

The purpose of this paper is to shed light on the changing pattern and characteristics of international financial flows in the emerging entrepreneurial ecosystems of Sub-Saharan Africa (SSA), provide a novel taxonomy to classify and analyze them, and discuss how such investments contribute to competence building and sustainable development.

In an exploratory study, the authors analyze the characteristics of international venture capital investors and the start-ups receiving funding in Kenya and map their interaction. The authors proceed by developing a novel taxonomy, classifying investors according to their main rationales (for-profit-for-impact), and start-ups according to the locus of needs and markets addressed by the start-up (local-global) and the locus of the start-ups capacity and knowledge (local-global).

The authors observe a new type of mainly western investors who support innovative ideas in SSA by identifying and investing in domestically developed technical innovations with the potential to address global market needs. The authors find such innovations to be mainly developed at the intersect of global and local knowledge.

The authors shed light on the – up to now – under-researched emerging phenomenon of international high-tech investments in SSA, and develop a novel taxonomy of technology investments in low-income countries, guiding further research on the conditions, impact, practical, and policy implications of this new form of finance flows.