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The widespread practice of dollar-cost averaging (DCA) amongst the investing public, has puzzled most financial economists, ever since Constantinides [2] demonstrated the dynamic inefficiency of this strategy under very general conditions. This enduring phenomena has forced researchers, such as Statman [12], to suggest behavioral explanations for DCA's popularity, predicated on the prospect theory of Kahneman and Tversky [4].

In this paper we reexamine the payoff structure of DCA via continuous-time financial mathematics and then ask the question: Is it possible to reconcile the theory and practice of dollar-cost averaging?

To answer this question, we take a slightly different approach to the issue by using the tools of stochastic calculus and Brownian bridges. We demonstrate that engaging in a dollar-cost averaging strategy is akin to purchasing a zero strike arithmetic Asian option on the underlying security. In other words, people who engage in dollar-cost averaging are implicitly purchasing a path-dependent contingent claim. We then prove that the expected return from this exotic option — i.e. the DCA strategy — conditional on knowing the final value of the security will uniformly exceed the return from the underlying security for all sufficiently large volatilities.

This leads us to argue that investors may be dollar-cost averaging because they have "target prices" for the underlying asset price. The strategy of dollar-cost averaging would then exceed the returns from lump-sum investing, based on their subjective conditional expectation. In fact, the more volatile the underlying security, the greater is the benefit to dollar-cost averaging — conditional on knowing the final value — which is consistent with common practice.

This article reveals the current status of biotechnology industry in Taiwan.

Biogen Idec's Aducanumab (BIIB037) shown to reduce brain amyloid plaque levels slow cognitive decline in patients with prodromal or mild Alzheimer's disease.

Johnson Matthey recognized in 2015 CMO Leaderships Awards.

Heraeus enters agreement to acquire NeoMetrics.

AstraZeneca and Daiichi Sankyo to jointly commercialize MOVANTIK in the US.

AbbVie and C2N enter worldwide license agreement for Alzheimer's disease therapy.

Menara Landmark Medical Suites expands healthcare and medical offerings in Johor Bahru.

Sigma-Aldrich® expands customer-centric model with investments in Singapore.

NTU setting up a new $30 million institute to boost Singapore's efforts in tackling human disease.

This paper presents a multicriteria approach to the evaluation of information technology (IT) projects. In this paper, we present the steps of the model to evaluate IT project investments, including the identification of IT project investment, the construction of IT investment or IT project categories, the assessment of the importance of criteria and establishes final recommendations. The methodology proposes a framework, based on multicriteria analysis, that describes the importance of classifying and prioritizing IT projects investments before taking decisions. Decisions on IT investments should consider the different characteristics of each IT project and in each case evaluate the tangible and intangible benefits. However, measurements of intangible benefits are usually subjective and require a formal procedure to minimize the difficulty and consequence of this. Thus, the model enables us to handle this subjectiveness and it is exemplified with a numerical illustration, the data being drawn from a preview study.

This study discusses the role of core and symbolic capabilities during due-diligence processes when investing in companies in turbulent fields such as the biotechnology industry. The results indicate that investors' evaluations are hierarchical and are based on two premises. First, investors look for core capabilities — the characteristics that signal the potential for future success. They then search for symbolic elements, such as reputation, to confirm their decisions. The study expands earlier models of investors' evaluation processes. It also offers new insights for entrepreneurs of biotechnology firms.

Transitioning to a low-carbon economy will require significant investment to transform energy systems, alter the built environment and adapt infrastructure. A strategy to finance this investment is needed if the limit of a 2°C increase in global mean temperatures is to be respected. Also, high-income countries have pledged to pay the "agreed full incremental costs" of climate-change mitigation by developing countries, which are not necessarily the same as incremental investment costs. Building on simulations using Integrated Assessment Models and historical evidence, this paper explores some of the issues posed by this dual financing challenge. We discuss the "fiscal self-reliance" of the energy sector, finding that carbon pricing would generate sufficient fiscal revenues within each region to finance total investment in energy supply. Even when allowing for trade in emission permits, regional carbon fiscal revenues should still suffice to cover both their own investment in energy supply and permit purchases from abroad. We show that incremental energy-supply investment (and saving) needs are well within the range of past variation of aggregate investment, and argue that the challenge is rather to ensure that revenues from carbon pricing and other sources are complemented by investment in the appropriate sectors. But fairness and equity are likely to warrant transfers from advanced industrial countries to developing nations.

We provide a structural equation model to analyze the influence of both willingness to trust others and personality factors such as the Big Five characteristics and optimism on retail investors’ risky assets share and general willingness to take risks. The main findings are as follows: The personality trait agreeableness has a significant and positive impact on general willingness to trust. Willingness to trust others has a significant negative influence on the willingness to take financial risk. More neurotic and more conscientious individuals are significantly more risk averse. Furthermore, more optimistic people reveal a significant lower degree of risk aversion.

This study examines the presence of the day-of-the-week effect on daily returns of biotechnology stocks over a 16-year period from January 2002 to December 2015. Using daily returns from the NASDAQ Biotechnology Index (NBI), we find that the stock returns were the lowest on Mondays, and compared to the Mondays the stock returns were significantly higher on Wednesdays, Thursdays, and Fridays. The day-of-the-week effect on returns of biotechnology stocks remained significant even after controlling for the Fama–French and Carhart factors. Moreover, the results from using the asymmetric generalized autoregressive conditional heteroskedastic (GARCH) processes reveal that momentum and small-firm effect were positively associated with the market risk-adjusted returns of the biotechnology stocks during this period. The findings of our study suggest that active portfolio managers need to consider the day of the week, momentum, and small-firm effect when making trading decisions for biotechnology stocks. Implications for portfolio managers, small investors, scholars, and policymakers are included.