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This study attempts to conduct a comparative analysis between dynamic and static asset allocation to achieve the long-term target return on asset liability management (ALM). This study conducts asset allocation using the ex ante expected rate of return through the outlook of future economic indicators because past economic indicators or realized rate of returns which are used as input data for expected rate of returns in the \"building block\" method, most adopted by domestic pension funds, does not fully reflect the future economic situation. Vector autoregression is used to estimate and forecast long-term interest rates. Furthermore, it is applied to gross domestic product and consumer price index estimation because it is widely used in financial time series data. Based on asset allocation simulations, this study derived the following insights: first, economic indicator filtering and upper-lower bound computation is needed to reduce the expected return volatility. Second, to reach the ALM goal, more stocks should be allocated than low-yielding assets. Finally, dynamic asset allocation which has been mirroring economic changes actively has a higher annual yield and risk-adjusted return than static asset allocation.

This study attempts to conduct a comparative analysis between dynamic and static asset allocation to achieve the long-term target return on asset liability management (ALM). This study conducts asset allocation using the ex ante expected rate of return through the outlook of future economic indicators because past economic indicators or realized rate of returns which are used as input data for expected rate of returns in the “building block” method, most adopted by domestic pension funds, does not fully reflect the future economic situation. Vector autoregression is used to estimate and forecast long-term interest rates. Furthermore, it is applied to gross domestic product and consumer price index estimation because it is widely used in financial time series data. Based on asset allocation simulations, this study derived the following insights: first, economic indicator filtering and upper-lower bound computation is needed to reduce the expected return volatility. Second, to reach theALMgoal, more stocks should be allocated than low-yielding assets. Finally, dynamic asset allocation which has been mirroring economic changes actively has a higher annual yield and risk-adjusted return than static asset allocation.

This paper shows how chief executive officer (CEO) characteristics affect the performance of acquirers in diversifying takeovers. When the acquirer's CEO has previous experience in the target industry, the acquirer's abnormal announcement returns are between 1.2 and 2.0 percentage points larger than those generated by a CEO who is new to the target industry. This outcome is driven by the industry-expert CEO's ability to capture a larger fraction of the merger surplus. Industry-expert CEOs typically negotiate better deals and pay a lower premium for the target. This effect is stronger when information asymmetry is high and in bilateral negotiations compared to auctions. We also find that industry-expert CEOs on average select lower surplus deals. This evidence is consistent with industry-expert CEOs having superior negotiation skills.

Purpose The purpose of this paper is to discuss the use of the internal rate of return (IRR) as a principal measure of performance of investments and to highlight some of the weaknesses of the IRR in evaluating investments in this way. Design/methodology/approach This Education Briefing is an overview of the limitations of the IRR in making capital budgeting decisions. It is illustrated with a number of counter-intuitive examples. Findings The advantage of the IRR is that it is, on the surface, a wonderfully simple benchmark. One figure that tells a story. But, the disadvantage is that if used in isolation the IRR can give misleading results when used to assess investment proposals. Practical implications The IRR should be used in conjunction with other analyses to appraise projects, so that the user can determine its veracity in the context of other benchmarks. This context is particularly important when assessing investments with unusual cash flows. Originality/value This is a review of existing models.

This paper studies the new model of analysis and prediction of enterprise investment targets, combines image text analysis technology, and designs a display system using multimedia technology, and then evaluates the model. Enterprise investment decision-making involves financial management, Market Research and other issues. It is necessary to evaluate the positioning of the investment field and the expectation of getting a report. It is also necessary to make a comprehensive evaluation based on the status quo of the research field and the assets and experience accumulation of the enterprise itself. Image text analysis technology is good at effectively utilizing the explosive growth of massive resources, extracting really useful and effective information from them, selecting appropriate methods to describe retrieval objects and corresponding search methods are the focus of this paper. Based on image text research technology, this paper carries out an analysis and prediction model of enterprise investment target and evaluates it. At the same time, in order to better show the model, this paper uses the most suitable display of multimedia technology, give full play to its advantages.

We document that announcement-period abnormal returns of sovereign wealth fund (SWF) equity investments in publicly traded firms are positive but lower than those of comparable private investments. Further, SWF investment targets suffer from declining return on assets and sales growth over the following three years. Our results are robust to controls for target and deal characteristics and are not driven by SWF target selection criteria. Larger discounts are associated with SWFs taking seats on boards of directors and with SWFs under strict government control acquiring greater stakes, supporting the hypothesis that political influence negatively affects firm value and performance.

An important focus of the research on mergers and acquisitions is the conditions under which acquisitions create value for the acquiring firm's shareholders. Given that the acquisition process is plagued by serious issues of information asymmetry, which are exacerbated in the context of knowledge acquisitions, we examine whether prior alliances with potential targets reduce the information asymmetry enough to create \"partner-specific absorptive capacity\" and yield superior stock returns on acquisition, compared with acquisitions not preceded by alliances. We test our hypotheses on a sample of high-technology acquisitions by U.S. firms during 1990-1998 using an event study methodology to assess abnormal stock returns. We find, unexpectedly, that no significant general effect emerges for acquisitions with prior alliances. However, international acquisitions following alliances show significantly better returns relative to both acquisitions without prior alliances and domestic acquisitions. Additionally, stronger forms of prior alliances lead to better acquisition performance than weaker forms of alliances. Together, the results broadly support our thesis that partner-specific absorptive capacity may be at work and suggest that under certain prior alliance conditions, acquisitions can indeed create value for acquirers.

We use text-based analysis of 10-K product descriptions to examine whether firms exploit product market synergies through asset complementarities in mergers and acquisitions. Transactions are more likely between firms that use similar product market language. Transaction stock returns, ex post cash flows, and growth in product descriptions all increase for transactions with similar product market language, especially in competitive product markets. These gains are larger when targets are less similar to acquirer rivals and when targets have unique products. Our findings are consistent with firms merging and buying assets to exploit synergies to create new products that increase product differentiation.