Throughout 1980's, Japanese science and technology policy was focused on promoting the basic research in the public sector, and encouraging the private sector to go into more basic fields instead of development of improved products. In fact, the annual expenditure for the basic research increased by 50 per cent during ten years since 1988. However, after the end of the "bubble economy", the outcome from the investment in the basic research has been seriously questioned. While the shares of Japanese papers and their citations in the scientific journals have increased by about 2 points, contribution to creation of new technologies fell short o expectation. The present paper discusses reasons for this situation and points out strategic inconsistencies in both the government and industry. Strengthening the competitiveness of Japan in the coming decade necessitates in a new mechanism to develop appropriate strategies for promising results already accumulated.

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Recent interest in artificial intelligence (AI) has necessarily led to is applications in financial engineering. Possible applications include: (1) "technology" such as risk management, price theory and performance evaluation, and (2) "art" such as prediction profitability and risk in future (usually the standard deviation of profitability). While the "technology" may advance relatively easily by application of theories of probability and statistics, the "art" depends much on investor's philosophy, which makes any "standard model" impossible. This is the very area where AI is beginning to find applications. After presenting a review of financial engineering, the present paper presents two examples of AI application in this field: a simulation of long-term forecasts of interest rates, and a virtual market studies in the Santa Fe Institute. In addition, methods and effectiveness of AI in financial engineering are discussed in comparison with applications in other fields.

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The validity of the Leland model, recently developed in the U.S., in the Japanese market is discussed by examining the insolvency risk premium in capital, shareholder capital and debt costs, with taxes neglected. The Leland model permits calculation of the company, shareholder and debt values with insolvency taken into account. Use of these values in calculation of the insolvency premium requires formulation of capital cost-company value, shareholder capital cost-shareholder value, and debt cost-debt value relationships. Assuming that the stochastic change of company value results from that of cash flow, the present study uses the cash discount model for these formulations, which are then used for calculation of the discount rate corresponding to company value, or the capital cost. Comparison of capital costs with and without insolvency gives the insolvency risk premium in capital cost. Similar calculations are made for shareholder capital and debt costs. Calculations based on current data on the Japanese financial market show that the insolvency risk premium increases rapidly when the debt ratio (i.e. the debt/company value ratio in the current values) exceeds 70%: when the debt ratio is 80%, the shareholder capital cost is about 20%, in which about 10% is the insolvency premium risk. These results are considered well representative of the present circumstances.

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History of development of financial engineering in the U.S. shows that many results were obtained in studies with actual business activities as the background, which have, in turn, readily found practical applications. In Japan, however, factual analysis has been hindered by various problems in both academic and business circles. Given that the social needs for financial engineering is certain to grow, the current situation should be improved to assure fruitful applications, with the limitation inherent to research in this field taken into account.

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In the "first financial engineering boom" in the latter half of the 1980's, Japanese financial organizations tried to introduce advanced financial technologies developed in Europe and the U.S., and recruited many science/engineering students. Although this boom was short-lived and vanished with the end of the "bubble economy", research efforts in this field were maintained until the advent of the "Japanese financial big bang", or attempts at radical reform of the financial system of the country, including opening up the market to other countries. This triggered a second boom, in which science/engineering schools, traditionally aloof from finance, began joining field. Following a brief summary of this development and the present states of financial engineering, the author presents a proposal on future curriculum in this field.

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This paper analyzes the diversification dynamics of R&D activities and business in the Japanese industry in terms of the entropy index. The 1980s saw extensive diversification in R&D, followed by that in businesses. The directions of diversification, i.e. diversification upstream and downstream, can be analyzed quantitatively using the diversification data in combination with input-output analysis. These directions can be regarded as representing technological opportunities in individual sectors. Results suggest that the opportunities lie downstream for high-tech and scale-intensive industries, and upstream for chemistry-related industries such as textile, pharmaceuticals, and paper and pulp. Case studies resulted in a hypothesis that diversification strategies downstream for higher added values contribute to increased profitability.

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Recently, universities are expected to contribute more directly to society by helping to create new industries, but the collaboration between universities and industry is not active enough in Japan. On the other hand, in the U.S., both of the collaboration between universities to industry and technology transfer from universities to industry is very active. This paper compares the systems for and real activities in collaboration of American and Japanese research universities (MIT, Stanford University, U.C. Berkeley, and Tokyo Institute of Technology) with industry, constructs a model of the process of those collaborations, and analyzes the mechanism behind them. The paper also discusses the desirable policy for Japanese universities' contribution to society through creation of new industries.

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