論文

The asset allocation strategy is important to manage assets effectively. In recent years, the risk parity strategy has become attractive to academics and practitioners. The risk parity strategy determines the allocation for asset classes in order to equalize their contributions to overall portfolio risk. Roncalli and Weisang (2016) propose the use of \risk factors" instead of asset classes. This approach achieves the portfolio diversification based on the decomposition of portfolio risk into risk factor contribution. The factor-based risk parity approach can diversify across the true sources of risk whereas the asset-class-based approach may lead to solutions with hidden risk concentration. However, it has some shortcomings. In our paper, we propose a methodology of constructing the well-balanced portfolio by the mixture of asset-classbased and factor-based risk parity approaches. We also propose the method of determining the weight of two approaches using the diversification index. We can construct the portfolio dynamically controlled with the weight which is adjusted in response to market environment. We examine the characteristics of the model through the numerical tests with seven global financial indices and three factors. We find it gives the well-balanced portfolio between asset and factor diversifications. We also implement the backtest from 2005 to 2018, and the performances are measured on a USD basis. We find our method decreases standard deviation of return and downside risk, and it has a higher Sharpe ratio than other portfolio strategies. These results show our new method has practical advantages.

In general, banks keep management costs for card loans down because the amounts are smaller than those of corporate loans. Therefore, they are not sufficiently managed after the money is lent. This study analyzes the deposit and withdrawal data of bank accounts used by card loan borrowers and proposes a default risk management technique. A previous study analyzed bank account data for screening applicants for card loans, and constructed a model to evaluate default risk. However, to the best of our knowledge, there are no studies that analyze bank account data to determine measures for managing the default risk while lending money with a card loan or construct a management model. In addition to the explanatory variables used in the screening model, we employ some variables observable after lending money that are related to individual behavior characteristics, such as number of borrowings and contract repayment rate, and analyze their relationships with default. We construct a logit model using these variables and examine the model using approximately 60 million observations. The result shows that the accuracy ratios exceed 50\%, and the model is effective in practice. We also confirm the robustness of the results through cross-validation and an out-of-sample test.

In this study, we construct an optimal currency portfolio using the implied return distribution in the mean-variance approach and examine the performance through a backtest. We estimate the implied expected spot return, implied volatility, and implied correlation from currency option price data, and propose a method of constructing a fully forward-looking optimal currency portfolio without historical data. We implement the backtest from January 2006 to October 2020 on a currency portfolio comprising seven currencies (the Japanese yen, the Swiss franc, the euro, the British pound, the Australian dollar, the New Zealand dollar, and the Canadian dollar) against the US dollar and US-dollar interest rate, and examine the usefulness of the proposed method. We find that the proposed method yields a higher performance than the conventional method in previous studies that use historical data. Furthermore, it is evidenced that the main factor in the performance gap between the proposed and the conventional methods is the high predictive power of the spot return.

This study examines the impact of macroeconomic announcements on the risk premium and its sources under time-varying preference. We propose a novel method to decompose risk premium changes into the risk and preference components, which are estimated from option prices immediately before and after the announcement using the Recovery Theorem. The results of the empirical analysis for the United States stock market indicate that (1) the negative (positive) macroeconomic announcement surprise increases (decreases) the risk premium; (2) the risk component mainly drives the increase (decrease) in the risk premium; and (3) the preference component has limited influence on the risk premium.

This research addresses the asymmetric acknowledgment given to local versus global crises, particularly within the BRICS nations. Local crises often surpass global events in their impact but remain underexplored. Using a comprehensive approach combining Financial and Economic, Public Sentiment, and Governance data, the research applies a novel Axiom and Inference model to identify overlooked crises. Results indicate that local crises in BRICS countries have measurable impacts exceeding global benchmarks, with distinctive patterns of herding behaviour: China primarily responds to global crises, India reacts equally to both, and Brazil, Russia, and South Africa exhibit stronger herding during local crises. The findings challenge traditional crisis frameworks, emphasizing the need to recognize and address local and non-financial crises to mitigate their potential escalation into global phenomena.

銀行のALM問題に必要な要因を取りあげ、それを目標計画モデルにより定式化し、具体的な最適方策を導いた。（8頁)