論文

Information security incidents could be one of the most concerns for corporate activities.Considering these factors, this study attempts to clarify the relationship between information securityincidents and stock market reactions. In this analysis, we analyze the stock market in Japan from March2005 to January 2015. As a result of intensive analyses, we confirm the following results; (1) informationsecurity incidents have a negative impact on corporate values, (2) information security incidents withsignificant impact have long-term negative effects on stock market.

Company executives play an important role in corporate activities. In this research, we focus onthe characteristics of the top executive, who make the important decisions. We attempt to measure the facialemotional score of these executives from the photographs published on their firm's annual report. Inaddition, we create a narcissism index from the number of times these executives appear on their reports.Finally, we analyze how these emotional scores or narcissism indexes relate with their company'sperformance and behavior.

Gas and electric power are one of the essential social infrastructure for social and economicactivities. The purpose of this research is to construct a gas' consumption model suitable for thedistribution and sales market of LP gas in Japan by utilizing temperature. As a method of predictingdemand, we would like to first create a model of power consumption and then apply it to LP gas. Analysisof customers' electric power and gas consumption can infer from what standpoint they were consumingpublic goods. Through this, we would like to offer users' reasonable prices to expand their choices andcontribute to the efficient use of social resources.

Gas and electric power are one of the essential social infrastructure for social and economicactivities. The purpose of this research is to construct a gas' consumption model suitable for thedistribution and sales market of LP gas in Japan by utilizing temperature. As a method of predictingdemand, we would like to first create a model of power consumption and then apply it to LP gas. Analysisof customers' gas consumption can infer from what standpoint they were consuming public goods.Through this, we would like to offer users' reasonable price and usage to expand their choices andcontribute to the efficient use of social resources. Furthermore, analysis of LP gas usage through deeplearning is possible.

Gas and electric power are one of the essential social infrastructure for social and economicactivities. The purpose of this research is to construct a Real Time Pricing (RTP) model suitable for thedistribution and sales market of LP gas in Japan by utilizing the Dynamic Pricing Model. As a method ofpredicting demand, we would like to first create a model of power consumption and then apply it to LPgas. Analysis of customers' electric power and gas consumption can infer from what standpoint they wereconsuming public goods. Through this, we would like to offer users' reasonable prices to expand theirchoices and contribute to the efficient use of social resources.

In this research, we analyze the impact of crypto assets on portfolio construction. Through this research, weattempt to clarify the risk return characteristics of portfolios that include crypto assets as investment targets. Theanalysis period is from 2014 to 2020, and in addition to the Cryptocurrency Index (CRIX), S&P500, Gold, Crude oil,PE, REITs, Goldman Sachs Commodity Index (GSCI), etc. Consider effectiveness and challenges.

本研究では、日本の株式市場における Twitter のツイート情報と小型株の株価との関連性について分析を行った。機関投資家と個人投資家の投資手法の違いを踏まえた上で、GoogleCloud Natural Language API を用いた感情分析を行い、ツイートと小型株の株価の関係を明らかにする。

近年、機械学習のアルゴリズムが発達し、様々な分野において応用がなされている。資産運用分野においても、企業の業績予測、倒産予測などをはじめとし、数多くの応用事例が報告されている。このような中、本研究では、株式ポートフォリオ構築時における個別銘柄のスクリーニングへの応用を試みる。具体的には、月ごとにTOPIXなどのインデックスに含まれる株式の中からポートフォリオに保有しない銘柄を機械学習を用いて分類し、優れたポートフォリオの構築を目的とする。本分析では、複数の機械学習手法を用いて、ポートフォリオ構築し、それらポートフォリオの収益性について分析を行う。

本研究は、外食産業の POS データを用いて経営力向上に繋げるサービスの実現を目的としている。日本の外食産業は、労働生産性が低い上、慢性的な人手不足で人材確保に苦労している。そこで、この課題を解消する対策として、1 テーブルごとの客単価向上が有効と仮説を立て、客単価の高い高級焼肉店の POS データを分析した。商品を提供する顧客層ごとに購買行動の特徴を明らかにし、機械学習を用いて販売政策の検討を行う。

本研究は、外食産業の POS データを用いて経営力向上に繋げるサービスの実現を目的としている。日本の外食産業は、労働生産性が低い上、慢性的な人手不足で人材確保に苦労している。そこで、この課題を解消する対策として、1 テーブルごとの客単価向上が有効と仮説を立て、客単価の高い高級焼肉店の POS データを分析した。顧客の購買行動の特徴を明らかにし、機械学習を用いてフィンテック応用を含めた販売政策の検討を行う。

製薬企業にとって特許は宝であり、新薬開発には欠かせない。近年、少子高齢化による社会保障費の上昇、それに伴い既存医薬品の薬価改定の㏿度が増している。新薬を矢継ぎ早に開発・販売しなければ製薬企業はたちまち衰退の道を歩むだろう。だが、新薬の開発には不確実性が高く、かつ莫大な予算が必要となってくる。その成果ともいえる特許データには製薬企業の戦略が詰まっているともいえる。本研究では、特許データベースである DWPI を用い、特許データを解析することで、製薬企業の戦略の分析を試みた。

Corporate valuation is an important process for determining corporate value for managersconsidering initial public offering (hereinafter IPO). However, in the IPO, the underprice phenomenonwhere the public price falls below the initial value has occurred. Due to this phenomenon, new publiccompanies suffer opportunity loss. In this study, we consider the cause of this phenomenon to be in theevaluation of corporate value and try to improve it by using patents in existing methods. Specifically,SCDVs are created based on patent documents held by companies and applied to similar companycomparison guns to evaluate the validity of the open price.