世界金融危機におけるヘッジファンドの損失と破綻について

The hedge fund industry is one of the fastest growing sectors in finance market, due to limitedregulatory oversight, flexible investment strategies, and performance-based fee structures. Therapidly growth of this industry has captured the attention of both academics and practitioners.Hedge funds held about 47 per cent of the $3 trillion worth of CDOs on the eve of the financialcrisis. Hedge funds and other financial institutions suffered huge losses in the global financialcrisis, because the price of securitized products such as CDOs plummeted to the ground whenthe crisis happened.This paper will consider the condition of financial markets during the financial crisis, and analyzewhy the loss and breakdown of hedge funds have happened

CodeTransOcean: A Comprehensive Multilingual Benchmark for Code Translation

Recent code translation techniques exploit neural machine translation models to translate source code from one programming language to another to satisfy production compatibility or to improve efficiency of codebase maintenance. Most existing code translation datasets only focus on a single pair of popular programming languages. To advance research on code translation and meet diverse requirements of real-world applications, we construct CodeTransOcean, a large-scale comprehensive benchmark that supports the largest variety of programming languages for code translation. CodeTransOcean consists of three novel multilingual datasets, namely, MultilingualTrans supporting translations between multiple popular programming languages, NicheTrans for translating between niche programming languages and popular ones, and LLMTrans for evaluating executability of translated code by large language models (LLMs). CodeTransOcean also includes a novel cross-framework dataset, DLTrans, for translating deep learning code across different frameworks. We develop multilingual modeling approaches for code translation and demonstrate their great potential in improving the translation quality of both low-resource and high-resource language pairs and boosting the training efficiency. We also propose a novel evaluation metric Debugging Success Rate@K for program-level code translation. Last but not least, we evaluate LLM ChatGPT on our datasets and investigate its potential for fuzzy execution predictions. We build baselines for CodeTransOcean and analyze challenges of code translation for guiding future research. The CodeTransOcean datasets and code are publicly available at https://github.com/WeixiangYAN/CodeTransOcean.Comment: Accepted by Findings of EMNLP 202

金融危機における投資銀行のビジネスモデルの崩壊に関する一考察

Investment banks have played an important role in the capital market, especially, the direct finance developed at present. Raising capital for corporations, providing advice on transactions such as mergers and acquisitions, as well as trading securities are the main businesses of invest¬ment banks. Because the financial engineering developed, investment banks have continuously created securitized products such as Residential Mortgage-Backed Security (RMBS) and Collateralized Debt Obligation (CDO) since 2000. The scale of securitized products climbed to $520 billion and reached the peak at the end of 2006. Investment banks and other financial institutions got huge profits from the capital market. But, the price of securitized products such as CDOs have plum¬meted to the ground when the subprime mortgage crisis happened, so hedge funds, mutual funds and investment banks have suffered huge losses in the global financial crisis. Even if the fourth biggest investment bank Lehman Brothers had to file for bankruptcy protection on September 15, 2008. This paper will analyze the business model of investment banks, and examine whether an excessively expanded business of investment banks connect with this financial crisis

Enhancing Generation through Summarization Duality and Explicit Outline Control

Automatically open-ended long text generation poses significant challenges due to semantic incoherence and plot implausibility. Previous works usually alleviate this problem through outlines in the form of short phrases or abstractive signals by designing unsupervised tasks, which tend to be unstable and weakly interpretable. Assuming that a summary serves as a mature outline, we introduce a two-stage, summary-enhanced outline supervised generation framework. This framework leverages the dual characteristics of the summarization task to improve outline prediction, resulting in more explicit and plausible outlines. Furthermore, we identify an underutilization issue in outline-based generation with both standard pretrained language models (e.g., GPT-2, BART) and large language models (e.g., Vicuna, ChatGPT). To address this, we propose a novel explicit outline control method for more effective utilization of generated outlines.Comment: 14 page

Local Resistance in Early Medieval Chinese Historiography and the Problem of Religious Overinterpretation

Official Chinese historiography is a treasure trove of information on local resistance to the centralised empire in early medieval China (third to sixth century). Sinologists specialised in the study of Chinese religions commonly reconstruct the religious history of the era by interpreting some of these data. In the process, however, the primary purpose of the historiography of local resistance is often overlooked, and historical interpretation easily becomes ‘overinterpretation’—that is, ‘fabricating false intensity’ and ‘seeing intensity everywhere’, as French historian Paul Veyne proposed to define the term. Focusing on a cluster of historical anecdotes collected in the standard histories of the four centuries under consideration, this study discusses the supposedly ‘religious’ nature of some of the data they contain