Machine Learning for Financial Risk Management with Python

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Saunders and Cornett's Financial Institutions Management: A Risk Management Approach provides an innovative approach that focuses on managing return and risk in modern financial institutions. The central theme is that the risks faced by financial institutions managers and the methods and markets through which these risks are managed are becoming increasingly similar whether an institution is chartered as a commercial bank, a savings bank, an investment bank, or an insurance company. Although the traditional nature of each sector's product activity is analyzed, a greater emphasis is placed on new areas of activities such as asset securitization, off-balance-sheet banking, and international banking.

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This book examines the role of risk management in the recent financial crisis and applies lessons from there to the national security realm. It rethinks the way risk contributes to strategy, with insi

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Risk management as a discipline is evolving, evolving to deal with fat tails, evolving to deal with macro-economic drivers and basic forms of nonlinearity. And yet, financial risk management remains l

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Risk has always been central to finance, and managing risk depends critically on information. As evidenced by recent events, the need has never been greater for skills, systems and methodologies to manage risk information in financial markets. Authored by leading figures in risk management and analysis, this handbook serves as a unique and comprehensive reference for the technical, operational, regulatory and political issues in collecting, measuring and managing financial data. It will appeal to a wide range of audiences, from financial industry practitioners and regulators responsible for implementing risk management systems, to system integrators and software firms helping to improve such systems. Volume 1 examines the business and regulatory context that makes risk information so important. Volume 2 describes a structural and operational framework for managing a financial risk data repository.

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本書講述了Python 語言與資料結構。主要內容包括資料結構與演算法、Python 開發環境、Python 資料類型、Python 三大程式結構、函數、線性資料結構、樹形結構、圖形結構、搜尋、排序、異常處理與調試等。 本書內容精煉、由淺入深，注重學習的連續性和漸進性，適合作為大專院校相關專業教材或教學參考書，也可作為電腦技術人員的應用參考書，還可作為全國電腦等級考試、軟體技術資格與水準考試的培訓資料。

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