Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Deep Dive Into Financial Models Modeling Risk And Uncertainty
Download Deep Dive Into Financial Models Modeling Risk And Uncertainty full books in PDF, epub, and Kindle. Read online Deep Dive Into Financial Models Modeling Risk And Uncertainty ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Deep Dive Into Financial Models: Modeling Risk And Uncertainty by : Mathieu Le Bellac
Download or read book Deep Dive Into Financial Models: Modeling Risk And Uncertainty written by Mathieu Le Bellac and published by World Scientific Publishing Company. This book was released on 2016-11-14 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since 2007, the repeated financial crises around the world have brought to the headlines financial practices and models considered to fuel the economic instabilities. Deep Dive into Financial Models: Modeling Risk and Uncertainty comes handy in demystifying the underlying quantitative finance concepts. With a limited use of mathematical formalism, the book explains thoroughly the models, their hypotheses, principles and other building blocks. A particular care is given to model limitations and their misuse for investment strategies, asset pricing, or risk management. Its reader-friendly nature provides readers with a head start in quantitative finance.
Book Synopsis Deep Dive Into Financial Models by : Mathieu Le Bellac
Download or read book Deep Dive Into Financial Models written by Mathieu Le Bellac and published by . This book was released on 2017 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Practical Guide for Startup Valuation by : Sinem Derindere Köseoğlu
Download or read book A Practical Guide for Startup Valuation written by Sinem Derindere Köseoğlu and published by Springer Nature. This book was released on 2023-09-25 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book sheds new light on the most important contemporary and emerging startup valuation topics. Drawing on the first-hand professional experience of practitioners, professionals, and startup experts from various fields of finance, combined with a sound academic foundation, it offers a practical guide to startup valuation and presents applications, practical examples, and case studies of real startup ecosystems. The book discusses pressing questions, such as: Why are startups in California are higher valued than those in New York? Or why do startups based in London receive higher valuations than those in Paris, Berlin, or Milan, even when they are based in similarly-sized economies, share the same industries, and often even have the same investors? Answering these questions, the authors present key topics, such as hierarchical and segmented approaches to startup valuation, business plans, and sensitivity analysis, many methods such as venture capital valuation, first Chicago valuation, scorecard valuation, Dave Berkus valuation, risk factor summation valuation, and discounted cash flow valuation, in addition to business valuation by data envelopment analysis and real options analysis, as well as critical conceptual issues in the valuation such as expected returns of the venture capital and price versus value concepts, among others. The book will help angel investors, venture capitalists, institutional investors, crowd-based fractional investors, and investment fund professionals understand how to use basic and advanced analytics for a more precise valuation that helps them craft their long-term capital-raising strategy and keep their funding requests in perspective. It will also appeal to students and scholars of finance and business interested in a better understanding of startup valuation.
Book Synopsis TURKISH ECONOMIC ASSOCIATION INTERNATIONAL CONFERENCE ON ECONOMICS ICE-TEA 2018 by : Ercan Uygur
Download or read book TURKISH ECONOMIC ASSOCIATION INTERNATIONAL CONFERENCE ON ECONOMICS ICE-TEA 2018 written by Ercan Uygur and published by Türkiye Ekonomi Kurumu. This book was released on 2018-12-31 with total page 2118 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance by : El Bachir Boukherouaa
Download or read book Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance written by El Bachir Boukherouaa and published by International Monetary Fund. This book was released on 2021-10-22 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.
Book Synopsis Handbook of Price Impact Modeling by : Kevin T Webster
Download or read book Handbook of Price Impact Modeling written by Kevin T Webster and published by CRC Press. This book was released on 2023-05-05 with total page 485 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Price Impact Modeling provides practitioners and students with a mathematical framework grounded in academic references to apply price impact models to quantitative trading and portfolio management. Automated trading is now the dominant form of trading across all frequencies. Furthermore, trading algorithm rise introduces new questions professionals must answer, for instance: How do stock prices react to a trading strategy? How to scale a portfolio considering its trading costs and liquidity risk? How to measure and improve trading algorithms while avoiding biases? Price impact models answer these novel questions at the forefront of quantitative finance. Hence, practitioners and students can use this Handbook as a comprehensive, modern view of systematic trading. For financial institutions, the Handbook’s framework aims to minimize the firm’s price impact, measure market liquidity risk, and provide a unified, succinct view of the firm’s trading activity to the C-suite via analytics and tactical research. The Handbook’s focus on applications and everyday skillsets makes it an ideal textbook for a master’s in finance class and students joining quantitative trading desks. Using price impact models, the reader learns how to: Build a market simulator to back test trading algorithms Implement closed-form strategies that optimize trading signals Measure liquidity risk and stress test portfolios for fire sales Analyze algorithm performance controlling for common trading biases Estimate price impact models using public trading tape Finally, the reader finds a primer on the database kdb+ and its programming language q, which are standard tools for analyzing high-frequency trading data at banks and hedge funds. Authored by a finance professional, this book is a valuable resource for quantitative researchers and traders.
Book Synopsis Decision Making for the Net Zero Transformation: Considerations and New Methodological Approaches by : Mark Workman
Download or read book Decision Making for the Net Zero Transformation: Considerations and New Methodological Approaches written by Mark Workman and published by Frontiers Media SA. This book was released on 2024-02-01 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: Special edition compiled in partnership with Frontiers sponsored by the Clean Air Task Force. The realisation of Net Zero by 2050 will require the ability for strategy developers, operational planners and decision makers to better manage uncertainty, complexity and emergence. The application of the orthodox set of decision support tools and processes that have been used to explore deep decarbonisation options to 2050 have blinded decision makers to uncertainty, complexity and emergence. Tools have often been used which are inappropriate to the types of decisions being made – a competency which has been glaringly revealed during the C-19 Pandemic. This Frontiers Research Topic will highlight the need for an interdisciplinary, mixed methods approach bringing together insights from modelling, decision science, psychology, anthropology, and sociology to form a compendium of current best practice for decision making for the net zero transformation and new research frontiers. Develop greater awareness amongst policymakers, practitioners and academics as to the importance of: • Understanding the nature of uncertainty when dealing with problems associated with the Net Zero Energy System Transformation; • Increasing importance of deliberative processes to map different value sets beyond least cost; • Acknowledging that decision making under uncertainty requires competency-based training leading to a full appreciation of the tasks at hand. Suggested areas within scope are listed in points 1-12 below. Authors are free to choose specific areas of interest, and to combine these where useful. In general, it will be useful to consider practical application of [ideas], e.g • development of `Use Cases’ and `Decision Making Contexts’ may be useful, e.g. National Govt establishing its Carbon Budget; Institution setting up its investment portfolio. • understanding of how decisions are being made within different jurisdictions, political cultures, and types of organizations (public/private). What is the role of `Decision Context' i.e. organisational decision-making structures, cultures, the role of zeitgeist and dominant narratives, or the relation between academic expertise and policy-makers. 1. Decision making from an end-to-end perspective and the need to take a holistic and interdisciplinary perspective [Editorial Cover Article]. 2. Gap between what policy makers and decision makers around net zero climate policy seek to address and what decision support tools can actually do. Why that gap is increasing (if it is)? 3. Understanding the nature of uncertainty when applying the relevant decision support tool and processes. Not all uncertainty can be addressed within the decision support tool itself. Role of optimism bias; potential role of least worst regret approaches etc 4. What different decision support tools can inform decision makers around net zero climate policy and need for a basket of tools. 5. Why parametric decision support tools and models are pre-eminent - the role of consolidative modelling and exploratory modelling. The inertia of modelling approaches: why it is so hard to break modelling paradigms? 6. What decision science informs us about how decisions are actually made - the importance of process, the role of transparency and deliberation with analysis. 7. Processes that address the biases identified in decision science and impact of identity politics on deliberative decision making. 8. Why decision making under deep uncertainty requires competency-based training, deep subject matter expertise and systemic knowledge. 9. Ministerial and policy making and the decision support requirements: US, EU, UK & China 10. The role of narratives and how uncertainty can be communicated to societal audiences. Storylines and other narrative approaches 11. How to develop participatory approaches allow multiple values, diversity of stakeholders in which climate communication and decision making exists in an iterative exchange with policy. We have started the journey e.g. the role of climate assemblies… what next? 12. Decision making under deep (climate) uncertainty by the financial sector We acknowledge the funding of the manuscripts published in this Research Topic by the Clean Air Task Force. We hereby state publicly that the Clean Air Task Force has had no editorial input in articles included in this Research Topic, thus ensuring that all aspects of this Research Topic are evaluated objectively, unbiased by any specific policy or opinion of the Clean Air Task Force.
Book Synopsis Business Economics and Finance with MATLAB, GIS, and Simulation Models by : Patrick L. Anderson
Download or read book Business Economics and Finance with MATLAB, GIS, and Simulation Models written by Patrick L. Anderson and published by CRC Press. This book was released on 2004-07-27 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book takes recent theoretical advances in Finance and Economics and shows how they can be implemented in the real world. It presents tactics for using mathematical and simulation models to solve complex tasks of forecasting income, valuing businesses, predicting retail sales, and evaluating markets and tax and regulatory problems. Busine
Book Synopsis Stochastic Calculus for Finance by : William Johnson
Download or read book Stochastic Calculus for Finance written by William Johnson and published by HiTeX Press. This book was released on 2024-10-17 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Stochastic Calculus for Finance: A Practical Guide" offers an insightful exploration into the mathematical intricacies underpinning modern financial markets. Designed to demystify complex concepts, this comprehensive text bridges rigorous theory with application, crafting a resource that is as invaluable to students embarking on a financial career as it is to seasoned professionals seeking to enrich their analytical toolkit. Through an elegant synthesis of probability theory, stochastic processes, and advanced calculus, readers are introduced to the foundational frameworks that drive market analysis, derivative pricing, and portfolio optimization. This guide stands out by making sophisticated mathematical models accessible, without sacrificing depth or precision. By delving into topics such as Brownian motion, stochastic differential equations, and applications of machine learning, the book equips readers with the tools needed to navigate and innovate in the financial landscape. It elucidates the power of stochastic calculus in shaping strategies and solutions to real-world financial challenges, fostering a nuanced understanding of risk management and asset allocation. With its blend of theoretical insight and practical application, this book promises to be an essential companion for those dedicated to mastering the art and science of finance.
Book Synopsis Model Risk in Financial Markets by : Radu Tunaru
Download or read book Model Risk in Financial Markets written by Radu Tunaru and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Dive Into Deep Learning by : Joanne Quinn
Download or read book Dive Into Deep Learning written by Joanne Quinn and published by Corwin Press. This book was released on 2019-07-15 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: The leading experts in system change and learning, with their school-based partners around the world, have created this essential companion to their runaway best-seller, Deep Learning: Engage the World Change the World. This hands-on guide provides a roadmap for building capacity in teachers, schools, districts, and systems to design deep learning, measure progress, and assess conditions needed to activate and sustain innovation. Dive Into Deep Learning: Tools for Engagement is rich with resources educators need to construct and drive meaningful deep learning experiences in order to develop the kind of mindset and know-how that is crucial to becoming a problem-solving change agent in our global society. Designed in full color, this easy-to-use guide is loaded with tools, tips, protocols, and real-world examples. It includes: • A framework for deep learning that provides a pathway to develop the six global competencies needed to flourish in a complex world — character, citizenship, collaboration, communication, creativity, and critical thinking. • Learning progressions to help educators analyze student work and measure progress. • Learning design rubrics, templates and examples for incorporating the four elements of learning design: learning partnerships, pedagogical practices, learning environments, and leveraging digital. • Conditions rubrics, teacher self-assessment tools, and planning guides to help educators build, mobilize, and sustain deep learning in schools and districts. Learn about, improve, and expand your world of learning. Put the joy back into learning for students and adults alike. Dive into deep learning to create learning experiences that give purpose, unleash student potential, and transform not only learning, but life itself.
Book Synopsis Models.Behaving.Badly. by : Emanuel Derman
Download or read book Models.Behaving.Badly. written by Emanuel Derman and published by Simon and Schuster. This book was released on 2011-10-25 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now in paperback, “a compelling, accessible, and provocative piece of work that forces us to question many of our assumptions” (Gillian Tett, author of Fool’s Gold). Quants, physicists working on Wall Street as quantitative analysts, have been widely blamed for triggering financial crises with their complex mathematical models. Their formulas were meant to allow Wall Street to prosper without risk. But in this penetrating insider’s look at the recent economic collapse, Emanuel Derman—former head quant at Goldman Sachs—explains the collision between mathematical modeling and economics and what makes financial models so dangerous. Though such models imitate the style of physics and employ the language of mathematics, theories in physics aim for a description of reality—but in finance, models can shoot only for a very limited approximation of reality. Derman uses his firsthand experience in financial theory and practice to explain the complicated tangles that have paralyzed the economy. Models.Behaving.Badly. exposes Wall Street’s love affair with models, and shows us why nobody will ever be able to write a model that can encapsulate human behavior.
Book Synopsis Advances in Credit Risk Modeling and Management by : Frédéric Vrins
Download or read book Advances in Credit Risk Modeling and Management written by Frédéric Vrins and published by MDPI. This book was released on 2020-07-01 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: Credit risk remains one of the major risks faced by most financial and credit institutions. It is deeply connected to the real economy due to the systemic nature of some banks, but also because well-managed lending facilities are key for wealth creation and technological innovation. This book is a collection of innovative papers in the field of credit risk management. Besides the probability of default (PD), the major driver of credit risk is the loss given default (LGD). In spite of its central importance, LGD modeling remains largely unexplored in the academic literature. This book proposes three contributions in the field. Ye & Bellotti exploit a large private dataset featuring non-performing loans to design a beta mixture model. Their model can be used to improve recovery rate forecasts and, therefore, to enhance capital requirement mechanisms. François uses instead the price of defaultable instruments to infer the determinants of market-implied recovery rates and finds that macroeconomic and long-term issuer specific factors are the main determinants of market-implied LGDs. Cheng & Cirillo address the problem of modeling the dependency between PD and LGD using an original, urn-based statistical model. Fadina & Schmidt propose an improvement of intensity-based default models by accounting for ambiguity around both the intensity process and the recovery rate. Another topic deserving more attention is trade credit, which consists of the supplier providing credit facilities to his customers. Whereas this is likely to stimulate exchanges in general, it also magnifies credit risk. This is a difficult problem that remains largely unexplored. Kanapickiene & Spicas propose a simple but yet practical model to assess trade credit risk associated with SMEs and microenterprises operating in Lithuania. Another topical area in credit risk is counterparty risk and all other adjustments (such as liquidity and capital adjustments), known as XVA. Chataignier & Crépey propose a genetic algorithm to compress CVA and to obtain affordable incremental figures. Anagnostou & Kandhai introduce a hidden Markov model to simulate exchange rate scenarios for counterparty risk. Eventually, Boursicot et al. analyzes CoCo bonds, and find that they reduce the total cost of debt, which is positive for shareholders. In a nutshell, all the featured papers contribute to shedding light on various aspects of credit risk management that have, so far, largely remained unexplored.
Book Synopsis Financial Modeling Under Non-Gaussian Distributions by : Eric Jondeau
Download or read book Financial Modeling Under Non-Gaussian Distributions written by Eric Jondeau and published by Springer Science & Business Media. This book was released on 2007-04-05 with total page 541 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines non-Gaussian distributions. It addresses the causes and consequences of non-normality and time dependency in both asset returns and option prices. The book is written for non-mathematicians who want to model financial market prices so the emphasis throughout is on practice. There are abundant empirical illustrations of the models and techniques described, many of which could be equally applied to other financial time series.
Book Synopsis The End of Theory by : Richard Bookstaber
Download or read book The End of Theory written by Richard Bookstaber and published by Princeton University Press. This book was released on 2019-04-02 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: An in-depth look at how to account for the human complexities at the heart of today’s financial system Our economy may have recovered from the Great Recession—but not our economics. The End of Theory discusses why the human condition and the radical uncertainty of our world renders the standard economic model—and the theory behind it—useless for dealing with financial crises. What model should replace it? None. At least not any version we’ve been using for the past two hundred years. Richard Bookstaber argues for a new approach called agent-based economics, one that takes as a starting point the fact that we are humans, not the optimizing automatons that standard economics assumes we are. Sweeping aside the historic failure of twentieth-century economics, The End of Theory offers a novel perspective and more realistic framework to help prevent today's financial system from blowing up again.
Book Synopsis Confronting Climate Uncertainty in Water Resources Planning and Project Design by : Patrick A. Ray
Download or read book Confronting Climate Uncertainty in Water Resources Planning and Project Design written by Patrick A. Ray and published by World Bank Publications. This book was released on 2015-08-20 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: Confronting Climate Uncertainty in Water Resources Planning and Project Design describes an approach to facing two fundamental and unavoidable issues brought about by climate change uncertainty in water resources planning and project design. The first is a risk assessment problem. The second relates to risk management. This book provides background on the risks relevant in water systems planning, the different approaches to scenario definition in water system planning, and an introduction to the decision-scaling methodology upon which the decision tree is based. The decision tree is described as a scientifically defensible, repeatable, direct and clear method for demonstrating the robustness of a project to climate change. While applicable to all water resources projects, it allocates effort to projects in a way that is consistent with their potential sensitivity to climate risk. The process was designed to be hierarchical, with different stages or phases of analysis triggered based on the findings of the previous phase. An application example is provided followed by a descriptions of some of the tools available for decision making under uncertainty and methods available for climate risk management. The tool was designed for the World Bank but can be applicable in other scenarios where similar challenges arise.
Book Synopsis Machine Learning for Algorithmic Trading by : Stefan Jansen
Download or read book Machine Learning for Algorithmic Trading written by Stefan Jansen and published by Packt Publishing Ltd. This book was released on 2020-07-31 with total page 822 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage machine learning to design and back-test automated trading strategies for real-world markets using pandas, TA-Lib, scikit-learn, LightGBM, SpaCy, Gensim, TensorFlow 2, Zipline, backtrader, Alphalens, and pyfolio. Purchase of the print or Kindle book includes a free eBook in the PDF format. Key FeaturesDesign, train, and evaluate machine learning algorithms that underpin automated trading strategiesCreate a research and strategy development process to apply predictive modeling to trading decisionsLeverage NLP and deep learning to extract tradeable signals from market and alternative dataBook Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This revised and expanded second edition enables you to build and evaluate sophisticated supervised, unsupervised, and reinforcement learning models. This book introduces end-to-end machine learning for the trading workflow, from the idea and feature engineering to model optimization, strategy design, and backtesting. It illustrates this by using examples ranging from linear models and tree-based ensembles to deep-learning techniques from cutting edge research. This edition shows how to work with market, fundamental, and alternative data, such as tick data, minute and daily bars, SEC filings, earnings call transcripts, financial news, or satellite images to generate tradeable signals. It illustrates how to engineer financial features or alpha factors that enable an ML model to predict returns from price data for US and international stocks and ETFs. It also shows how to assess the signal content of new features using Alphalens and SHAP values and includes a new appendix with over one hundred alpha factor examples. By the end, you will be proficient in translating ML model predictions into a trading strategy that operates at daily or intraday horizons, and in evaluating its performance. What you will learnLeverage market, fundamental, and alternative text and image dataResearch and evaluate alpha factors using statistics, Alphalens, and SHAP valuesImplement machine learning techniques to solve investment and trading problemsBacktest and evaluate trading strategies based on machine learning using Zipline and BacktraderOptimize portfolio risk and performance analysis using pandas, NumPy, and pyfolioCreate a pairs trading strategy based on cointegration for US equities and ETFsTrain a gradient boosting model to predict intraday returns using AlgoSeek's high-quality trades and quotes dataWho this book is for If you are a data analyst, data scientist, Python developer, investment analyst, or portfolio manager interested in getting hands-on machine learning knowledge for trading, this book is for you. This book is for you if you want to learn how to extract value from a diverse set of data sources using machine learning to design your own systematic trading strategies. Some understanding of Python and machine learning techniques is required.
