موضوعات
آموزش و پرورش
ادبیات و زبان
پزشکی، دندانپزشکی و داروسازی
تاریخ و جغرافیا
داستان و رمان
دیگر
دین و فلسفه
روانشناسی
ریاضیات و آمار
سلامتی، تناسب اندام و رژیم غذایی
شیمی و پلیمر
علوم اجتماعی و حقوق
علوم زیستی و بیوتکنولوژی
فیزیک و نجوم
کامپیوتر و اینترنت
کتابهای کودکان و داستان
کسب و کار و اقتصاد
کشاورزی و دامپزشکی و غذا
معماری
مهندسی و فناوری
هنر و تئاتر
محصولات
Hands-On Financial Modeling with Excel for Microsoft 365: Build your own practical financial models for effective forecasting, valuation, trading, and growth analysis, 2nd Edition - Original PDF
نویسندگان: خلاصه: Explore a variety of Excel features, functions, and productivity tips for various aspects of financial modeling Key Features Explore Excel's financial functions and pivot tables with this updated second edition Build an integrated financial model with Excel for Microsoft 365 from scratch Perform financial analysis with the help of real-world use cases Book Description Financial modeling is a core skill required by anyone who wants to build a career in finance. Hands-On Financial Modeling with Excel for Microsoft 365 explores financial modeling terminologies with the help of Excel. Starting with the key concepts of Excel, such as formulas and functions, this updated second edition will help you to learn all about referencing frameworks and other advanced components for building financial models. As you proceed, you'll explore the advantages of Power Query, learn how to prepare a 3-statement model, inspect your financial projects, build assumptions, and analyze historical data to develop data-driven models and functional growth drivers. Next, you'll learn how to deal with iterations and provide graphical representations of ratios, before covering best practices for effective model testing. Later, you'll discover how to build a model to extract a statement of comprehensive income and financial position, and understand capital budgeting with the help of end-to-end case studies. By the end of this financial modeling Excel book, you'll have examined data from various use cases and have developed the skills you need to build financial models to extract the information required to make informed business decisions. What you will learn Identify the growth drivers derived from processing historical data in Excel Use discounted cash flow (DCF) for efficient investment analysis Prepare detailed asset and debt schedule models in Excel Calculate profitability ratios using various profit parameters Obtain and transform data using Power Query Dive into capital budgeting techniques Apply a Monte Carlo simulation to derive key assumptions for your financial model Build a financial model by projecting balance sheets and profit and loss Who this book is for This book is for data professionals, analysts, traders, business owners, and students who want to develop and implement in-demand financial modeling skills in their finance, analysis, trading, and valuation work. Even if you don't have any experience in data and statistics, this book will help you get started with building financial models. Working knowledge of Excel is a prerequisite.
Developing High Frequency Trading Systems: Learn how to implement high-frequency trading from scratch with C++ or Java basics - Original PDF
نویسندگان: خلاصه: Use your programming skills to create and optimize high-frequency trading systems in no time with Java, C++, and Python Key Features • Learn how to build high-frequency trading systems with ultra-low latency • Understand the critical components of a trading system • Optimize your systems with high-level programming techniques Book Description The world of trading markets is complex, but it can be made easier with technology. Sure, you know how to code, but where do you start? What programming language do you use? How do you solve the problem of latency? The Developing High-Frequency Trading Systems book answers all these questions. This practical guide will help you navigate the fast-paced world of algorithmic trading and show you how to build a high-frequency trading system from complex technological components, supported by accurate data. Starting off with an introduction to high-frequency trading, exchanges, and the critical components of a trading system, the book quickly moves on to the nitty-gritty of optimizing hardware and your operating system for low-latency trading, such as bypassing the kernel, memory allocation, and the danger of context switching. Monitoring your system’s performance is vital, so you’ll also get up to speed with logging and statistics. As you move beyond the traditional high-frequency trading programming languages, such as C++ and Java, you’ll learn how to use Python to achieve high levels of performance. And what book on trading would be complete without diving into cryptocurrency? By the end of this book, you’ll be ready to take on the markets with high-frequency trading systems. What you will learn • Understand the architecture of high-frequency trading systems • Boost system performance to achieve the lowest possible latency • Leverage the power of Python, C++, and Java to build your trading systems • Bypass your kernel and optimize your operating system • Use static analysis to improve code development • Use C++ templates and Java multithreading for super-low latency • Apply your knowledge to cryptocurrency trading Who This Book Is For This book is for software engineers, quantitative developers or researchers, and DevOps engineers who want to understand the technical side of high-frequency trading systems and the optimizations that are needed to get to ultra-low latency systems. Prior experience working with C++ and Java will help you grasp the topics covered in this book.
Maximum Trading Gains with Anchored VWAP: The Perfect Combination of Price, Time, and Volume - Original PDF
نویسندگان: خلاصه: My goal for this book is to give you a thorough understanding of the VWAP and the AVWAP so you can learn how to interpret market action more accurately. This knowledge will allow you to make better trades.
From Data to Trade: A Machine Learning Approach to Quantitative Trading - Original PDF
نویسندگان: خلاصه: Machine Learning has revolutionized the field of quantitative trading, enabling traders to develop and implement sophisticated trading strategies that leverage large amounts of data and advanced modeling techniques. In this book, we provide a comprehensive overview of Machine Learning for quantitative trading, covering the fundamental concepts, techniques, and applications of Machine Learning in the financial industry. We start by introducing the key concepts and challenges of Machine Learning for quantitative trading, including feature engineering, model selection, and backtesting. We then delve into the various Machine Learning approaches that are commonly used in quantitative trading, including supervised learning, unsupervised learning, and reinforcement learning. We also discuss the challenges and best practices of implementing Machine Learning models in the live market, including the role of data quality, the importance of risk management, and the need for ongoing model monitoring and validation. Throughout the book, we provide numerous examples and case studies to illustrate the concepts and techniques discussed, and we also include practical tips and resources to help traders and practitioners get started with Machine Learning for quantitative trading. This book is an essential resource for anyone looking to gain a deeper understanding of how Machine Learning is transforming the world of finance. This groundbreaking work offers a unique perspective on the use of Machine Learning in the financial markets, as it was created by an advanced Artificial Intelligence (AI) using its own Machine Learning algorithms to analyze vast amounts of data and construct a comprehensive guide on the subject. Machine Learning is a type of artificial intelligence that enables computers to learn and adapt without being explicitly programmed. It involves the use of algorithms and statistical models to analyze data and make predictions or decisions based on the patterns and trends that it identifies. In Machine Learning, a computer is trained to recognize patterns in data by being presented with a large number of examples of the patterns that it should recognize. As the computer processes these examples, it "learns" the characteristics of the patterns and becomes better at recognizing them. Once the computer has learned to recognize the patterns, it can then be used to make predictions or decisions based on new data that it has not seen before. There are many different types of machine learning, including supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Each type of Machine Learning involves a different approach to training the computer and making predictions or decisions based on the data. Machine Learning is used in a wide range of applications, including image and speech recognition, natural language processing (NLP), recommendation systems, and fraud detection. It has the potential to transform many different industries by automating tasks that would be difficult or impossible for humans to perform, and by enabling computers to make decisions and predictions based on data in a way that is more accurate and efficient than human judgment. In “From Data to Trade: A Quantitative Approach to Machine Learning,” readers will learn about the latest techniques and approaches for using Machine Learning in quantitative trading, as well as practical advice for implementing these methods in their own trading strategies. From basic concepts to advanced techniques, this book covers it all and is an invaluable resource for traders at any level of experience.
Trading For Dummies (For Dummies (Business & Personal Finance)) - Original PDF
نویسندگان: خلاصه: Become a savvy trader and make money in both up and down markets These days, the market is volatile, and you need to know how to ride the waves and navigate the changing tides. Trading For Dummies is for investors in search of a clear guide to trading stocks in any type of market. Inside, you'll get sample stock charts, position trading tips and techniques, and fresh ways to analyze trends and indicators. Learn how to make smart decisions by identifying the stocks, bonds, funds, and commodities that will net you the maximum gain. Assume more risk, reap more benefits, build a more aggressive portfolio, and enjoy the greater gains that come with short- and medium-term trading methods. Learn about due diligence, key indicator analysis, and reading market trends Trade successfully in downward market trends and during recessions Use the latest tools to create your own charts and make smart decisions Profit from ETFs, bonds, and commodities, along with good old-fashioned stocks
Self of the Therapist in Medical Settings: A Sociocultural and Systemic Perspective - Original PDF
نویسندگان: خلاصه: This brief explores how the “person” of the therapist is developed when training and working in medical settings. It highlights important and often unspoken topics such as the personal, professional, cultural, ethical, and competency dilemmas new clinicians regularly face. The brief also addresses how personal experience with illness, death, cultural differences, and stigma may impact professionals in everyday practice. Topics featured in this Brief include: Helpful tips and tricks for new professionals entering a medical setting for the first time. Working with patients who suffer from chronic and terminal illnesses. Sociocultural norms and values that are often present in a medical setting. A new framework for identifying and treating professional burnout. How to handle ethical situations in medical organizations. Self of the Therapist in Medical Settings is a must-have resource for clinicians, professionals, supervisors, and faculty working in medical settings.
Clinical Methods in Medical Family Therapy (Focused Issues in Family Therapy) - Original PDF
نویسندگان: خلاصه: This landmark text describes research-informed practices and applications of Medical Family Therapy (MedFT) across a range of care environments and clinical populations (e.g., family medicine, obstetrics and gynecology, psychiatry, alcohol and drug treatment, community health centers, and military and veteran health systems). It is a timely release for a rapidly growing field. It includes the work of some of MedFT’s most innovative leaders, who expertly: illustrate MedFT in action across primary, secondary, tertiary, and other unique health contexts describe the make-up of healthcare teams tailored to each chapter’s distinct environment(s) highlight fundamental knowledge and critical skillsets across diverse healthcare contexts detail research-informed practices for MedFTs who treat patients, couples, families, and communities Clinical Methods in Medical Family Therapy is a comprehensive source for any behavioral health student, trainee, or professional looking to understand the necessary skills for MedFTs entering the healthcare workforce. It is also an essential read for trainers and instructors who are covering the fundamental MedFT knowledge and skills across diverse healthcare contexts. This text was written to be applicable for a wide variety of healthcare disciplines, including family therapy, counseling nursing, medicine, psychology and social work.
Advanced Methods in Family Therapy Research: a focus on validity and change - Original PDF
نویسندگان: خلاصه: I (L.J.) remember when I started graduate school as a new student in the field of marriage and family therapy (MFT). One of the required classes in my first semester was statistics. I was an engineering major and I enjoy math so I thought statistics would be fun. The teacher was great, and I learned a lot. The one downside to the experience was that the course was taught in the agriculture department. The class focused mostly on analysis of variance (ANOVA), and the instructor would draw a 2 × 2 or larger plot on the chalk- board and say something like, “You can randomly assign conditions to each square in your field, and then you plant your seeds in the randomly assigned quadrant, and you can ‘see’ what happens and calculate an ANOVA.” After a few class periods of plot drawing and hearing examples from agriculture, I felt like I was starting to learn what an ANOVA was and how to calculate it. But I was missing the application to people. So, being the good graduate student that I was, I raised my hand and asked, “How do you do this with people?” The instructor replied, “You don’t.” I was dumbfounded. Why was I taking this class if I could not apply what I was learning to people? Why was I taking this class from someone who was a fine teacher but did not know how to apply this information to people? As I progressed through graduate school and took other statistics and research methods courses, I was able to fill in the gaps and learn how to apply statistics to people. I also learned how much more compli- cated research was when trying to apply what I had learned about researching individual people to researching more complex configurations that included couples and families.
Elements of Mathematics for Economics and Finance - PDF
نویسندگان: خلاصه: Based on over 15 years’ experience in the design and delivery of successful first-year courses, this book equips undergraduates with the mathematical skills required for degree courses in economics, finance, management and business studies. The book starts with a summary of basic skills and takes its readers as far as constrained optimisation helping them to become confident and competent in the use of mathematical tools and techniques that can be applied to a range of problems in economics and finance. Designed as both a course text and a handbook, the book assumes little prior mathematical knowledge beyond elementary algebra and is therefore suitable for students returning to mathematics after a long break. The fundamental ideas are described in the simplest mathematical terms, highlighting threads of common mathematical theory in the various topics. Features include: a systematic approach: ideas are touched upon, introduced gradually and then consolidated through the use of illustrative examples; several entry points to accommodate differing mathematical backgrounds; numerous worked examples and exercises to illustrate the theory and applications; full solutions to exercises, available to lecturers via the web. Vass Mavron is Professor of Mathematics in the Institute of Mathematical and Physical Sciences at the University of Wales Aberystwyth. Tim Phillips is Professor of Mathematics and Professorial Fellow in the School of Mathematics at Cardiff University.
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