| building automated trading systems: Building Automated Trading Systems Benjamin Van Vliet, 2007-03-07 Over the next few years, the proprietary trading and hedge fund industries will migrate largely to automated trade selection and execution systems. Indeed, this is already happening. While several finance books provide C++ code for pricing derivatives and performing numerical calculations, none approaches the topic from a system design perspective. This book will be divided into two sections: programming techniques and automated trading system ( ATS ) technology and teach financial system design and development from the absolute ground up using Microsoft Visual C++.NET 2005. MS Visual C++.NET 2005 has been chosen as the implementation language primarily because most trading firms and large banks have developed and continue to develop their proprietary algorithms in ISO C++ and Visual C++.NET provides the greatest flexibility for incorporating these legacy algorithms into working systems. Furthermore, the .NET Framework and development environment provide the best libraries and tools for rapid development of trading systems. The first section of the book explains Visual C++.NET 2005 in detail and focuses on the required programming knowledge for automated trading system development, including object oriented design, delegates and events, enumerations, random number generation, timing and timer objects, and data management with STL.NET and .NET collections. Furthermore, since most legacy code and modeling code in the financial markets is done in ISO C++, this book looks in depth at several advanced topics relating to managed/unmanaged/COM memory management and interoperability. Further, this book provides dozens of examples illustrating the use of database connectivity with ADO.NET and an extensive treatment of SQL and FIX and XML/FIXML. Advanced programming topics such as threading, sockets, as well as using C++.NET to connect to Excel are also discussed at length and supported by examples. The second section of the book explains technological concerns and design concepts for automated trading systems. Specifically, chapters are devoted to handling real-time data feeds, managing orders in the exchange order book, position selection, and risk management. A .dll is included in the book that will emulate connection to a widely used industry API ( Trading Technologies, Inc.'s XTAPI ) and provide ways to test position and order management algorithms. Design patterns are presented for market taking systems based upon technical analysis as well as for market making systems using intermarket spreads. As all of the chapters revolve around computer programming for financial engineering and trading system development, this book will educate traders, financial engineers, quantitative analysts, students of quantitative finance and even experienced programmers on technological issues that revolve around development of financial applications in a Microsoft environment and the construction and implementation of real-time trading systems and tools. - Teaches financial system design and development from the ground up using Microsoft Visual C++.NET 2005 - Provides dozens of examples illustrating the programming approaches in the book - Chapters are supported by screenshots, equations, sample Excel spreadsheets, and programming code |
| building automated trading systems: Building Winning Algorithmic Trading Systems, + Website Kevin J. Davey, 2014-07-21 Develop your own trading system with practical guidance and expert advice In Building Algorithmic Trading Systems: A Trader's Journey From Data Mining to Monte Carlo Simulation to Live Training, award-winning trader Kevin Davey shares his secrets for developing trading systems that generate triple-digit returns. With both explanation and demonstration, Davey guides you step-by-step through the entire process of generating and validating an idea, setting entry and exit points, testing systems, and implementing them in live trading. You'll find concrete rules for increasing or decreasing allocation to a system, and rules for when to abandon one. The companion website includes Davey's own Monte Carlo simulator and other tools that will enable you to automate and test your own trading ideas. A purely discretionary approach to trading generally breaks down over the long haul. With market data and statistics easily available, traders are increasingly opting to employ an automated or algorithmic trading system—enough that algorithmic trades now account for the bulk of stock trading volume. Building Algorithmic Trading Systems teaches you how to develop your own systems with an eye toward market fluctuations and the impermanence of even the most effective algorithm. Learn the systems that generated triple-digit returns in the World Cup Trading Championship Develop an algorithmic approach for any trading idea using off-the-shelf software or popular platforms Test your new system using historical and current market data Mine market data for statistical tendencies that may form the basis of a new system Market patterns change, and so do system results. Past performance isn't a guarantee of future success, so the key is to continually develop new systems and adjust established systems in response to evolving statistical tendencies. For individual traders looking for the next leap forward, Building Algorithmic Trading Systems provides expert guidance and practical advice. |
| building automated trading systems: Automated Option Trading Sergey Izraylevich Ph.D., Vadim Tsudikman, 2012-03-12 The first and only book of its kind, Automated Options Trading describes a comprehensive, step-by-step process for creating automated options trading systems. Using the authors’ techniques, sophisticated traders can create powerful frameworks for the consistent, disciplined realization of well-defined, formalized, and carefully-tested trading strategies based on their specific requirements. Unlike other books on automated trading, this book focuses specifically on the unique requirements of options, reflecting philosophy, logic, quantitative tools, and valuation procedures that are completely different from those used in conventional automated trading algorithms. Every facet of the authors’ approach is optimized for options, including strategy development and optimization; capital allocation; risk management; performance measurement; back-testing and walk-forward analysis; and trade execution. The authors’ system reflects a continuous process of valuation, structuring and long-term management of investment portfolios (not just individual instruments), introducing systematic approaches for handling portfolios containing option combinations related to different underlying assets. With these techniques, it is finally possible to effectively automate options trading at the portfolio level. This book will be an indispensable resource for serious options traders working individually, in hedge funds, or in other institutions. |
| building automated trading systems: Professional Automated Trading Eugene A. Durenard, 2013-10-04 An insider's view of how to develop and operate an automated proprietary trading network Reflecting author Eugene Durenard's extensive experience in this field, Professional Automated Trading offers valuable insights you won't find anywhere else. It reveals how a series of concepts and techniques coming from current research in artificial life and modern control theory can be applied to the design of effective trading systems that outperform the majority of published trading systems. It also skillfully provides you with essential information on the practical coding and implementation of a scalable systematic trading architecture. Based on years of practical experience in building successful research and infrastructure processes for purpose of trading at several frequencies, this book is designed to be a comprehensive guide for understanding the theory of design and the practice of implementation of an automated systematic trading process at an institutional scale. Discusses several classical strategies and covers the design of efficient simulation engines for back and forward testing Provides insights on effectively implementing a series of distributed processes that should form the core of a robust and fault-tolerant automated systematic trading architecture Addresses trade execution optimization by studying market-pressure models and minimization of costs via applications of execution algorithms Introduces a series of novel concepts from artificial life and modern control theory that enhance robustness of the systematic decision making—focusing on various aspects of adaptation and dynamic optimal model choice Engaging and informative, Proprietary Automated Trading covers the most important aspects of this endeavor and will put you in a better position to excel at it. |
| building automated trading systems: Trading Systems Emilio Tomasini, Urban Jaekle, 2009 Trading Systems offers an insight into what a trader should know and do in order to achieve success on the markets. |
| building automated trading systems: Automated Trading with R Chris Conlan, 2016-09-28 Learn to trade algorithmically with your existing brokerage, from data management, to strategy optimization, to order execution, using free and publicly available data. Connect to your brokerage’s API, and the source code is plug-and-play. Automated Trading with R explains automated trading, starting with its mathematics and moving to its computation and execution. You will gain a unique insight into the mechanics and computational considerations taken in building a back-tester, strategy optimizer, and fully functional trading platform. The platform built in this book can serve as a complete replacement for commercially available platforms used by retail traders and small funds. Software components are strictly decoupled and easily scalable, providing opportunity to substitute any data source, trading algorithm, or brokerage. This book will: Provide a flexible alternative to common strategy automation frameworks, like Tradestation, Metatrader, and CQG, to small funds and retail traders Offer an understanding of the internal mechanisms of an automated trading system Standardize discussion and notation of real-world strategy optimization problems What You Will Learn Understand machine-learning criteria for statistical validity in the context of time-series Optimize strategies, generate real-time trading decisions, and minimize computation time while programming an automated strategy in R and using its package library Best simulate strategy performance in its specific use case to derive accurate performance estimates Understand critical real-world variables pertaining to portfolio management and performance assessment, including latency, drawdowns, varying trade size, portfolio growth, and penalization of unused capital Who This Book Is For Traders/practitioners at the retail or small fund level with at least an undergraduate background in finance or computer science; graduate level finance or data science students |
| building automated trading systems: Python for Algorithmic Trading Yves Hilpisch, 2020-11-12 Algorithmic trading, once the exclusive domain of institutional players, is now open to small organizations and individual traders using online platforms. The tool of choice for many traders today is Python and its ecosystem of powerful packages. In this practical book, author Yves Hilpisch shows students, academics, and practitioners how to use Python in the fascinating field of algorithmic trading. You'll learn several ways to apply Python to different aspects of algorithmic trading, such as backtesting trading strategies and interacting with online trading platforms. Some of the biggest buy- and sell-side institutions make heavy use of Python. By exploring options for systematically building and deploying automated algorithmic trading strategies, this book will help you level the playing field. Set up a proper Python environment for algorithmic trading Learn how to retrieve financial data from public and proprietary data sources Explore vectorization for financial analytics with NumPy and pandas Master vectorized backtesting of different algorithmic trading strategies Generate market predictions by using machine learning and deep learning Tackle real-time processing of streaming data with socket programming tools Implement automated algorithmic trading strategies with the OANDA and FXCM trading platforms |
| building automated trading systems: Automated Stock Trading Systems: A Systematic Approach for Traders to Make Money in Bull, Bear and Sideways Markets Laurens Bensdorp, 2020-03-31 Consistent, benchmark-beating growth, combined with reduced risk, are the Holy Grail of traders everywhere. Laurens Bensdorp has been achieving both for more than a decade. By combining multiple quantitative trading systems that perform well in different types of markets--bull, bear, or sideways--his overall systematized and automated system delivers superlative results regardless of overall market behavior. In his second book, Automated Stock Trading Systems, Bensdorp details a non-correlated, multi-system approach you can understand and build to suit yourself. Using historical price action to develop statistical edges, his combined, automated systems have been shown to deliver simulated consistent high double-digit returns with very low draw downs for the last 24 years, no matter what the market indices have done. By following his approach, traders can achieve reliable, superlative returns without excessive risk. |
| building automated trading systems: Building Reliable Trading Systems Keith Fitschen, 2013-05-09 An award winning system developer explains how to create, test, and implement a profitable trading system Traders have long been drawn to the idea of translating their strategies and ideas into trading systems. While successful trading systems have been developed, in most cases, they work very well for a period of time in specific markets, but perform less well across all markets in all time frames. Nobody understands this better than author Keith Fitschen—a thought-leader in trading system development—and now, with Trading Strategy Generation + Website, he shares his extensive experience in this field with you. Trading Strategy Generation skillfully explains how to take market insights or trading ideas and develop them into a robust trading system. In it, Fitschen describes the critical steps a trader needs to follow, including: translating the market insight into a rules-based approach; determining entry and exit points; testing against historical data; and integrating money management and position sizing into the system. Written by an award winning system developer who has actively traded his systems for thirty years Introduces new ideas on money management and position sizing for different markets Details exactly what it takes to build, test, and implement a profitable technical trading system A companion Website contains supplementary material, including Excel spreadsheets designed to rate the strength of entry signals and provide money management guidance based on market volatility and portfolio correlations Written with the serious trader in mind, Trading Strategy Generation is an accessible guide to building a system that will generate realistic returns over time. |
| building automated trading systems: Trading Systems and Methods, + Website Perry J. Kaufman, 2013-01-29 The ultimate guide to trading systems, fully revised and updated For nearly thirty years, professional and individual traders have turned to Trading Systems and Methods for detailed information on indicators, programs, algorithms, and systems, and now this fully revised Fifth Edition updates coverage for today's markets. The definitive reference on trading systems, the book explains the tools and techniques of successful trading to help traders develop a program that meets their own unique needs. Presenting an analytical framework for comparing systematic methods and techniques, this new edition offers expanded coverage in nearly all areas, including trends, momentum, arbitrage, integration of fundamental statistics, and risk management. Comprehensive and in-depth, the book describes each technique and how it can be used to a trader's advantage, and shows similarities and variations that may serve as valuable alternatives. The book also walks readers through basic mathematical and statistical concepts of trading system design and methodology, such as how much data to use, how to create an index, risk measurements, and more. Packed with examples, this thoroughly revised and updated Fifth Edition covers more systems, more methods, and more risk analysis techniques than ever before. The ultimate guide to trading system design and methods, newly revised Includes expanded coverage of trading techniques, arbitrage, statistical tools, and risk management models Written by acclaimed expert Perry J. Kaufman Features spreadsheets and TradeStation programs for a more extensive and interactive learning experience Provides readers with access to a companion website loaded with supplemental materials Written by a global leader in the trading field, Trading Systems and Methods, Fifth Edition is the essential reference to trading system design and methods updated for a post-crisis trading environment. |
| building automated trading systems: Algorithmic Trading Ernie Chan, 2013-05-28 Praise for Algorithmic TRADING “Algorithmic Trading is an insightful book on quantitative trading written by a seasoned practitioner. What sets this book apart from many others in the space is the emphasis on real examples as opposed to just theory. Concepts are not only described, they are brought to life with actual trading strategies, which give the reader insight into how and why each strategy was developed, how it was implemented, and even how it was coded. This book is a valuable resource for anyone looking to create their own systematic trading strategies and those involved in manager selection, where the knowledge contained in this book will lead to a more informed and nuanced conversation with managers.” —DAREN SMITH, CFA, CAIA, FSA, Managing Director, Manager Selection & Portfolio Construction, University of Toronto Asset Management “Using an excellent selection of mean reversion and momentum strategies, Ernie explains the rationale behind each one, shows how to test it, how to improve it, and discusses implementation issues. His book is a careful, detailed exposition of the scientific method applied to strategy development. For serious retail traders, I know of no other book that provides this range of examples and level of detail. His discussions of how regime changes affect strategies, and of risk management, are invaluable bonuses.” —ROGER HUNTER, Mathematician and Algorithmic Trader |
| building automated trading systems: Automation of Trading Machine for Traders Jacinta Chan, 2019-12-02 This Palgrave Pivot innovatively combines new methods and approaches to building dynamic trading systems to forecast future price direction in today’s increasingly difficult and volatile financial markets. The primary purpose of this book is to provide a structured course for building robust algorithmic trading models that forecast future price direction. Chan provides insider information and insights on trading strategies; her knowledge and experience has been gained over two decades as a trader in foreign exchange, stock and derivatives markets. She guides the reader to build, evaluate, and test the predictive ability and the profitability of abnormal returns of new hybrid forecasting models. |
| building automated trading systems: Learn Algorithmic Trading Sourav Ghosh, Sebastien Donadio, 2019-11-07 Understand the fundamentals of algorithmic trading to apply algorithms to real market data and analyze the results of real-world trading strategies Key Features Understand the power of algorithmic trading in financial markets with real-world examples Get up and running with the algorithms used to carry out algorithmic trading Learn to build your own algorithmic trading robots which require no human intervention Book Description It's now harder than ever to get a significant edge over competitors in terms of speed and efficiency when it comes to algorithmic trading. Relying on sophisticated trading signals, predictive models and strategies can make all the difference. This book will guide you through these aspects, giving you insights into how modern electronic trading markets and participants operate. You'll start with an introduction to algorithmic trading, along with setting up the environment required to perform the tasks in the book. You'll explore the key components of an algorithmic trading business and aspects you'll need to take into account before starting an automated trading project. Next, you'll focus on designing, building and operating the components required for developing a practical and profitable algorithmic trading business. Later, you'll learn how quantitative trading signals and strategies are developed, and also implement and analyze sophisticated trading strategies such as volatility strategies, economic release strategies, and statistical arbitrage. Finally, you'll create a trading bot from scratch using the algorithms built in the previous sections. By the end of this book, you'll be well-versed with electronic trading markets and have learned to implement, evaluate and safely operate algorithmic trading strategies in live markets. What you will learn Understand the components of modern algorithmic trading systems and strategies Apply machine learning in algorithmic trading signals and strategies using Python Build, visualize and analyze trading strategies based on mean reversion, trend, economic releases and more Quantify and build a risk management system for Python trading strategies Build a backtester to run simulated trading strategies for improving the performance of your trading bot Deploy and incorporate trading strategies in the live market to maintain and improve profitability Who this book is for This book is for software engineers, financial traders, data analysts, and entrepreneurs. Anyone who wants to get started with algorithmic trading and understand how it works; and learn the components of a trading system, protocols and algorithms required for black box and gray box trading, and techniques for building a completely automated and profitable trading business will also find this book useful. |
| building automated trading systems: Building Winning Trading Systems with Tradestation George Pruitt, John R. Hill, 2012-08-15 The updated edition of the guide to building trading systems that can keep pace with the market The stock market is constantly evolving, and coupled with the new global economic landscape, traders need to radically rethink the way they do business at home and abroad. Enter Building Winning Trading Systems, Second Edition, the all-new incarnation of the established text on getting the most out of the trading world. With technology now a pervasive element of every aspect of trading, the issue has become how to create a new system that meets the demands of the altered financial climate, and how to make it work. Giving voice to the question on every trader and investor's lips, the book asks, How can we build a trading system that will be paramount for our increasingly stressed markets? The answer? Establish mechanical trading systems that remove human emotion from the equation and form the cornerstone of a complete trading plan and with greater agility, characteristics that are more important than ever given the kinetic pace of the markets. Presents an all-new strategy for trading systems that will show traders how to create systems that will work in the twenty first century Expert advice from highly respected trading authority, George Pruitt Includes a new website featuring updated TradeStation code and shows how to use the world's best investment software platform to develop and utilize trading systems that really work Once again paving the way for traders who want to adapt to their environment, Building Winning Trading Systems, Second Edition combines expertise in indicator design and system building in one indispensable volume. |
| building automated trading systems: Machine Learning for Algorithmic Trading Stefan Jansen, 2020-07-31 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. |
| building automated trading systems: Building Trading Bots Using Java Shekhar Varshney, 2016-12-07 Build an automated currency trading bot from scratch with java. In this book, you will learn about the nitty-gritty of automated trading and have a closer look at Java, the Spring Framework, event-driven programming, and other open source APIs, notably Google's Guava API. And of course, development will all be test-driven with unit testing coverage. The central theme of Building Trading Bots Using Java is to create a framework that can facilitate automated trading on most of the brokerage platforms, with minimum changes. At the end of the journey, you will have a working trading bot, with a sample implementation using the OANDA REST API, which is free to use. What You'll Learn Find out about trading bots Discover the details of tradeable instruments and apply bots to them Track and use market data events Place orders and trades Work with trade/order and account events Who This Book Is For Experienced programmers new to bots and other algorithmic trading and finance techniques. |
| building automated trading systems: An Introduction to Algorithmic Trading Edward Leshik, Jane Cralle, 2011-09-19 Interest in algorithmic trading is growing massively – it’s cheaper, faster and better to control than standard trading, it enables you to ‘pre-think’ the market, executing complex math in real time and take the required decisions based on the strategy defined. We are no longer limited by human ‘bandwidth’. The cost alone (estimated at 6 cents per share manual, 1 cent per share algorithmic) is a sufficient driver to power the growth of the industry. According to consultant firm, Aite Group LLC, high frequency trading firms alone account for 73% of all US equity trading volume, despite only representing approximately 2% of the total firms operating in the US markets. Algorithmic trading is becoming the industry lifeblood. But it is a secretive industry with few willing to share the secrets of their success. The book begins with a step-by-step guide to algorithmic trading, demystifying this complex subject and providing readers with a specific and usable algorithmic trading knowledge. It provides background information leading to more advanced work by outlining the current trading algorithms, the basics of their design, what they are, how they work, how they are used, their strengths, their weaknesses, where we are now and where we are going. The book then goes on to demonstrate a selection of detailed algorithms including their implementation in the markets. Using actual algorithms that have been used in live trading readers have access to real time trading functionality and can use the never before seen algorithms to trade their own accounts. The markets are complex adaptive systems exhibiting unpredictable behaviour. As the markets evolve algorithmic designers need to be constantly aware of any changes that may impact their work, so for the more adventurous reader there is also a section on how to design trading algorithms. All examples and algorithms are demonstrated in Excel on the accompanying CD ROM, including actual algorithmic examples which have been used in live trading. |
| building automated trading systems: Build an Automated Stock Trading System in Excel Lawrence H. Klamecki, 2012-12-07 Build an Automated Stock Trading System in Excel is a step-by-step how to guide on building a sophisticated automated stock trading model using Microsoft Excel. Microsoft's Visual Basic (VBA) language is used in conjunction with Excel's user interface, formulas, and calculation capabilities to deliver a powerful and flexible trading tool. The Model includes five proven technical indicators (ADX, moving average crossovers, stochastics, Bollinger bands, and DMI). You are guided in a detailed fashion through creating worksheets, files, ranges, indicator formulas, control buttons, DDE/Active-X links, and code modules. The model incorporates both trend-trading and swing-trading features. The swing-trading feature can be turned on or off, depending upon your investing style. After building the model, you simply import the data you need, run the model automatically with a click of a button, and make your trading decisions. The system operates with your choice of FREE ASCII .TXT files available on the internet (from Yahoo Finance or other provider), or your subscription data service (with our without a DDE link). The model can be used alone or in conjunction with your existing fundamental and market analysis to improve investment timing and avoid unprofitable situations. A separate pre-built Backtesting Model is included by email for historical analysis and testing various stocks and time periods. What You Get: A Tremendous 3-in-1 Value! - A complete how to guide PLUS VBA Code and FAQs sections. - Detailed instructions on importing price data into Excel using a DDE link or Yahoo Finance. - Pre-built Backtesting Model in Excel with graphs and trade statistics for your historical analysis. Features & Benefits: - Learn to integrate Excel, VBA, formulas, and data sources into a profitable trading tool. - Acquire unique knowledge applicable to any Excel modeling or analysis project. - Save money by eliminating recurring software costs. - Calculate trading signals on a large number of stocks within seconds. Technical Requirements: - Microsoft Excel - 2 megabytes disk space (for files and stock data storage) - Intraday, daily, or weekly Open-High-Low-Close-Volume price data - Internet access |
| building automated trading systems: Systematic Trading Robert Carver, 2015-09-14 This is not just another book with yet another trading system. This is a complete guide to developing your own systems to help you make and execute trading and investing decisions. It is intended for everyone who wishes to systematise their financial decision making, either completely or to some degree. Author Robert Carver draws on financial theory, his experience managing systematic hedge fund strategies and his own in-depth research to explain why systematic trading makes sense and demonstrates how it can be done safely and profitably. Every aspect, from creating trading rules to position sizing, is thoroughly explained. The framework described here can be used with all assets, including equities, bonds, forex and commodities. There is no magic formula that will guarantee success, but cutting out simple mistakes will improve your performance. You'll learn how to avoid common pitfalls such as over-complicating your strategy, being too optimistic about likely returns, taking excessive risks and trading too frequently. Important features include: - The theory behind systematic trading: why and when it works, and when it doesn't. - Simple and effective ways to design effective strategies. - A complete position management framework which can be adapted for your needs. - How fully systematic traders can create or adapt trading rules to forecast prices. - Making discretionary trading decisions within a systematic framework for position management. - Why traditional long only investors should use systems to ensure proper diversification, and avoid costly and unnecessary portfolio churn. - Adapting strategies depending on the cost of trading and how much capital is being used. - Practical examples from UK, US and international markets showing how the framework can be used. Systematic Trading is detailed, comprehensive and full of practical advice. It provides a unique new approach to system development and a must for anyone considering using systems to make some, or all, of their investment decisions. |
| building automated trading systems: The Ultimate Algorithmic Trading System Toolbox + Website George Pruitt, 2016-06-20 The accessible, beneficial guide to developing algorithmic trading solutions The Ultimate Algorithmic Trading System Toolbox is the complete package savvy investors have been looking for. An integration of explanation and tutorial, this guide takes you from utter novice to out-the-door trading solution as you learn the tools and techniques of the trade. You'll explore the broad spectrum of today's technological offerings, and use several to develop trading ideas using the provided source code and the author's own library, and get practical advice on popular software packages including TradeStation, TradersStudio, MultiCharts, Excel, and more. You'll stop making repetitive mistakes as you learn to recognize which paths you should not go down, and you'll discover that you don't need to be a programmer to take advantage of the latest technology. The companion website provides up-to-date TradeStation code, Excel spreadsheets, and instructional video, and gives you access to the author himself to help you interpret and implement the included algorithms. Algorithmic system trading isn't really all that new, but the technology that lets you program, evaluate, and implement trading ideas is rapidly evolving. This book helps you take advantage of these new capabilities to develop the trading solution you've been looking for. Exploit trading technology without a computer science degree Evaluate different trading systems' strengths and weaknesses Stop making the same trading mistakes over and over again Develop a complete trading solution using provided source code and libraries New technology has enabled the average trader to easily implement their ideas at very low cost, breathing new life into systems that were once not viable. If you're ready to take advantage of the new trading environment but don't know where to start, The Ultimate Algorithmic Trading System Toolbox will help you get on board quickly and easily. |
| building automated trading systems: Automated Option Trading Sergey Izraylevich, Vadim Tsudikman, 2012 The first and only book of its kind, Automated Options Trading describes a comprehensive, step-by-step process for creating automated options trading systems. Using the authors' techniques, sophisticated traders can create powerful frameworks for the consistent, disciplined realization of well-defined, formalized, and carefully-tested trading strategies based on their specific requirements. Unlike other books on automated trading, this book focuses specifically on the unique requirements of options, reflecting philosophy, logic, quantitative tools, and valuation procedures that are completely different from those used in conventional automated trading algorithms. Every facet of the authors' approach is optimized for options, including strategy development and optimization; capital allocation; risk management; performance measurement; back-testing and walk-forward analysis; and trade execution. The authors' system reflects a continuous process of valuation, structuring and long-term management of investment portfolios (not just individual instruments), introducing systematic approaches for handling portfolios containing option combinations related to different underlying assets. With these techniques, it is finally possible to effectively automate options trading at the portfolio level. This book will be an indispensable resource for serious options traders working individually, in hedge funds, or in other institutions. |
| building automated trading systems: Expert Advisor Programming Gerard Desjardins, Andrew R. Young, 2009-12 Finally, the first comprehensive guide to MQL programming is here! Expert Advisor Programming guides you through the process of developing robust automated forex trading systems for the popular MetaTrader 4 platform. In this book, the author draws on several years of experience coding hundreds of expert advisors for retail traders worldwide. You'll learn how to program these common trading tasks, and much more: - Place market, stop and limit orders. - Accurately calculate stop loss and take profit prices. - Calculate lot size based on risk. - Add flexible trailing stops to your orders. - Count, modify and close multiple orders at once. - Verify trading conditions using indicators and price data. - Create flexible and reusable source code functions. - Add advanced features such as timers, email alerts and Martingale lot sizing. - Avoid common trading errors and easily troubleshoot your programs. - Adjustments for fractional pip brokers and FIFO. - Plus, learn how to create your own custom indicators and scripts! Whether you're a beginner or an experienced programmer, Expert Advisor Programming can help you realize your automated trading ideas in the shortest amount of time. This book features dozens of code examples with detailed explanations, fully-functioning example programs, and reusable functions that you can use in your own expert advisors! |
| building automated trading systems: BUILDING AUTOMATED TRADING STRATEGIES George Protonotarios, 2018-09-21 This eBook includes general information and educational resources for explaining the modern use of automated trading, plus some practical information and advice on how to create a proprietary automated trading system. The optimization of a trading strategy through sophisticated backtesting and walk-through steps is maybe the most difficult part of strategy building. This eBook contains information on how to successfully backtest and optimize automated trading strategies. |
| building automated trading systems: Electronic and Algorithmic Trading Technology Kendall Kim, 2010-07-27 Electronic and algorithmic trading has become part of a mainstream response to buy-side traders' need to move large blocks of shares with minimum market impact in today's complex institutional trading environment. This book illustrates an overview of key providers in the marketplace. With electronic trading platforms becoming increasingly sophisticated, more cost effective measures handling larger order flow is becoming a reality. The higher reliance on electronic trading has had profound implications for vendors and users of information and trading products. Broker dealers providing solutions through their products are facing changes in their business models such as: relationships with sellside customers, relationships with buyside customers, the importance of broker neutrality, the role of direct market access, and the relationship with prime brokers. Electronic and Algorithmic Trading Technology: The Complete Guide is the ultimate guide to managers, institutional investors, broker dealers, and software vendors to better understand innovative technologies that can cut transaction costs, eliminate human error, boost trading efficiency and supplement productivity. As economic and regulatory pressures are driving financial institutions to seek efficiency gains by improving the quality of software systems, firms are devoting increasing amounts of financial and human capital to maintaining their competitive edge. This book is written to aid the management and development of IT systems for financial institutions. Although the book focuses on the securities industry, its solution framework can be applied to satisfy complex automation requirements within very different sectors of financial services – from payments and cash management, to insurance and securities. Electronic and Algorithmic Trading: The Complete Guide is geared toward all levels of technology, investment management and the financial service professionals responsible for developing and implementing cutting-edge technology. It outlines a complete framework for successfully building a software system that provides the functionalities required by the business model. It is revolutionary as the first guide to cover everything from the technologies to how to evaluate tools to best practices for IT management. - First book to address the hot topic of how systems can be designed to maximize the benefits of program and algorithmic trading - Outlines a complete framework for developing a software system that meets the needs of the firm's business model - Provides a robust system for making the build vs. buy decision based on business requirements |
| building automated trading systems: Algorithmic Trading & DMA Barry Johnson, 2010 |
| building automated trading systems: Trading Systems 2nd Edition Urban Jaekle, Emilio Tomasini, 2019-12-17 Completely revised and updated second edition, with new AmiBroker codes and new complete portfolio tests Every day, there are traders who make a fortune. It may seem that it seldom happens, but it does – as William Eckhardt, Ed Seykota, Jim Simons, and many others remind us. You can join them by using systems to manage your trading. This book explains how you can build a winning trading system. It is an insight into what a trader should know and do in order to achieve success in the markets, and it will show you why you don't need to be a rocket scientist to become successful. It shows how to adapt existing codes to the current market conditions, how to build a portfolio, and how to know when the moment has come to stop one system and use another one. There are three main parts to Trading Systems. Part One is a short, practical guide to trading systems development and evaluation. It condenses the authors' years of experience into a number of practical tips. It also forms the theoretical basis for Part Two, in which readers will find a step-by-step development process for building a trading system, covering everything from writing initial code to walk-forward analysis and money management. Two examples are provided, including a new beginning of the month trading system that works on over 20 different stock indices worldwide – from the US, to Europe, to Asian indices. Part Three shows you how to build portfolios in two different ways. The first method is to combine a number of different trading systems, for a number of different markets, into an effective portfolio of systems. The second method is a new approach to system development: it provides step-by-step instructions to trade a portfolio of hundreds of stocks using a Bollinger Band trading strategy. A trader can never really say they were successful, but only that they survived to trade another day; the black swan is always just around the corner. Trading Systems will help you find your way through the uncharted waters of systematic trading and show you what it takes to be among those that survive. |
| building automated trading systems: Hands-On Financial Trading with Python Jiri Pik, Sourav Ghosh, 2021-04-29 Build and backtest your algorithmic trading strategies to gain a true advantage in the market Key FeaturesGet quality insights from market data, stock analysis, and create your own data visualisationsLearn how to navigate the different features in Python's data analysis librariesStart systematically approaching quantitative research and strategy generation/backtesting in algorithmic tradingBook Description Creating an effective system to automate your trading can help you achieve two of every trader's key goals; saving time and making money. But to devise a system that will work for you, you need guidance to show you the ropes around building a system and monitoring its performance. This is where Hands-on Financial Trading with Python can give you the advantage. This practical Python book will introduce you to Python and tell you exactly why it's the best platform for developing trading strategies. You'll then cover quantitative analysis using Python, and learn how to build algorithmic trading strategies with Zipline using various market data sources. Using Zipline as the backtesting library allows access to complimentary US historical daily market data until 2018. As you advance, you will gain an in-depth understanding of Python libraries such as NumPy and pandas for analyzing financial datasets, and explore Matplotlib, statsmodels, and scikit-learn libraries for advanced analytics. As you progress, you'll pick up lots of skills like time series forecasting, covering pmdarima and Facebook Prophet. By the end of this trading book, you will be able to build predictive trading signals, adopt basic and advanced algorithmic trading strategies, and perform portfolio optimization to help you get —and stay—ahead of the markets. What you will learnDiscover how quantitative analysis works by covering financial statistics and ARIMAUse core Python libraries to perform quantitative research and strategy development using real datasetsUnderstand how to access financial and economic data in PythonImplement effective data visualization with MatplotlibApply scientific computing and data visualization with popular Python librariesBuild and deploy backtesting algorithmic trading strategiesWho this book is for If you're a financial trader or a data analyst who wants a hands-on introduction to designing algorithmic trading strategies, then this book is for you. You don't have to be a fully-fledged programmer to dive into this book, but knowing how to use Python's core libraries and a solid grasp on statistics will help you get the most out of this book. |
| building automated trading systems: Testing and Tuning Market Trading Systems Timothy Masters, 2018-10-26 Build, test, and tune financial, insurance or other market trading systems using C++ algorithms and statistics. You’ve had an idea and have done some preliminary experiments, and it looks promising. Where do you go from here? Well, this book discusses and dissects this case study approach. Seemingly good backtest performance isn't enough to justify trading real money. You need to perform rigorous statistical tests of the system's validity. Then, if basic tests confirm the quality of your idea, you need to tune your system, not just for best performance, but also for robust behavior in the face of inevitable market changes. Next, you need to quantify its expected future behavior, assessing how bad its real-life performance might actually be, and whether you can live with that. Finally, you need to find its theoretical performance limits so you know if its actual trades conform to this theoretical expectation, enabling you to dump the system if it does not live up to expectations. This book does not contain any sure-fire, guaranteed-riches trading systems. Those are a dime a dozen... But if you have a trading system, this book will provide you with a set of tools that will help you evaluate the potential value of your system, tweak it to improve its profitability, and monitor its on-going performance to detect deterioration before it fails catastrophically. Any serious market trader would do well to employ the methods described in this book. What You Will Learn See how the 'spaghetti-on-the-wall' approach to trading system development can be done legitimatelyDetect overfitting early in developmentEstimate the probability that your system's backtest results could have been due to just good luckRegularize a predictive model so it automatically selects an optimal subset of indicator candidatesRapidly find the global optimum for any type of parameterized trading systemAssess the ruggedness of your trading system against market changesEnhance the stationarity and information content of your proprietary indicatorsNest one layer of walkforward analysis inside another layer to account for selection bias in complex trading systemsCompute a lower bound on your system's mean future performanceBound expected periodic returns to detect on-going system deterioration before it becomes severeEstimate the probability of catastrophic drawdown Who This Book Is For Experienced C++ programmers, developers, and software engineers. Prior experience with rigorous statistical procedures to evaluate and maximize the quality of systems is recommended as well. |
| building automated trading systems: Quantitative Trading Systems, Second Edition Howard Bandy, 2011-06-02 |
| building automated trading systems: Automated Trading Strategies Using C# and Ninjatrader 7 Ryan M. Moore, 2014-07-22 In this book, we'll be walking hands-on-tutorial-style through the creation of an automated stock trading strategy using C# and the NinjaTrader platform, as well as methods for testing out its potential success. By the end of this book, you should be able to not only create a simple trading strategy, but also understand how to test it against historical market data, debug it, and even log data into a custom database for further analysis. Even if you have limited C# and trading strategy experience, the examples in this book will provide a great foundation for getting into automated trading and safely testing out strategy ideas before risking real money in the market. |
| building automated trading systems: Python Algorithmic Trading Cookbook Pushpak Dagade, 2020-08-28 Build a solid foundation in algorithmic trading by developing, testing and executing powerful trading strategies with real market data using Python Key FeaturesBuild a strong foundation in algorithmic trading by becoming well-versed with the basics of financial marketsDemystify jargon related to understanding and placing multiple types of trading ordersDevise trading strategies and increase your odds of making a profit without human interventionBook Description If you want to find out how you can build a solid foundation in algorithmic trading using Python, this cookbook is here to help. Starting by setting up the Python environment for trading and connectivity with brokers, you’ll then learn the important aspects of financial markets. As you progress, you’ll learn to fetch financial instruments, query and calculate various types of candles and historical data, and finally, compute and plot technical indicators. Next, you’ll learn how to place various types of orders, such as regular, bracket, and cover orders, and understand their state transitions. Later chapters will cover backtesting, paper trading, and finally real trading for the algorithmic strategies that you've created. You’ll even understand how to automate trading and find the right strategy for making effective decisions that would otherwise be impossible for human traders. By the end of this book, you’ll be able to use Python libraries to conduct key tasks in the algorithmic trading ecosystem. Note: For demonstration, we're using Zerodha, an Indian Stock Market broker. If you're not an Indian resident, you won't be able to use Zerodha and therefore will not be able to test the examples directly. However, you can take inspiration from the book and apply the concepts across your preferred stock market broker of choice. What you will learnUse Python to set up connectivity with brokersHandle and manipulate time series data using PythonFetch a list of exchanges, segments, financial instruments, and historical data to interact with the real marketUnderstand, fetch, and calculate various types of candles and use them to compute and plot diverse types of technical indicatorsDevelop and improve the performance of algorithmic trading strategiesPerform backtesting and paper trading on algorithmic trading strategiesImplement real trading in the live hours of stock marketsWho this book is for If you are a financial analyst, financial trader, data analyst, algorithmic trader, trading enthusiast or anyone who wants to learn algorithmic trading with Python and important techniques to address challenges faced in the finance domain, this book is for you. Basic working knowledge of the Python programming language is expected. Although fundamental knowledge of trade-related terminologies will be helpful, it is not mandatory. |
| building automated trading systems: Algorithmic Trading with Python Chris Conlan, 2020-04-09 Algorithmic Trading with Python discusses modern quant trading methods in Python with a heavy focus on pandas, numpy, and scikit-learn. After establishing an understanding of technical indicators and performance metrics, readers will walk through the process of developing a trading simulator, strategy optimizer, and financial machine learning pipeline. This book maintains a high standard of reprocibility. All code and data is self-contained in a GitHub repo. The data includes hyper-realistic simulated price data and alternative data based on real securities. Algorithmic Trading with Python (2020) is the spiritual successor to Automated Trading with R (2016). This book covers more content in less time than its predecessor due to advances in open-source technologies for quantitative analysis. |
| building automated trading systems: The Fourth Industrial Revolution Klaus Schwab, 2017-01-03 World-renowned economist Klaus Schwab, Founder and Executive Chairman of the World Economic Forum, explains that we have an opportunity to shape the fourth industrial revolution, which will fundamentally alter how we live and work. Schwab argues that this revolution is different in scale, scope and complexity from any that have come before. Characterized by a range of new technologies that are fusing the physical, digital and biological worlds, the developments are affecting all disciplines, economies, industries and governments, and even challenging ideas about what it means to be human. Artificial intelligence is already all around us, from supercomputers, drones and virtual assistants to 3D printing, DNA sequencing, smart thermostats, wearable sensors and microchips smaller than a grain of sand. But this is just the beginning: nanomaterials 200 times stronger than steel and a million times thinner than a strand of hair and the first transplant of a 3D printed liver are already in development. Imagine “smart factories” in which global systems of manufacturing are coordinated virtually, or implantable mobile phones made of biosynthetic materials. The fourth industrial revolution, says Schwab, is more significant, and its ramifications more profound, than in any prior period of human history. He outlines the key technologies driving this revolution and discusses the major impacts expected on government, business, civil society and individuals. Schwab also offers bold ideas on how to harness these changes and shape a better future—one in which technology empowers people rather than replaces them; progress serves society rather than disrupts it; and in which innovators respect moral and ethical boundaries rather than cross them. We all have the opportunity to contribute to developing new frameworks that advance progress. |
| building automated trading systems: Python for Automated Trading Systems J P Morgan, 2024-08-06 Transform Your Trading Game with Automated Bots: A Comprehensive Guide to Python for Automated Trading Systems Unlock the future of trading with Python for Automated Trading Systems: Building Your Own Bots for Stock and Crypto Markets. This essential guide dives deep into the world of automated trading using Python, providing you with the tools and knowledge to build your own trading bots. Key Features and Benefits: Tailored for Cryptocurrency Trading: Specialized for Digital Currencies: Learn to develop a crypto automated trading system specifically designed for the dynamic world of cryptocurrency trading. Stay Ahead in the Market: Gain insights into the latest trends and techniques in the burgeoning field of digital currencies. Build Powerful Trading Bots: From Concept to Deployment: Follow step-by-step guidance on how to automate stock trading using Python, taking you from idea to deployment. Utilize Advanced Python Libraries: Leverage powerful Python libraries to enhance the functionality and efficiency of your trading bots. Enhance Trading Efficiency: Automate Trading Processes: Reduce manual intervention and increase accuracy by automating your trading strategies using Python. Optimize Performance: Fine-tune your bots for optimal performance, ensuring consistent and reliable trading results with an automated trading system Python. Boost Your Profitability: Maximize Returns: Implement strategies that maximize your trading returns through data-driven decisions and automated systems. Minimize Risks: Learn to identify and mitigate potential risks, ensuring more profitable and secure trades with automated trading systems that work. Practical and Accessible: Hands-On Learning: Engage with practical examples and projects that provide real-world applications of the concepts covered. Suitable for All Levels: Whether you're a beginner or an experienced professional, this book offers valuable insights and guidance tailored to all skill levels. Who Should Read This Book? Python Programmers: Enhance your coding skills with finance-specific applications using Python for automated trading. Web Developers: Integrate financial analytics and trading systems into your projects with ease. Trading Enthusiasts: Develop and implement automated trading bots to improve your trading efficiency. Students: Build a solid foundation in automated trading systems, preparing you for a successful career in finance and technology. Technology Professionals: Stay ahead in your field by mastering the latest tools and techniques in automated trading Why Choose This Book? Comprehensive Coverage: Gain a thorough understanding of both stock and cryptocurrency markets, and how to navigate them with automated bots. Optimized for Success: Whether you're new to automated trading or looking to refine your strategies, this book offers valuable insights and practical guidance to help you succeed. Elevate Your Trading Skills with Automated Bots! Don't miss this opportunity to revolutionize your trading approach. Add Python for Automated Trading Systems: Building Your Own Bots for Stock and Crypto Markets to your library and take the first step towards mastering the art of automated trading. Order your copy today and unlock the potential of automated trading using Python! |
| building automated trading systems: Mechanical Trading Systems Earik Beann, 2013-10-01 |
| building automated trading systems: Python for Finance Yves J. Hilpisch, 2018-12-05 The financial industry has recently adopted Python at a tremendous rate, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. Updated for Python 3, the second edition of this hands-on book helps you get started with the language, guiding developers and quantitative analysts through Python libraries and tools for building financial applications and interactive financial analytics. Using practical examples throughout the book, author Yves Hilpisch also shows you how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks. |
| building automated trading systems: Algorithmic and High-Frequency Trading Álvaro Cartea, Sebastian Jaimungal, José Penalva, 2015-08-06 The design of trading algorithms requires sophisticated mathematical models backed up by reliable data. In this textbook, the authors develop models for algorithmic trading in contexts such as executing large orders, market making, targeting VWAP and other schedules, trading pairs or collection of assets, and executing in dark pools. These models are grounded on how the exchanges work, whether the algorithm is trading with better informed traders (adverse selection), and the type of information available to market participants at both ultra-high and low frequency. Algorithmic and High-Frequency Trading is the first book that combines sophisticated mathematical modelling, empirical facts and financial economics, taking the reader from basic ideas to cutting-edge research and practice. If you need to understand how modern electronic markets operate, what information provides a trading edge, and how other market participants may affect the profitability of the algorithms, then this is the book for you. |
| building automated trading systems: Learn Algorithmic Trading with Python Jamal Sinclair O’Garro, 2022-01-14 Develop and deploy an automated electronic trading system with Python and the SciPy ecosystem. This book introduces you to the tools required to gather and analyze financial data through the techniques of data munging and data visualization using Python and its popular libraries: NumPy, pandas, scikit-learn, and Matplotlib. You will create a research environment using Jupyter Notebooks while leveraging open source back-testing software to analyze and experiment with several trading strategies. Next, you will measure the level of return and risk of a portfolio using measures such as Alpha, Beta, and the Sharpe Ratio. This will set the stage for the use of open source backtesting and scientific computing libraries such as zipline, NumPy, and scikit-learn to develop models that will help you identify, buy, and sell signals for securities in your portfolio and watch-list. With Learn Algorithmic Trading with Python you will explore key techniques used to analyze the performance of a portfolio and trading strategies and write unit tests on Python code that will send live orders to the market. What You'll Learn Analyze financial data with Pandas Use Python libraries to perform statistical reviews Review algorithmic trading strategies Assess risk management with NumPy and StatsModels Perform paper and Live Trading with IB Python API Write unit tests and deploy your trading system to the Cloud Who This Book Is For Software developers, data scientists, or students interested in Python and the SciPy ecosystem |
| building automated trading systems: Quantitative Trading with R Harry Georgakopoulos, 2015-02-02 Quantitative Finance with R offers a winning strategy for devising expertly-crafted and workable trading models using the R open source programming language, providing readers with a step-by-step approach to understanding complex quantitative finance problems and building functional computer code. |
| building automated trading systems: Following the Trend Andreas F. Clenow, 2012-11-21 During bull and bear markets, there is a group of hedge funds and professional traders which have been consistently outperforming traditional investment strategies for the past 30 odd years. They have shown remarkable uncorrelated performance and in the great bear market of 2008 they had record gains. These traders are highly secretive about their proprietary trading algorithms and often employ top PhDs in their research teams. Yet, it is possible to replicate their trading performance with relatively simplistic models. These traders are trend following cross asset futures managers, also known as CTAs. Many books are written about them but none explain their strategies in such detail as to enable the reader to emulate their success and create their own trend following trading business, until now. Following the Trend explains why most hopefuls fail by focusing on the wrong things, such as buy and sell rules, and teaches the truly important parts of trend following. Trading everything from the Nasdaq index and T-bills to currency crosses, platinum and live hogs, there are large gains to be made regardless of the state of the economy or stock markets. By analysing year by year trend following performance and attribution the reader will be able to build a deep understanding of what it is like to trade futures in large scale and where the real problems and opportunities lay. Written by experienced hedge fund manager Andreas Clenow, this book provides a comprehensive insight into the strategies behind the booming trend following futures industry from the perspective of a market participant. The strategies behind the success of this industry are explained in great detail, including complete trading rules and instructions for how to replicate the performance of successful hedge funds. You are in for a potentially highly profitable roller coaster ride with this hard and honest look at the positive as well as the negative sides of trend following. |
NYC Department of Buildings
Required safety training courses for construction site supervisors and workers. See highlights of DOB's actions to sanction and deter industry bad actors.
DOB Building Information Search - New York City
If you have any questions please review these Frequently Asked Questions, the Glossary, or call the 311 Citizen Service Center by dialing 311 or (212) NEW YORK outside of New York City.
33 Thomas Street - Wikipedia
33 Thomas Street (also known as the AT&T Long Lines Building) is a 550-foot-tall (170 m) windowless skyscraper in the Tribeca neighborhood of Lower Manhattan in New York City, …
20 famous buildings in New York City | CNN
Feb 18, 2020 · From soaring skyscrapers to hallowed entertainment venues, take a tour with CNN Style and discover fascinating facts and historical tidbits of 20 celebrated buildings: The bright …
Empire State Building: Visit the Top New York City Attraction
Enjoy a guided 90-minute tour that includes the building’s lovingly restored Art Deco lobby on 5th Avenue, the Celebrity Walk, and exhibits that celebrate the building’s history and heritage. Get …
Building Standards and Codes - Department of State
These Codes provide for the construction of safe, resilient, and energy efficient buildings throughout New York State.
Buildings and New Developments in New York City - StreetEasy
Find the perfect NYC building to move into by filter amenities like doorman, swimming pool, gym, parking, and laundry.
The 10 Tallest Buildings in New York City - TripSavvy
Jun 26, 2019 · New York City’s signature skyline has been a sight to behold since its first skyscraper went up in the late 19th century. Today, thousands of high-rise behemoths make up …
Most Beautiful NYC Buildings You Have to See Before You Die
Nov 30, 2018 · These stunning NYC buildings—from Flatiron to the World Trade—will have you falling in love with the city all over again. Whether it’s skyscrapers and art museums or …
Building - The Shed
The Shed’s Bloomberg Building, designed by Diller Scofidio + Renfro, Lead Architect, and Rockwell Group, Collaborating Architect, is an innovative 200,000-square-foot structure that …
NYC Department of Buildings
Required safety training courses for construction site supervisors and workers. See highlights of DOB's actions to sanction and deter industry bad actors.
DOB Building Information Search - New York City
If you have any questions please review these Frequently Asked Questions, the Glossary, or call the 311 Citizen Service Center by dialing 311 or (212) NEW YORK outside of New York City.
33 Thomas Street - Wikipedia
33 Thomas Street (also known as the AT&T Long Lines Building) is a 550-foot-tall (170 m) windowless skyscraper in the Tribeca neighborhood of Lower Manhattan in New York City, …
20 famous buildings in New York City | CNN
Feb 18, 2020 · From soaring skyscrapers to hallowed entertainment venues, take a tour with CNN Style and discover fascinating facts and historical tidbits of 20 celebrated buildings: The bright …
Empire State Building: Visit the Top New York City Attraction
Enjoy a guided 90-minute tour that includes the building’s lovingly restored Art Deco lobby on 5th Avenue, the Celebrity Walk, and exhibits that celebrate the building’s history and heritage. Get …
Building Standards and Codes - Department of State
These Codes provide for the construction of safe, resilient, and energy efficient buildings throughout New York State.
Buildings and New Developments in New York City - StreetEasy
Find the perfect NYC building to move into by filter amenities like doorman, swimming pool, gym, parking, and laundry.
The 10 Tallest Buildings in New York City - TripSavvy
Jun 26, 2019 · New York City’s signature skyline has been a sight to behold since its first skyscraper went up in the late 19th century. Today, thousands of high-rise behemoths make …
Most Beautiful NYC Buildings You Have to See Before You Die
Nov 30, 2018 · These stunning NYC buildings—from Flatiron to the World Trade—will have you falling in love with the city all over again. Whether it’s skyscrapers and art museums or …
Building - The Shed
The Shed’s Bloomberg Building, designed by Diller Scofidio + Renfro, Lead Architect, and Rockwell Group, Collaborating Architect, is an innovative 200,000-square-foot structure that …
