The Monthly Income Machine is NOT just another book that simply defines option terms, strategies, and when you might use various speculative approaches.It reveals instead a specific, detailed list of exact entry and trade management rules for the conservative investor seeking reliable monthly income... up to 8-10% per MONTH Return on Investment (ROI).The technique it offers is suitable for regular accounts, retirement accounts and any investor wanting to consistently seek profit from the markets with minimum and controllable risk.When the reader finishes this readable step-by-step guide to risk-adverse income investing, he will see why the principle it is built on is the way many pro's invest.
This is a book for people like us, and we all know who we are. We make our own hours, keep our own profits, chart our own way. We have things like gigs, contracts, clients, and assignments. All of us are working toward our dreams: doing our own work, on our own time, on our own terms. We have no real boss, no corporate nameplate, no cubicle of our very own. Unfortunately, we also have no 401(k)s and no one matching them, no benefits package, and no one collecting our taxes until April 15th. It’s time to take stock of where you are and where you want to be. Ask yourself: Who is planning for your retirement? Who covers your expenses when clients flake out and checks are late? Who is setting money aside for your taxes? Who is responsible for your health insurance? Take a good look in the mirror: You are. The Money Book for Freelancers, Part-Timers, and the Self-Employed describes a completely new, comprehensive system for earning, spending, saving, and surviving as an independent worker. From interviews with financial experts to anecdotes from real-life freelancers, plus handy charts and graphs to help you visualize key concepts, you’ll learn about topics including: • Managing Cash Flow When the Cash Isn’t Flowing Your Way • Getting Real About What You’re Really Earning • Tools for Getting Out of Debt and Into Financial Security • Saving Consistently When You Earn Irregularly • What To Do When a Client’s Check Doesn’t Come In • Health Savings Accounts and How To Use Them • Planning for Retirement, Taxes and Dreams—All On Your Own
Are you having trouble finding any kind of reasonable return for the risk in your investments? Do you stay up at night worrying about your money in the stock market? Does the financial system have you nervous? This informative and easy to read book will introduce you to an investment that will guarantee you returns on the downside, without limiting the upside. In fact, it will show you how to invest once and begin acquiring multiple income producing assets over time from that same initial investment (A Perpetual Passive Income Machine). As an accredited investor, you have more options than most. However, in our current ZIRP environment, getting a reasonable return requires a lot of risk. Investing in income producing real estate sounds great, but you don't have the time to master it. The Perpetual Passive Income Machine: A Proven 4-Step Process for Putting An Extra Paycheck In Your Pocket Every 30 Days will bust the myth that you can't get good returns for your risk, secured by a valuable real asset. Jim Small is an active real estate broker, Equity Marketing Specialist, holds a designation from the National Council of Exchangors and is an Associate Member of the Institute of Real Estate Management. Jenny, a user of the SANTÉ Realty Investments 10-30 Plan(tm), says, "I now have real professionals working for me and finding the best deals on real estate, taking all the risks, and I get my profit paid monthly." "The explanation of how Wall Street uses funny math when the calculate returns is worth the price of the book alone," says Fred B. In the book, Jim explains his brainchild, the SANTÉ Realty Investments 10-30 Plan(tm). This plan will: - Explain a simple 4-Step Process for getting a guaranteed return - Show you how to do it while someone else takes all the risk - Allow you to realize the returns of a real income-producing asset - Receive a guaranteed a minimum preferred investor return - Show you how to get a paycheck every 30 days - Learn the dirty little secret about stock market "returns" that Wall Street doesn't want you to know about, you will be shocked when you see it!! Follow the advice in this book and you can be off and receiving passive income paychecks in as little as 30 days, every 30 days thereafter. What is stopping your from getting out of the rat race and building your passive income portfolio the right way? Scroll to the top and click the "ADD TO CART" button. This book describes an investing program that is available to accredited investors.
Author of cult classics The Pumpkin Plan and The Toilet Paper Entrepreneur offers a simple, counterintuitive cash management solution that will help small businesses break out of the doom spiral and achieve instant profitability. Conventional accounting uses the logical (albeit, flawed) formula: Sales - Expenses = Profit. The problem is, businesses are run by humans, and humans aren't always logical. Serial entrepreneur Mike Michalowicz has developed a behavioral approach to accounting to flip the formula: Sales - Profit = Expenses. Just as the most effective weight loss strategy is to limit portions by using smaller plates, Michalowicz shows that by taking profit first and apportioning only what remains for expenses, entrepreneurs will transform their businesses from cash-eating monsters to profitable cash cows. Using Michalowicz's Profit First system, readers will learn that: · Following 4 simple principles can simplify accounting and make it easier to manage a profitable business by looking at bank account balances. · A small, profitable business can be worth much more than a large business surviving on its top line. · Businesses that attain early and sustained profitability have a better shot at achieving long-term growth. With dozens of case studies, practical, step-by-step advice, and his signature sense of humor, Michalowicz has the game-changing roadmap for any entrepreneur to make money they always dreamed of.
This book introduces machine learning methods in finance. It presents a unified treatment of machine learning and various statistical and computational disciplines in quantitative finance, such as financial econometrics and discrete time stochastic control, with an emphasis on how theory and hypothesis tests inform the choice of algorithm for financial data modeling and decision making. With the trend towards increasing computational resources and larger datasets, machine learning has grown into an important skillset for the finance industry. This book is written for advanced graduate students and academics in financial econometrics, mathematical finance and applied statistics, in addition to quants and data scientists in the field of quantitative finance. Machine Learning in Finance: From Theory to Practice is divided into three parts, each part covering theory and applications. The first presents supervised learning for cross-sectional data from both a Bayesian and frequentist perspective. The more advanced material places a firm emphasis on neural networks, including deep learning, as well as Gaussian processes, with examples in investment management and derivative modeling. The second part presents supervised learning for time series data, arguably the most common data type used in finance with examples in trading, stochastic volatility and fixed income modeling. Finally, the third part presents reinforcement learning and its applications in trading, investment and wealth management. Python code examples are provided to support the readers' understanding of the methodologies and applications. The book also includes more than 80 mathematical and programming exercises, with worked solutions available to instructors. As a bridge to research in this emergent field, the final chapter presents the frontiers of machine learning in finance from a researcher's perspective, highlighting how many well-known concepts in statistical physics are likely to emerge as important methodologies for machine learning in finance.
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.
Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures
Bill Spetrino was just an ordinary accountant more than 20 years ago when he discovered the best investment secret ever. Bill calls his secret “the dividend machine” -- and he has been sharing his secrets with hundreds of thousands of investors who have subscribed to his popular Dividend Machine newsletter, rated by Hulbert Digest as the #1 low risk investment letter. But many readers asked Bill to write a book about his secret and how ordinary investors can become millionaires just like him. Bill did just that. Now his new The Great American Dividend Machine reveals his own story, and how he went from becoming a middle-class accountant to having a net worth exceeding more than $5 million! Traders who jump from stock to stock in the hunt for a major Wall Street score often lose money or, at best, break even. That's not an acceptable fate for the retirement nest egg or for Bill. Instead, true investors trust Bill Spetrino's proven advice: "Keep investments boring and the rest of life fun and exciting." By valuing safety and income above all else, Spetrino guides the reader through the process of unearthing true bargains in the marketplace. Adhering to the author's model, The Great American Dividend Machine portfolio is composed of stocks that he picks using his unique system. The companies that pass Spetrino's rigorous, multi-step vetting process must have a number of key characteristics, such as: Resonant brand names Strong, competitive advantages in their industries Pristine balance sheets Capital to help survive and thrive in difficult markets Bill believes anyone can become a millionaire by ignoring the Wall Street pros and using his time-tested strategies
