Simon Thompson - Böcker
160 kr
Skickas inom 7-10 vardagar
Have you ever wondered how the top City traders make big profits from share trading? Do you know why the best investors know exactly when the market is going to rise or fall? And do you wish you could do the same?
By following 20 hard and fast rules,Trading Secrets shows you how you can make the same high returns as experienced investors and traders. Using historical, economic and technical trend analysis from the last fifty years, it identifies the ways for you to capitalise on such events as the clocks going back or moving forward, religious holidays, major sporting events and even the US presidential election.
Written for both experienced investors and also those with little knowledge of the stock market, Simon Thompson’s practical investing guide offers trading strategies that you can use over the short-term or the long-term. For instance, do you know how daylight changes affect how the stock market performs and, more importantly, how to make big gains by trading on this knowledge? Or do you know which sector has massively outperformed the market in the first quarter of the year – posting a quarterly return of 12 per cent – in all bar four years in the past three decades?
Trading Secrets uncovers all and more importantly explains why these trends occur, so that you can be confident your investments will pay off, even when the market is falling.
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Green and Sustainable Finance
Principles and Practice in Banking, Investment and Insurance
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Green and Sustainable Finance
Principles and Practice in Banking, Investment and Insurance
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Politics and the Emotions
The Affective Turn in Contemporary Political Studies
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Kun sinä olet ruuhkassa, minä pelaan golfia! (While You're in a Traffic Jam, I'm Playing Golf!)
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Skickas inom 5-8 vardagar
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Tillfälligt slut
The go-to guide in machine learning projects from design to production. No ML skills required!
In Managing Machine Learning Projects, you will learn essential machine learning project management techniques, including:
Understanding an ML project's requirements Setting up the infrastructure for the project and resourcing a team Working with clients and other stakeholders Dealing with data resources and bringing them into the project for use Handling the lifecycle of models in the project Managing the application of ML algorithms Evaluating the performance of algorithms and models Making decisions about which models to adopt for delivery Taking models through development and testing Integrating models with production systems to create effective applications Steps and behaviours for managing the ethical implications of ML technologyAbout the technology
Companies of all shapes, sizes, and industries are investing in machine learning (ML). Unfortunately, around 85% of all ML projects fail. Managing machine learning projects requires adopting a different approach than you would take with standard software projects.
You need to account for large and diverse data resources, evaluate and track multiple separate models, and handle the unforeseeable risk of poor performance. Never fear — this book lays out the unique practices you will need to ensure your projects succeed!
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Authority Guide to Financial Forecasting for SMEs
Pain-free financials for finance and planning
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Skickas inom 3-6 vardagar
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