Moving averages are a great way to provide support and resistance levels among other uses. There are many types of moving averages and in this article, we will discuss the Triangular Moving Average and some strategies revolving around it. For more on other types of moving averages, feel free to check the below article…
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In our recent work, we detail an AI and machine learning mechanism able to assist in correlating a large body of text with numerical data series used to describe financial performance as it evolves over time. Our deep learning-based system pulls out from large amounts of textual data potentially relevant and useful textual descriptions that explain the performance of a financial metric of interest – without the need of human experts or labelled data.
The post IBM’s Squawk Bot AI helps make sense of financial data flood appeared first on IBM Research Blog.
Anyone who’s ever been on an earnings call knows company executives already tend to look at the world through rose-colored glasses, but a new study by economics and machine learning researchers says that’s getting worse, thanks to Machine Learning.
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At a time when more companies are building machine learning models, Arthur.ai wants to help by ensuring the model accuracy doesn’t begin slipping over time, thereby losing its ability to precisely measure what it was supposed to. As demand for this type of tool has increased this year, in spite of the pandemic, the startup announced a $15 million Series A today.
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When it comes to finance, ‘black swans’ are rare and unexpected events that impact global activity. For example, the coronavirus pandemic that caused a global economic crisis in 2020. As every year, Saxo Bank released its predictions on 10 events that could affect global markets in 2021.
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Tecton.ai, the startup founded by three former Uber engineers who wanted to bring the machine learning feature store idea to the masses, announced a $35 million Series B today, just seven months after announcing their $20 million Series A.
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Where would you invest in an endless world of the Pandemic? Pharmaceuticals, 5G network, Apple stock, cloud storage? Well, if you believed in no end to lockdowns, you’d probably invest in all the above and diversify. That’s precisely what Buffett and his team at Berkshire Hathaway have done. So, let me walk you through Buffett’s eight most significant moves during the last quarter.
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Artificial intelligence (AI) is revolutionizing the transformation of interaction with money, and how consumers and companies alike access and manage their finances. AI in finance encompasses everything from chatbot assistants to fraud detection and task automation. AI is helping the financial industry to streamline and optimize processes ranging from credit decisions to quantitative trading and financial risk management. I’ve put together a rundown of how Artificial Intelligence can be used in finance leading the way.
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Reinforcement learning (RL) is used to automate decision-making in a variety of domains, including games, autoscaling, finance, robotics, recommendations, and supply chain. Launched at AWS re:Invent 2018, Amazon SageMaker RL helps you quickly build, train, and deploy policies learned by RL.
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The 3 main types of technical debt are: deliberate, accidental/ outdated design, and bit rot. Just as smart financial debt can help you reach major life goals faster, not all technical debt is bad, and managing it well can yield tremendous benefits for your company.
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Curated list of 2020 Tech Landscape Maps from around the world.
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The COVID19 crisis has been playing out globally for over half a year, or almost a year counting its early phase in China. It’s been hurting a lot of sectors, but one particular sector stood to benefit — Fintech.
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A lot of definitions and formulations of entropy are available. What in general is true is that entropy is used to measure information, surprise, or uncertainty regarding experiments’ possible outcomes. In particular, Shannon entropy is the one that is used most frequently in statistics and machine learning. For this reason, it’s the focus of our attention here.
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An easy to use trading simulator to test trading (ML/AI) algorithms and strategies on Python.
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One of Bitcoin’s strengths and the thing that makes it unique in the finance world is its radical transparency. Blockchain data is like a window, you can see right through it. But if Blockchain data is a window, it often feels less like the one in your apartment to look out of (solemnly during a pandemic, possibly), and more like this:
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Banks have come a long way in their digital journey. From the advent of ATMs in the 1960s to AI-powered chatbots, fraud detectors, and digital advisers. Let’s look into the various ways AI benefits banks.
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Today, in several aspects of the world of finance, machine learning is playing a crucial role, from loan acceptance to wealth management, to risk evaluation. However, few functionally-savvy practitioners see a clear understanding of how many ML cases mature into everyday use.
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Irrespective of the type and scale of the business, ranging from a remotely operating technology business to a multinational corporation, there are some financial mistakes that founders should avoid at all costs.
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There’s nothing stagnant about the financial services industry any longer.
Tectonic shifts in technology have created positive and transformational
reverberations in the world of personal finance. And the more we understand these shifts, the more informed decisions we can make around spending, saving, and investing.
While AI isn’t ready to replace humans, Elkan suggested, it has a unique ability to provide actionable guidance based on large quantities of data — assuming companies are realistic about its capabilities and limitations.
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