Lecture

Artificial Intelligence in Finance

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Description

This lecture, moderated by the instructor, explores the applications of artificial intelligence in finance, including trading, investing, risk management, and marketing of financial services. The event features talks, a panel discussion, and showcases by FinTech companies. It also introduces a new research program at EPFL focusing on the intersection of finance and technology.

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Related concepts (24)

Data science

Data science is an interdisciplinary academic field that uses statistics, scientific computing, scientific methods, processes, algorithms and systems to extract or extrapolate knowledge and insights from noisy, structured, and unstructured data. Data science also integrates domain knowledge from the underlying application domain (e.g., natural sciences, information technology, and medicine). Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession.

Data

In common usage and statistics, data (USˈdætə; UKˈdeɪtə) is a collection of discrete or continuous values that convey information, describing the quantity, quality, fact, statistics, other basic units of meaning, or simply sequences of symbols that may be further interpreted formally. A datum is an individual value in a collection of data. Data is usually organized into structures such as tables that provide additional context and meaning, and which may themselves be used as data in larger structures.

Big data

Big data primarily refers to data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many entries (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. Though used sometimes loosely partly because of a lack of formal definition, the interpretation that seems to best describe big data is the one associated with a large body of information that we could not comprehend when used only in smaller amounts.

Value investing

Value investing is an investment that involves buying securities that appear underpriced by some form of fundamental analysis. The various forms of value investing derive from the investment philosophy first taught by Benjamin Graham and David Dodd at Columbia Business School in 1928, and subsequently developed in their 1934 text Security Analysis. The early value opportunities identified by Graham and Dodd included stock in public companies trading at discounts to book value or tangible book value, those with high dividend yields, and those having low price-to-earning multiples, or low price-to-book ratios.

Investment

Investment is traditionally defined as the "commitment of resources to achieve later benefits". If an investment involves money, then it can be defined as a "commitment of money to receive more money later". From a broader viewpoint, an investment can be defined as "to tailor the pattern of expenditure and receipt of resources to optimise the desirable patterns of these flows". When expenditure and receipts are defined in terms of money, then the net monetary receipt in a time period is termed as cash flow, while money received in a series of several time periods is termed as cash flow stream.

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