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News analytics

News analytics is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand News analytics rather than just read about it. In short: In trading strategy, news analysis refers to the measurement of the various qualitative and quantitative attributes of textual (unstructured data) news stories. Some of these attributes are: sentiment, relevance, and novelty.

Key takeaways

  • News analytics belongs to science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect News analytics to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of News analytics from memory before moving on to harder problems.

Reference excerpt

In trading strategy, news analysis refers to the measurement of the various qualitative and quantitative attributes of textual (unstructured data) news stories. Some of these attributes are: sentiment, relevance, and novelty. Expressing news stories as numbers and metadata permits the manipulation of everyday information in a mathematical and statistical way. This data is often used in financial markets as part of a trading strategy or by businesses to judge market sentiment and make better business decisions. News analytics are usually derived through automated text analysis and applied to digital texts using elements from natural language processing and machine learning such as latent semantic analysis, support vector machines, "bag of words" among other techniques.

Applications and strategies The application of sophisticated linguistic analysis to news and social media has grown from an area of research to mature product solutions since 2007. News analytics and news sentiment calculations are now routinely used by both buy-side and sell-side in alpha generation, trading execution, risk management, and market surveillance and compliance. There is however a good deal of variation in the quality, effectiveness and completeness of currently available solutions. A large number of companies use news analysis to help them make better business decisions. Academic researchers have become interested in news analysis especially with regards to predicting stock price movements, volatility and traded volume. Provided a set of values such as sentiment and relevance as well as the frequency of news arrivals, it is possible to construct news sentiment scores for multiple asset classes such as equities, Forex, fixed income, and commodities. Sentiment scores can be constructed at various horizons to meet the different needs and objectives of high and low frequency trading strategies, whilst characteristics such as direction and volatility of asset returns as well as the traded volume may be addressed more directly via the construction of tailor-made sentiment scores. Scores are generally constructed as a range of values. For instance, values may range between 0 and 100, where values above and below 50 convey positive and negative sentiment, respectively.

Absolute return strategies The objective of absolute return strategies is absolute (positive) returns regardless of the direction of the financial market. To meet this objective, such strategies typically involve opportunistic long and short positions in selected instruments with zero or limited market exposure. In statistical terms, absolute return strategies should have very low correlation with the market return. Typically, hedge funds tend to employ absolute return strategies. Below, a few examples show how news analysis can be applied in the absolute return strategy space with the purpose to identify alpha opportunities applying a market neutral strategy or based on volatility trading. Example 1 Scenario: The gap between the news sentiment scores for direction, S {\displaystyle S} , of Company X {\displaystyle X} and Market Y {\displaystyle Y} has moved beyond + 20 {\displaystyle +20} . That is, S X − S Y {\displaystyle S_{X}-S_{Y}} ≥ 20 {\displaystyle 20} . Action: Buy the stock on Company X {\displaystyle X} and short the future on Market Y {\displaystyle Y} . Exit Strategy: When the gap in the news sentiment scores for direction of Company X {\displaystyle X} and Market Y {\displaystyle Y} has disappeared, S X − S Y {\displaystyle S_{X}-S_{Y}} = 0 {\displaystyle 0} , sell the stock on Company X {\displaystyle X} and go long the future on Market Y {\displaystyle Y} to close the positions. Example 2 Scenario: The news sentiment score for volatility of Company X {\displaystyle X} goes above 70 {\displaystyle 70} out of 100 {\displaystyle 100} indicating an expected volatility above the option implied volatility. Action: Buy a short-dated straddle (the purchase of both a put and a call) on the stock of Company

X {\displaystyle X} . Exit Strategy: Keep the straddle on Company X {\displaystyle X} until expiry or until a certain profit target has been reached.

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with News analytics

Start with the simplest possible case. Write down what News analytics claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to News analytics before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about News analytics ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of News analytics

In research
News analytics appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses News analytics in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
News analytics is common in secondary-school and first-year university syllabi. It links to neighbouring topics Natural language processing, so understanding it makes those chapters shorter.
In everyday life
Look for News analytics outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study News analytics in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what News analytics means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain News analytics out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is News analytics in simple terms?

In trading strategy, news analysis refers to the measurement of the various qualitative and quantitative attributes of textual (unstructured data) news stories. Some of these attributes are: sentiment, relevance, and novelty.

Why does News analytics matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study News analytics?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on News analytics.

Tags

  • Natural language processing

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