2021. Nicholas Mangee. Cambridge University Press.
“Where there is novelty, there is instability. Where there is instability, there is uncertainty. Where there is uncertainty, there are narratives – narratives are the currency of uncertainty.”
Nicholas MangeeAssociate Professor of Finance at Georgia Southern University’s Parker College of Business, begins with a proof that encompasses the issue he addresses and the compelling reason investors are fascinated by the brand new pondering that addresses it.
This detailed stock market study attempts to increase Nobel Prize winner Robert Shiller’s development of narrative economics, although Mangee’s focus is on novel information embedded in textual news narratives. Using a series of text-based indices to capture uncertainty and ambiguity in unplanned messages, Mangee measures the impact of stories narratives on stock behavior.
News reports are stories and narratives that contain unique information that can not be easily qualified or assigned to probability estimates to quantify risk. This novel information confronts investors with “Knightian uncertainty” (i.e., the shortcoming to measure probabilities of future conditions, as described by Chicago economist Frank Knight). Mangee shapes advances in text evaluation and categorization into a technique for measuring nonquantitative information that affects stock prices and enriches the discussion of stock price behavior by incorporating the mountains of latest and unplanned information in news reports. Trying to categorize and measure the impact of stories and the accompanying narrative is a frightening task, but this book represents a major advance that’s price an investor’s time.
Text evaluation through natural language processing and machine learning, which has gone beyond the conventional planned announcement of macroeconomic and company-specific information, has turn into the innovative of quantitative finance research. Mangee links this evaluation to the brand new conception of narrative economy as a driver of moods and expectations. He focuses on measuring uncertainty and ambiguity to expand our knowledge of stock drivers beyond normally planned and repeatable data. Stock market volatility and changes in factor behavior are found to be related to the flow of unique information collected in financial news reporting.
The book begins with the so-called novelty narrative hypothesis (NNH) and links this idea to Knightian uncertainty. The NNH states that unplanned and unique information that is available in the shape of narratives can’t be easily obstructed but can still influence stock behavior. Novel, rare and unexpected information is subject to interpretation through narratives or stories in our financial press because there isn’t any good method to convert this information into measurable risks. These novel narratives influence stock behavior whilst they supply explanations for uncertain events.
For Mangee, the connection between unique news and stock market forecasts, an area not typically explored, can provide explanations for increased volatility, breaks in model behavior and parameter uncertainty. Unique textual information and novel data could be systematized, encoded, and clustered into categories and indices to offer meaningful information that may aid our understanding of stock behavior. Using many years of knowledge from leading news organizations, the writer creates so-called Knightian Uncertainty (KU) indices for macro and micro data (i.e., enterprise-level data).
Mangee first introduces us to text evaluation using Google trends and word cluster maps to reveal how investment themes change in financial news. What attracts the eye of stories organizations in a given period can change significantly over time. Based on this high-level evaluation, the writer uses the news evaluation platform RavenPack to categorize text evaluation into macro and micro news categories. These are further divided into indices of uncertainty, sentiment, recency, relevance and aggregate event volume, based on different characterizations to categorize news events. The resulting categorizations represent an unlimited effort to aggregate information from tens of millions of stories across quite a few news reporting services over many years to form tons of of clusters that could be aggregated based on their stock-based importance. Millions of latest stories are grouped and categorized into nearly 1,400 event categories to form indices as tools for measuring various types of uncertainty.
These text information indices are related to fluctuations in stock market volatility. Stock volatility is caused not only by surprises in planned news, but in addition by the multitude of unplanned and random recent data that could be reflected in market reactions. For example, a rise in KU indices, which measure novel narrative news, results in a rise in stock volatility. Regime changes in stock style and behavior and changes in model parameters could also be related to fluctuations in unscheduled, unique information embedded in our news reports. Examining unplanned fluctuations in novel news provides insight into market instability that improves our understanding of the complexities of the stock market. What is relevant to investors will change over time depending on mood and focus.
This comprehensive book is aimed toward an educational audience and addresses several difficult research topics related to uncertainty and textual narratives. However, the important thing conclusions and messages are accessible to most financial professionals. Planned and measurable news is vital, but so is the continual flow of commentary and interpretation of the unique information entering the markets every day. Detailed and comprehensive evaluation of text data gives recent intending to market sentiment and the impact of stories on stock prices.
Exploring stock reactions by converting textual narratives into measurable indices is more likely to be of great interest to many investors searching for to know market volatility. It represents a brand new direction to potentially cracking the code on stock market predictions. Mangee provides a solid introduction to a novel approach to explaining stock instability; Still, the complexity of sifting through all the information and attempting to make meaning of it remains to be in its infancy and doesn’t translate easily into investing rules. With novelty comes narrative and uncertainty, however the reader will still be left wondering: What’s next?
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