Return to site

Applying Natural Language Process For Investing

· NLP,Investing,Wall Street,Trading,Ai Investing

Applying Natural Language Process For Investing

Why can we apply the Natural Language Process (NLP) in quantitative analysis?

Traditional quantitative analysis is based on numbers, including macro data, industry data, enterprise fundamental data and market data. The data source used by each quant is basically the same, and strategies on quantitative ideas and algorithms are only things they can explore.

However, experience tells us that market sentiment is largely influenced by public opinions. Financial news reflects to a certain extent whether people are pessimistic or optimistic about the market.

The degree of attention to the industry, the sentiment of the wording, and the comments of economists all affect market trends.

In short, public opinion contains valuable information.

If such information can be extracted using NLP, it will expand the data source of quantitative analysis and increase the analysis dimension, which would undoubtedly be meaningful in analyzing the market's direction.

How can we apply the NLP in quantitative analysis?

There are many ways to apply Natural Language Processing to quant analysis, for example, word classification.

Bayes' theorem, building a corpus, or using GRU, LSTM and other neural network algorithms for sentiment analysis allow us to classify words based on their meaning and tone.

But before we take any method, we should first have an idea of the NLP pipeline.

After the processor carries out these steps, we can now analyze the text.

Where can we apply the NLP in quantitative analysis?

One of the most important resources we can apply the NLP to is financial statements released by the SEC. These documents have long been used as a valuable source of information for making investment decisions.

But it is undeniable that for investors, sorting out these reports is often tedious.

In some cases, financial disclosures are used by companies to hide the fact and the effect of changing accounting rules, which might hurt stock prices. Having the ability to detect these warning signs in financial reports sets apart the elite investors from the average ones.

Through Natural Language Processing however, investors can quickly and efficiently catch these obscure points and get an idea of the current situation and the expectation of future performance from management teams.

Another resource we can use NLP on is the daily market news. Big news usually causes large price movement instantly, and sometimes due to overshoot, it reverses later. Thus, NLP is a perfect tool to analyze the news within milliseconds and make trading decisions instantly.

However, unlike financial statements which are well-structured, these multimedia contents are unstructured data and even harder to be understood directly by computer. To process unstructured data, sentiment analysis (a subfield of natural language processing) is the best method to estimate it.

Simply speaking, sentiment uses the emotion of different words to measure the quality of the news.

The basic sentiment looks at the polarity of the news: good, bad, or neutral.

More advanced sentiment analysis can further express more sophisticated emotional details, such as “anger,” “surprise,” or “beyond expectation.” Some typical trading strategies could be following the sentiment directly.

News sentiment is just a fact. In order to pass to the market, they need to be processed by human beings.

Thus, public sentiment may also play an equally important role. We know from psychological research that emotions play an important role in human decision-making processes.

Behavioral finance further proves that financial decision-making is largely driven by emotions. So we have reason to assume that public sentiment can drive stock market prices like news. This is seen in a recent study where analysts were able to use the mood of Twitter by using NLP on tweets and predicting the stock market.

My Experience With Coronavirus

Why did Coronavirus Spread so Fast?

Coronavirus and Globalization Moving Forward

Disinfecting Surfaces Against Coronavirus

Contagion Risks from Coronavirus

Coronavirus Oxygen Supplementation 101

Coronavirus: The Global Economic Impact

Home Care for Coronavirus

Coronavirus Causes Long Term Problems?

Online Coronavirus Scams Proliferate

What Is The True Coronavirus Case Fatality Rate For Young People?

How Likely Are Young People to be Hospitalized With Coronavirus?

Living On The Edge of A New Society

Coronavirus Will Test the Limits of Our Hospitals

Coronavirus Catapults Global Testing Innovation

Spain Suffers Under Coronavirus

Data, Models & Misinformation on the Coronavirus

Origins of the Coronavirus

Coronavirus Travels the Silk Road

Coronavirus Attacks Italy's Sick and Elderly

Is the New Coronavirus Drug a Cure?

What is the Mystery of Germany's Low Coronavirus Fatality Rate?

Coronavirus & the Economy

The World Will Be More Technologically Advanced After the COVID-19 Pandemic

Why has the Coronavirus Not Exploded in Japan?

Italy's Coronavirus Death Rate is Falling

Conquering The Coronavirus

Coronavirus Speeds Up Robotic Revolution

Economic Depression Will Destroy More Lives Than Coronavirus

Can Hydroxychloroquine be Used to Treat Coronavirus?

Northern Italy & Wuhan: Partners for Better or Worse

The Race for the Coronavirus Cure

How Did Taiwan Manage the Coronavirus so Well?

What is the US Coronavirus Fatality Rate?

Travel Ban Saves Airlines Billions

Coronavirus Superspreader?

Deep Learning Detects Coronavirus

Singapore's Coronavirus Patients Have a 0% Mortality Rate So Far... Why?

AI is Mapping the Coronavirus and Inferring its Possible Economic Impact

Coronavirus: Fact from Fiction

Coronavirus Attacks Italy's Sick and Elderly

Interview with NASA Astronaut Scott Kelly: An American Hero​

13 Questions With General David Petraeus

Why Choose Machine Learning Investing Over A Traditional Financial Advisor?

Interview With Home Depot Co-Founder Ken Langone

Interview with the Inventor of Amazon's Alexa

Automation and the Rebirth of American Retail

China Debuts Stealth Unmanned Combat Aerial Vehicle

Sweden's Economy Embraces AI & Automation

Austria's Automated Ai & Robotic Future Is Now

Nuclear Submarines: A 7,000 Lb Swiss Watch

Ai Can Write Its Own Computer Program

On Black Holes: Gateway to Another Dimension, or Ghosts of Stars’ Pasts?

Egypt's Artificial Intelligence Future

Supersonic Travel: The Future of Aviation

Was Our Moon Once Habitable?

The Modern Global Arms Race

NASA Seeks New Worlds

Cowboy Turned Space Surgeon

Shedding Light on Dark Matter: Using Machine Learning to Unravel Physics’ Hardest Questions

When High-Tech Meets Low-Tech Economy: Ai & the Construction Industry

Aquaponics: How Advanced Technology Grows Vegetables In The Desert

The World Cup Does Not Have a Lasting Positive Impact on Hosting Countries

Artificial Intelligence is Transforming the Forex Market

Do Machines Dream? Inside the Dreams of a Machine

Can Ai Replace Human Ski Coaches?

America’s Next Spy Plane

Faster than Sound and Undetectable by Radar

The Implications of Machine Learning on Condensed Matter Physics & Quantum Computing

Crafting Eco-Sustainability: WTC and Environmental Sustainability

Can Ai Transform Swimming?

Argentina's AI Future: Reversing a Century of Decline

Tennis & Artificial Intelligence

Kazakhstan's Ai Aspirations

Peru's Ai Future Will Drive Economic Growth

The Colombian Approach to the AI Revolution

How AI Can Explain Its Thinking

Singapore: Ai & Robotic City

Ai in New Zealand

Brazil & Artificial Intelligence​

Denmark & Ai

Can Ai Replace Human Ski Coaches?

Tennis & Artificial Intelligence

Written by Harrison Pan, Edited by Han Cui & Alexander Fleiss

Citation:

‘Finding Alpha: A Quantitative Approach to Building Trading Strategies’, Igor Tulchinsky, P50 & P91

All Posts
×

Almost done…

We just sent you an email. Please click the link in the email to confirm your subscription!

OK