Investing, while a rational pursuit in theory , is highly influenced by human emotions and social dynamics. The phenomenon of herd behavior , where investors follow the majority, making decisions based on the actions of others rather than their own analysis, is well-documented in the world of finance. Herd behavior can lead to market bubbles, as well as their inevitable bursts, causing significant economic fallout. One field that is actively working on understanding and predi

Deep learning, a subset of machine learning, has made significant strides over the last decade, enabling advancements in areas like...

The groundbreaking study by Charles Jin and Martin Rinard offers a compelling exploration of language models, specifically those trained...

Nash Equilibrium , named after the mathematician John Forbes Nash Jr. , is a fundamental concept in the field of game theory , providing a solution concept of a non-cooperative game involving two or more players. In such a game, a Nash Equilibrium occurs when each player is assumed to know the strategies of the other players, and no player has anything to gain by changing only their own strategy. This principle can be translated into various real-world scenarios, and in th

The influence of social media on human emotions and behavior has become a subject of great interest in recent years. Researchers have...

Financial engineering, a field interconnecting finance, mathematics, and computational tools, is designed to tackle complex financial...

Artificial Intelligence (AI) has been an influential factor in various fields, and investing is no exception. Investors and financial...

The General Data Protection Regulation (GDPR) in Europe and the California Consumer Privacy Act (CCPA) in the United States are...

Causal inference is a core principle of scientific reasoning and is crucial in many fields, including finance and investing. While the phrase " correlation does not imply causation " is often repeated, the practical implications and application of this in finance are perhaps not as well understood. This article aims to shed light on the topic of causal inference in finance, including what it is, why it's important, and how it can be applied, with practical examples. What is

In the world of economics, finance, and decision theory, utility plays a pivotal role in shaping our understanding of human behavior. The...

Large language models such as GPT-4, developed by OpenAI, are transformative tools in the field of artificial intelligence (AI). They...

The advent of Large Language Models (LLMs) like GPT-Series has propelled the field of natural language processing (NLP) to new heights. These models can generate human-like text, answer questions, translate languages, and even write poetry. However, despite their capabilities, they come with certain limitations, one of the most significant being token limits. In this article, we'll delve into what these token limits are, how they affect various use cases, techniques to wor

In the world of finance and investing, the principle-agent problem presents itself in various forms, posing challenges for individuals,...

Active inference is a theoretical framework in the field of artificial intelligence (AI) that seeks to explain how intelligent agents can...

Prompt engineering is a specialized field within AI and ML that focuses on designing effective and efficient prompts to generate desired...

Large Language Models (LLMs) , with their capacity to understand and generate human-like text, are transforming the financial industry. From multimodal systems that analyze multiple types of data to a multi-model approach utilizing various LLMs with different capabilities, these innovations are reshaping the way we approach financial services. Another significant aspect to consider is the use of open-source versus closed , proprietary models, and the implications of each app