The harms of terminology: why we should reject so-called “frontier AI” HealthManagement.org, The Journal, Volume 19, Issue 2, 2019, Artificial Hype How AI hype impacts the LGBTQ + community How AI lies, cheats, and grovels to succeed - and what we need to do about it Identifying...
Reinforcement learning Portfolio allocation Sentiment analysis Deep learning Stock trading 1. Introduction 1.1. Motivation Portfolio allocation is one of the most challenging and interesting problems in modern finance. This is because the stock market is a complex system [1], permeated by a web of in...
Here’sa bit of machine learning terminology as a refresher: theinput variablesinto this problem are the text of the emails. These input variables are also known asfeaturesorpredictorsorindependent variables. Theoutput variable—what we are trying to predict—is thelabel“spam” or “not spam.”...
Stock trading algorithms that analyze market data and execute trades. Narrow AI operates based on predefined algorithms and rules. This type of AI is highly specialized and cannot perform tasks outside its scope. Another common name for narrow AI isartificial narrow intelligence (ANI). On the oth...
Recognizing bases starts with two gauges: duration and depth. On the time side, flat bases can occur in as few as five weeks. Six weeks is enough time for a cup. All others, including a cup with handle, must be at least seven weeks long. The count begins in a stock's...
Research conducted by Harvard Business School professor Boris Groysberg revealed that executives who demonstrated strong command of business terminology were 60% more likely to be perceived as competent leaders by their peers and subordinates. This perception isn’t just about appearances – it directly...
Sousa answers, “I can think of two possible cases. The first case is the early exercise of an American call option on a dividend-paying stock. The second case is the early exercise of an American put option.” Interest Rate Option The fi...
This chapter replicates a novel approach to generate synthetic stock price data that could be used to train an ML model or backtest a strategy, and also evaluate its quality.Chapter 22, Deep Reinforcement Learning – Building a Trading Agent, presents how reinforcement learning (RL) permits the...
Tip: If you have questions about terms on this page like P&L or Simple rate of return,Learning modeis here to help. Learning mode helps you learn new trading terminology, and understand how the market works so you can become a better trader. ...
, in this domain (Chullamonthon and Tangamchit2023). However, RL still has certain applications in the stock markets. Lei (2020) combined deep learning and RL models to develop a time-driven, feature-aware joint deep RL model for financial time-series forecasting in algorithmic trading, thus...