Designing a machine learning algorithm to predict stock prices is a subject of interest for economists and machine learning practitioners. Financial modeling is a challenging task, not only from an analytical perspective but also from a psychological perspective. After 2008 financial crisis, many ...
To analysis the trend of global economy, many economists believe U.S. Treasury Yield has the ability to predict the fluence of other financial markets such as stock market, futures market, Option market, etc. However, However, most financial prediction models focus only on predicting stock price...
JD Explore Academy also developed the few-shot learning capability of the large-scale ViTAEv2 model by fine-tuning the large-scale ViTAEv2 model with 1, 10 and 100 percent of the data respectively, and the result showed that when fine-tuned with only a small amount of data, namely 10 per...
AI technology is still new and exciting, with expectations of its growth continuing to rise, leaving many investors wanting a piece of the profit pie. Let me introduce a fund that can offer investors exposure to this tempting opportunity. Enter theTrueShares Technology, AI & Deep Learning ETF ...
Future projections of transport demands were based on the Shared Socioeconomic Pathway (SSP)36,37,38database. The SSPs39,40,41were created by an international team of climate researchers, economists, and energy systems modelers to generate internally consistent pathways for future worlds across the...
for accurate forecasting. Traditional forecasting methods, while valuable, often struggle with the non-linear and non-stationary nature of time series data. To address this challenge, we propose an innovative model that combines signal decomposition and deep learning techniques. Our model employs ...
Recent progress in deep learning is essentially based on a “big data for small tasks” paradigm, under which massive amounts of data are used to train a classifier for a single narrow task. In this paper, we call for a shift that flips this paradigm upside down. Specifically, we propose...
Whether investor sentiment affects stock prices is a question of long-standing interest for economists. Numerous authors have considered the possibility that a significant presence of sentiment-driven investors can cause prices to depart from their fundamental values. The “noise trader” theories of Bla...
AI systems, even carefully designed to be fair, are heavily criticized for delivering misjudged and discriminated outcomes against individuals and groups. Numerous work on AI algorithmic fairness is devoted on Machine Learning pipelines which address biases and quantify fairness under a pure computational...
The software platform is open-source and combines tasks such as normalised difference vegetation index (NDVI) aerial imagery for data collection, computer vision for image processing, deep learning (i.e., convolutional neural networks, CNNs) for crop counting, and supervised machine learning for ...