Online learning represents a family of machine learning methods, where a learner attempts
to tackle some predictive (or any type of decision-making) task by learning from a sequence …

For time series prediction tasks, the autoregressive integrated moving average (ARIMA)
model is one of the most classical and popular linear models, and extended applications …

Autoregressive integrated moving average (ARIMA) is one of the most popular linear models
for time series forecasting due to its nice statistical properties and great flexibility. However …

A classic problem in statistics is the estimation of the expectation of random variables from
samples. This gives rise to the tightly connected problems of deriving concentration …

Online portfolio selection has attracted increasing attention from data mining and machine
learning communities in recent years. An important theory in financial markets is mean …

Recently, models that based on Transformer (Vaswani et al., 2017) have yielded superior
results in many sequence modeling tasks. The ability of Transformer to capture long-range …

As an application of machine learning techniques in financial fields, online portfolio
selection has been attracting great attention from practitioners and researchers, which …

Machine learning (ML) is progressively resha** the fields of quantitative finance and
algorithmic trading. ML tools are increasingly adopted by hedge funds and asset managers …

In this paper, we propose a new online portfolio selection strategy based on a weighted
learning technique and an online gradient descent algorithm. Our strategy, named …

Online portfolio selection is an important problem in financial trading which has attracted
increasing interests from the machine learning and data mining community. Most existing …