DeepAI
Log In Sign Up

Deep Video Prediction for Time Series Forecasting

02/24/2021
by   Zhen Zeng, et al.
14

Time series forecasting is essential for decision making in many domains. In this work, we address the challenge of predicting prices evolution among multiple potentially interacting financial assets. A solution to this problem has obvious importance for governments, banks, and investors. Statistical methods such as Auto Regressive Integrated Moving Average (ARIMA) are widely applied to these problems. In this paper, we propose to approach economic time series forecasting of multiple financial assets in a novel way via video prediction. Given past prices of multiple potentially interacting financial assets, we aim to predict the prices evolution in the future. Instead of treating the snapshot of prices at each time point as a vector, we spatially layout these prices in 2D as an image, such that we can harness the power of CNNs in learning a latent representation for these financial assets. Thus, the history of these prices becomes a sequence of images, and our goal becomes predicting future images. We build on a state-of-the-art video prediction method for forecasting future images. Our experiments involve the prediction task of the price evolution of nine financial assets traded in U.S. stock markets. The proposed method outperforms baselines including ARIMA, Prophet, and variations of the proposed method, demonstrating the benefits of harnessing the power of CNNs in the problem of economic time series forecasting.

READ FULL TEXT

page 4

page 5

01/22/2021

Where does the Stimulus go? Deep Generative Model for Commercial Banking Deposits

This paper examines deposits of individuals ("retail") and large compani...
07/02/2021

Visual Time Series Forecasting: An Image-driven Approach

In this work, we address time-series forecasting as a computer vision ta...
10/19/2021

Forecasting Market Prices using DL with Data Augmentation and Meta-learning: ARIMA still wins!

Deep-learning techniques have been successfully used for time-series for...
06/20/2011

Large Vector Auto Regressions

One popular approach for nonstructural economic and financial forecastin...
11/21/2018

Multivariate Forecasting of Crude Oil Spot Prices using Neural Networks

Crude oil is a major component in most advanced economies of the world. ...
12/13/2021

Sequential Break-Point Detection in Stationary Time Series: An Application to Monitoring Economic Indicators

Monitoring economic conditions and financial stability with an early war...