A Functional Time Series Analysis of Forward Curves Derived from Commodity Futures

38 Pages Posted: 27 Aug 2018 Last revised: 29 Jul 2019

See all articles by Lajos Horváth

Lajos Horváth

University of Utah - Department of Mathematics

Zhenya Liu

Renmin University of China; CERGAM, Aix-Marseille University

Gregory Rice

University of Waterloo - Department of Statistics and Actuarial Science

Shixuan Wang

University of Reading - Department of Economics

Date Written: July 27, 2019

Abstract

We study forward curves formed from commodity futures prices listed on the Standard and Poor's-Goldman Sachs Commodities Index (S&P GSCI) using recently developed tools in functional time series analysis. Functional tests for stationarity and serial correlation suggest that log-differenced forward curves may be generally considered as stationary and conditionally heteroscedastic sequences of functions. Several functional methods for forecasting forward curves that more accurately reflect the time to expiry of contracts are developed, and we found that these typically outperformed their multivariate counterparts, with the best among them using the method of predictive factors introduced by Kargin and Onatski (2008).

Keywords: Forward curves, S&P GSCI, Commodity Futures, Functional Data Analysis, Functional Autoregressive Models, Functional Principal Component Analysis

JEL Classification: C12, C32, C58, G15, G17, Q02

Suggested Citation

Horváth, Lajos and Liu, Zhenya and Rice, Gregory and Wang, Shixuan, A Functional Time Series Analysis of Forward Curves Derived from Commodity Futures (July 27, 2019). Available at SSRN: https://ssrn.com/abstract=3227025 or http://dx.doi.org/10.2139/ssrn.3227025

Lajos Horváth

University of Utah - Department of Mathematics ( email )

1645 E. Campus Center
Salt Lake City, UT 84112
United States
801 581-8159 (Phone)

Zhenya Liu (Contact Author)

Renmin University of China ( email )

School of Finance
Beijing, Beijing 100872
China

CERGAM, Aix-Marseille University ( email )

Aix-Marseille University
3 Avenue Robert Schuman,
Aix-en-Provence, 13628
France
0781668685 (Phone)

Gregory Rice

University of Waterloo - Department of Statistics and Actuarial Science ( email )

200 University Avenue West
Waterloo, Ontario N2L 3G1
Croatia

Shixuan Wang

University of Reading - Department of Economics ( email )

Reading, RG6 6AA
United Kingdom

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
95
Abstract Views
503
rank
287,740
PlumX Metrics