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Predicting commodity futures trading volumes represents an important matter to policymakers and a wide spectrum of market participants. The purpose of this study is to concentrate on the energy sector and explore the trading volume prediction issue for the thermal coal futures traded in Zhengzhou Commodity Exchange in China with daily data spanning January 2016–December 2020.

The nonlinear autoregressive neural network is adopted for this purpose and prediction performance is examined based upon a variety of settings over algorithms for model estimations, numbers of hidden neurons and delays and ratios for splitting the trading volume series into training, validation and testing phases.

A relatively simple model setting is arrived at that leads to predictions of good accuracy and stabilities and maintains small prediction errors up to the 99.273th quantile of the observed trading volume.

The results could, on one hand, serve as standalone technical trading volume predictions. They could, on the other hand, be combined with different (fundamental) prediction results for forming perspectives of trading trends and carrying out policy analysis.

This study presents time-series data estimations on the association between the indicators of institutional environment and inward foreign direct investment (FDI) in India utilizing a comprehensive data set from 1996 to 2021.

The study employs the nonlinear autoregressive distributive lag (NARDL) model. The asymmetric ARDL framework evaluates the existence of cointegration among the factors under study and highlights the underlying nonlinear effects that may exist in the long and short run.

The significance of coefficients of negative shock to “control of corruption” and positive shock to “rule of law” is greater when compared to “government effectiveness, regulatory quality, political stability/absence of violence.” The empirical outcomes suggest the positive influence of rule of law, political stability and government effectiveness on FDI inflows. A high “regulatory quality” is observed to deter foreign investment. The “voice and accountability” index and negative shocks to the “rule of law” are exhibited to have no substantial impact on the amount of FDI that the country receives.

This study empirically examines the institutional determinants of FDI in India for a comprehensive period of 1996–2021. The study's findings imply that quality of the institutional environment has a significant bearing on India's inward FDI.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0375