Appendix A. List of acronyms

ABC: Approximate Bayesian Computation
ACC: Ant Colony Clustering
ACD: Autoregressive Conditional Duration
ADIDA: Aggregate–Disaggregate Intermittent Demand Approach
ADL: Autoregressive Distributed Lag
ADMM: Alternating Direction Method of Multipliers
AI: Artificial Intelligence
AIC: Akaike’s Information Criterion
AICc: Akaike’s Information Criterion corrected (for small sample sizes)
ANACONDA: Analysis of National Causes of Death for Action
ANFIS: Adaptive Neuro-Fuzzy Inference System
ANN: Artificial Neural Network
AO: Additive Outlier
AR: AutoRegressive (model)
ARX: AutoRegressive with eXogenous variables (model)
ARCH: AutoRegressive Conditional Heteroskedasticity
ARMA: AutoRegressive-Moving Average (model)
ARIMA: AutoRegressive Integrated Moving Average (model)
ARIMAX: AutoRegressive Integrated Moving Average with eXogenous variables (model)
B&M: Brick and Mortar
BATS: Box-Cox transform, ARMA errors, Trend, and Seasonal components (model)
BEER: Behavioural Equilibrium Exchange Rate
BEKK: Baba-Engle-Kraft-Kroner GARCH
BEKK-HL: BEKK High Low
BIC: Bayesian Information Criterion
BLAST: Building Loads Analysis and System Thermodynamics
BM: Bass Model
BMC: Bootstrap Model Combination
BPNN: Back-Propagation Neural Network
CARGPR: Conditional AutoRegressive Geometric Process Range (model)
CARR: Conditional AutoRegressive Range (model)
CARRS: Conditional AutoRegressive Rogers and Satchell (model)
CBC: Choice Based Conjoint (analysis)
CBO: Congressional Budget Office
CDS: Credit Default Swap
CNN: Convolutional Neural Network
COVID-19: Coronavirus disease 2019
CVAR: Cointegrated Vector AutoRegressive (model)
CAViaR: Conditional AutoRegressive Value At Risk
CL: Cross Learning
CPFR: Collaborative Planning, Forecasting, and Replenishment
CRCD: Competition and Regime Change Diachronic (model)
CRPS: Continuous Ranked Probability Score CSR: Complete Subset Regression
CV: Cross-Validation
DA: Deterministic Annealing
DC: Distribution Centre
DCC: Dynamic Conditional Correlation
DCC-RGARCH: Range GARCH DCC
DFM: Dynamic Factor Model
DGP: Data Generating Process
DJI: Dow Jones Industrial DM: Diebold-Mariano (test)
DSGE: Dynamic Stochastic General Equilibrium
DSHW: Double Seasonal Holt-Winters
DSTCC-CARR: Double Smooth Transition Conditional Correlation CARR
DT: Delay Time
EEG: ElectroEncephaloGram
EGARCH: Exponential GARCH
EH: Expectations Hypothesis
EMD: Empirical Mode Decomposition
ENet: Elastic Net
ENSO: El Niño Southern Oscillation
ERCOT: Electric Reliability Council of Texas
ES: Expected Shortfall
ESP-r: Environmental Systems Performance – research
ESTAR: Exponential STAR ETS: ExponenTial Smoothing (or Error, Trend, Seasonality)
EVT: Extreme Value Theory
EWMA: Exponentially Weighted Moving Average
FAR: Functional AutoRegressive (model)
FASSTER: Forecasting with Additive Switching of Seasonality, Trend and Exogenous Regressors
FCM: Fuzzy C-Means
FIGARCH: Fractionally Integrated GARCH
FIS: Fuzzy Inference System
FFNN: Feed-Forward Neural Network
FFORMA: Feature-based FORecast Model Averaging
FMCG: Fast Moving Consumer Goods
FPCA: Functional Principal Component Analysis
FRB/EDO: Federal Reserve Board’s Estimated, Dynamic, Optimisation-based (model)
FSS: Forecasting Support System
FVA: Forecast Value Added
GARCH: General AutoRegressive Conditional Heteroscedasticity
GARCH-PARK-R: GARCH PARKinson Range
GARCH-TR: GARCH True Range
GB: Givon-Bass (model)
GBM: Generalised Bass Model
GDP: Gross Domestic Product
GGM: Guseo-Guidolin Model (GGM)
GJR-GARCH: Glosten-Jagannathan-Runkle GARCH
GM: Generalised M-estimator
GMM: Generalised Methods of Moments
GPU: Graphics Processing Unit
GRNN: Generalised Regression Neural Network
HAR: Heterogeneous AutoRegressive (model)
HDFS: Hadoop Distributed File System
HMD: Human Mortality Database
HP: Hodrick-Prescott
HPU: House Price Uncertainty
HVAC: Heating, Ventilation, and Air Conditioning (system)
HAR: Heterogeneous AutoRegressive (model)
HQ: Hannan-Quinn
IEA: International Energy Agency
IG: Interaction Groups
iid: independent and identically distributed
IIS: Impulse Indicator Saturation
IO: Innovation Outlier
IT: Information Technology
KBKD: Krishnan-Bass-Kummar Diachronic (model)
KISS: Keep It Simple, Stupid (principle)
\(k\)NN: \(k\) Nearest Neighbours
KPSS: Kwiatkowski–Phillips–Schmidt–Shin
L-IVaR: Liquidity-adjusted Intraday Value-at-Risk
LASSO: Least Absolute Shrinkage and Selection Operator
LH: Low and High
LLN: Law of Large Numbers
LN-CASS: Logit-Normal Continuous Analogue of the Spike-and-Slab
LS (or LPS): Logarithmic (Predictive) Score (log-score)
LSTAR: Logistic STAR
LSTM: Long Short-Term Memory Networks
LTLF: Long-Term Load Forecasting
LV: Lotka-Volterra (model)
LVac: Lotka-Volterra with asymmetric churn (model)
LVch: Lotka-Volterra with churn (model)
MAE: Mean Absolute Error
MAPE: Mean Absolute Percentage Error
MASE: Mean Absolute Scaled Error
MCMC: Markov Chain Monte Carlo
MFI: Marginal Forecast Interval
MICE: Meetings, Incentives, Conventions, and Exhibitions/Events MIDAS: MIxed DAta Sampling
MJO: Madden Julian Oscillation
ML: Machine Learning
MLP: MultiLayer forward Perceptron
MLR: Multiple Linear Regression
MS: Markov Switching
MS VAR: Markov Switching VAR
MSARIMA: Multiple/Multiplicative Seasonal ARIMA
MSC: Multiple Seasonal Cycles
MSE: Mean Squared Error
MSRB: Markov-Switching Range-Based
MTA: Multiple Temporal Aggregation
MTLF: Medium-Term Load Forecasting
NAO: North Atlantic Oscillation
NLS: Nonlinear Least Squares
NLTK: Natural Language Toolkit
NMAE: Normalised Mean Absolute Error
NN: Neural Network
NNAR: Neural Network AutoRegressive
NOB: Non-Overlapping Blocks
NPF: New Product Forecasting
NWP: Numerical Weather Prediction
OB: Overlapping Blocks
OBR: Office for Budget Responsibility
ODE: Ordinary Differential Equations
OLS: Ordinary Least Squares
OWA: Overall Weighted Average
PAR: Periodic AutoRegressive (model)
PCA: Principal Components Analysis
pdf: probability density function
PdM: Predictive Maintenance
PFEM: Point Forecast Error Measure
PHANN: Physical Hybrid Artificial Neural Network
pHDR: predictive Highest Density Region
PI: Prediction Interval
PIT: Probability Integral Transform
PL: Product Level
PLS: Partial Least Squares
PM: Particulate Matter
POT: Peak Over Threshold
PPP: Purchasing Power Parity
PSO: Particle Swarm Intelligence
PV: PhotoVoltaic
\(Q_\alpha\): quantile score or pinball loss for a level \(\alpha \in (0, 1)\)
RAF: Royal Air Force (UK)
RB: Range-Based
RB-copula: Range-Based copula
RB-DCC: Range-Based DCC
RB-MS-DCC: Range-Based Markov-Switching DCC
RBF: Radial Basis Function
REGARCH: Range-Based Exponential GARCH
RET: Renewable Energy Technology
RGARCH: Range GARCH
RMSE: Root Mean Squared Error
RNN: Recurrent Neural Network
RR-HGADCC: Return and Range Heterogeneous General Asymmetric DCC
RTV: Real Time Vintage
SA: Structured Analogies
SARIMA: Seasonal AutoRegressive Integrated Moving Average (model)
SARIMAX: Seasonal AutoRegressive Integrated Moving Average with eXogenous variables
SARMA: Seasonal AutoRegressive Moving Average (model)
SARMAX: Seasonal AutoRegressive Moving Average with eXogenous variables
SBA: Syntetos-Boylan Approximation
SBC: Syntetos-Boylan-Croston (classification)
SEATS: Seasonal Extraction in ARIMA Time Series
SES: Simple (or Single) Exponential Smoothing
SETAR: Self-Exciting Threshold AutoRegressive (model)
SFI: Simultaneous Forecast Interval
SKU: Stock Keeping Unit
SGD: Stochastic Gradient Descent
SIS: Step Indicator Saturation
SL: Serial number Level
SMA: Simple Moving Average
sMAPE: symmetric Mean Absolute Percentage Error
SOM: Self-Organising Map
SS: State Space
sSA: semi-Structured Analogies
SSARIMA: Several Seasonalities (or State Space) ARIMA
STAR: Smooth Transition AutoRegressive (model)
STARR: Smooth Transition conditional AutoRegressive Range (model)
STL: Seasonal Trend decomposition using Loess
STLF: Short-Term Load Forecasting
STR: Seasonal-Trend decomposition based on Regression
SV: Stochastic Volatility
SVA: Stochastic Value Added
SVD: Singular Value Decomposition
SVM: Support Vector Machine
SWAN: Simulating WAves Nearshore
S&OP: Sales and Operations Planning
S&P: Standard & Poor’s
TAR: Threshold AutoRegressive (model)
TARMA: Threshold AutoRegressive Moving Average (model) TARMASE: Threshold AutoRegressive Moving Average (model)
TARR: Range-Based Threshold conditional AutoRegressive (model)
TBATS: Exponential Smoothing state space model with Box-Cox transformation, ARMA errors, Trend and Seasonal components
TFR: Total Fertility Rate
TGARCH: Threshold GARCH
TMA: Threshold Moving Average (model)
TPU: Tensor Processing Unit
TRAMO: Time series Regression with ARIMA noise, Missing values and Outliers
TSB: Teunter-Syntetos-Babai (method)
UCRCD: Unbalanced Competition and Regime Change Diachronic (model)
UIP: Uncovered Interest Party
VaR: Value at Risk
VAR: Vector AutoRegressive (model)
VARX: VAR with eXogenous variables (model)
VARMA: Vector AutoRegressive Moving Average (model)
VAT: Value Added Tax
VARIMAX: Vector AutoRegressive Integrated Moving Average with eXogenous variables (model)
VECM (or VEC): Vector Error Correction Model
VEqCM: Vector Equilibrium-Correction Model
VSTLF: Very Short-Term Load Forecasting
WLS: Weighted Least Squares
WNN: Wavelet Neural Network
WOM: Word-Of-Mouth
WW2: World War 1
WW2: World War 2
WW3: World War 3
XGBoost: eXtreme Gradient Boosting