Forecasting precious metal returns with multivariate random forests
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- Type
- article
- Published
- 2018-09-04
- Cited by
- 51
- References
- 51
- OpenAlex
- https://openalex.org/W2889939530
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:253722470
Keywords
Univariate, Multivariate statistics, Precious metal, Multivariate analysis, Econometrics
References
- A Quantile-Boosting Approach to Forecasting Gold Returns
- EVALUATING FORECASTS OF A VECTOR OF VARIABLES: A GERMAN FORECASTING COMPETITION
- Does gold offer a better protection against losses in sovereign debt bonds than other metals
- Classification and regression trees
- Gold and the Dollar (and the Euro, Pound, and Yen)
- On the efficiency of the gold market: Results of a real-time forecasting approach
- What precious metals act as safe havens, and when? Some US evidence
- Oil and gold price dynamics in a multivariate cointegration framework
- Dynamics of oil price, precious metal prices, and exchange rate
- Which precious metals spill over on which, when and why? Some evidence
- Evaluating a Vector of the Fed's Forecasts
- Is Gold a Safe Haven? International Evidence
- Comparing Predictive Accuracy
- Does gold act as a hedge or a safe haven for stocks? A smooth transition approach
- Uncertainty principles and fourier analysis
- Classification and regression trees
- Tree-Structured Methods for Longitudinal Data
- Forecasting the price of gold using dynamic model averaging
- Is gold a hedge or safe haven against oil price movements
- The Elements of Statistical Learning
Cited by
- Ensemble approach based on bagging, boosting and stacking for short-term prediction in agribusiness time series
- Forecasting Realized Volatility of Bitcoin: The Role of the Trade War
- Tree-Based Methods: Consequences of Moving the US Embassy
- Modeling Precious Metal Returns through Fractional Jump-Diffusion Processes Combined with Markov Regime-Switching Stochastic Volatility
- Gold and the global financial cycle
- Predicting Gold and Silver Price Direction Using Tree-Based Classifiers
- Forecasting gold price with the XGBoost algorithm and SHAP interaction values
- Gold Price Forecasting Using Machine Learning Techniques: Review of a Decade
- The (Asymmetric) effect of El Niño and La Niña on gold and silver prices in a GVAR model
- Multi-step metal prices forecasting based on a data preprocessing method and an optimized extreme learning machine by marine predators algorithm
- An interpretable decision-support systems for daily cryptocurrency trading
- Forecasting Bitcoin price direction with random forests: How important are interest rates, inflation, and market volatility?
- Forecasting gold price using a novel hybrid model with ICEEMDAN and LSTM-CNN-CBAM
- Applying Block Bootstrap Methods in Silver Prices Forecasting
- Macroeconomic Multivariate Statistics and Regionalization Management Strategy Based on Random Matrix
- Gold risk premium estimation with machine learning methods
- Steel price index forecasting through neural networks: the composite index, long products, flat products, and rolled products
- Multivariate Random Forest for Digital Soil Mapping
- Scrap steel price forecasting with neural networks for east, north, south, central, northeast, and southwest China and at the national level
- Construction cost prediction system based on Random Forest optimized by the Bird Swarm Algorithm.
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