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Long-Term Exchange Rate Probability Density Forecasting Using Gaussian Kernel and Quantile Random Forest

https://doi.org/10.1155/2020/1972962
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1016/0014-2921(89)90095-0openalex-snapshot
Exchange rate uncertainty and foreign trade
inferredcites →https://doi.org/10.1016/j.bspc.2017.01.012openalex-snapshot
Decision tree and random forest models for outcome prediction in antibody incompatible kidney transplantation
inferredcites →https://doi.org/10.1016/j.jjie.2016.05.001openalex-snapshot
Exchange rate exposure and risk management: The case of Japanese exporting firms
inferredcites →https://doi.org/10.1016/j.joat.2017.12.002openalex-snapshot
Effect of exchange rate volatility on trade in Sub-Saharan Africa☆
inferredcites →https://doi.org/10.1016/s0164-0704(01)00178-1openalex-snapshot
Exchange rate uncertainty and firm profitability
inferredcites →https://doi.org/10.1016/s2212-5671(13)00079-8openalex-snapshot
Exchange Rate Volatility and Foreign Trade: The Case for Cyprus and Croatia
inferredcites →https://doi.org/10.13014/k2m61hf4openalex-snapshot
Exchange Rate Volatility and Foreign Direct Investment in Sub-Saharan Africa
inferredcites →https://doi.org/10.1371/journal.pone.0205155openalex-snapshot
A quantile regression forest based method to predict drug response and assess prediction reliability
inferredcites →https://doi.org/10.2307/1913643openalex-snapshot
Regression Quantiles
inferredcites →https://doi.org/10.2307/2110011openalex-snapshot
Exchange Rates and Investment in United States Industry

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4618973openalex-extracted
Out-of-Sample Exchange rate Forecasting in Ghana using Bayesian Model Averaging
inferred← citeshttps://doi.org/10.1016/j.inffus.2023.02.033openalex-snapshot
The relative roles of different land-use types in bike-sharing demand: A machine learning-based multiple interpolation fusion method
inferred← citeshttps://doi.org/10.1080/00036846.2024.2339188openalex-snapshot
Forecasting the future: applying Bayesian model averaging for exchange rates drivers in Ghana
inferred← citeshttps://doi.org/10.1109/cait64506.2024.10963106openalex-snapshot
Research on Exchange Rate Prediction Driven by Multi-Source Heterogeneous Data: Based on Retrieval Augmented Generation and Explainable Machine Learning Models
inferred← citeshttps://doi.org/10.21105/joss.05976openalex-snapshot
quantile-forest: A Python Package for Quantile Regression Forests
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.