MACROCAST is the first leakage-free time series foundation model for real-time macroeconomic forecasting, trained exclusively on synthetic series and vintage data, outperforming AR(1), Chronos-2, BVAR, and DFM benchmarks on FRED-MD.
Stochastic Volatility With Leverage: F ast and Efficient Likelihood Inference
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A new Bayesian dynamic model integrates realized volatility proxies with price series via dynamic gamma processes and DLMs to enhance financial forecasting.
stochvol is an R package providing MCMC-based Bayesian inference for stochastic volatility models, with examples on exchange rate data.
citing papers explorer
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MACROCAST: A Vintage-Consistent Time Series Foundation Model for Real-Time Macroeconomic Forecasting
MACROCAST is the first leakage-free time series foundation model for real-time macroeconomic forecasting, trained exclusively on synthetic series and vintage data, outperforming AR(1), Chronos-2, BVAR, and DFM benchmarks on FRED-MD.
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Bayesian Dynamic Modeling of Realized Volatility in Financial Asset Price Forecasting
A new Bayesian dynamic model integrates realized volatility proxies with price series via dynamic gamma processes and DLMs to enhance financial forecasting.
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Dealing with Stochastic Volatility in Time Series Using the R Package stochvol
stochvol is an R package providing MCMC-based Bayesian inference for stochastic volatility models, with examples on exchange rate data.