A Dynamic Bayesian Model for Interpretable Decompositions of Market Behaviour
We propose a heterogeneous simultaneous graphical dynamic linear model (H-SGDLM), which extends the standard SGDLM framework to incorporate a heterogeneous autoregressive realised volatility (HAR-RV) model. This novel approach creates a GPU-scalable multivariate volatility estimator, which decomposes multiple time series into economically-meaningful variables to explain the endogenous and exogenous factors driving the underlying variability. This unique decomposition goes beyond the classic one step ahead prediction; indeed, we investigate inferences up to one month into the future using stocks, FX futures and ETF futures, demonstrating its superior performance according to accuracy of large moves, longer-term prediction and consistency over time.
Code (0)
등록된 구현이 없습니다.
Tasks
GPUPredictionTime SeriesTime Series AnalysisSimilar Papers 제목 키워드 기반
Bayesian Spillover Graphs for Dynamic Networks
We present Bayesian Spillover Graphs (BSG), a novel method for learning temporal relationships, identifying critical nodes, and quantifying uncertainty for multi-horizon spillover effects in a dynamic system. BSG leverag…
Time SeriesTime Series AnalysisUncertainty QuantificationConcentrated Liquidity Provision: a Reinforcement Learning Perspective
Automated market makers (AMMs) are a cornerstone of decentralised finance (DeFi). Constant product markets with concentrated liquidity, such as UniswapV3, are now a well-established design. In these markets, liquidity pr…
Reinforcement LearningDiscovering Persistent Behavioural Patterns for Interpretable Blockchain Forensics
Public blockchain data enables large-scale DeFi-related analysis, but many existing approaches are application-specific, difficult to scale, or hard to interpret. This research proposes a scalable, application-agnostic f…
Collective correlations, dynamics, and behavioural inconsistencies of the cryptocurrency market over time
This paper introduces new methods to study behaviours among the 52 largest cryptocurrencies between 01-01-2019 and 30-06-2021. First, we explore evolutionary correlation behaviours and apply a recently proposed turning p…
Advanced simulation paradigm of human behaviour unveils complex financial systemic projection
The high-order complexity of human behaviour is likely the root cause of extreme difficulty in financial market projections. We consider that behavioural simulation can unveil systemic dynamics to support analysis. Simul…
Language ModelingLanguage ModellingLarge Language Model