Changepoint Detection in Heteroscedastic Random Coefficient Autoregressive Models
Bibliographic Data
| ID | 19418409 |
|---|---|
| Authors | Lajos Horváth (0000-0003-3558-7094, University of Utah), Lorenzo Trapani (0000-0003-3425-2786, University of Nottingham, corresponding author) |
| Year | 2023 |
| Volume | 41 |
| Issue | 4 |
| Pages | 1300-1314 |
| Publication date | 2023-10-02 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Business and Economic Statistics (JOURNAL) |
| Journal identifiers | ISSN: 0735-0015 • E-ISSN: 1537-2707 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/07350015.2022.2120485 |
| OpenAlex | W4295860407 |
| Language | EN |
| Citations received | 1 |
| References cited | 59 |
We propose a family of CUSUM-based statistics to detect the presence of changepoints in the deterministic part of the autoregressive parameter in a Random Coefficient Autoregressive (RCA) sequence. Our tests can be applied irrespective of whether the sequence is stationary or not, and no prior knowledge of stationarity or lack thereof is required. Similarly, our tests can be applied even when the error term and the stochastic part of the autoregressive coefficient are non iid, covering the cases of conditional volatility and shifts in the variance, again without requiring any prior knowledge as to the presence or type thereof. In order to ensure the ability to detect breaks at sample endpoints, we propose weighted CUSUM statistics, deriving the asymptotics for virtually all possible weighing schemes, including the standardized CUSUM process (for which we derive a Darling-Erdős theorem) and even heavier weights (so-called Rényi statistics). Simulations show that our procedures work very well in finite samples. We complement our theory with an application to several financial time series
Autoregressive conditional heteroskedasticity · Autoregressive integrated moving average · Autoregressive model · CUSUM · Econometrics · Heteroscedasticity · SETAR · STAR model · Statistics · Stochastic volatility · Time series · Complex Systems and Time Series Analysis · Financial Risk and Volatility Modeling · Market Dynamics and Volatility · Mathematics · Applied Mathematics
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| Unique citing works | 1 |
|---|---|
| Citations per year | 1 |
| Citation span | 2025 - 2025 (1) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 1 |