Volatility and regime models
GARCH and regime-switching models describe how volatility clusters and when markets move between calm and stressed regimes, with regime probabilities reported rather than certainties.
GRA · Capital Markets Nexus
空间金融资本与危害、风险暴露和转型的交汇之处
Econometrics turns market data into estimates with stated uncertainty: volatility regimes, liquidity premia, spillovers between markets and the price response to news and policy. In capital markets it supplies the measures behind most indicators and the tests that show when a relationship has changed.
Econometrics applies statistical methods to economic data to estimate relationships, test theories and forecast. It provides empirical evidence on how shocks and policies affect economic outcomes. In capital markets and investment and financial stability, econometric evidence estimates how disasters, pandemics and financial shocks affect output, employment and prices. It informs the economic case for 风险削减. The canonical description is on STEM Commons.
GARCH and regime-switching models describe how volatility clusters and when markets move between calm and stressed regimes, with regime probabilities reported rather than certainties.
Abnormal returns around announcements, policy decisions or geopolitical events are estimated against a model of normal returns, with the estimation window and benchmark stated.
Bid-ask spreads, price impact and illiquidity ratios are estimated from trade and quote data, and their agreement across measures is checked before any one is relied on.
团队遵循该方法时会使用的界面:其指标、状态与决策。名称为示例,数值仅作示意。
Capital markets · Econometrics for capital markets · Run R-3425
稳健标准误
| 买卖价差 | 0.15 | 0.11 | [−0.1, 1.0] | 否 |
| 市场深度 | −0.38 | 0.07 | [−0.3, 0.8] | 是 |
| 初始保证金 | −0.40 | 0.19 | [−0.2, 0.9] | 是 |
| 结算失败 | 0.13 | 0.14 | [−0.1, 0.9] | 否 |
Datasets and records used by econometrics on this platform, with the role each plays and the label its values carry. Sources are listed in 来源登记册.
| 数据 | 角色 | 标签 |
|---|---|---|
| Trade and quote data | Liquidity and volatility estimation | 观测 |
| Index and security returns | Event studies and regime models | 观测 |
| Announcement and policy calendars | Event dating | 已发布统计 |
| Financial stress indices | Regime identification | 模型估算 |
风险官、监管者或财政部会要求的风险暴露、损失、情景和资本视图,以及它们据以报告的框架。结构遵循监管和精算实务。数值为说明性:绝非价格、评级或建议。
The indicators a risk officer, supervisor or ministry of finance reads first on econometrics for capital markets.
| 指标 | 单位 | 谁来阅读 | 框架 |
|---|---|---|---|
| CET1 比率 | 占风险加权资产的百分比 | 银行、监管机构 | 巴塞尔框架 |
| 流动性覆盖率 | 压力流出的 % | 银行、中央银行 | 巴塞尔框架 |
| 偿付能力充足率 | 占偿付能力资本要求的百分比 | 保险公司、监管机构 | IAIS《保险核心原则》 |
| 综合成本率 | 占已赚保费的百分比 | 保险公司 | 精算实践 |
| 保护缺口 | 未投保部分占经济损失的比例 | 保险公司、财政部 | 已公布的损失统计 |
| 公共债务 | 占 GDP 的 % | 财政部、IMF | 债务可持续性框架 |
| 总融资需求 | 每年占 GDP 的 % | 财政部、投资者 | 债务可持续性框架 |
Models are assessed through specification tests, robustness checks and out-of-sample performance. Results are compared across datasets and methods.
| 核查 | 如何开展 |
|---|---|
| Structural break tests | Stability is tested before a relationship estimated in one period is applied to another |
| Robustness to specification | Results are compared across estimation windows, benchmarks and model forms |
| Out-of-sample evaluation | Volatility and liquidity models are scored on periods not used in estimation |
Endogeneity, measurement error and structural change can bias estimates. Relationships may shift under extreme conditions.
Process explorer · Process
10 steps·4 个阶段
流程
PRISMA 2020 是系统综述的报告指南;各步骤依循其核查清单,而非强制顺序,且没有任何 Nexus 文件采纳它。
报告Outline of an externally published reporting guideline, not a Nexus process and not a record of operation. PRISMA 2020 mainly covers reviews of intervention effects. No Nexus page names it. Every programme is at service level R0.
经济发展 stewards econometrics for the Consortium and reviews how it is applied across platforms.
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