Testing the martingale hypothesis in deutsche mark futures with models specifying the form of heteroscedasticity
通过异方差模型检验德国马克期货的鞅假说AI 解读 ↓
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Abstract We examine the form of heteroscedasticity in Deutsche Mark futures price data and compare different specifications of the particular way that the variance is changing over time. The martingale hypothesis is tested with daily and weekly rates of change of futures prices for the Deutsche Mark and some evidence is found against this hypothesis in analyses of daily data from 1981 to 1985. This rejection of the martingale hypothesis may be attributed to trading day effects in foreign currency prices and the resulting day‐of‐the‐week patterns in futures prices. When the martingale hypothesis is tested with weekly data the null hypothesis is retained.
非平稳波动环境下股票收益可预测性的实时监测
Stock return predictability, should it exist, is likely to be episodic in nature. In order to exploit such pockets of predictability it is essential that they are rapidly detected, in real-time, as the nascent predictive regime emerges. This will typically entail the repeated (sequential) application of one-shot end-of-sample predictability statistics, updated as new data become available. Consequently, in addition to dealing with the usual inference problems caused by…
We analyze 18 quadrillion models for the joint pricing of corporate bond and stock returns. Strikingly, we find that equity and nontradable factors alone suffice to explain corporate bond risk premia once their Treasury term structure risk is accounted for, rendering the extensive bond factor literature largely redundant for this purpose. While only a handful of factors, behavioral and nontradable, are likely robust sources of priced risk, the true latent stochastic discount…
Summary Jumps and market microstructure noise are stylized features of high-frequency financial data. It is well known that they introduce bias in the estimation of volatility (including integrated and spot volatilities) of assets, and many methods have been proposed to deal with this problem. When the jumps are intensive with infinite variation, the efficient estimation of spot volatility under serially dependent noise is not available and is thus in need. For this purpose,…
Summary We consider here penalized likelihood-based estimation and model selection applied to econometric time series models, which allow for nonnegativity (boundary) constraints on some or all of the parameters. We establish that joint model selection and estimation result in standard asymptotic Gaussian distributed estimators. The results contrast with nonpenalized estimation, which, as is well-known, leads to nonstandard asymptotic distributions that depend on the unknown…
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Some events impact volatilities of most assets, asset classes, sectors and countries, causing serious damage to investment portfolios. The magnitude of such shocks is defined as global COVOL which is an abbreviation for global common volatility, a broad measure of all types of global financial risk. This paper introduces a statistical formulation of such events as common volatility innovations in both a multivariate volatility and an asset pricing context. Simulations verify…