Publications - Daniela Osterrieder

The VIX, the Variance Premium, and Expected Returns

Osterrieder, D., Ventosa-Santaulària, D., Vera-Valdés, J. E. — Tue, 01 Jan 2019 12:01:41 +0100

Existing studies find conflicting estimates of the risk-return relation. We show that the trade-off parameter is inconsistently estimated when observed or estimated conditional variances measure risk. The inconsistency arises from misspecified, unbalanced, and endogenous return regressions. These problems are eliminated if risk is captured by the variance premium (VP) instead; it is unobservable, however. We propose a 2SLS estimator that produces consistent estimates without observing the VP. Using this method, we find a positive risk-return trade-off and long-run return predictability. Our approach outperforms commonly used risk-return estimation methods, and reveals a significant link between the VP and economic uncertainty.

The volatility of long-term bond returns

Osterrieder, D., Schotman, P. C. — Fri, 01 Dec 2017 12:01:41 +0100

We develop an almost affine term-structure model with a closedform solution for factor loadings in which the spot rate and the risk price are fractionally integrated processes with different integration orders. This model is used to explain two stylized facts. First, predictability of longterm excess bond returns requires sufficient volatility and persistence in the risk price. Second, the large volatility of long-term bond returns requires persistence in the spot rate. Decomposing long-term bond returns, we find that the expectations component from the level factor is more volatile than returns themselves and that the risk premium correlates negatively with level-factor innovations.

Risk and return: Long-run relations, fractional cointegration, and return predictability

Bollerslev, T., Osterrieder, D., Sizova, N., Tauchen, G. — Tue, 01 Jan 2013 12:01:41 +0100

Univariate dependencies in market volatility, both objective and risk neutral, are best described by long-memory fractionally integrated processes. Meanwhile, the ex post difference, or the variance swap payoff reflecting the reward for bearing volatility risk, displays far less persistent dynamics. Using intraday data for the Standard & Poor's 500 and the volatility index (VIX), coupled with frequency domain methods, we separate the series into various components. We find that the coherence between volatility and the volatility-risk reward is the strongest at long-run frequencies. Our results are consistent with generalized long-run risk models and help explain why classical efforts of establishing a naïve return-volatility relation fail. We also estimate a fractionally cointegrated vector autoregression (CFVAR). The model-implied long-run equilibrium relation between the two variance variables results in nontrivial return predictability over interdaily and monthly horizons, supporting the idea that the cointegrating relation between the two variance measures proxies for the economic uncertainty rewarded by the market.