11 research outputs found
The scale of predictability
We introduce a new stylized fact: the hump-shaped behavior of slopes and coefficients of determination as a function of the aggregation horizon when running (forward/backward) predictive regressions of future excess market returns onto past economic uncertainty (as proxied by market variance, consumption variance, or economic policy uncertainty). To justify this finding formally, we propose a novel modeling framework in which predictability is specified as a property of low-frequency components of both excess market returns and economic uncertainty. We dub this property scale-specific predictability. We show that classical predictive systems imply restricted forms of scale-specific predictability. We conclude that for certain predictors, like economic uncertainty, the restrictions imposed by classical predictive systems may be excessively strong
Zero-intelligence realized variance estimation
Limit order book, Market microstructure noise, Micro-price, Realized variance, Sampling schemes, 62E20, 62P20, C10, C80,
Autologous fat graft in scar treatment
Regenerative medicine is an emerging and rapidly evolving field of research and therapy, thanks to new discoveries on stem cells. Adipose tissue is a connective tissue which contains a reserve of mesenchymal stem cells. Clinical improvements in trophic characteristics of teguments after autologous fat graft are well described in literature. In this paper, we present our observation after 6 years of autologous fat graft experience in scar remodeling
Volatilidade e Previsão de Retorno com Modelos de Alta Frequência e GARCH: Evidências para o Mercado Brasileiro
Com base em estudos desenvolvidos em anos recentes sobre o uso de dados de alta frequência para a estimação da volatilidade, este artigo implementa o modelo Autorregressivo Heterogêneo (HAR)desenvolvido por Andersen, Bollerslev, e Diebold (2007) e Corsi (2009), e o modelo Componente (2-Comp) desenvolvido por Maheu e McCurdy (2007) e os compara com a família de modelos Autorregressivos com Heteroscedasticidade Generalizados (GARCH)para estimar a volatilidade e os retornos. Durante o período analisado, os modelos que usam dados intraday obtiveram melhores previsões de retornos dos ativos avaliados, tanto dentro como fora da amostra, confirmando assim que esses modelos possuem informações importantes para uma série de agentes econômicos
Bias-correcting the realized range-based variance in the presence of market microstructure noise
Bias correction, Integrated variance, Market microstructure noise, Realized range-based variance, Realized variance, 62E20, 62P20, C10, C80,
Stochastic volatility and stochastic leverage
This paper proposes the new concept of stochastic leverage in stochastic volatility models. Stochastic leverage refers to a stochastic process which replaces the classical constant correlation parameter between the asset return and the stochastic volatility process. We provide a systematic treatment of stochastic leverage and propose to model the stochastic leverage effect explicitly, e.g. by means of a linear transformation of a Jacobi process. Such models are both analytically tractable and allow for a direct economic interpretation. In particular, we propose two new stochastic volatility models which allow for a stochastic leverage effect: the generalised Heston model and the generalised Barndorff-Nielsen & Shephard model. We investigate the impact of a stochastic leverage effect in the risk neutral world by focusing on implied volatilities generated by option prices derived from our new models. Furthermore, we give a detailed account on statistical properties of the new mod