BlackRock

About: BlackRock is a based out in . It is known for research contribution in the topics: Portfolio & Population. The organization has 874 authors who have published 1111 publications receiving 34042 citations. The organization is also known as: BlackRock, Inc..

A No-Arbitrage Vector Autoregression of Term Structure Dynamics with Macroeconomic and Latent Variables

Abstract: This paper describes the joint dynamics of bond yields and macroeconomic variables in a vector autoregression, where identifying restrictions are based on the absence of arbitrage. Using a term structure model with inflation and economic growth factors, we investigate how macro factors affect bond prices and the dynamics of the yield curve. Higher order autoregressive lags and moving-average error terms for macro factors are accommodated. The macro factors are augmented by traditional unobserved term-structure factors. Models that incorporate macro factors give better forecasts than traditional term-structure models with only unobservable factors. Variance decompositions show that macro factors explain up to 30\% of the variation in bond yields. Macro factors primarily explain movements at the short end and middle of the yield curve while unobservable factors still account for most movement at the long end of the yield curve.

Why Do Security Prices Change? A Transaction-Level Analysis of Nyse Stocks

Abstract: This paper develops a structural model of intraday price formation that embodies both information shocks and microstructure effects in an internally consistent, unified setting. The model allows us to better understand the observed intra-day patterns in bid-ask spreads, price volatility, transaction costs, as well as the autocorrelations of transaction returns and quote revisions. For example, the model simultaneously sheds light on why, over the day, (i) the variance of transaction price changes is U-shaped while the variance of ask price changes is declining, (ii) the bid-ask spread is U-shaped although information asymmetry and uncertainty over fundamentals is decreasing, and (iii) the autocorrelations of transaction price changes are large and negative, yet the autocorrelations of ask price changes are small and negative. In addition, the model s parameters also provide a natural metric of price discovery and effective trading costs, which may prove useful in future studies.

Regime Switches in Interest Rates

Abstract: Regime-switching models are well suited to capture the non-linearities in interest rates. This paper examines the econometric performance of regime-switching models for interest rate data from the US, Germany and the UK. There is strong evidence supporting the presence of regime switches but univariate models are unlikely to yield consistent estimates of the model parameters. Regime-switching models incorporating international short rate and term spread information forecast better, match sample moments better, and classify regimes better than univariate models. We show that the regimes in interest rates correspond reasonably well with business cycles, at least in the US. This may explain why regime-switching models forecast interest rates better than single regime models. Finally, the non-linear interest rate dynamics implied by regime-switching models have potentially important implications for the macroeconomic literature documenting the effects of monetary policy shocks on economic aggregates. Moreover, the implied volatility and drift functions are rich enough to resemble those recently estimated using non-parametric techniques.

Contribution of copy number variants to schizophrenia from a genome-wide study of 41,321 subjects

Abstract: Copy number variants (CNVs) have been strongly implicated in the genetic etiology of schizophrenia (SCZ). However, genome-wide investigation of the contribution of CNV to risk has been hampered by limited sample sizes. We sought to address this obstacle by applying a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. A global enrichment of CNV burden was observed in cases (odds ratio (OR) = 1.11, P = 5.7 × 10-15), which persisted after excluding loci implicated in previous studies (OR = 1.07, P = 1.7 × 10-6). CNV burden was enriched for genes associated with synaptic function (OR = 1.68, P = 2.8 × 10-11) and neurobehavioral phenotypes in mouse (OR = 1.18, P = 7.3 × 10-5). Genome-wide significant evidence was obtained for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. Suggestive support was found for eight additional candidate susceptibility and protective loci, which consisted predominantly of CNVs mediated by nonallelic homologous recombination.

A contribution of novel CNVs to schizophrenia from a genome-wide study of 41,321 subjects

Abstract: Genomic copy number variants (CNVs) have been strongly implicated in the etiology of schizophrenia (SCZ). However, apart from a small number of risk variants, elucidation of the CNV contribution to risk has been difficult due to the rarity of risk alleles, all occurring in less than 1% of cases. We sought to address this obstacle through a collaborative effort in which we applied a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. We observed a global enrichment of CNV burden in cases (OR=1.11, P=5.7e-15), which persisted after excluding loci implicated in previous studies (OR=1.07, P=1.7e-6). CNV burden is also enriched for genes associated with synaptic function (OR = 1.68, P = 2.8e-11) and neurobehavioral phenotypes in mouse (OR = 1.18, P= 7.3e-5). We identified genome-wide significant support for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. We find support at a suggestive level for nine additional candidate susceptibility and protective loci, which consist predominantly of CNVs mediated by non-allelic homologous recombination (NAHR).