The price impact of economic news, private information and trading intensity

In this paper we use three years high-frequency data to investigate the role played by public and private information in the process of price formation in two secondary government bond markets. As public information we examine the impact of regularly scheduled macroeconomic news announcements. We identify those announcements with the greatest impact on these markets. As private information we estimate the price impact of order flow. In fact, according to the microstructure models, private information in this context is related to the subjective evaluation of information and order flow can reflect difference of opinions among market participants. Thus, market participant may infer information about the subjective beliefs of other market participants looking at the aggregate order flow. We then use a vector autoregressive model for prices and trades to empirically test the role played by intraday trading intensity and by the waiting time between consecutive transactions in the process of price formations

The impact of economic news on bond prices: evidence from the MTS platform

Although there is an extensive literature on the impact of macroeconomic announcements on asset prices, the bond market has received less attention than the foreign exchange and equity markets, even less if we consider the European market. This paper uses high-frequency intra-day data over a three-year period to investigate the impact of regularly scheduled macroeconomic news and monetary policy announcements on the returns of the Italian government bond market, the largest one in the Euro-zone. With respect to the previous papers, we use a much broader set of announcements, sixty-eight, and a relatively novel dataset (MTS). We find that twenty-five news have a significant impact on bond returns and that almost all announcements are incorporated into prices within twenty minutes from the release

Probability of informed trading and volatility for an ETF

We use the new procedure developed by Easley et al. to estimate the Probability of Informed Trading (PIN), based on the volume imbalance: Volume-Synchronized Probability of Informed Trading (VPIN). Unlike the previous method, this one does not require the use of numerical methods to estimate unobservable parameters. We also relate the VPIN metric to volatility measures. However, we use most efficient estimators of volatility which consider the number of jumps. Moreover, we add the VPIN to a Heterogeneous Autoregressive model of Realized Volatility to further investigate its relation with volatility. For the empirical analysis we use data on the exchange traded fund (SPY)

Informed trading in parallel bond markets

In this paper we investigate the presence of asymmetric information in the parallel trading of ten-year government fixed rate bonds (BTP) on two secondary electronic platforms: the business-to-business (B2B) MTS platform and the business-to-customer (B2C) BondVision one. The two platforms are typified by a different degree of transparency. We investigate whether the probability to encounter an informed trader on the less transparent market is higher than the corresponding probability on the more transparent one. Our results show that on BondVision, that is the less transparent platform, the probability of encountering an informed trader is higher. Finally we perform a series of tests to check the robustness of our estimates. Two tests do not meet the hypothesis of independence. Nevertheless, these findings do not controvert the hypothesis of our model, but call for further analysis

Informed Trading in Parallel Bond Markets

In this paper we investigate the presence of asymmetric information in the parallel trading of ten-year government fixed rate bonds (BTP) on two secondary electronic platforms: the business-to-business (B2B) MTS platform and the business-to-customer (B2C) BondVision one. The two platforms are typified by a different degree of transparency. We investigate whether the probability to encounter an informed trader on the less transparent market is higher than the corresponding probability on the more transparent one. Our results show that on BondVision, that is the less transparent platform, the probability of encountering an informed trader is higher. Finally we perform a series of tests to check the robustness of our estimates. Two tests do not meet the hypothesis of independence. Nevertheless, these findings do not controvert the hypothesis of our model, but call for further analysis.Market microstructure; Informed trading; Parallel trading; Transparency

Molecular analysis of sarcomeric and non-sarcomeric genes in patients with hypertrophic cardiomyopathy.

Background: Hypertrophic cardiomyopathy (HCM) is a common genetic heart disorder characterized by unexplained left ventricle hypertrophy associated with non-dilated ventricular chambers. Several genes encoding heart sarcomeric proteins have been associated to HCM, but a small proportion of HCM patients harbor alterations in other non-sarcomeric loci. The variable expression of HCM seems influenced by genetic modifier factors and new sequencing technologies are redefining the understanding of genotype–phenotype relationships, even if the interpretations of the numerous identified variants pose several challenges. Methods and results: We investigated 62 sarcomeric and non-sarcomeric genes in 41 HCM cases and in 3 HCM-related disorders patients. We employed an integrated approach that combines multiple tools for the prediction, annotation and visualization of functional variants. Genotype–phenotype correlations were carried out for inspecting the involvement of each gene in age onset and clinical variability of HCM. The 80% of the non-syndromic patients showed at least one rare non-synonymous variant (nsSNV) and among them, 58% carried alterations in sarcomeric loci, 14% in desmosomal and 7% in other non-sarcomeric ones without any sarcomere change. Statistical analyses revealed an inverse correlation between the number of nsSNVs and age at onset, and a relationship between the clinical variability and number and type of variants. Conclusions: Our results extend the mutational spectrum of HCM and contribute in defining the molecular pathogenesis and inheritance pattern(s) of this condition. Besides, we delineate a specific procedure for the identification of the most likely pathogenetic variants for a next generation sequencing approach embodied in a clinical context

The archaeal elongation factor EF-2 induces the release of aIF6 from 50S ribosomal subunit

The translation factor IF6 is a protein of about 25 kDa shared by the Archaea and the Eukarya but absent in Bacteria. It acts as a ribosome anti-association factor that binds to the large subunit preventing the joining to the small subunit. It must be released from the large ribosomal subunit to permit its entry to the translation cycle. In Eukarya, this process occurs by the coordinated action of the GTPase Efl1 and the docking protein SBDS. Archaea do not possess a homolog of the former factor while they have a homolog of SBDS. In the past, we have determined the function and ribosomal localization of the archaeal (Sulfolobus solfataricus) IF6 homolog (aIF6) highlighting its similarity to the eukaryotic counterpart. Here, we analyzed the mechanism of aIF6 release from the large ribosomal subunit. We found that, similarly to the Eukarya, the detachment of aIF6 from the 50S subunit requires a GTPase activity which involves the archaeal elongation factor 2 (aEF-2). However, the release of aIF6 from the 50S subunits does not require the archaeal homolog of SBDS, being on the contrary inhibited by its presence. Molecular modeling, using published structural data of closely related homologous proteins, elucidated the mechanistic interplay between the aIF6, aSBDS, and aEF2 on the ribosome surface. The results suggest that a conformational rearrangement of aEF2, upon GTP hydrolysis, promotes aIF6 ejection. On the other hand, aSBDS and aEF2 share the same binding site, whose occupation by SBDS prevents aEF2 binding, thereby inhibiting aIF6 release

Prediction and visualization data for the interpretation of sarcomeric and non-sarcomeric DNA variants found in patients with hypertrophic cardiomyopathy

AbstractGenomic technologies are redefining the understanding of genotype–phenotype relationships and over the past decade, many bioinformatics algorithms have been developed to predict functional consequences of single nucleotide variants. This article presents the data from a comprehensive computational workflow adopted to assess the biomedical impact of the DNA variants resulting from the experimental study “Molecular analysis of sarcomeric and non-sarcomeric genes in patients with hypertrophic cardiomyopathy” (Bottillo et al., 2016) [1]. Several different independently methods were employed to predict the functional consequences of alleles that result in amino acid substitutions, to study the effect of some DNA variants over the splicing process and to investigate the impact of a sequence variant with respect to the evolutionary conservation

The Price Impact of Economic News, Private Information and Trading Intensity

In this paper we use three years high-frequency data to investigate the role played by public and private information in the process of price formation in two secondary government bond markets. As public information we examine the impact of regularly scheduled macroeconomic news announcements. We identify those announcements with the greatest impact on these markets. As private information we estimate the price impact of order flow. In fact, according to the microstructure models, private information in this context is related to the subjective evaluation of information and order flow can reflect difference of opinions among market participants. Thus, market participant may infer information about the subjective beliefs of other market participants looking at the aggregate order flow. We then use a vector autoregressive model for prices and trades to empirically test the role played by intraday trading intensity and by the waiting time between consecutive transactions in the process of price formations.