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Bond Liquidity at the Oslo Stock Exchange
Get PDFWe characterize the liquidity of bond trading at the Oslo Stock Exchange (OSE). We use the complete history of bond prices quoted at the OSE from 1990 to 2016. We first characterize the market place, summarize trading grouped by type of issuers. The OSE can be characterized as a market place with a few bonds traded often, the rest traded seldom. The active bonds are Treasury securities, which typically trade on a daily basis. A second category of active bonds are covered bonds, a type of bond introduced as recent as 2008 (in the wake of the financial crisis). The remainder of bonds at the OSE are traded seldom. The activity of the bond market at the OSE has increased markedly in the post-2008 period. While Treasury securities remain the most active class, covered bonds has seen a marked increase in liquidity. We also see an increase in activity for the other bond groups. The number of bonds listed has doubled in the last ten years, with financial and industrial issuers increasing the most. The market had more than 3000 different bond issues active in the last five years. However, only half of these bonds trade more than five times a year. The second part of the paper investigates the feasibility of measuring liquidity in the Norwegian bond market. Is it possible to construct liquidity measures that are informative about the state of the Norwegian financial market? We calculate three different measures that can be calculated from daily data: Bid/Ask Spreads, the Amihud [2002] ILLIQ measure, and the Corwin and Schultz [2012] spread estimate from high/low prices. Except for Treasuries, the liquidity measures are hard to calculate due to limited trading interest. Of the three liquidity measures, the Corwin and Schultz measure seem to be the preferred, although the measures are clearly correlated. All measures show that aggregate bond market liquidity covary with slowdowns in the Norwegian economy, with liquidity worsening (trading costs/spreads increasing) around such events as the 1992 Banking Crisis and the 2008 Financial Crisis. We also compare estimates of trading costs for various types of bonds with equities, and find that the most expensive to trade is equities. Trading costs for corporate bonds are lower than equities, but higher than Treasury bonds, which is the category with lowest estimated transaction costs. This is contrary to the evidence from the US, and most European bond markets, where estimates of transaction costs for corporate bonds are much higher than trading costs for equities
Petroleumsfondsmekanismen og utviklingen i petrobufferporteføljen (PBP)
Get PDFStaten har over tid hatt store inntekter i både kroner og valuta fra petroleumssektoren (statens netto kontantstrøm). Samtidig har staten også store valutainntekter i form av avkastning i Statens Pensjonsfond Utland (SPU). En del av disse inntektene brukes hvert år til å dekke det oljekorrigerte underskuddet på statsbudsjettet i tråd med handlingsregelen. Frem til og med 2015 var statens netto kontantstrøm fra petroleumsvirksomheten større enn det oljekorrigerte underskuddet. Differansen ble da overført til SPU. Fra 2016 har situasjonen vært motsatt. Statens netto kontantstrøm fra petroleumsvirksomheten er ikke lenger nok til å dekke hele det oljekorrigerte underskuddet. Deler av avkastningen i SPU overføres derfor fra SPU til bruk over statsbudsjettet. I Norges Bank håndteres valutatransaksjonene knyttet til petroleumfondsmekanismen i en egen valutaportefølje kalt petrobufferporteføljen (PBP). Overgangen fra at det tidligere var en overføring til SPU til at det nå er en overføring fra SPU, har skapt endringer i utviklingen i denne porteføljen både gjennom måneden og året som helhet. Mens PBP tidligere steg gjennom måneden, vil den nå falle gjennom måneden. Dette gir et behov for å øke størrelsen på PBP fremover.publishedVersio
Branches of Foreign Banks and Credit Supply
No full textOver time, the government has received substantial revenues in both NOK and foreign currency from the petroleum sector (the government’s net cash flow). At the same time, the government earns considerable foreign currency income in the form of returns on the Government Pension Fund Global (GPFG). Some of this revenue is used each year to finance the non-oil budget deficit in line with the fiscal rule. Up until 2015, the government’s net cash flow from petroleum activities exceeded the non-oil deficit. The difference was then transferred to the GPFG. From 2016, the situation has been the reverse. The government’s net cash flow from petroleum activities is no longer sufficient to finance the entire non-oil deficit. Portions of the return on the GPFG are therefore transferred from the GPFG to be spent via the central government budget. At Norges Bank, foreign exchange transactions associated with the petroleum fund mechanisms are managed in a separate foreign exchange portfolio called the petroleum buffer portfolio (PBP). The transition from the previous situation with transfers to the GPFG to the current situation with transfers from the GPFG has resulted in changes in movements in this portfolio, both in the course of the month and during the year as a whole. While the level of the PBP previously rose through the month, it will now fall through the month. This results in a need to increase the size of the PBP ahead.publishedVersio
Finansiell stabilitet 2017: sårbarhet og risiko
No full textI den årlige rapporten Finansiell stabilitet vurderer Norges Bank sårbarhet og risiko i det finansielle systemet. Det legges vekt på langsiktige og strukturelle trekk ved bankene, finansmarkedene og norsk økonomi som har betydning for finansiell stabilitet. I Pengepolitisk rapport med vurdering av finansiell stabilitet gis en vurdering av den løpende utviklingen i finansielle ubalanser og i bankene, sammen med Norges Banks pengepolitiske vurderinger og beslutningsgrunnlaget for motsyklisk kapitalbuffer i bankene. Rapporten Det norske finansielle systemet gir en samlet oversikt over det finansielle systemet i Norge, dets oppgaver og hvordan disse oppgavene blir utført. Hovedstyret drøftet innholdet i rapporten Finansiell stabilitet 2017 på møtene 9. og 25. oktober.publishedVersio
Norsk økonomi og havet
Get PDFForedrag av sentralbanksjef Øystein Olsen på næringslivsseminar i Lofoten, i forbindelse med lanseringen av de nye 100- og 200-kronesedlene
Forvaltningen av Statens pensjonsfond utland
Get PDFSentralbanksjef Øystein Olsen. Innledning til høring om forvaltningen av Statens pensjonsfond utland 2016 i Stortingets finanskomité
What Should the Future Form of Our Money Be?
Get PDFSpeech by Deputy Governor Jon Nicolaisen at the Norwegian Academy of Science and Letters, 25 April 2017
Pengepolitisk rapport med vurdering av finansiell stabilitet 1/17
Get PDFPengepolitisk rapport med vurdering av finansiell stabilitet 1/17 har en annen kapittelinndeling enn de foregående rapportene. Prognosen for styringsrenten presenteres i kapittel 1 i rapporten. Rapporten blir lagt frem fire ganger i året, i mars, juni, september og desember. Rapporten vurderer utsiktene for renten og danner grunnlaget for Norges Banks råd om nivået på den motsykliske kapitalbufferen. Rapporten inneholder anslag for utviklingen i norsk økonomi. I møtet 8. mars 2017 drøftet hovedstyret de økonomiske utsiktene, hovedlinjene i pengepolitikken og behovet for en motsyklisk kapitalbuffer i bankene. På grunnlag av denne drøftingen og en tilråding fra bankens ledelse fattet hovedstyret i møtet 14. mars 2017 vedtak om styringsrenten. Hovedstyret vedtok også Norges Banks råd til Finansdepartementet om nivået på den motsykliske kapitalbufferen. Hovedstyrets vurdering av de økonomiske utsiktene og pengepolitikken er gjengitt i avsnittet «Hovedstyrets vurdering». Rådet om nivået på den motsykliske kapitalbufferen sendes Finansdepartementet i forbindelse med publisering av rapporten. Rådet offentliggjøres når Finansdepartementet har fattet sin beslutning
Asymmetric effects of monetary policy in regional housing markets
Get PDFThe responsiveness of house prices to monetary policy shocks depends both on the nature of the shock – expansionary versus contractionary – and on city-specific housing supply elasticities. We test and find supporting evidence for the hypothesis that expansionary monetary policy shocks have a larger impact on house prices when supply elasticities are low on 263 US metropolitan areas. We also test whether contractionary shocks are orthogonal to supply elasticities, as implied by downward rigidity of housing supply, and find supporting evidence. A final theoretical conjecture is that contractionary shocks should have a greater impact on house prices than expansionary shocks, as long as supply is not perfectly inelastic. For areas with high housing supply elasticity, our results are in line with this conjecture. However, for areas with an inelastic housing supply, we find that expansionary shocks have a greater impact on house prices than contractionary shocks. We provide evidence that this is related to a momentum effect that is more pronounced when house prices are increasing than when they are falling.publishedVersio
Conditional Forecasting with DSGE Models - a Conditional Copula Approach
Get PDFDSGE models may be misspecified in many dimensions, which can affect their forecasting performance. To correct for these misspecifications we can apply conditional information from other models or judgment. Conditional information is not accurate, and can be provided as a probability distribution over different outcomes. These probability distributions are often provided by a set of marginal distributions. To be able to condition on this information in a structural model we must construct the multivariate distribution of the conditional information, i.e. we need to draw multivariate paths from this distribution. One way to do this is to draw from the marginal distributions given a correlation structure between the different marginal distributions. In this paper we use the theoretical correlation structure of the model and a copula to solve this problem. The copula approach makes it possible to take into account more flexible assumption on the conditional information, such as skewness and/or fat tails in the marginal density functions. This method may not only improve density forecasts from the DSGE model, but can also be used to interpret the conditional information in terms of structural shocks/innovations.publishedVersio