Geir Høidal Bjønnes

Multinational Finance Journal 28(3-4) p. 3-39 Doi: https://doi.org/10.2139/ssrn.4022550

Journal of Finance 79(3) Doi: https://doi.org/10.1111/jofi.13337

In statistics, samples are drawn from a population in a data‐generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence‐generating process (EGP). We claim that EGP variation across researchers adds uncertainty—nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer‐review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.

International Journal of Finance and Economics Doi: https://doi.org/10.1002/ijfe.1953

This paper examines the price discovery process in a two-tier market, specifically the foreign-exchange market. The goal is to identify the sources of private information and to gain insights into the process through which that informa- tion influences the market price. Using a transactions database that includes trading-party identities, we show that sustained post-trade returns rise with bank size, implying that larger banks have an information advantage. The larger banks exploit this information advantage in placing limit orders as well as market orders. We also show that the bank's private information does not come from their corporate or government customers or from some asset managers. Instead, the bank's private information appears to come from other asset managers, including hedge funds, and from the bank's own analysis

Beta – Scandinavian Journal of Business Research 33(1) p. 43-60 Doi: https://doi.org/10.18261/issn.1504-3134-2019-01-04

We examine the volume-volatility relation in the foreign exchange (FX) market using a unique data set from the Swedish krona (SEK) market that contains observations of 90–95 percent of all transactions from 1995 until 2002. We show that the strength of the volume-volatility relation depends on the group of market participants trading. Financial trading volume has the highest correlation with volatility. Interbank trading between the largest Market-making banks is also positively correlated with volatility, while trading among Other market-making banks show no correlation with volatility. Trading by Non-Financial customers is not correlated with volatility at all when controlling for trading by other market participants. Interestingly, we show that (unexpected) spot volume and changes in net positions (spot and forward) by Financial customers Granger cause spot volume and changes in net positions by Non-Financial customers. Our results clearly show that market participants in the FX market are heterogeneous, suggesting that differences in trading strategies and information may explain the volume-volatility relation.

Praktisk Økonomi & Finans 34(3) p. 239-254 Doi: https://doi.org/10.18261/issn.1504-2871-2018-03-07

Selv om valutamarkedet er verdens største finansmarked, og ofte brukes som skolebokeksempelet på et marked med «perfekt konkurranse», finner vi at markedsmakt og prisdiskriminering spiller en betydelig rolle. Bankene prisdiskriminerer kundene sine basert på tilgjengelig informasjon. Dette er mulig fordi banken kjenner kundens identitet før den stiller kjøps- og salgskurser. Kunder med god innsikt i hvordan markedet fungerer kan kjøpe og selge valuta til en svært lav kostnad. Tilsvarende oppnår kunder som handler ofte en volumrabatt. Resultatene tilsier at kundene i valutamarkedet, for eksempel import- og eksportbedrifter, kan spare penger ved å vise innsikt i markedet. Dette kan de for eksempel gjøre gjennom å skaffe tilgang til bankens elektroniske handleplattform, og ved å anvende handleplattformer der bankene må konkurrere om kundene.