Volume and Volatility in the FX-Market: Does it matter who you are?

The relationship between volume and volatility has received much attention in the the literature of financial markets. However, due to the lack of data, few results have been presented for the foreign exchange market. Further, most studies contain only aggregate series, and can not distinguish between the impact of different instruments or participants.We study the impact of volume on volatility in the the FX-market using a unique data set of daily trading in the Swedish krona (SEK) market. The data set covers 95 per cent of worldwide SEK-trading, and is disaggregated on a number of reporting banks’ buying and selling in five different instruments on a daily basis over a period of nine years. We find that volume in general depict a positive correlation with volatility. However, the strength of the relationship depends on the instrument used and the identity of the reporting bank. In particular we find that it is the large Swedish banks that dominate the relationship. These banks are probably also the best informed banks. We interpret this is as evidence that heterogeneous expectations are important to understand the volume-volatility relationship.volume volatility relation, microstructure, exchange rates.

“Large” vs. “small” players: A closer look at the dynamics of speculative attacks

What is the role of “large players” like hedge funds and other highly leveraged institutions in speculative attacks? In recent theoretical work, large players may induce an attack by an early move, providing information to smaller agents. In contrast, many observers argue that large players are in the rear. We propose a model that allows both the large player to move early in order to induce speculation by small players, or wait so as to benefit from a high interest rate prior to the attack. Using data on net positions of “large” (foreigners) and “small” (locals) players,we find that large players moved last in three attacks on the Norwegian krone (NOK) during the1990s: The ERM-crisis of 1992, the NOK-pressure in 1997, and after the Russian moratorium in1998. In 1998 there was a contemporaneous attack on the Swedish krona (SEK) in which large players moved early. Interest rates did not increase in Sweden so there was little to gain by a delayed attack.Speculative attacks, microstructure, international finance, large players

Non-Standard Errors

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: Non-standard 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 better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Non-Standard Errors

In statistics, samples are drawn from a population in a datagenerating 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: Non-standard 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 better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants