Abstracts for published papers
Using unique data, we address the issue of price formation in a limit order market. A standard volume–volatility relation is documented with the number of trades acting as the important component of volume. The main contribution of the paper is to identify strong evidence that volume, volatility, and the volume–volatility relation are negatively related to the order book slope. These results are robust to the inclusion of several liquidity measures. A significant empirical relationship between the order book slope and the coefficient of variation in earnings forecasts by financial analysts suggests that the slope is proxying for disagreement among investors. Hence, our results support models where investor heterogeneity intensifies the volume–volatility relation.
"Equity trading by institutional investors: Evidence on order submission strategies" (with Randi Næs), Journal of Banking and Finance, vol.27, issue 7 (2003), p. 1779 - 1817
The trading volume channelled through off-market crossing networks is growing. Passive matching of orders outside the primary market lowers several components of execution costs compared to regular trading. On the other hand, the risk of non-execution imposes opportunity costs, and the inherent “free riding” on the price discovery process raises concerns that this eventually will lead to lower liquidity in the primary market. Using a detailed data set from a large investor in the US equity markets, we find evidence that competition from crossing networks is concentrated in the most liquid stocks in a sample of the largest companies in the US. Simulations of alternative trading strategies indicate that the investor’s strategy of initially trying to cross all stocks was cost e.ective: in spite of their high liquidity, the crossed stocks would have been unlikely to achieve at lower execution costs in the open market.
"On- or off-market trading? Evidence on Competition, Liquidity and Execution Costs" (with Randi Næs), Canadian Investment Review, Fall 2003, pp. 47-51
There is currently a plethora of venues for trading equities. Some fit the needs of small retail investors, while others are more suited for large institutional investors and portfolio managers. In this article, we summarize the results from a case study of a large institutional investor in the U.S. equity market who tried to acquire a stock portfolio through crossing networks rather than the primary markets. A crossing network is a satellite-trading place: orders are matched passively (crossed) at prices taken from a primary market. Compared to regular market trading, crossing networks have low commissions, and there is no direct priceimpact costs related to a crossed order. On the other hand, there may be opportunity costs associated with the fact that traders are not guaranteed execution in the network. In addition, the execution probability may be associated with adverse selection. This can happen if there are participants in the network with private information. Satellite trading does not contribute to price discovery. This has raised concerns about potentially negative effects from this form of trading on the liquidity in the primary market.
"Scaling in the Norwegian Stock Market", Physica A, issue 283, (2000), pp. 486-528.
The main objective of this paper is to investigate the validity of the much used assumptions that stock market returns follow a random walk and are normally distributed. For this purpose the concepts of chaos theory and fractals are applied. Two independent models are used to examine price variations in the Norwegian and US stock markets. The first model used is the range over standard deviation or R/S statistic which tests for persistence or antipersistence in the time series. Both the Norwegian and US stock markets show significant persistence caused by long run "memory" components in the series. In addition, an average non-periodic cycle of four years is found for the US stock market. These results are not consistent with the random walk assumption.The second model investigates the distributional scaling behaviour of the high-frequency price variations in the Norwegian stock market. The results show a remarkable constant scaling behaviour between different time intervals. This means that there is no intrinsic time scale for the dynamics of stock price variations. The relationship can be expressed through a scaling exponent, describing the development of the distributions as the time scale changes. This description may be important when constructing or improving pricing models such that they coincide more closely with the observed market behaviour. The empirical distributions of high-frequency price variations for the Norwegian stock market is then compared to the Lévy stable distribution with the relevant scaling exponent found by using the R/S- and distributional scaling analysis. Good agreement is found between the Lévy profile and the empirical distribution for price variations less than ±6 standard deviations, covering almost three orders of magnitude in the data. For probabilities larger than ±6 standard deviations, there seem to be an exponential fall-off from the Lévy profile in the tails which indicates that the second-moment may be finite.
