This article examines whether reducing a market's transparency, by delaying the publication of prices for block trades, has any impact on liquidity. The analysis uses a sample of 5987 blocks from the London Stock Exchange that cover three different publication regimes: immediate (1987/88), 90 minutes (1991/92), and 24 hours (1989/90). Delaying publication does not affect the time taken by prices to reach a new level, which is rapid under all regimes. Spreads differ across years, but their size relates more closely to market volatility than to speed of publication. There is therefore no gain in liquidity from delayed publication.

This article examines whether reducing a market's transparency, by delaying the publication of prices for block trades, has any impact on liquidity. The analysis uses a sample of 5,987 blocks from the London Stock Exchange that cover three different publication regimes: immediate (1987/88), ninety minutes (1991/92), and twenty-four hours (1989/90). Delaying publication does not affect the time taken by prices to reach a new level, which is rapid under all regimes. Spreads differ across years but their size relates more closely to market volatility than to speed of publication. There is, therefore, no gain in liquidity from delayed publication.

This article examines whether reducing a market's transparency, by delaying the publication of prices for block trades, has any impact on liquidity. The analysis uses a sample of 5987 blocks from the London Stock Exchange that cover three different publication regimes: immediate (1987/88), 90 minutes (1991/92), and 24 hours (1989/90). Delaying publication does not affect the time taken by prices to reach a new level, which is rapid under all regimes. Spreads differ across years, but their size relates more closely to market volatility than to speed of publication. There is therefore no gain in liquidity from delayed publication.

We investigate why spreads on corporate bonds are so much larger than expected losses from default. Systematic factors make very little contribution to spreads, even if higher moments or downside effects are taken into account. Instead we find that sizes of spreads are strongly related to idiosyncratic-risk factors: not only to idiosyncratic equity volatility, but even more to idiosyncratic bond volatility and idiosyncratic bond value-at-risk. Idiosyncratic bond volatility helps to explain spreads because it reflects not just the distribution of firm value but is also a proxy for liquidity risk. Idiosyncratic bond value-at-risk adds to this by capturing the left-skewness of the firm-value distribution. We confirm our results both for the initial 1997–2004 sample period and also out of sample for 2005–2009, which includes the sub-prime crisis. Overall, credit spreads are large because they incorporate a large risk premium related to investors’ fears of extreme losses.

This study of warrants on the London Stock Exchange examines whether they display particular pricing biases and whether investors understand how to value them at the time of issue. In a sample of 72 warrants on closed-end funds (investment trusts) over the 1985–94 period, more than one third of the 12,673 prices are anomalously low. The other two thirds behave like stock options, with lower volatility when they are in-the-money or have a long time until maturity. Despite their frequent undervaluation, it is rational to add warrants to a new equity issue: an examination of 127 new equity issues (95 with warrants) reveals that attaching warrants significantly increases market value. The reason for this appears to be investor confusion: they do not seem to understand that the more the warrants are worth, the less the value of the ordinary shares.

We examine whether CDS prices around the Credit Crisis can be explained with Merton’s model. First we invert the model with market prices to reveal skewed volatility smiles over the whole 2005–2012 period. Then we calibrate the model to pre-Crisis data in two novel ways that allow for skewness, one based on equity-index options (MEIV) and the other on the sensitivity of CDS prices to equity volatility (MSKEW). In out-of-sample forecasts both calibrations match the in-Crisis peak of prices, but the second is better at capturing the systematic component of prices thereafter. Average CDS prices remain at twice their pre-Crisis level long after that event; the MSKEW calibration demonstrates that this is due to extra idiosyncratic risks, which are important for some firms but have negligible impact on others.

If arbitrage is costly and noise traders are active, asset prices may deviate from fundamental values for long periods of time. We use a sample of 158 closed‐end funds to show that noise‐trader sentiment, as proxied by retail‐investor flows, leads to fluctuations in the discount. Nevertheless, we reject the hypothesis that noise‐trader risk is the cause of the long‐run discount. Instead we find that funds which are more difficult to arbitrage have larger discounts, due to: (1) the censoring of the discount by the arbitrage bounds, and (2) the freedom of managers to increase charges when arbitrage is costly.