This paper introduces a new bias reducing method for kernel hazard estimation. The method is called global polynomial adjustment (GPA). It is a global correction which is applicable to any kernel hazard estimator. The estimator works well from a theoretical point of view as it asymptotically reduces bias with unchanged variance. A simulation study investigates the finite-sample properties of GPA. The method is tested on local constant and local linear estimators. From the simulation experiment we conclude that the global estimator improves the goodness-of-fit. An especially encouraging result is that the bias-correction works well for small samples, where traditional bias reduction methods have a tendency to fail.

This article presents an optional bonus-malus contract based on a priori risk classification of the underlying insurance contract. By inducing self-selection, the purchase of the bonus-malus contract can be used as a screening device. This gives an even better pricing performance than both an experience rating scheme and a classical no-claims bonus system. An application to the Danish automobile insurance market is considered.

5 Introduction 6 Problem statement 7 Methodology: 8 Standard & Poor 500 S&P 500 10 Financial Times Stock Exchange FTSE 100 11 Nihon Keizai Shimbun Stock Exchange Nikkei 225 13 Why these three markets 14 Gold market description 14 Dotcom bubble 2000 – 2002 16 The Housing crisis 2007-2008 16 Market capitalization weighted 18 Price-Weighted Index 19 Volatility index 21 Single linear regression theory 23 Estimating the Coefficients 24 Assumptions 25 Test if a linear relationship exists 26 Example 27 The Correlation equation 30 Example 30 Return on investment calculation 32 Real rate of return 32 Assumptions between S&P 500 and Nikkei 225 during the IT bubble: 32 Normality: 32 Mean of residuals is 0: 33 Heteroscedasticity: 33 No independence: 34 Critical assumptions between the indices: 34 Data analysis Nominal values 36 IT-bubble 36 Between crisis 38

AbstractWe study in detail the log-linear return approximation introduced by Campbell and Shiller (1988a). First, we derive an upper bound for the mean approximation error, given stationarity of the log dividend-price ratio. Next, we simulate various rational bubbles that have explosive conditional expectation, and we investigate the magnitude of the approximation error in those cases. We find that, surprisingly, the Campbell-Shiller approximation is very accurate even in the presence of large explosive bubbles. Only in very large samples do we find evidence that bubbles generate large approximation errors. Finally, we show that a bubble model in which expected returns are constant can explain the predictability of stock returns from the dividend-price ratio that many previous studies have documented.

We analyze the pitfalls involved in VAR based return decompositions. First, we show that recent criticism of such decompositions is misplaced and builds on invalid VAR models and erroneous interpretations. Second, we derive the requirements needed for VAR decompositions to be valid. A crucial – but often neglected – requirement is that the asset price needs to be included as a state variable in the VAR. In equity return decompositions this requirement is equivalent to including the dividend–price ratio in the VAR. Finally, we clarify the intriguing issue of the role of the residual component in return decompositions. In a properly specified first-order VAR, it makes no difference whether cash flow news or discount rate news is backed out residually, and it makes no difference whether both news components are computed directly or one of them is backed out residually.

Inherited corporate governance characteristics largely determine the ownership structure in Danish banks. Bad characteristics, including severe restrictions on shareholder rights, are associated with dispersed ownership. Banks with dispersed ownership take more risk and perform much worse than banks with a large individual shareholder. CEOs in banks with dispersed ownership are powerful, but only half of the CEOs in the sample studied decided to extract rents using incentive-based compensation – and only these banks took more risks and performed much worse than other banks. Given that these banks took more risk already before the introduction of incentive-based compensation, the use thereof is found to be an indicator of unfortunate traits of the CEO, which cannot be identified by other observable characteristics of the CEO.

Based on Chen and Zhao's (2009) criticism of VAR based return decompositions, we explain in detail the various limitations and pitfalls involved in such decompositions. First, we show that Chen and Zhao's interpretation of their excess bond return decomposition is wrong: the residual component in their analysis is not cashflow but interest rate which should not be zero. Consequently, in contrast to what Chen and Zhao claim, their decomposition does not serve as a valid caution against VAR based decompositions. Second, we point out that in order for VAR based decompositions to be valid, the asset price needs to be included as a state variable. In parts of Chen and Zhao's analysis the price does not appear as a state variable, thus rendering those parts of their analysis invalid. Finally, we clarify the intriguing issue of the role of the residual component in equity return decompositions. In a properly specified VAR, it makes no difference whether return news and dividend news are both computed directly or one of them is backed out as a residual.

Many financial markets, including electronic limit order markets, assign designated liquidity providers (LPs). We study the experience of the Stockholm Stock Exchange, where listed firms contract directly with LPs. Our analysis offers insights regarding situations where designated liquidity provision may be beneficial. In addition, we consider the form of liquidity provision contracts, including affirmative obligations required of the LP and compensation for LP services. We find that low current trading activity, wide spreads, and higher information asymmetry increase the attractiveness of contracted liquidity provision. The evidence indicates that LPs trade against market movements and in times of wide spreads. On balance, firms contracting with LPs experience a decreased cost of capital and significant improvements in market quality and price discovery.

A class of local linear kernel density estimators based on weighted least squares kernel estimation is considered within the framework of Aalen’s multiplicative intensity model. This model includes the filtered data model that, in turn, allows for truncation and/or censoring in addition to accommodat- ing unusual patterns of exposure as well as occurrence. It is shown that the local linear estimators corresponding to all different weightings have the same pointwise asymptotic properties. However, the weighting previously used in the literature in the i.i.d. case is seen to be far from optimal when it comes to exposure robustness, and a simple alternative weighting is to be preferred. Indeed, this weighting has, effectively, to be well chosen in a ‘pilot’ estimator of the survival function as well as in the main estimator itself. We also investigate multiplicative and additive bias correction methods within our framework. The multiplicative bias correction method proves to be best in a simulation study comparing the performance of the considered estimators. An example concerning old age mortality demonstrates the importance of the improvements provided.

With augmented demands on power grids resulting in longer and larger blackouts combined with heightened concerns of terrorist attacks, trading institutions and policy makers have widened their search for systems that avoid market failure during these disturbing events. We provide insight into this issue by examining trading behaviour at the Copenhagen Stock Exchange during a major blackout. We find that although market quality declined, markets remained functional and some price discovery occurred during the blackout period suggesting that the NOREX structure of interlinked trading systems combined with widely dispersed trading locations may be a viable means of protection against market failure during massive power disruptions or terrorist attacks.

We use a vector-autoregression, with parameter estimates corrected for small-sample bias, to decompose US and German unexpected bond returns into three ‘news’ components: news about future inflation, news about future real interest rates, and news about future excess bond returns (term premia). We then cross-country correlate these news components to see which component is responsible for the high degree of comovement of US and German bond markets. For the period 1975–2003 we find that inflation news is the main driving force behind this comovement. When news is coming to the US market that future US inflation will increase, there is a tendency that German inflation will also increase. This is regarded bad news for the bond market in both countries whereby bond prices are bid down leading to immediate negative return innovations and changing expectations of future excess bond returns. Thus, comovement in expected future inflation is the main reason for bond market comovement.

We present a new dividend-adjusted blue chip index for the Danish stock market covering the period 1985–2002. In contrast to other indices on the Danish stock market, the index is calculated on a daily basis. In the first part of the paper a detailed description of the construction of the index is given. In the second part of the paper we analyze the time-series properties of daily, weekly, and monthly returns, and we present evidence on predictability of multi-period returns. We also compare stock returns with the returns on long-term bonds and short-term money market instruments (that is, the equity risk premium), and we compute the Hansen–Jagannathan bound to infer the properties of the underlying stochastic discount factor generating Danish asset returns.