A comparison of extreme value theory approaches for determining value at risk

This paper compares a number of different extreme value models for determining the value at risk (VaR) of three LIFFE futures contracts. A semi-nonparametric approach is also proposed, where the tail events are modeled using the generalised Pareto distribution, and normal market conditions are captured by the empirical distribution function. The value at risk estimates from this approach are compared with those of standard nonparametric extreme value tail estimation approaches, with a small sample bias-corrected extreme value approach, and with those calculated from bootstrapping the unconditional density and bootstrapping from a GARCH(1,1) model. The results indicate that, for a holdout sample, the proposed semi-nonparametric extreme value approach yields superior results to other methods, but the small sample tail index technique is also accurate.

Does active management add any value?

The question as to whether active management adds any value above that of the funds investment policy is one of continual interest to investors. In order to investigate this issue in the UK real estate market we examine a number of related questions. First, how much return variability is explained by investment policy? Second, how similar are the policies across funds? Third, how much of a fund’s return is determined by investment policy? Finally, how was this added value achieved? Using data for 19 real estate funds we find that investment policy explains less than half of the variability in returns over time, nothing of the variation across funds and that more than 100% of a level of return is attributed to investment policy. The results also show UK real estate fund focus exclusively on trying to pick winners to add value and that in pursuit of active return fund mangers incur high tracking error risk, consequently, successful active management is very difficult to achieve. In addition, the results are dependent on the benchmark used to represent the investment policy of the fund. Nonetheless, active management can indeed add value to a real estate funds performance. This is the good news. The bad news is adding value is much more difficult to achieve than is generally accepted.

Explaining deviations from NAV in UK property companies: rationality and sentimentality

One of the most vexing issues for analysts and managers of property companies across Europe has been the existence and persistence of deviations of Net Asset Values of property companies from their market capitalisation. The issue has clear links to similar discounts and premiums in closed-end funds. The closed end fund puzzle is regarded as an important unsolved problem in financial economics undermining theories of market efficiency and the Law of One Price. Consequently, it has generated a huge body of research. Although it can be tempting to focus on the particular inefficiencies of real estate markets in attempting to explain deviations from NAV, the closed end fund discount puzzle indicates that divergences between underlying asset values and market capitalisation are not a ‘pure’ real estate phenomenon. When examining potential explanations, two recurring factors stand out in the closed end fund literature as often undermining the economic rationale for a discount – the existence of premiums and cross-sectional and periodic fluctuations in the level of discount/premium. These need to be borne in mind when considering potential explanations for real estate markets. There are two approaches to investigating the discount to net asset value in closed-end funds: the ‘rational’ approach and the ‘noise trader’ or ‘sentiment’ approach. The ‘rational’ approach hypothesizes the discount to net asset value as being the result of company specific factors relating to such factors as management quality, tax liability and the type of stocks held by the fund. Despite the intuitive appeal of the ‘rational’ approach to closed-end fund discounts the studies have not successfully explained the variance in closed-end fund discounts or why the discount to net asset value in closed-end funds varies so much over time. The variation over time in the average sector discount is not only a feature of closed-end funds but also property companies. This paper analyses changes in the deviations from NAV for UK property companies between 2000 and 2003. The paper present a new way to study the phenomenon ‘cleaning’ the gearing effect by introducing a new way of calculating the discount itself. We call it “ungeared discount”. It is calculated by assuming that a firm issues new equity to repurchase outstanding debt without any variation on asset side. In this way discount does not depend on an accounting effect and the analysis should better explain the effect of other independent variables.

The effect of asymmetries on stock index return value-at-risk estimates

It is widely accepted that equity return volatility increases more following negative shocks rather than positive shocks. However, much of value-at-risk (VaR) analysis relies on the assumption that returns are normally distributed (a symmetric distribution). This article considers the effect of asymmetries on the evaluation and accuracy of VaR by comparing estimates based on various models.