What makes students satisfied? A discussion and analysis of the UK’s national student survey

This paper analyses data from the National Students Survey, determining which groups of students expressed the greatest levels of satisfaction. We find students registered on clinical degrees and those studying humanities to be the most satisfied, with those in general engineering and media studies the least. We also find contentment to be higher among part-time students, and significantly higher among Russell group and post-1992 universities. We further investigate the sub-areas that drive overall student satisfaction, finding teaching and course organisation to be the most important aspects, with resources and assessment and feedback far less relevant. We then develop a multi- attribute measure of satisfaction which we argue produces a more accurate and more stable reflection of overall student satisfaction than that based on a single question

Value at Risk and Market Crashes

Many popular techniques for determining a securities firm’s value at risk are based upon the calculation of the historical volatility of returns to the assets that comprise the portfolio, and of the correlations between them. One such approach is the J.P. Morgan RiskMetrics methodology using Markowitz portfolio theory. An implicit assumption underlying this methodology is that the volatilities and correlations are constant throughout the sample period, and in particular that they are not systematically related to one another. However, it has been suggested in a number of studies that the correlation between markets increases when the individual volatilities are high. This paper demonstrates that this type of relationship between correlation and volatility can lead to a downward bias in the estimated value at risk, and proposes a number of pragmatic approaches that risk managers might adopt for dealing with this issue.Internal Risk Management Models, Stock Market Volatility, Value at Risk Models, Extreme Market Movements, Correlation Matrices, Mulivariate ARCH Model

The Extremes of the P/E Effect

The price-earnings effect has been a challenge to the idea of efficient markets for many years. The P/E used has always been the ratio of the current price to the previous year’s earnings. However, the P/E is partly determined by outside influences, such as the year in which it was measured, the size of the company, and the sector in which the company operates. Looking at all UK companies since 1975, we determine the power of these influences, and find that the sector influences the P/E in the opposite direction to the others. We use a regression to weight the influences according to their power in predicting returns, reversing the sector influence so that it works for us and not against us. The resulting weighted P/E widens the gap in annual returns between the value and glamour deciles by 8%, and identifies a value decile with average returns of 32%.

Decomposing the P/E Ratio

The price-earnings effect has been a challenge to the idea of efficient markets for many years. The P/E used has always been the ratio of the current price to the previous year’s earnings. However, the P/E is partly determined by outside influences, such as the year in which it was measured, the size of the company, and the sector in which the company operates. Looking at all UK companies since 1975, we determine the power of these influences, and find that the sector influences the P/E in the opposite direction to the others. We use a regression to weight the influences according to their power in predicting returns, reversing the sector influence so that it works for us and not against us. The resulting weighted P/E widens the gap in annual returns between the value and glamour deciles by 8%, and identifies a value decile with average returns of 32%.

The Long-Term P/E Radio

The price-earnings effect has been thoroughly documented and widely studied around the world. However, it has always been calculated on the basis of the previous year’s earnings. We show that the power of the effect has until now been seriously underestimated, due to taking too short-term a view of earnings. We look at all UK companies since 1975, and using the traditional P/E ratio we find the difference in average annual returns between the value and glamour deciles to be 6%, similar to other authors’ findings. We almost double that gap by calculating P/E ratios using earnings averaged over the last eight years. Averaging, however, implies equal weights for each past year. We widen the gap further by optimising the weights of the past years of earnings in the P/E ratio.

A Three-Regime Model of Speculative Behaviour: Modelling the Evolution of Bubbles in the S&P 500 Composite Index

In this paper we examine whether a three-regime model that allows for dormant, explosive and collapsing speculative behaviour can explain the dynamics of the S&P 500 Composite Index for the period 1888-2001. We extend existing two-regime models of speculative behaviour by including a third regime that allows for a bubble to grow at a steady growth rate, and examine whether other variables, beyond the deviation of actual prices from fundamental values can help predict the level and the generating state of returns. We propose abnormal volume as an indicator of the probable time of the bubble collapse and thus include abnormal volume in the state and the classifying equations of the surviving regime in the explosive state. We show that abnormal volume is a significant predictor and classifier of returns. Furthermore, we find that the spread of the 6-month average actual returns above the 6-month average fundamental returns can help predict when a bubble will enter the explosive state. Finally, we examine the financial usefulness of the three-regime model by studying the risk-adjusted profits of a trading rule formed using inferences from it. Use of the three-regime model trading rule leads to higher risk adjusted returns and end of period wealth than those obtained from employing existing models or a buy and hold strategy.Stock market bubbles, fundamental values, dividends, regime switching, speculative bubble tests

Speculative Bubbles in the S&P 500: Was the Tech Bubble Confined to the Tech Sector?

This study tests for the presence of periodically, partially collapsing speculative bubbles in the sector indices of the S&P 500 using a regime-switching approach. We also employ an augmented model that includes trading volume as a technical indicator to improve the ability of the model to time bubble collapses and to better capture the temporal variations in returns. We find that over 70% of the S&P 500 index by market capitalization, and seven of its ten sector component indices exhibited bubble-like behaviour over our sample period. Thus the speculative bubble that grew in the 1990’s and subsequently collapsed was pervasive in the US equity market. The bubble affected numerous sectors including energy and industrials, rather than being confined to information technology, telecommunications and the media.Stock market bubbles, fundamental values, dividends, regime switching, speculative bubble test.

Optimal Hedging with Higher Moments

This study proposes a utility-based framework for the determination of optimal hedge ratios that can allow for the impact of higher moments on the hedging decision. The approach is applied to a set of 20 commodities that are hedged with futures contracts. We find that in sample, the performance of hedges constructed allowing for non-zero higher moments is only very slightly better than the performance of the much simpler OLS hedge ratio. When implemented out of sample, utility-based hedge ratios are usually less stable over time, and can make investors worse off for some assets compared to hedging using the traditional methods. We conclude, in common with a growing body of very recent literature, by suggesting that higher moments matter in theory but not in practice.Utility-based hedging, OLS, Non-normality, risk, commodity futures, skewness, kurtosis

The Statistical Properties of Hedge Fund Index Returns

he monthly return distributions of many hedge fund indices exhibit highly unusual skewness and kurtosis properties as well as first-order serial correlation. This has important consequences for investors. We demonstrate that although hedge fund indices are highly attractive in mean-variance terms, this is much less the case when skewness, kurtosis and autocorrelation are taken into account. Sharpe Ratios will substantially overestimate the true risk-return performance of (portfolios containing) hedge funds. Similarly, mean-variance portfolio analysis will over-allocate to hedge funds and overestimate the attainable benefits from including hedge funds in an investment portfolio. We also find substantial differences between indices that aim to cover the same type of strategy. Investors’ perceptions of hedge fund performance and value added will therefore strongly depend on the indices used.Hedge fund, hedge fund index, skewness, kurtosis, autocorrelation, sharpe ratio, mean-variance analysis

A New Tool for Detecting Intraday Periodicities with Application to High Frequency Exchange Rates

In this paper we investigate the claim that hedge funds offer investors a superior risk-return trade-off. We do so using a continuous time version of Dybvig’s (1988a, 1988b) payoff distribution pricing model. The evaluation model, which does not require any assumptions with regard to the return distribution of the funds in question, is applied to the monthly returns of 77 hedge funds and 13 hedge fund indices over the period May 1990 – April 2000. The results show that as a stand-alone investment hedge funds do not offer a superior risk-return profile. We find 12 indices and 72 individual funds to be inefficient, with the average efficiency loss amounting to 2.76% per annum for indices and 6.42% for individual funds. Part of the inefficiency cost of individual funds can be diversified away. Funds of funds, however, are not the preferred vehicle for this as their performance appears to suffer badly from their double fee structure. Looking at hedge funds in a portfolio context results in a marked improvement in the evaluation outcomes. Seven of the 12 hedge fund indices and 58 of the 72 individual funds classified as inefficient on a stand-alone basis are capable of producing an efficient payoff profile when mixed with the S&P 500. The best results are obtained when 10-20% of the portfolio value is invested in hedge funds.Spectral Analysis, Periodicities, Seasonality, Forecasting Exchange Rates, Trading Rules