Return Persistence and Fund Flows in the Worst Performing Mutual Funds

We document that the observed persistence amongst the worst performing actively managed mutual funds is attributable to funds that have performed poorly both in the current and prior year. We demonstrate that this persistence results from an unwillingness of investors in these funds to respond to bad performance by withdrawing their capital. In contrast, funds that only performed poorly in the current year have a significantly larger (out)flow of funds/return sensitivity and consequently show no evidence of persistence in their returns.

Mutual Fund Flows and Performance in Rational Markets

We develop a simple rational model of active portfolio management that provides a natural benchmark against which to evaluate observed relationship between returns and fund flows. We show that many effects widely regarded as anomalous are consistent with this simple explanation. In the model, investments with active managers do not outperform passive benchmarks because of the competitive market for capital provision, combined with decreasing returns to scale in active portfolio management. Consequently, past performance cannot be used to predict future returns, or to infer the average skill level of active managers. The lack of persistence in active manager returns does not imply that differential ability across managers is nonexistent or unrewarded, that gathering information about performance is socially wasteful, or that chasing performance is pointless. A strong relationship between past performance and the ow of funds exists in our model, indeed this is the market mechanism that ensures that no predictability in performance exists. Calibrating the model to the fund flows and survivorship rates, we nd these features of the data are consistent with the vast majority (80%) of active managers having at least enough skill to make back their fees.

Human Capital, Bankruptcy and Capital Structure

We derive a firm's optimal capital structure and managerial compensation contract when employees are averse to bearing their own human capital risk, while equity holders can diversify this risk away. In the presence of corporate taxes, our model delivers optimal debt levels consistent with those observed in practice. It also makes a number of predictions for the cross-sectional distribution of firm leverage. Consistent with existing empirical evidence, it implies persistent idiosyncratic differences in leverage across firms. An important new empirical prediction of the model is that, ceteris paribus, firms with more leverage should pay higher wages.

Modelling the impacts of pasture contamination and stocking rate for the development of targeted selective treatment strategies for Ostertagia ostertagi infection in calves

A simulation study was carried out to assess whether variation in pasture contamination or stocking rate impact upon the optimal design of targeted selective treatment (TST) strategies. Two methods of TST implementation were considered: 1) treatment of a fixed percentage of a herd according to a given phenotypic trait, or 2) treatment of individuals that exceeded a threshold value for a given phenotypic trait. Four phenotypic traits, on which to base treatment were considered: 1) average daily bodyweight gain, 2) faecal egg count, 3) plasma pepsinogen, or 4) random selection. Each implementation method (fixed percentage or threshold treatment) and determinant criteria (phenotypic trait) was assessed in terms of benefit per R (BPR), the ratio of average benefit in weight gain to change in frequency of resistance alleles R (relative to an untreated population). The impact of pasture contamination on optimal TST strategy design was investigated by setting the initial pasture contamination to 100, 200 or 500 O. ostertagi L3/kg DM herbage; stocking rate was investigated at a low (3calves/ha), conventional (5 calves/ha) or high (7 calves/ha) stocking rates. When treating a fixed percentage of the herd, treatments according to plasma pepsinogen or random selection were identified as the most beneficial (i.e. resulted in the greatest BPR) for all levels of initial pasture contamination and all stocking rates. Conversely when treatments were administered according to threshold values ADG was most beneficial, and was identified as the best TST strategy (i.e. resulted in the greatest overall BPR) for all levels of initial pasture contamination and all stocking rates

Modelling the consequences of targeted selective treatment strategies on performance and emergence of anthelmintic resistance amongst grazing calves

The development of anthelmintic resistance by helminths can be slowed by maintaining refugia on pasture or in untreated hosts. Targeted selective treatments (TST) may achieve this through the treatment only of individuals that would benefit most from anthelmintic, according to certain criteria. However TST consequences on cattle are uncertain, mainly due to difficulties of comparison between alternative strategies. We developed a mathematical model to compare: 1) the most ‘beneficial’ indicator for treatment selection and 2) the method of selection of calves exposed to Ostertagia ostertagi, i.e. treating a fixed percentage of the population with the lowest (or highest) indicator values versus treating individuals who exceed (or are below) a given indicator threshold. The indicators evaluated were average daily gain (ADG), faecal egg counts (FEC), plasma pepsinogen, combined FEC and plasma pepsinogen, versus random selection of individuals. Treatment success was assessed in terms of benefit per R (BPR), the ratio of average benefit in weight gain to change in frequency of resistance alleles R (relative to an untreated population). The optimal indicator in terms of BPR for fixed percentages of calves treated was plasma pepsinogen and the worst ADG; in the latter case treatment was applied to some individuals who were not in need of treatment. The reverse was found when calves were treated according to threshold criteria, with ADG being the best target indicator for treatment. This was also the most beneficial strategy overall, with a significantly higher BPR value than any other strategy, but its degree of success depended on the chosen threshold of the indicator. The study shows strong support for TST, with all strategies showing improvements on calves treated selectively, compared with whole-herd treatment at 3, 8, 13 weeks post-turnout. The developed model appeared capable of assessing the consequences of other TST strategies on calf populations

A stochastic model to investigate the effects of control strategies on calves exposed to Ostertagia ostertagi

Predicting the effectiveness of parasite control strategies requires accounting for the responses of individual hosts and the epidemiology of parasite supra- and infra-populations. The first objective was to develop a stochastic model that predicted the parasitological interactions within a group of first season grazing calves challenged by Ostertagia ostertagi, by considering phenotypic variation amongst the calves and variation in parasite infra-population. Model behaviour was assessed using variations in parasite supra-population and calf stocking rate. The model showed the initial pasture infection level to have little impact on parasitological output traits, such as worm burdens and FEC, or overall performance of calves, whereas increasing stocking rate had a disproportionately large effect on both parasitological and performance traits. Model predictions were compared with published data taken from experiments on common control strategies, such as reducing stocking rates, the ‘dose and move’ strategy and strategic treatment with anthelmintic at specific times. Model predictions showed in most cases reasonable agreement with observations, supporting model robustness. The stochastic model developed is flexible, with the potential to predict the consequences of other nematode control strategies, such as targeted selective treatments on groups of grazing calves

Committee structure and its implications for Monetary policy decision-making

We investigate the implications for the setting of interest rates when monetary policy decisions are taken by a committee, in which a subset of members may meet prior to the voting in the committee and therefore has the possibility to reach consensus ex ante to vote unanimously ex post. We allow for different committee sizes, various voting rules and differences in skills among committee members. We find that the size of the committee is much less important in deter- mining the degree of interest rate inertia than the skills of committee members. Moreover, prior interaction of a subgroup only has a minor effect on the setting of interest rates by the committee, provided that members on average are equally skilled and voting takes place using a simple majority rule. If either of those assumptions are relaxed, prior interaction has substantial effects on the setting of interest rates. In addition, prior interaction increases the optimal size of the Committee, ceteris paribus