Why Do Traders Split Orders?

We examine factors that influence decisions by U.S. equity traders to execute a string of orders, in the same stock, in the same direction, around the same time. Order splitting is more likely to occur when traders submit larger‐size orders and when market depth and trading activity are lower. Order splitters demand liquidity more and pay higher trading costs, but their overall performance is better. When controlling for execution time, split orders are more informative than single orders. Our results suggest that order splitting arises from a variety of factors, including informational differences, order and trader characteristics, and market conditions.     

<Emphasis Type="Italic">K</Emphasis>-fold cross validation performance comparisons of six naive portfolio selection rules: how naive can you be and still have successful out-of-sample portfolio performance?

Recent research reports that optimal portfolio selection models often perform worse than equal-weight naive diversification in out-of-sample testing. This paper extends this line of inquiry by comparing the out-of-sample performance of the equal-weight naive strategy to the out-of-sample performance of five alternative naive strategies, each of which derives from a simple heuristic that does not require any optimization. Out-of-sample portfolio performance is assessed by mean, standard deviation, skewness, and Sharpe ratio; k-fold cross validation is used as the out-of-sample testing mechanism. The results indicate that the proposed naive heuristic rules exhibit strong out-of-sample performance, in most cases superior to the equal-weight naive strategy. These findings are consequential for at least two reasons: first, if these simple heuristic-based rules outperform the equal-weight naive strategy, then by transitivity they can outperform the mean–variance- and shortfall-optimal portfolio rules that have been shown in the literature to be inferior to the equal-weight naive rule, which further emphasizes the out-of-sample fragility of “optimal” methods; and second, among naive diversification strategies, some appear more robust in out-of-sample testing than others, hence the proposed methods may be useful when forming mixed portfolio selection models wherein a naive strategy is combined with an optimal strategy to improve performance.     

ETF Competition and Market Quality

This paper examines competition between exchange traded funds (ETFs) that hold nearly identical portfolios of securities. We provide evidence that incumbent‐fund liquidity is negatively affected when a new ETF is added to an asset class. The degradation in liquidity is even more severe whenever both funds follow the same benchmark. We also document a decline in primary‐market activity for the incumbent ETFs after the arrival of new competitors. Furthermore, increasing the number of funds in an asset class does not put downward pressure on fund management fees. Thus, the deterioration in market quality may not be offset by decreasing costs of fund ownership.     

Optimum government credibility in an open-economy fiscal expansion

A real open-economy model is constructed in which the government's commitment to a future fiscal expansion is not credible. Government credibility (measured by the growth rate of the probability that the expansion will occur) becomes a parameter of the system and appears directly in the eigenvalues. Simulations are performed demonstrating the effect of credibility on GNP, the exchange rate, and other variables. Lastly, the optimum credibility is determined which minimizes a loss function associated with deviations from full employment.     

Tourist experiences,phenomenographic analysis,post‐postivism and neural network software

This paper argues that tourist experiences are essentially individualistic, although it is possible to discern consensual realties. It follows the viewpoint that positivistic research methodologies contain limitations in not being able to define the nature of individual tourist experience, and suggests that phenomenographic analysis may be one approach that permits both a revelation of individual experience while permitting model building of the shared consensus of what is actually happening. More tentatively it is suggested that, when allied with the use of current developments in software, such as that of CATPAC™, a post‐positivist paradigm of research results. Some results of research using this approach are indicated. Copyright © 2000 John Wiley & Sons, Ltd.     

A post-carbon aviation future: Airports and the transition to a cleaner aviation sector

There is an increasing global interest in sustainable aviation technologies as a result of concerns associated with the carbon-intensive nature of the industry and the imminence of reaching peak oil. Available options such as biofuels, liquid hydrogen and electric propulsion will not only impact on the design and functionality of commercial airplanes, but also will affect the entire industry from supply through to operation and maintenance. However, on account of the global spread and international nature of aviation, in addition to the lock-in effect associated with existing fossil-fuel driven technology, the present aviation paradigm is not well equipped for a massive or rapid technological transition. This paper first provides an overview of selected available propulsion options, as well as their possible impact on the aviation infrastructure. It then sets out to identify the existing regime players in the aviation transition arena as a means to provide an overview of potential path trajectories, with a view to assessing how airport owners and other salient regime players can either facilitate or hinder the transition to alternative and less carbon-intensive technologies.     

Profiling road transport activity: Emissions from 2000 to 2005 in Ireland using national car test data

This work describes a methodology for determining the average vehicle kilometres travelled by the private national car fleet in Ireland and estimating the disaggregated CO₂ and NO_x emissions from private vehicles in the Irish road transport sector for the period 2000–2005 using national car test records. The developed methodology facilitates the calculation of greatly improved estimates for vehicle kilometres under a range of constraint variables and thereby enables the disaggregated analysis of specific vehicle fleet groups and their associated activity patterns to support evidence-based policy development. The results indicate that while older vehicles are contributing significantly to car NO_x emissions; newer cars produce a higher share of CO₂ emissions than older cars in the vehicle fleet.     

Confirming the timing of phase-based costing in oncology studies: a case example in advanced melanoma

Aims: The utilization of healthcare services and costs among patients with cancer is often estimated by the phase of care: initial, interim, or terminal. Although their durations are often set arbitrarily, we sought to establish data-driven phases of care using joinpoint regression in an advanced melanoma population as a case example.

Methods: A retrospective claims database study was conducted to assess the costs of advanced melanoma from distant metastasis diagnosis to death during January 2010–September 2014. Joinpoint regression analysis was applied to identify the best-fitting points, where statistically significant changes in the trend of average monthly costs occurred. To identify the initial phase, average monthly costs were modeled from metastasis diagnosis to death; and were modeled backward from death to metastasis diagnosis for the terminal phase. Points of monthly cost trend inflection denoted ending and starting points. The months between represented the interim phase.

Results: A total of 1,671 patients with advanced melanoma who died met the eligibility criteria. Initial phase was identified as the 5-month period starting with diagnosis of metastasis, after which there was a sharp, significant decline in monthly cost trend (monthly percent change [MPC]?=?–13.0%; 95% CI?=?–16.9% to –8.8%). Terminal phase was defined as the 5-month period before death (MPC?=?–14.0%; 95% CI?=?–17.6% to –10.2%).

Limitations: The claims-based algorithm may under-estimate patients due to misclassifications, and may over-estimate terminal phase costs because hospital and emergency visits were used as a death proxy. Also, recently approved therapies were not included, which may under-estimate advanced melanoma costs.

Conclusions: In this advanced melanoma population, optimal duration of the initial and terminal phases of care was 5 months immediately after diagnosis of metastasis and before death, respectively. Joinpoint regression can be used to provide data-supported phase of cancer care durations, but should be combined with clinical judgement.     

Real-world utilization of molecular diagnostic testing and matched drug therapies in the treatment of metastatic cancers

Aims: To assess the frequency of biopsies and molecular diagnostic testing (human DNA/RNA analysis), anti-cancer drug use (genomically-matched targeted therapy [GMTT], unmatched targeted therapy [UTT], endocrine therapy [ET], and chemotherapy [CT]), and medical service costs among adults with metastatic cancer.

Methods: Adults diagnosed with metastatic breast, non-small cell lung (NSCLC), colorectal, head and neck, ovarian, and uterine cancer (2010Q1–2015Q1) were identified in the OptumHealth Care Solutions claims database and followed from first metastatic diagnosis for ≥1 month and until the end of data availability. Utilization was assessed for each cancer cohort (all and patients aged ≥65 years); per-patient-per-month (PPPM) medical service costs were assessed for all patients. Testing frequency estimates were applied to Surveillance, Epidemiology, and End Results Program data to estimate the number of untested patients (2010–2014).

Results: Patients with metastatic cancer (n?=?8,193; breast [n?=?3,414], NSCLC [n?=?2,231], colorectal [n?=?1,611], head and neck [n?=?511], ovarian [n?=?275], and uterine [n?=?151]) were 63 years old (mean), with 11.1–22.2 months of observation. Biopsy and molecular diagnostic testing frequencies ranged from 7% (uterine) to 73% (ovarian), and from 34% (head and neck) to 52% (breast), respectively. Few were treated with GMTT (breast, 11%; NSCLC, 9%; colorectal, 6%). Treatment with UTT ranged from 0.7% (uterine) to 21% (colorectal). Biopsy, diagnostic testing, and anti-cancer drug therapy were less frequent for those ≥65 years. Medical service costs (PPPM, mean) ranged from $6,618 (head and neck) to $9,940 (ovarian). The estimated number of untested new patients with metastatic cancer was 636,369 (all) and 341,397 (≥65).

Limitations: In addition to the limitations of claims analyses, diagnostic testing frequency may be under-estimated if patients underwent testing prior to study inclusion.

Conclusions: The low frequency of molecular diagnostic testing suggests there are opportunities to better inform management of patients with advanced cancer, particularly decisions to treat with GMTT.