255 research outputs found

    The Random Walk of High Frequency Trading

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    This paper builds a model of high-frequency equity returns by separately modeling the dynamics of trade-time returns and trade arrivals. Our main contributions are threefold. First, we characterize the distributional behavior of high-frequency asset returns both in ordinary clock time and in trade time. We show that when controlling for pre-scheduled market news events, trade-time returns of the highly liquid near-month E-mini S&P 500 futures contract are well characterized by a Gaussian distribution at very fine time scales. Second, we develop a structured and parsimonious model of clock-time returns by subordinating a trade-time Gaussian distribution with a trade arrival process that is associated with a modified Markov-Switching Multifractal Duration (MSMD) model. This model provides an excellent characterization of high-frequency inter-trade durations. Over-dispersion in this distribution of inter-trade durations leads to leptokurtosis and volatility clustering in clock-time returns, even when trade-time returns are Gaussian. Finally, we use our model to extrapolate the empirical relationship between trade rate and volatility in an effort to understand conditions of market failure. Our model suggests that the 1,200 km physical separation of financial markets in Chicago and New York/New Jersey provides a natural ceiling on systemic volatility and may contribute to market stability during periods of extremely heavy trading

    Order protection through delayed messaging

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    Several financial exchanges have recently introduced messaging delays (e.g., a 350 microsecond delay at IEX and NYSE American) intended to protect ordinary investors from high-frequency traders who exploit stale orders. We propose an equilibrium model of this exchange design as a modification of the standard continuous double auction market format. The model predicts that a messaging delay will generally improve price efficiency and lower transactions cost but will increase queuing costs. Some of the predictions are testable in the field or in a laboratory environment

    Experiments in high-frequency trading: comparing two market institutions

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    Order Protection Through Delayed Messaging

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    Several financial exchanges (e.g., IEX and NYSE American) recently introduced messaging delays to protect ordinary investors from high-frequency traders who exploit stale orders. To capture the impact of such delays, we propose a simple parametric model of the continuous double auction market format. The model examines the dynamics of midpoint pegged order queues and finds their steady states. It shows how messaging delays can protect pegged orders and improve investor welfare, but typically increase queuing costs. Recently available field data show that the empirical distribution of queued pegged orders is highly leptokurtotic and resembles the discrete Laplace distribution predicted by the model

    Tapping the Supercomputer Under Your Desk: Solving Dynamic Equilibrium Models with Graphics Processors

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    This paper shows how to build algorithms that use graphics processing units (GPUs) installed in most modern computers to solve dynamic equilibrium models in economics. In particular, we rely on the compute unified device architecture (CUDA) of NVIDIA GPUs. We illustrate the power of the approach by solving a simple real business cycle model with value function iteration. We document improvements in speed of around 200 times and suggest that even further gains are likely.

    Prediction of Breast Cancer-Related Lymphedema By Dermal Backflow Detected With Near-infrared Fluorescence Lymphatic Imaging

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    PURPOSE: Mild breast cancer-related lymphedema (BCRL) is clinically diagnosed as a 5%-10% increase in arm volume, typically measured no earlier than 3-6 months after locoregional treatment. Early BCRL treatment is associated with better outcomes, yet amid increasing evidence that lymphedema exists in a latent form, treatment is typically delayed until arm swelling is obvious. In this study, we investigated whether near-infrared fluorescence lymphatic imaging (NIRF-LI) surveillance could characterize early onset of peripheral lymphatic dysfunction as a predictor of BCRL. METHODS: In a prospective, longitudinal cohort/observational study (NCT02949726), subjects with locally advanced breast cancer who received axillary lymph node dissection and regional nodal radiotherapy (RT) were followed serially, between 2016 and 2021, before surgery, 4-8 weeks after surgery, and 6, 12, and 18 months after RT. Arm volume was measured by perometry, and lymphatic (dys) function was assessed by NIRF-LI. RESULTS: By 18 months after RT, 30 of 42 study subjects (71%) developed mild-moderate BCRL (i.e., ≥ 5% arm swelling relative to baseline), all manifested by dermal backflow of lymph into lymphatic capillaries or interstitial spaces. Dermal backflow had an 83% positive predictive value and 86% negative predictive value for BCRL, with a sensitivity of 97%, specificity of 50%, accuracy of 83%, positive likelihood ratio of 1.93, negative likelihood ratio of 0.07, and odds ratio of 29.00. Dermal backflow appeared on average 8.3 months, but up to 23 months, before the onset of mild BCRL. CONCLUSION: BCRL can be predicted by dermal backflow, which often appears months before arm swelling, enabling early treatment before the onset of edema and irreversible tissue changes

    Halal market emergence and export opportunity: the comparative advantage perspective

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    The comparative advantage theory of international trade states that countries should export commodities for which they have high comparative advantage and import commodities for which they have low comparative advantage. Analyzing the Halal trade flows for Malaysia’s 11 food/foodrelated commodities from 1991 to 2012, this study finds an interesting development of the standard view of comparative advantage in the emerging Halal export market. It finds that the greater the country’s current comparative advantage in an exported good, the higher the risk of export diversion (one- or two-way causality) between the Halal market and the conventional market with the country’s expansion of Halal exports; while the diversion risk disappears with lower current comparative advantage. Thus, the study suggests that if a country wants to take advantage of the fast-emerging market, it should aim to expand export of commodities with relatively low current comparative advantage but high demand in the emerging market

    Obesity, Metabolic Factors and Risk of Different Histological Types of Lung Cancer: A Mendelian Randomization Study

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    Background Assessing the relationship between lung cancer and metabolic conditions is challenging because of the confounding effect of tobacco. Mendelian randomization (MR), or the use of genetic instrumental variables to assess causality, may help to identify the metabolic drivers of lung cancer. Methods and findings We identified genetic instruments for potential metabolic risk factors and evaluated these in relation to risk using 29,266 lung cancer cases (including 11,273 adenocarcinomas, 7,426 squamous cell and 2,664 small cell cases) and 56,450 controls. The MR risk analysis suggested a causal effect of body mass index (BMI) on lung cancer risk for two of the three major histological subtypes, with evidence of a risk increase for squamous cell carcinoma (odds ratio (OR) [95% confidence interval (CI)] = 1.20 [1.01–1.43] and for small cell lung cancer (OR [95%CI] = 1.52 [1.15–2.00]) for each standard deviation (SD) increase in BMI [4.6 kg/m2]), but not for adenocarcinoma (OR [95%CI] = 0.93 [0.79–1.08]) (Pheterogeneity = 4.3x10-3). Additional analysis using a genetic instrument for BMI showed that each SD increase in BMI increased cigarette consumption by 1.27 cigarettes per day (P = 2.1x10-3), providing novel evidence that a genetic susceptibility to obesity influences smoking patterns. There was also evidence that low-density lipoprotein cholesterol was inversely associated with lung cancer overall risk (OR [95%CI] = 0.90 [0.84–0.97] per SD of 38 mg/dl), while fasting insulin was positively associated (OR [95%CI] = 1.63 [1.25–2.13] per SD of 44.4 pmol/l). Sensitivity analyses including a weighted-median approach and MR-Egger test did not detect other pleiotropic effects biasing the main results. Conclusions Our results are consistent with a causal role of fasting insulin and low-density lipoprotein cholesterol in lung cancer etiology, as well as for BMI in squamous cell and small cell carcinoma. The latter relation may be mediated by a previously unrecognized effect of obesity on smoking behavior
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