Cross-Sectional Variation of Intraday Liquidity, Cross-Impact, and Their Effect on Portfolio Execution

Over the past decade, there has been a significant rise in assets managed under passive and systematic strategies. Such strategies hold and trade portfolios in a coordinated manner, often concentrating trading around the end of the trading session. Simultaneously, there has been a rise in activity from market participants that act as liquidity providers, themselves trading along portfolio directions. In “Cross-Sectional Variation of Intraday Liquidity, cross-impact, and Their Effect on Portfolio Execution,” Min, Maglaras, and Moallemi investigate the implications of these two observations, specifically exploring how the phenomenon of portfolio liquidity provision leads to cross-security impact and influences the optimal execution schedules of risk-neutral traders that seek to minimize their expected execution costs. They show that the optimized schedules deviate from the naïve approach that trades each security separately and instead, couple the trading intensity across stocks so as to benefit from the liquidity provided along attractive portfolio trading directions. Empirical analysis demonstrates that coupled optimized schedules could lower costs by as much as 15% relative to the naïve approach.

Sistem Forecasting Keuangan Inventaris Sarana dan Prasarana dengan Metode Naive Approach pada Universitas CIC

University Catur Insan Cendekia (UCIC) is a university located at Kesambi street number 202 Cirebon city. As one of the new universities in Cirebon city of course, would need inventory records of facilities and infrastructure that’s what at the university. Additionally, records spending on facilities and infrastucture costs is important. To optimize that cost recording requires a system. To Improve management facilities and infrastructure requires data related to facilities conditions and infrastructure. Naïve’s own method was the result of his prediction of the previous year’s real data as a benchmark for forecasting the following year. The process of this method is to collect the data of the cost of facilities and infrastructure spending first, after which the system will predict the cost of facilities and infrastructure using the formula N= t-1, in addition to this web based research using the framework codeigniter. The forecast method conducted in the study using the naïve approach method, which is more effective than the moving average method. Naïve’s method was used to predict the cost data of facilities and infrastructure available at UCIC. The study also had the naïve approach prediction reached the following year’s prediction.

Tracking bacteria at high density with FAST, the Feature-Assisted Segmenter/Tracker

Most bacteria live attached to surfaces in densely-packed communities. While new experimental and imaging techniques are beginning to provide a window on the complex processes that play out in these communities, resolving the behaviour of individual cells through time and space remains a major challenge. Although a number of different software solutions have been developed to track microorganisms, these approaches typically rely on a large number of user-defined parameters that must be carefully tuned to effectively track cells. Testing a given parameter combination can take hours to days depending on the size of the dataset, making iterative optimisation impractical. To overcome these limitations, we have developed FAST, the Feature-Assisted Segmenter/Tracker, which uses unsupervised machine learning to optimise tracking while maintaining ease of use. Our approach, rooted in information theory, largely eliminates the need for users to iteratively adjust parameters manually and make qualitative assessments of the resulting cell trajectories. Instead, FAST measures multiple distinguishing "features" for each cell and then autonomously quantifies the amount of unique information each feature provides. We then use these measurements to determine how data from each feature should be combined to minimize tracking errors. Comparing our algorithm with a naïve approach that uses cell position alone revealed that FAST produced 4 to 10 times fewer tracking errors. The modular design of FAST combines our novel tracking method with tools for segmentation, extensive data visualisation, lineage assignment, and manual track correction. It is also highly extensible, allowing users to extract custom information from images and seamlessly integrate it into downstream analyses. FAST therefore enables high-throughput, data-rich analyses with minimal user input. It has been released for use in either Matlab or as a compiled stand-alone application, and is available at https://bit.ly/3vovDHn, along with extensive tutorials and detailed documentation.

Algorithmic Structures for Realizing Short-Length Circular Convolutions with Reduced Complexity

A set of efficient algorithmic solutions suitable to the fully parallel hardware implementation of the short-length circular convolution cores is proposed. The advantage of the presented algorithms is that they require significantly fewer multiplications as compared to the naive method of implementing this operation. During the synthesis of the presented algorithms, the matrix notation of the cyclic convolution operation was used, which made it possible to represent this operation using the matrix–vector product. The fact that the matrix multiplicand is a circulant matrix allows its successful factorization, which leads to a decrease in the number of multiplications when calculating such a product. The proposed algorithms are oriented towards a completely parallel hardware implementation, but in comparison with a naive approach to a completely parallel hardware implementation, they require a significantly smaller number of hardwired multipliers. Since the wired multiplier occupies a much larger area on the VLSI and consumes more power than the wired adder, the proposed solutions are resource efficient and energy efficient in terms of their hardware implementation. We considered circular convolutions for sequences of lengths N= 2, 3, 4, 5, 6, 7, 8, and 9.

Reevaluating Scorpion Ecomorphs using a Naïve Approach

BackgroundEcomorphs create the opportunity to investigate ecological adaptation because they encompass organisms that evolved characteristic morphologies under similar ecological demands. For over 50 years, scorpions have been empirically assigned to ecomorphs based on the characteristic morphologies that rock, sand, vegetation, underground, and surface dwellers assume. This study aims to independently test the existence of scorpion ecomorphs by quantifying the association between their morphology and ecology across 61 species, representing 14 families of the Scorpiones order.ResultsWithout a priori categorization of species into ecomorphs, we identified four groups based on microhabitat descriptors, which reflect how scorpion ecospace is clustered. Moreover, these microhabitat groups, i.e. ecotypes, have significantly divergent morphologies; therefore, they represent ecomorphs. These ecomorphs largely correspond with the ones previously described in the literature. Therefore, we retained the names Lithophilous, Psammophilous, and Pelophilous, and proposed the name Phytophilous for vegetation dwellers. Finally, we sought to map the morphology-ecology association in scorpions. We provide evidence that the morphological regions most tightly associated with ecology are the walking legs and pedipalps. Moreover, the major trend in ecomorphological covariation is that longer walking legs and relatively slender pedipalps (pincers) are associated with sandy microhabitats, while the inverse morphological proportions are associated with rocky microhabitats. ConclusionsScorpion ecomorphs are validated in a naïve approach, from ecological descriptors and whole body anatomy. This places them on a more solid quantitative footing for future studies of ecological adaptation in scorpions. Our results verify some of the previously defined ecomorphotypes and can be used as a starting point to understand the adaptive significance of ecological morphology.

Computing crisp simulations for fuzzy labeled transition systems

The problem of checking whether a state in a finite fuzzy labeled transition system (FLTS) crisply simulates another is one of the fundamental problems of the theory of FLTSs. This problem is of the same nature as computing the largest crisp simulation between two finite FLTSs. A naive approach to the latter problem is to crisp the given FLTSs and then apply one of the currently known best methods to the obtained crisp labeled transition systems. The complexity of the resulting algorithms is of order O (l (m + n) n), where l is the number of fuzzy values occurring in the specification of the input FLTSs, m is the number of transitions and n is the number of states of the input FLTSs. In the worst case, l can be m + n and O (l (m + n) n) is the same as O ((m + n) 2 n). In this article, we design an efficient algorithm with the complexity O ((m + n) n) for computing the largest crisp simulation between two finite FLTSs. This gives a significant improvement. We also adapt our algorithm to computing the largest crisp simulation between two finite fuzzy automata.

Revisiting Text Guide, a Truncation Method for Long Text Classification

The quality of text classification has greatly improved with the introduction of deep learning, and more recently, models using attention mechanism. However, to address the problem of classifying text instances that are longer than the length limit adopted by most of the best performing transformer models, the most common method is to naively truncate the text so that it meets the model limit. Researchers have proposed other approaches, but they do not appear to be popular, because of their high computational cost and implementation complexity. Recently, another method called Text Guide has been proposed, which allows for text truncation that outperforms the naive approach and simultaneously is less complex and costly than earlier proposed solutions. Our study revisits Text Guide by testing the influence of certain modifications on the method’s performance. We found that some aspects of the method can be altered to further improve performance and confirmed several assumptions regarding the dependence of the method’s quality on certain factors.

Multi-armed bandits for bid shading in first-price real-time bidding auctions

Online advertisements are bought through a mechanism called real-time bidding (RTB). In RTB, the ads are auctioned in real-time on every webpage load. The ad auctions can be of two types: second-price or first-price auctions. In second-price auctions, the bidder with the highest bid wins the auction, but they only pay the second-highest bid. This paper focuses on first-price auctions, where the buyer pays the amount that they bid. This research evaluates how multi-armed bandit strategies optimize the bid size in a commercial demand-side platform (DSP) that buys inventory through ad exchanges. First, we analyze seven multi-armed bandit algorithms on two different offline real datasets gathered from real second-price auctions. Then, we test and compare the performance of three algorithms in a production environment. Our results show that real data from second-price auctions can be used successfully to model first-price auctions. Moreover, we found that the trained multi-armed bandit algorithms reduce the bidding costs considerably compared to the baseline (naïve approach) on average 29%and optimize the whole budget by slightly reducing the win rate (on average 7.7%). Our findings, tested in a real scenario, show a clear and substantial economic benefit for ad buyers using DSPs.