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Keywords = quant trading

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20 pages, 950 KB  
Article
Genome-Informed Real-Time PCR Assay for Detection of ‘Candidatus Phytoplasma Prunorum,’ Which Is Associated with European Stone Fruit Yellows
by Jarred Yasuhara-Bell and Yazmín Rivera
Microorganisms 2025, 13(4), 929; https://doi.org/10.3390/microorganisms13040929 - 17 Apr 2025
Viewed by 1285
Abstract
Candidatus Phytoplasma prunorum’ has been associated with severe disease in Prunus spp., which are commodities of economic importance in the USA. The introduction and establishment of ‘Ca. P. prunorum’ in the USA could result in huge economic losses, thus creating a [...] Read more.
Candidatus Phytoplasma prunorum’ has been associated with severe disease in Prunus spp., which are commodities of economic importance in the USA. The introduction and establishment of ‘Ca. P. prunorum’ in the USA could result in huge economic losses, thus creating a need for validated diagnostic tools, which are the cornerstone of successful surveillance, quarantine, and eradication measures. Whole-genome comparisons led to the identification of a diagnostic marker gene specific to ‘Ca. P. prunorum’ (PE639). The PE639 assay was duplexed with an 18S rDNA plant internal control and compared to modified 23S (phytoplasmas) and imp (‘Ca. P. mali’) assays. The PE639 assay produced congruent results to 23S and imp assays for all metrics, demonstrating high linearity, repeatability, intermediate precision, and reproducibility. The limit of detection was comparable for all assays tested, and all demonstrated 100% analytical specificity, selectivity, and diagnostic specificity for their respective target species. Assays metrics were consistent across two platforms, the ABI QuantStudio™ 5 and Bio-Rad CFX96™ OPUS. A synthetic gBlocks™ control was designed and validated to work with all assays, as well as conventional PCR assays targeting 16S rDNA and tuf genes. These validated assays and synthetic control represent beneficial tools that support efforts to protect USA agriculture and facilitate safe trade. Full article
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16 pages, 294 KB  
Article
Challenges in Gluten Analysis: A Comparison of Four Commercial Sandwich ELISA Kits
by Plaimein Amnuaycheewa, Lynn Niemann, Richard E. Goodman, Joseph L. Baumert and Steve L. Taylor
Foods 2022, 11(5), 706; https://doi.org/10.3390/foods11050706 - 27 Feb 2022
Cited by 22 | Viewed by 5086
Abstract
Gluten is composed of prolamin and glutelin proteins from several related grains. Because these proteins are not present in identical ratios in the various grains and because they have some differences in sequence, the ability to accurately quantify the overall amount of gluten [...] Read more.
Gluten is composed of prolamin and glutelin proteins from several related grains. Because these proteins are not present in identical ratios in the various grains and because they have some differences in sequence, the ability to accurately quantify the overall amount of gluten in various food matrices to support gluten-free labeling is difficult. Four sandwich ELISAs (the R-Biopharm AG R5 RIDASCREEN®, the Neogen Veratox® R5, the Romer Labs AgraQuant® G12, and the Morinaga Wheat kits) were evaluated for their performance to quantify gluten concentrations in various foods and ingredients. The Morinaga and AgraQuant® G12 tests yielded results comparable to the two R5 kits for most, but not for certain, foods. The results obtained with the Morinaga kit were lower when compared to the other kits for analyzing powders of buckwheat and several grass-based products. All four kits were capable of detecting multiple gluten-containing grain sources including wheat, rye, barley, semolina, triticale, spelt, emmer, einkorn, Kamut™, and club wheat. Users of the ELISA kits should verify the performance in their hands, with matrices that are typical for their specific uses. The variation in results for some food matrices between test methods could result in trade disputes or regulatory disagreements. Full article
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27 pages, 382 KB  
Article
Custom v. Standardized Risk Models
by Zura Kakushadze and Jim Kyung-Soo Liew
Risks 2015, 3(2), 112-138; https://doi.org/10.3390/risks3020112 - 20 May 2015
Cited by 9 | Viewed by 6640
Abstract
We discuss when and why custom multi-factor risk models are warranted and give source code for computing some risk factors. Pension/mutual funds do not require customization but standardization. However, using standardized risk models in quant trading with much shorter holding horizons is suboptimal: [...] Read more.
We discuss when and why custom multi-factor risk models are warranted and give source code for computing some risk factors. Pension/mutual funds do not require customization but standardization. However, using standardized risk models in quant trading with much shorter holding horizons is suboptimal: (1) longer horizon risk factors (value, growth, etc.) increase noise trades and trading costs; (2) arbitrary risk factors can neutralize alpha; (3) “standardized” industries are artificial and insufficiently granular; (4) normalization of style risk factors is lost for the trading universe; (5) diversifying risk models lowers P&L correlations, reduces turnover and market impact, and increases capacity. We discuss various aspects of custom risk model building. Full article
(This article belongs to the Special Issue Financial Engineering to Address Complexity)
14 pages, 656 KB  
Article
U.S. Equity Mean-Reversion Examined
by Jim Liew and Ryan Roberts
Risks 2013, 1(3), 162-175; https://doi.org/10.3390/risks1030162 - 4 Dec 2013
Cited by 4 | Viewed by 10209
Abstract
In this paper we introduce an intra-sector dynamic trading strategy that captures mean-reversion opportunities across liquid U.S. stocks. Our strategy combines the Avellaneda and Lee methodology (AL; Quant. Financ. 2010, 10, 761–782) within the Black and Litterman framework (BL; J. Fixed [...] Read more.
In this paper we introduce an intra-sector dynamic trading strategy that captures mean-reversion opportunities across liquid U.S. stocks. Our strategy combines the Avellaneda and Lee methodology (AL; Quant. Financ. 2010, 10, 761–782) within the Black and Litterman framework (BL; J. Fixed Income, 1991, 1, 7–18; Financ. Anal. J. 1992, 48, 28–43). In particular, we incorporate the s-scores and the conditional mean returns from the Orstein and Ulhembeck (Phys. Rev. 1930, 36, 823–841) process into BL. We find that our combined strategy ALBL has generated a 45% increase in Sharpe Ratio when compared to the uncombined AL strategy over the period from January 2, 2001 to May 27, 2010. These new indices, built to capture dynamic trading strategies, will definitely be an interesting addition to the growing hedge fund index offerings. This paper introduces our first “focused-core” strategy, namely, U.S. Equity Mean-Reversion. Full article
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