RESUMO

ABSTRACT Assets and Liabilities Management (ALM) has been a topic of interest for decision makers in the private and public sectors. This study shows a systematic review of 416 published research paper; in the Scopus citation index, associated with ALM in a period of time from 1983 to 2021. The main objective is to identify the lines of publication over time, emphasize the journals most associated with the subject, as well as the relevant authors. The tool that was used was Bibliometrix of R, which allowed to identify the bibliometric indicators in the publications. In addition, the work proposes a modeling of themes based on text mining methodologies. The results allow us to conclude that quantitative research has been widely exploited through the 6 themes: Financial risk management, Stochastic modeling, Pension funds, Capital markets and the insurance industry, Mean-variance models, General optimization models. This research allows us to identify gaps in the literature to frame future research. JEL CLASSIFICATION G10. G21. G22. G30

RESUMEN La gestión de activos y pasivos (ALM - Assets and Liabilities Management por sus siglas en inglés) ha sido un tema de interés para tomadores de decisión en el sector privado y público. Este estudio muestra una revisión sistemática de 416 investigaciones publicadas, en el indice de citas Scopus, asociadas con el ALM en un periodo de tiempo de 1983 a 2021. El objetivo principal es identificar las líneas de publicación a través del tiempo, enfatizar en las revistas más asociadas con el tema, así como los autores relevantes. La herramienta que se utilizò fue Bibliometrix de R, la cuál permitió identificar los indicadores bibliométricos en las publicaciones. Además, en el trabajo se propone una modelación de temas a partir de metodologías de minería de texto. Los resultados permiten concluir que la investigación cuantitativa ha sido ampliamente explotada a través de las 6 temáticas: Financial risk management, Stochastic modeling, Pension funds, Capital markets and the insurance industry, Mean-variance models, General optimization models. Esta investigación permite identificar brechas en la literatura para enmarcar futuras investigaciones. CLASIFICACIÓN JEL G10. G21. G22. G30

RESUMO A Gestão de Ativos e Passivos (ALM) tem sido um tema de interesse para os tomadores de decisão nos setores privado e público. Este estudo mostra uma revisão sistemática de 416 artigos de pesquisa publicados, no índice de citação Scopus, associados à ALM, durante um período de 1983 a 2021. O principal objetivo é identificar as linhas de publicação ao longo do tempo, enfatizando as revistas mais associadas ao tema, assim como os autores relevantes. A ferramenta utilizada foi a Bibliometrix da R, que nos permitiu identificar os indicadores bibliométricos nas publicações. Além disso, o documento propõe uma modelagem de tópicos baseada em metodologias de mineração de texto. Os resultados nos permitem concluir que a pesquisa quantitativa foi amplamente explorada através dos 6 temas: Gerenciamento de risco financeiro, Modelagem estocástica, Fundos de pensão, Mercado de capitais e indústria de seguros, Modelos de média-variância, Modelos de otimização geral. Esta pesquisa nos permite identificar lacunas na literatura para enquadrar futuras pesquisas. CLASSIFICAÇÃO JEL G10. G21. G22. G30

RESUMO

Breeding cassava relies on a phenotypic recurrent selection that takes advantage of the vegetative propagation of this crop. Successive stages of selection (single row trial-SRT; preliminary yield trial-PYT; advanced yield trial-AYT; and uniform yield trials UYT), gradually reduce the number of genotypes as the plot size, number of replications and locations increase. An important feature of this scheme is that, because of the clonal, reproduction of cassava, the same identical genotypes are evaluated throughout these four successive stages of selection. For this study data, from 14 years (more than 30,000 data points) of evaluation in a sub-humid tropical environment was consolidated for a meta-analysis. Correlation coefficients for fresh root yield (FRY), dry matter content (DMC), harvest index (HIN), and plant type score (PTS) along the different stages of selection were estimated. DMC and PTS measured in different trials showed the highest correlation coefficients, indicating a relatively good repeatability. HIN had an intermediate repeatability, whereas FRY had the lowest value. The association between HIN and FRY was lower than expected, suggesting that HIN in early stages was not reliable as indirect selection for FRY in later stages. There was a consistent decrease in the average performance of clones grown in PYTs compared with the earlier evaluation of the same genotypes at SRTs. A feasible explanation for this trend is the impact of the environment on the physiological and nutritional status of the planting material and/or epigenetic effects. The usefulness of HIN is questioned. Measuring this variable takes considerable efforts at harvest time. DMC and FRY showed a weak positive association in SRT (r = 0.21) but a clearly negative one at UYT (r = -0.42). The change in the relationship between these variables is the result of selection. In later stages of selection, the plant is forced to maximize productivity on a dry weight basis either by maximizing FRY or DMC, but not both. Alternatively, the plant may achieve high dry root yield by simultaneously attaining "acceptable" (but not maximum) levels of FRY and DMC.

RESUMO

Breeding cassava relies on several selection stages (single row trial-SRT; preliminary; advanced; and uniform yield trials-UYT). This study uses data from 14 years of evaluations. From more than 20,000 genotypes initially evaluated only 114 reached the last stage. The objective was to assess how the data at SRT could be used to predict the probabilities of genotypes reaching the UYT. Phenotypic data from each genotype at SRT was integrated into the selection index (SIN) used by the cassava breeding program. Average SIN from all the progenies derived from each progenitor was then obtained. Average SIN is an approximation of the breeding value of each progenitor. Data clearly suggested that some genotypes were better progenitors than others (e.g., high number of their progenies reaching the UYT), suggesting important variation in breeding values of progenitors. However, regression of average SIN of each parental genotype on the number of their respective progenies reaching UYT resulted in a negligible coefficient of determination (r (2) = 0.05). Breeding value (e.g., average SIN) at SRT was not efficient predicting which genotypes were more likely to reach the UYT stage. Number of families and progenies derived from a given progenitor were more efficient predicting the probabilities of the progeny from a given parent reaching the UYT stage. Large within-family genetic variation tends to mask the true breeding value of each progenitor. The use of partially inbred progenitors (e.g., S1 or S2 genotypes) would reduce the within-family genetic variation thus making the assessment of breeding value more accurate. Moreover, partial inbreeding of progenitors can improve the breeding value of the original (S0) parental material and sharply accelerate genetic gains. For instance, homozygous S1 genotypes for the dominant resistance to cassava mosaic disease (CMD) could be generated and selected. All gametes from these selected S1 genotypes would carry the desirable allele and 100% of their progenies would be resistant. Only half the gametes produced by the heterozygous S0 progenitor would carry the allele of interest. For other characteristics, progenies from the S1 genotypes should be, at worst, similar to those generated by the S0 progenitors.