DSAE – Deep Stack Auto Encoder and RCBO – Rider Chaotic Biogeography Optimization Algorithm for Big Data Classification

In today’s era Big data classification is a very crucial and equally widely arise issue is many applications. Not only engineering applications but also in social, agricultural, banking, educational and many more applications are there in science and engineering where accurate big data classification is required. We proposed a very novel and efficient methodology for big data classification using Deep stack encoder and Rider chaotic biogeography algorithms. Our proposed algorithms are the combinations of two algorithms. First one is Rider Optimization algorithm and second one is chaotic biogeography-based optimization algorithm. So, we named it as RCBO which is integration is ROA and CBBO. Our proposed system also uses the Deep stack auto encoder for the purpose of training the system which actually produced the accurate classification. The Apache spark platform is used initial distribution of the data from master node to slave nodes. Our proposed system is tested and executed on the UCI Machine learning data set which gives the excellent results while comparing with other algorithms such as KNN classification, Extreme Learning Machine Random Forest algorithms.

The Influence of Financial Well-Being, Financial Literacy, Financial Capability, and Money Attitude on Local Farmers’ Attitude in Using Agricultural Banking Service in Blitar Regency, Indonesia

The purpose of this research is to generate the correlation between several variables of financial perceptions which consist of financial well-being, financial literacy, financial capability, and money attitude towards local farmers’ attitude in using agricultural banking services in Blitar Regency. This research uses the theory which stated that financial perception has direct influences on the individual financial attitude. A total of 502 sample which includes local farmers in Blitar Regency were selected through a systematic random sampling technique. The instruments of this study using previous questionnaire that have been adjusted in terms of language and evaluated by using reliability testing. The output from data collection were analysed using multiple linear regression technique. The findings indicate that there is a high and positive linear relation ship between financial well-being, financial literacy, money attitude, and local farmers’ attitude in using agricultural banking services in Blitar Regency. On the other hand, financial capability variable indicates unsignificant relationship with local farmers’ attitude in using agricultural banking services. The findings also proved that the combination of predictor variables of financial perception contributed significantly to the local farmers attitude in using agricultural banking services in Blitar Regency. This study suggested that the manager of Blitar Raya Agricultural Bank should focus more in developing the local farmers’ knowledge in terms of the importance of financial well-being, the level of financial literacy, and money attitude by changing the curriculum of bi-weekly workshop which supported by several material related with financial knowledge.

Competition, performance and financial stability in US agricultural banking

PurposeThe number of US commercial banks has declined by about 50% over the last two decades. This change could lead to a potential decline in competition and a potential increase in market power in the agricultural banking market. The focus of this study is to examine whether the risk of failure and the performance of agricultural banks has been affected by bank consolidations.Design/methodology/approachThe impact of bank competition on performance and financial stability of agricultural banks is studied using a Lerner index as a measure of market power. A Z-score is constructed to measure bank stability. Similarly, the return on assets (net income to total assets ratio), return on equity (net income to the total equity ratio), agricultural loan ratio and agricultural loan volume are used as performance measures for agricultural banks. Two-way fixed effect regression models are estimated to measure the impact of competition on financial stability and performance.FindingsResults indicate that bank competition has a U-shaped effect on the probability of default and an inverted U-shaped effect on volume and proportion of agricultural lending. There also exists evidence of a positive but non-linear effect of bank market power on the profitability of agricultural banks.Originality/valueThere is limited literature on the impact of bank competition on financial stability and performance of US agricultural banks. Agricultural banks hold more than 40% of US farm debt. A decrease in the number of banks or the level of competition in agricultural banking may cause an adverse effect on relationship lending. The key findings imply that bank regulatory strategies should focus on enhancing (reducing) competition in more (less) concentrated banking markets to improve the financial health and performance of agricultural banks.

Dividends Announcement and Semi Strong Form of Efficiency at The Nairobi Securities Exchange in Kenya

The objective of this study was to establish the effects of dividend announcement to current market prices at the Nairobi Securities Exchange, with four specific objectives; to determine the information content of dividend announcements, to determine the extent to which prices converge to new values after dividend announcements on a sector by sector basis, to establish the market reaction to announced information and also to establish whether investors can secure excess returns by acting on announced information. A 66 days event timeline was employed from 2005 to 2015 on daily closing stock prices. A sample of 179 dividend announcements from 22 listed companies in 8 sectors were drawn and analysed using an OLS Market Model. Findings of the research conclude that; dividend announcements do have an impact on stock prices for the Agricultural, Banking, Commercial, Construction, Manufacturing and Telecomm Sectors and not for the Energy Sector, Insurance Sector and the Nairobi Securities Exchange Market. It takes more than five days for prices to adjust to their correct values and this makes it possible for market players to profit from the inefficiency by earning abnormal returns. We conclude that the Nairobi Securities Exchange is not semi-strong form efficient.