Results 61 to 70 of about 7,740,955 (377)
DEEP LEARNING FOR STOCK MARKET TRADING: A SUPERIOR TRADING STRATEGY?
Neural Network World, 2019 Deep-learning initiatives have vastly changed the analysis of data. Complex networks became accessible to anyone in any research area. In this paper we are proposing a deep-learning long short-term memory network (LSTM) for automated stock trading.
D. Fister +3 more
semanticscholar +1 more source
Evaluating the origin and spread of spotted lanternfly (Lycorma delicatula) in Japan
Population Ecology, EarlyView.The invasive spotted lanternfly (Lycorma delicatula) is native to China and is a serious economic pest in the Republic of Korea and the United States, though it is not considered a pest in Japan. We established a distribution map of L. delicatula in Japan through a comprehensive review of published literature and citizen science reports and analyzed ...
Matthew T. Kamiyama +5 more
wiley +1 more source
Evaluation of pairs trading strategy at the Brazilian financial market [PDF]
, 2007 Pairs trading is a popular trading strategy that tries to take advantage of market inefficiencies in order to obtain profit. The idea is simple: find two stocks that move together and take long/short positions when they diverge abnormally, hoping that ...
Perlin, M.
core
Population Ecology, EarlyView.In this study, we compared three methods for kinship identification using different algorithms in samples of wild Pacific bluefin tuna and generated genotyping data. The three methods resulted in different numbers of inferred kinship pairs for both generated and actual data. Particularly for the half‐sibling pairs, considerable number of false‐positive
Yohei Tsukahara +5 more
wiley +1 more source
LETS get real: constraints on the development of Local Exchange Trading Schemes [PDF]
, 2004 Local Exchange Trading Schemes (LETS) are widely promoted as a new tool for local economic development, but until recently the focus has been on their alleged ‘potential’ rather than the realities of their operation.
Aldridge, T. J., Patterson, A.
core +1 more source
TSFDC: A trading strategy based on forecasting directional change
Intell. Syst. Account. Finance Manag., 2018 Directional Change (DC) is a technique to summarize price movements in a financial market. According to the DC concept, data is sampled only when the magnitude of price change is significant according to the investor.
Amer Bakhach, E. Tsang, V. Chinthalapati
semanticscholar +1 more source
Molecular Oncology, EarlyView.The complex mode of action of the topoisomerase II inhibitor etoposide in triggering apoptosis involves several mechanisms: overexpression of the mitochondrial protein VDAC1, leading to its oligomerization and formation of a large channel that mediates the release of pro‐apoptotic protein; and overexpression of the apoptosis regulators p53, Bax, and ...
Aditya Karunanithi Nivedita +1 more
wiley +1 more source
Evolutionary computation enabled game theory based modelling of electricity market behaviours and applications [PDF]
, 2007 The collapse of the Californian electricity market system in 2001 has highlighted urgency in research in intelligent electricity trading systems and strategies involving both suppliers and customs.
Chen, W., Li, Y., Yin, J.
core +1 more source
Peripheral blood proteome biomarkers distinguish immunosuppressive features of cancer progression
Molecular Oncology, EarlyView.Immune status significantly influences cancer progression. This study used plasma proteomics to analyze benign 67NR and malignant 4T1 breast tumor models at early and late tumor stages. Immune‐related proteins–osteopontin (Spp1), lactotransferrin (Ltf), calreticulin (Calr) and peroxiredoxin 2 (Prdx2)–were associated with systemic myeloid‐derived ...
Yeon Ji Park +6 more
wiley +1 more source
Financial Trading with Feature Preprocessing and Recurrent Reinforcement Learning [PDF]
arXiv, 2021 Financial trading aims to build profitable strategies to make wise investment decisions in the financial market. It has attracted interests in the machine learning community for a long time. This paper proposes to trade financial assets automatically using feature preprocessing skills and Recurrent Reinforcement Learning (RRL) algorithm.
arxiv