Search Results - subject:"MACD"

Investor sentiment and optimizing traditional quantitative investments

Chen, Zheng; Li, Wenlin; Huang, Jia - In: International review of economics & finance : IREF 101 (2025), pp. 1-27

Persistent link: https://www.econbiz.de/10015461790

Technical indicator empowered intelligent strategies to predict stock trading signals

Saud, Arjun Singh; Shakya, Subarna - In: Journal of open innovation : technology, market, and … 10 (2024) 4, pp. 1-16

Technical analysis is widely employed in stock trading, relying on popular indicators such as MACD, DMI, KST etc. to … strategies using MACD, DMI, and KST indicators, and implemented these strategies with LSTM and GRU networks due to their ability … strategies based on MACD and DMI, while a 10-day period is best for the KST-based strategy. (2) Intelligent trading strategies …

Persistent link: https://www.econbiz.de/10015184932

Synergizing quantitative finance models and market microstructure analysis for enhanced algorithmic trading strategies

Mengshetti, Om; Gupta, Kanishk; Zade, Nilima; Kotecha, Ketan - In: Journal of open innovation : technology, market, and … 10 (2024) 3, pp. 1-11

Price (VWAP), and Moving Average Convergence/Divergence (MACD) Relative Strength Index (RSI), Exponential Moving Average … (EMA), Volume-Weighted Average Price (VWAP), and Moving Average Convergence/Divergence (MACD) to create and develop a …

Persistent link: https://www.econbiz.de/10015071775

Improving MACD technical analysis by optimizing parameters and modifying trading rules : evidence from the Japanese Nikkei 225 futures market

Kang, Byung-Kook - In: Journal of risk and financial management : JRFM 14 (2021) 1/37, pp. 1-21

Much research has examined performance or market efficiency by using the moving average convergence divergence (MACD … performance over the period of 2011-2019. Yet, it also finds that the MACD tool can earn significant positive returns when it uses … do not reflect all public information. Hence, the three parameters values of the MACD tool should be optimized for each …

Persistent link: https://www.econbiz.de/10012417747

Artificial intelligence applied to investment in variable income through the MACD (moving average convergence/divergence) indicator

Agudelo Aguirre, Alberto Antonio; Duque Méndez, … - In: Journal of Economics, Finance and Administrative Science 26 (2021) 52, pp. 268-281

traditional technical analysis (TA) using moving average convergence/divergence (MACD), is possible to achieve higher yields than … MACD. GA approach took place by chromosome encoding, fitness evaluation and genetic operators. Traditional genetic … chromosome encoding stage used MACD to represent the genes of each chromosome to encode the parameters of MACD in a chromosome …

Persistent link: https://www.econbiz.de/10013192206

Artificial intelligence applied to investment in variable income through the MACD (moving average convergence/divergence) indicator

Agudelo Aguirre, Alberto Antonio; Duque Méndez, … - In: Journal of economics, finance & administrative science 26 (2021) 52, pp. 268-281

Persistent link: https://www.econbiz.de/10012813879

Improving MACD technical analysis by optimizing parameters and modifying trading rules: Evidence from the Japanese Nikkei 225 futures market

Kang, Byung-Kook - In: Journal of Risk and Financial Management 14 (2021) 1, pp. 1-21

Persistent link: https://www.econbiz.de/10012611595

Efficiency of technical analysis for the stock trading

Pramudya, Rommy; Ichsani, Sakina - In: International journal of finance & banking studies : JJFBS 9 (2020) 1, pp. 58-67

Persistent link: https://www.econbiz.de/10012266563

Testing of EMA and MACD on equity indices in India with special reference to Oil & Gas, Power and IT index

Jyoti; Singla, Rajat; Mittal, Suresh K. - In: Finance India : the quarterly journal of Indian … 35 (2021) 4, pp. 1149-1172

Persistent link: https://www.econbiz.de/10013257989

Optimization of backtesting techniques in automated high frequency trading systems using the d-Backtest PS method

Vezeris, D. Th.; Schinas, C. J.; Kyrgos, Th. S.; … - In: Computational economics 56 (2020) 4, pp. 975-1054

Persistent link: https://www.econbiz.de/10012390502