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Comparative study on directional and reverse directional expert systems
Published in Lin Liu, Automotive, Mechanical and Electrical Engineering, 2017
Zhiheng Lin, Haiping Huang, Pin Wang
The mathematic formula of relative strength index is: RSI=100×RS1+RSRS=Average Rise Point in i daysAverage Dropped Point in i days(i=1,2,⋯n)
The design and implementation of membership functions in acoustic emission forecasting rock-burst
Published in Amir Hussain, Mirjana Ivanovic, Electronics, Communications and Networks IV, 2015
Weidong Liu, Ciyang Zheng, Fenfen Sheng
AE technology is the main method of forecasting rock burst. To predict based on the fact that AE parameters change over time is possible. Considering the rock AE event rate, the rate of energy and the value m and so on, and adopting the adaptive fuzzy neural network, its membership function is established. Based on AE evaluation of rock mass stability relative strength index, the impact of rock burst can be predicted more accurately. The results are pretty consistent with the actual situation.
Random Forest and Grey Methodology in Dynamic Portfolio Selection
Published in Noura Metawa, M. Kabir Hassan, Saad Metawa, Artificial Intelligence and Big Data for Financial Risk Management, 2023
Tihana Škrinjarić, Silvija Vlah Jerić
In this chapter, RF is used for regression, i.e. for forecasting stock market index value based on its previous values (including also high and low values, as well as returns) and selected technical indices. The technical indices used are the same as were used in the research by Vlah Jerić (2021, 2020a,b). The description of calculations of those indicators is omitted here since they are done exactly as suggested by Bruni et al. (2016). The calculations include choosing certain parameters and those were set at values often used as defaults by traders and scientists in intraday trading. The indicators used are the following: Momentum over five periods (MOM),Exponential moving average (EMA) over 12 and 26 periods (EMA12 and EMA26, respectively),Moving average convergence/divergence with 12, 26, and 9 time periods (respectively) selected as three parameters needed for calculation (MACD),Return on investment (ROI) over 10, 20, and 30 periods (ROI10, ROI20, and ROI30, respectively),Relative strength index (RSI) over 10, 14, and 30 periods (RSI10, RSI14, and RSI30, respectively),Stochastic relative strength index (SRSI) over 10, 14, and 30 periods (SRSI10, SRSI14, and SRSI30, respectively),Average true range over 14 periods (ATR),Average directional index over the last 14 periods (ADX),Williams %R over 14 periods (WPR),Commodity channel index over 20 periods (CCI), andUltimate oscillator with 7, 14, and 28 time periods (respectively) selected as three parameters needed for calculation (UO).
Blended computation of machine learning with the recurrent neural network for intra-day stock market movement prediction using a multi-level classifier
Published in International Journal of Computers and Applications, 2021
Krishna Kumar, Md. Tanwir Uddin Haider
Intra-day Momentum Index(IMI) is a momentum indicator that shows the relationship between close price and open price. In our proposed work, the IMI is calculated using ICP of the previous interval and IOP of the current interval for one period to find the gain and losses. Relative Strength Index (RSI) is a momentum indicator that measures the speed and change in price movements. In our study, we have calculated RSI using two consecutive intervals close price for one period to find the gain and losses. Money Flow Index (MFI) is an oscillator that was developed by Gene Quong and Avrum Soudack to measure the selling and buying pressure using both the stock price and volume. where typical price is the mean of the IH, IL, and ICP; money flow is the multiplication of typical price and volume; and positive money flow and negative money flow are the sum of gains and losses for the n interval present in the window.
A fuzzy neural network combined with technical indicators and its application to Baltic Dry Index forecasting
Published in Journal of Marine Engineering & Technology, 2019
Chien-Chang Chou, Keng-Shou Lin
The RSI method is mostly typically used on 14-day timeframe, measured on a scale from 0 to 100. A value of 0 means the relative weakness. A value of 100 means the relative strength. The RSI is presented on a graph above or below the price chart. The index has a lower line typically at 30, a higher line at 70, and a middle line at 50.