scholarly journals AN EMPIRICAL ANALYSIS OF TRADING STRATEGY BASED ON SIMPLE MOVING AVERAGE CROSSOVERS

2017 ◽  
Vol 03 (01) ◽  
pp. 423-426
Author(s):  
Arumugam P ◽  
◽  
Saranya R
Keyword(s):  
Empirical Analysis ◽  
Moving Average ◽  
Trading Strategy

scholarly journals A Fuzzy Set-Valued Autoregressive Moving Average Model and Its Applications

Symmetry ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 324 ◽  
Author(s):  
Dabuxilatu Wang ◽  
Liang Zhang
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Empirical Analysis ◽  
Moving Average ◽  
Arma Model ◽  
Autoregressive Moving Average ◽  
Complex Data ◽  
Arma Models ◽  
Linguistic Data ◽  
Series Analysis

Autoregressive moving average (ARMA) models are important in many fields and applications, although they are most widely applied in time series analysis. Expanding the ARMA models to the case of various complex data is arguably one of the more challenging problems in time series analysis and mathematical statistics. In this study, we extended the ARMA model to the case of linguistic data that can be modeled by some symmetric fuzzy sets, and where the relations between the linguistic data of the time series can be considered as the ordinary stochastic correlation rather than fuzzy logical relations. Therefore, the concepts of set-valued or interval-valued random variables can be employed, and the notions of Aumann expectation, Fréchet variance, and covariance, as well as standardized process, were used to construct the ARMA model. We firstly determined that the estimators from the least square estimation of the ARMA (1,1) model under some L2 distance between two sets are weakly consistent. Moreover, the justified linguistic data-valued ARMA model was applied to forecast the linguistic monthly Hang Seng Index (HSI) as an empirical analysis. The obtained results from the empirical analysis indicate that the accuracy of the prediction produced from the proposed model is better than that produced from the classical one-order, two-order, three-order autoregressive (AR(1), AR(2), AR(3)) models, as well as the (1,1)-order autoregressive moving average (ARMA(1,1)) model.

scholarly journals Various moving average convergence divergence trading strategies: a comparison

2016 ◽  
Vol 13 (2) ◽  
pp. 363-369 ◽  
Author(s):  
Nguyen Hoang Hung
Keyword(s):  
Moving Average ◽  
Predictive Ability ◽  
Trading Strategy ◽  
Trading Strategies ◽  
Trading Cost ◽  
Trading Rules

Some studies published recently (Dejan Eric, 2009; R. Rosillo, 2013; Terence Tai-Leung Chong, 2008; Ülkü and Prodan, 2013) uncover that moving average convergence divergence (MACD) trading rules have predictive ability in many countries. The MACD trading strategies applied by these papers to execute the trading signals are various. This study analyzes the performance of a MACD trading strategy (MACD-4 in the current study), which is applied popularly by practitioners, but was not tested by prior academicians. Furthermore, the author compares the performance of each of the strategies on a group of markets to identify the best one. Before considering the costs, the author finds that the MACD-4 trading strategy has predictive ability. The best performance is MACD strategy applied by Terence Tai-Leung Chong (2008). This strategy is also the most effective one if it is applied in a high trading cost environmentm because the numbers of trades created are the lowest. Especially, the strategy applied by R. Rosillo (2013) is unpredictable in the selected samples

scholarly journals Implementation of Fibonacci Retracements and Exponential Moving Average (EMA) Trading Strategy in Indonesia Stock Exchange

2021 ◽  
Vol 6 (4) ◽  
pp. 402-408
Author(s):  
Lusindah Lusindah ◽  
Erman Sumirat
Keyword(s):  
Stock Market ◽  
Stock Price ◽  
Stock Exchange ◽  
Moving Average ◽  
Time Frame ◽  
Trading Strategy ◽  
Individual Investors ◽  
Individual Investor ◽  
Back Testing ◽  
The Individual

Based on KSEI statistic data on March 2021, IDX individual stock market investor is increasing 199% compared to 2018 becoming 4,848,954 number of investors. 56.9% population of the individual investor is having ages that less than 30 years. In the period where IDX was bullish in November 2020 - January 2021, there is a phenomenon where stocks influencers appeared in social media and impacted to the stock price movement after the announcement is done by the influencer. In contrary, during bearish and sideways condition, those influencers were gone and changed with bad news that went viral where many individual investors are lost their capital in IDX. They lose money since they are gambling in the stock market without any analysis and no establishment of trading plan. This research is aimed as a strategy to individual investors in IDX to implement trading strategy based on Fibonacci retracements and projections, EMA lines, trendlines, stochastic, and volume. Back testing is conducted in IDX SMC Liquid index constituents during January 2018 until December 2020 period. By implementing this trading strategy, return generated is 164% for 3 years trading time frame. Author also found that this trading strategy is effective in bullish trend condition especially for individual investors that have long position.

scholarly journals The Long Memory Characteristics of Inflation in Turkey and Analysis of Inflation Persistence

2013 ◽  
Author(s):  
Zühal Kurul ◽  
Pınar Sezer
Keyword(s):  
Empirical Analysis ◽  
Long Memory ◽  
Structural Breaks ◽  
Structural Changes ◽  
Moving Average ◽  
Dynamic Structure ◽  
Inflation Persistence ◽  
Inflation Rates ◽  
Arfima Model ◽  
Memory Characteristics

The aim of this paper is to illustrate the long memory characteristics of the Turkish inflation rates and to analyze the potential inflation persistence. Our empirical analysis is carried out for inflation series of Turkey during the period of 1980-2013. We used the Autoregressive Fractionally Integrated Moving Average (ARFIMA) model and find that inflation in Turkey has long memory properties when structural breaks are not taken into account. When structural changes are considered, the long memory properties show different and ambiguous results. The exogenously identified structural changes have altered the dynamic structure of the inflation process and weakened the long memory characteristics of the series.

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