Optimizing Moving-Average Trading Strategy: Evidence in Malaysia Equity Market

2016 ◽  
Author(s):  
Afiruddin Tapa Tapa
Keyword(s):  
Moving Average ◽  
Equity Market ◽  
Trading Strategy

scholarly journals Research on Volatility Pattern of BSE BANKEX Index & BSE SENSEX Index using Exponential Weighted moving Average Model

2020 ◽  
Vol 9 (4) ◽  
pp. 3195-3199
Keyword(s):  
Financial Services ◽  
Stock Exchange ◽  
Moving Average ◽  
Equity Market ◽  
Long Duration ◽  
Moving Average Model ◽  
Growth Prospects ◽  
High Level ◽  
Exponential Weighted Moving Average ◽  
Weighted Moving Average

India, a country with impressive growth prospects has stunned many developed nations. As far as performance of equity market concern, last 25 years among more than $1-trillion markets in the world, Indian equity market was best performer outpacing some of bigwigs such as US, Germany and Hong Kong. Last 25 years return in local money of SENSEX was so high in comparisons to others. Banking sectors have specific and an important role in the economic development of a India. With the reconstitution of BSE Sensex in last few years, the weightage of the Banking, Financial Services and Insurance (BFSI) sector. In the BSE 30 will touch its all-time high level to 40.1% which will be more than the combined weights of technology as consumer and auto. The weightage of financials in the Sensex has more than doubled from financial year 2009. In the long duration index weightage affect portfolio in major funds. The main objective of this research paper is to show the volatility patterns of Bombay Stock Exchange SENSEX and BSE BANKEX Index using Exponential weighted moving average (EWMA) model.

scholarly journals Value-at-Risk Estimation of Equity Market Risk in India

2021 ◽  
Vol 9 (1) ◽  
pp. 1-24
Author(s):  
Jitender
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Stock Exchange ◽  
Risk Estimation ◽  
Moving Average ◽  
Equity Market ◽  
Market Risk ◽  
Financial Instrument ◽  
Historical Simulation ◽  
Distributed Models

Abstract The value-at-risk (Va) method in market risk management is becoming a benchmark for measuring “market risk” for any financial instrument. The present study aims at examining which VaR model best describes the risk arising out of the Indian equity market (Bombay Stock Exchange (BSE) Sensex). Using data from 2006 to 2015, the VaR figures associated with parametric (variance–covariance, Exponentially Weighted Moving Average, Generalized Autoregressive Conditional Heteroskedasticity) and non-parametric (historical simulation and Monte Carlo simulation) methods have been calculated. The study concludes that VaR models based on the assumption of normality underestimate the risk when returns are non-normally distributed. Models that capture fat-tailed behaviour of financial returns (historical simulation) are better able to capture the risk arising out of the financial instrument.

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 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 Did Institutional Investors’ Behavior Affect U.S.-China Equity Market Sentiment? Evidence from the U.S.-China Trade Turbulence

Mathematics ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 952 ◽  
Author(s):  
Shu-Ling Lin ◽  
Jun Lu
Keyword(s):  
Panel Data ◽  
Institutional Investors ◽  
Equity Market ◽  
Trading Strategy ◽  
Securities Markets ◽  
Market Sentiment ◽  
China Trade ◽  
Smart Money ◽  
The U.S ◽  
Feedback Trading

In the current situation of U.S.-China trade turbulence, this study focuses on quarterly panel data from May 2016 to September 2019 in order to verify the effectiveness of feedback trading strategy and smart money theory in stabilizing U.S.-China securities markets and to understand the role of institutional investors’ behavior, to come up with suggestions for improving and perfecting the market mechanism in stabilizing the U.S.-China securities markets. In this study, we adopt the generalized method of moments (GMM) to perform dynamic panel data analysis and discuss the changes in professional institutional investors’ behavior and equity market sentiment in the U.S. and China during the trade turbulence, and then analyze whether that behavior will suppress local stock market sentiment. Through empirical research, we found that institutional investors on both sides of the trade turbulence have a different impact on the stability of the local securities market. The behavior of institutional investors in the United States has played a role in stabilizing equity market sentiment in accordance with feedback trading strategy and smart money theory. However, the behavior of institutional investors in China is the opposite.

scholarly journals Connectedness between crude oil and US equities: The impact of COVID-19 pandemic

2021 ◽  
Author(s):  
Aktham Maghyereh ◽  
hussein abdoh
Keyword(s):  
Correlation Analysis ◽  
Long Range ◽  
Cross Correlation ◽  
Moving Average ◽  
Equity Market ◽  
Cross Correlation Analysis ◽  
Cross Correlations ◽  
The Impact ◽  
Dynamical Connection

Abstract In this paper, we exploit multifractal detrended cross-correlation analysis (MF-DCCA) to investigate the impact of COVID-19 pandemic on the cross-correlations between oil and US equity market (as represented by the S&P 500 index). First, we examine the detrended moving average cross-correlation coefficient between oil and S&P 500 returns before and during the COVID-19 pandemic. The correlation analysis shows that US stock markets became more correlated with oil during the pandemic in the long term. Second, we find that the pandemic has caused an increase in the long range cross correlations over the small fluctuations. Third, the MF-DCCA method shows that the pandemic caused an increase of multifractality in cross-correlations between the two markets. In sum, the pandemic caused a closer correlation between oil and US equity in the long range and a deeper dynamical connection between oil and US equity markets as indicated by the multifractality tests.

scholarly journals A cointegrating stock trading strategy: application to listed tanker shipping companies

2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Nektarios A. Michail ◽  
Konstantinos D. Melas
Keyword(s):  
Stock Market ◽  
Moving Average ◽  
Trading Strategy ◽  
Investment Strategies ◽  
Shipping Industry ◽  
Stock Market Returns ◽  
Average Rule ◽  
Stock Market Performance ◽  
Close Relationship ◽  
The Baltic

Abstract In the current paper, we propose a strategy to trade a portfolio of listed shipping companies in the US market. In particular, we estimate a co-integrating relationship between the weekly stock market returns of a portfolio of tanker shipping companies and the Baltic Tanker Index, exploiting the close relationship between freight rates and the stock market performance of shipping companies. Our results suggest that a trading strategy on the basis of a co-integrating relationship and a simple moving average rule outperforms, by approximately 50%, a standard buy-and-hold strategy in various investment horizons, often by a very wide margin. Given the latter, the results allow us to enhance the current literature on shipping finance by providing evidence of how simple investment strategies can benefit both retail and institutional investors who do not have direct exposure or experience in the shipping industry by allowing them to include shipping stocks in their portfolios.

scholarly journals Value Premium and Technical Analysis: Evidence from the China Stock Market

Economies ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 92 ◽  
Author(s):  
Lam ◽  
Dong ◽  
Yu
Keyword(s):  
Stock Market ◽  
Transaction Costs ◽  
Moving Average ◽  
Technical Analysis ◽  
Trading Strategy ◽  
Value Premium ◽  
Chinese Stock Market ◽  
New Strategy ◽  
The One ◽  
Three Factor

We find value premium in the Chinese stock market using a conventional buy-and-hold approach which longs the portfolio with the highest BM ratio and shorts the one with the lowest BM ratio. Based on the finding, we test a new strategy by combining the value premium effect and technical analysis. During the sample period (1995 to 2015), we trade the objective portfolio or risk-free asset according to the moving average timing signals, and we find excess return from such a zero-cost trading strategy. We perform various robustness tests and find that the excess returns remain significantly positive after adjusting for risks (on three factor models) and transaction costs. In general, we find that the combined trading strategy can generate significant positive risk-adjusted returns after the transaction costs.

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