scholarly journals Profitability of The Moving Averages Technical Trading Rules in an Emerging Stock Market-A Study of Individual Stocks Listed On Pakistan Stock Exchange

2018 ◽  
Vol 14 (2) ◽  
pp. 67-76
Author(s):  
Muhammad Arif ◽  
Keyword(s):  
Stock Market ◽  
Stock Returns ◽  
Stock Exchange ◽  
Moving Average ◽  
Market Development ◽  
Moving Averages ◽  
Technical Trading ◽  
Technical Trading Rules ◽  
Trading Rules ◽  
Portfolio Returns

This paper investigates the gainfulness of moving averages (MA) timing method over the purchase and hold procedure for single stocks deal in Pakistan Stock Exchange. We used (Han et al., 2013) approach of single stock returns and indeterminate evidence of MA timing methodology insightful ability to increase higher returns over the strategy of purchase and hold. In addition, we report market risk-adjusted returns to expel any market development impacts and apply elective moving averages lag lengths to check the robustness of our outcomes. We look at that individual stock returns are noisier than portfolio returns and the fundamental technical exchanging principle of moving average don't be able to anticipate single stock returns. We propose the utilization of more perplexing trading rules in future investigations to determine the gainfulness of technical trading rules in individual stocks.

scholarly journals Profitability of the Moving Averages Technical Trading Rules in an Emerging Stock Market: A Study of Stocks Listed in Pakistan Stock Exchange

2020 ◽  
Vol 12 (2) ◽  
pp. 165-176
Author(s):  
Muhammad Arif ◽  
Abdul Rauf Laghari ◽  
Avinash Advani
Keyword(s):  
Stock Returns ◽  
Stock Exchange ◽  
Moving Average ◽  
Predictive Ability ◽  
Moving Averages ◽  
Technical Trading ◽  
Technical Trading Rules ◽  
Trading Rules ◽  
Future Studies ◽  
Portfolio Returns

This study examines the profitability of Moving Averages (MA) timing strategy over the buy and hold strategy for individual stocks listed at Pakistan Stock Exchange (PSX). We applied Han, Yang, and Zhou (2013), methodology to individual stock returns and found inconclusive evidence of MA timing strategy’s predictive ability to earn higher returns over buy and hold strategy. We also report market risk-adjusted returns to remove any market movement effects and apply alternative moving averages lag lengths to check the robustness of our results. We observe individual stock returns are noisier than portfolio returns and the simple technical trading rule of moving average lack the ability to predict individual stock returns. We propose the use of more complex trading rules in future studies to ascertain the profitability of technical trading rules in individual stocks.

Profitability of Trading Strategies Before and During the Greek Crisis: An Empirical Study.

2017 ◽  
Vol 11 (1) ◽  
pp. 1-26
Author(s):  
Efstathios Xanthopoulos ◽  
Konstantinos Aravossis ◽  
Spyros Papathanasiou
Keyword(s):  
Stock Exchange ◽  
Statistical Tests ◽  
Moving Average ◽  
Efficient Market Hypothesis ◽  
Trading Strategies ◽  
Technical Trading ◽  
Technical Trading Rules ◽  
Trading Rules ◽  
Greek Crisis ◽  
Athens Stock Exchange

This paper investigates the profitability of technical trading rules in the Athens Stock Exchange (ASE), utilizing the FTSE Large Capitalization index over the seven-year period 2005-2012, which was before and during the Greek crisis. The technical rules that will be explored are the simple moving average, the envelope (parallel bands) and the slope (regression). We compare technical trading strategies in the spirit of Brock, Lakonishok, and LeBaron (1992), employing traditional t-test and Bootstrap methodology under the Random Walk with drift, AR(1) and GARCH(1,1) models. We enrich our analysis via Fourier analysis technique (FFT) and more statistical tests. The results provide strong evidence on the profitability of the examined technical trading rules, even during recession period (2009-2012), and contradict the Efficient Market Hypothesis.

scholarly journals Profitable Technical Trading Rules For The Austrian Stock Market

2011 ◽  
Vol 6 (9) ◽  
Author(s):  
Massoud Metghalchi ◽  
Yong Glasure ◽  
Xavier Garza-Gomez ◽  
Chien Chen
Keyword(s):  
Stock Market ◽  
Predictive Power ◽  
Moving Average ◽  
Trading Costs ◽  
Technical Trading ◽  
Technical Trading Rules ◽  
Trading Rules ◽  
Price Patterns

Two moving average technical trading rules for the Austrian stock market are tested. Results indicate that moving average rules do indeed have predictive power and could discern recurring-price patterns for profitable trading. Results also support the hypothesis that technical trading rules can outperform the buy-and-hold strategy. Break-even one-way trading costs are estimated to be between .61 and 2.36 %. These break-even costs are larger than recent estimates of actual trading costs, implying profitable trading rules for the Austrian stock market.

scholarly journals Are Moving Average Trading Rules Profitable? Evidence From The Mexican Stock Market

2011 ◽  
Vol 24 (1) ◽  
Author(s):  
Massoud Metghalchi ◽  
Xavier Garza-Gomez ◽  
Yong Glasure ◽  
Yung-Ho Chang
Keyword(s):  
Stock Market ◽  
Transaction Costs ◽  
Predictive Power ◽  
Moving Average ◽  
Trading Costs ◽  
Font Size ◽  
Technical Trading ◽  
Technical Trading Rules ◽  
Trading Rules ◽  
Price Patterns

<p class="MsoBodyText2" style="text-justify: inter-ideograph; text-align: justify; line-height: normal; margin: 0in 0.5in 0pt;"><span style="font-family: Times New Roman;"><span style="font-size: 10pt; font-weight: normal; mso-bidi-font-family: 'Times New Roman';">This paper tests three moving average technical trading rules for the Mexican Stock Market. </span><span style="font-size: 10pt; font-weight: normal; mso-bidi-font-weight: bold; mso-bidi-font-family: 'Times New Roman';">Results indicate that moving average rules do indeed have predictive power and can discern recurring-price patterns for profitable trading and support the hypothesis that technical trading rules can outperform the buy-and-hold strategy. Break-even one-way trading costs are estimated to be</span><span style="font-size: 10pt; mso-bidi-font-weight: normal; mso-bidi-font-family: 'Times New Roman';"><strong> </strong></span><span style="font-size: 10pt; font-weight: normal; mso-bidi-font-weight: bold; mso-bidi-font-family: 'Times New Roman';">in the range of 1% to 3% over the period under consideration. These break-even costs, we believe, are large compared to recent estimates of actual trading costs, implying that moving average trading rules have predictive power and can generate consistent profits even after transaction costs are considered. </span></span></p>

scholarly journals Technical Analysis on the Bitcoin Market: Trading Opportunities or Investors’ Pitfall?

Risks ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 44 ◽  
Author(s):  
Marina Resta ◽  
Paolo Pagnottoni ◽  
Maria Elena De Giuli
Keyword(s):  
Technical Analysis ◽  
Daily Basis ◽  
Moving Averages ◽  
Technical Trading ◽  
Technical Trading Rules ◽  
Trading Rules ◽  
Price Series ◽  
Daily Data

In this paper we aimed to examine the profitability of technical trading rules in the Bitcoin market by using trend-following and mean-reverting strategies. We applied our strategies on the Bitcoin price series sampled both at 5-min intervals and on a daily basis, during the period 1 January 2012 to 20 August 2019. Our findings suggest that, overall, trading on daily data is more profitable than going intraday. Furthermore, we concluded that the Buy and Hold strategy outperforms the examined alternatives on an intraday basis, while Simple Moving Averages yield the best performances when dealing with daily data.

scholarly journals Market Efficiency For S&P 500: 1954-2004

2011 ◽  
Vol 4 (7) ◽  
Author(s):  
Massoud Metghalchi ◽  
Xavier Garza-Gomez ◽  
Chien-Ping Chen ◽  
Stanley Monsef
Keyword(s):  
Market Efficiency ◽  
Predictive Power ◽  
Moving Average ◽  
Stock Index ◽  
Technical Trading ◽  
Technical Trading Rules ◽  
Trading Rules ◽  
Daily Data ◽  
Market Inefficiency ◽  
Price Patterns

This paper tests three moving average technical trading rules for the S&P 500 stock index. Using daily data from 1954 to 2004, our results indicate that moving average rules did indeed had predictive power and could discern recurring-price patterns for the period up to mid 1980s. However, since mid 1980s, technical trading rules do not work and could not discern recurring-price patterns. Our results are consistent with market inefficiency from 1954 to 1984 and market efficiency from 1984 to present.

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