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.

HOW TO MAKE A PROFITABLE TRADING STRATEGY MORE PROFITABLE?

2013 ◽  
Vol 58 (03) ◽  
pp. 1350019 ◽  
Author(s):  
TERENCE TAI-LEUNG CHONG ◽  
TAU-HING LAM
Keyword(s):  
Stock Market ◽  
Trading Strategy ◽  
Chinese Stock Market ◽  
Chinese Market ◽  
Trading Rules ◽  
New Strategy ◽  
Market Indexes ◽  
The U.S

Chong and Lam and Chong et al. show that SETAR(200) and MA(50) outperform other rules in both the U.S. and the Chinese stock market. This paper investigates the synergy of combining SETAR(200) and MA(50) rules in ten U.S. and Chinese stock market indexes. It is found that the SETAR rule performs better in the U.S. market, while the MA rule performs better in the Chinese market. In addition, we find evidence that a new strategy combining the two rules together is able to create synergy. An immediate implication of our result is that investors are able to improve the performance of their portfolios by combining existing profitable trading rules.

scholarly journals Machine learning applied in the stock market through the Moving Average Convergence Divergence (MACD) indicator

2020 ◽  
Vol 17 (4) ◽  
pp. 44-60
Author(s):  
Alberto Antonio Agudelo Aguirre ◽  
Ricardo Alfredo Rojas Medina ◽  
Néstor Darío Duque Méndez
Keyword(s):  
Machine Learning ◽  
Genetic Algorithms ◽  
Stock Market ◽  
Moving Average ◽  
Asset Price ◽  
Technical Analysis ◽  
Investment Strategies ◽  
Historical Data Analysis ◽  
Financial Asset Returns ◽  
Technical Indicator

The implementation of tools such as Genetic Algorithms has not been exploited for asset price prediction despite their power, robustness, and potential application in the stock market. This paper aims to fill the gap existing in the literature on the use of Genetic Algorithms for predicting asset pricing of investment strategies into stock markets and investigate its advantages over its peers Buy & Hold and traditional technical analysis. The Genetic Algorithms strategy applied to the MACD was carried out in two different validation periods and sought to optimize the parameters that generate the buy-sell signals. The performance between the machine learning-based approach, technical analysis with the MACD and B&H was compared. The results suggest that it is possible to find optimal values of the technical indicator parameters that result in a higher return on investment through Genetic Algorithms, beating the traditional technical analysis and B&H by around 4%. This study offers a new insight for practitioners, traders, and finance researchers to take advantage of Genetic Algorithms for trading rules application in forecasting financial asset returns under a more efficient and robust methodology based on historical data analysis.

scholarly journals Value premium in the Chinese stock market: free lunch or paid lunch?

2013 ◽  
Vol 23 (4) ◽  
pp. 315-324 ◽  
Author(s):  
Yujia Huang ◽  
Jiawen Yang ◽  
Yongji Zhang
Keyword(s):  
Stock Market ◽  
Value Premium ◽  
Chinese Stock Market ◽  
Free Lunch

Is Technical Analysis Profitable even for an Amateur Investor?

2015 ◽  
pp. 255-269
Author(s):  
Vasileiou Evangelos
Keyword(s):  
Stock Market ◽  
Transaction Costs ◽  
Behavioral Finance ◽  
Investment Decisions ◽  
Technical Analysis ◽  
Moving Averages ◽  
Trading Rules ◽  
Trading Decisions ◽  
Transaction Fees

The purpose of this chapter is to examine if even the simplest trading rules could take advantage of the market's inefficiency and lead to profitable trading decisions. For this reason, this study examined the profitability of the simplest trading rules, using only the simple moving averages (SMA) rules that even an amateur investor could apply. In order to examine the specific issue a data sample from the Greek stock market during the period 2002-12 was used. The results suggest that even if one takes into account the most expensive transaction fees, the trading rules signal profitable investment decisions; therefore, even an amateur trader and/or investor who does not have a significant amount of money to invest (which may lead to reduced transaction costs) could take advantage of the market's inefficiency. Behavioral finance theories may provide some useful and alternative explanations regarding some of the reasons that contribute to the Greek stock market's inefficient environment.

Data Snooping on Technical Analysis: Evidence from the Taiwan Stock Market

2011 ◽  
Vol 14 (02) ◽  
pp. 195-212 ◽  
Author(s):  
Cheng-Wei Chen ◽  
Chin-Sheng Huang ◽  
Hung-Wei Lai
Keyword(s):  
Stock Market ◽  
Transaction Costs ◽  
Market Efficiency ◽  
Technical Analysis ◽  
The Other ◽  
Trading Rule ◽  
Data Snooping ◽  
Empirical Results

The main purpose of this paper is to investigate the validity and predictability of technical analysis in the Taiwan stock market. Bootstrapped tests of White (2000) and of Hansen (2005) are employed to ascertain whether there exists a superior trading rule among two broadly used sets of technical analysis. One coming from Brock et al. (1992) and the other from Sullivan et al. (1999). Moreover, this study brings together powerful bootstrapped tests along with two institutional adjustments to ascertain the efficacy of technical analysis: (1) non-synchronous trading and (2) transaction costs. The empirical results indicate that this triad-data snooping, non-synchronous trading and transaction costs, has a great impact on the performance of technical analysis. In fact, the Taiwan stock market stands for market efficiency, and economical profits cannot be rendered from technical analysis in this market.

ARE NONLINEAR TRADING RULES PROFITABLE IN THE CHINESE STOCK MARKET?

2009 ◽  
Vol 05 (01) ◽  
pp. 0950002
Author(s):  
TERENCE TAI-LEUNG CHONG ◽  
TAU-HING LAM ◽  
MELVIN J. HINICH
Keyword(s):  
Stock Market ◽  
World Economy ◽  
Moving Average ◽  
Ar Model ◽  
Chinese Stock Market ◽  
Trading Rules ◽  
Threshold Autoregressive ◽  
International Attention ◽  
Rise Of China ◽  
The Rise Of China

The rise of China in the world economy has attracted a great deal of international attention. This paper investigates the performance of nonlinear self-exciting threshold autoregressive (SETAR) model-based trading rules in the Chinese stock market. We compare the performance of the SETAR model with the autoregressive (AR) model and the moving average (MA) trading rules. Our results indicate that trading rules are profitable in the B-share market, and that the nonlinear SETAR rule outperforms the other two linear rules in general.

scholarly journals Optimization of investment management in Warsaw stock market

2014 ◽  
Vol 15 (2) ◽  
pp. 143-156 ◽  
Author(s):  
Maciej Janowicz ◽  
Arkadiusz Orłowski ◽  
Franciszek Michał Warzyński
Keyword(s):  
Stock Market ◽  
Time Perspective ◽  
Moving Average ◽  
Technical Analysis ◽  
Relative Strength ◽  
Optimal Management ◽  
Brute Force ◽  
Exchange Market ◽  
Strength Index ◽  
Optimal Values

Abstract Application of simple prescriptions of technical analysis on the Warsaw Exchange Market (GPW) has been analyzed using several stocks belonging to WIG20 group as examples. Only long positions have been considered. Three well-known technical-analysis indicators of the market have been investigated: the Donchian channels, the Relative Strength Index, and Moving Average Convergence-Divergence indicator. Optimal values of parameters of those indicators have been found by „brute force“ evaluation of (linear) returns. It has been found that trading based on both Donchian channels and Relative Strength Index easily outperform the „buy and hold“ strategy if supplied with optimal values of parameters. However, those optimal values are by now means universal in the sense that they depend on particular stocks, and are functions of time. The optimal management of capital in the stock market strongly depends on the time perspective of trading. Finally, it has been argued that the criticism of technical analysis which is often delivered by academic quantitative financial science is unjustified as based of false premises.

scholarly journals Effectiveness of Technical Analysis Signals Around the Earning Announcements in Malaysian Stock Market

2018 ◽  
Vol 7 (3.21) ◽  
pp. 109
Author(s):  
Kelvin Lee Yong Ming ◽  
Mohamad Jais
Keyword(s):  
Stock Market ◽  
Stock Exchange ◽  
Moving Average ◽  
Technical Analysis ◽  
Relative Strength ◽  
Kuala Lumpur ◽  
Earning Announcement ◽  
Strength Index ◽  
Corporate Announcements ◽  
Technical Indicator

Technical analysis is an analysis that widely applied by the investor in the stock market. However, various corporate announcements could cause the market to react, and the most significant corporate announcement is the earnings announcement (1). Thus, this study examines the effectiveness of technical analysis signals around the earning announcements dates in Malaysian stock market. In doing so, this study applied and tested four technical indicators, namely Simple Moving Average (SMA), Relative Strength Index (RSI), Stochastic (K line), and Moving Average Convergence/Divergence (MACD) in Malaysian stock market. The sample of this study consisted of 30 largest capitalization companies from the main market of Kuala Lumpur Stock Exchange (KLSE). Meanwhile, the sample period covered from 2nd January 2014 to 31st March 2016. This study found that Moving Average Convergence/Divergence (MACD) significantly produced higher returns as compared to the other technical indicator before the earning announcement dates in financial year 2014 and 2015. The combined indicator of MA-MACD also found to have higher return in financial year 2015. The findings conclude that the technical analysis signals can be used to generate returns before earning announcement dates.  

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