Naive Trading Rules in Financial Markets and Wiener-Kolmogorov Prediction Theory: A Study of "Technical Analysis"

1991 ◽  
Vol 64 (4) ◽  
pp. 549 ◽  
Author(s):  
Salih N. Neftci
Keyword(s):  
Financial Markets ◽  
Technical Analysis ◽  
Prediction Theory ◽  
Trading Rules

TECHNICAL ANALYSIS OF FINANCIAL MARKETS USING MARKET INDICATORS ON THE EXAMPLE OF SAMSUNG SHARES

2021 ◽  
pp. 34-34
Author(s):  
K. V. Ketova ◽  
A.V. Shishova ◽  
S.V. Dorofeeva
Keyword(s):  
Financial Markets ◽  
Technical Analysis

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.

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.

Forecast Studies for Financial Markets using Technical Analysis

2005 ◽  
Author(s):  
V. Nagarajan ◽  
Ying Wu ◽  
Min Liu ◽  
Qing-Guo Wang
Keyword(s):  
Financial Markets ◽  
Technical Analysis

Effective Trading in Financial Markets Using Technical Analysis

2020 ◽  
Author(s):  
Smita Roy Trivedi ◽  
Ashish H. Kyal
Keyword(s):  
Financial Markets ◽  
Technical Analysis

Adaptive Bands Z-Test-Statistics in Futures Markets: A New Technical Analysis Indicator

2013 ◽  
Vol 12 (3) ◽  
pp. 19-47
Author(s):  
Mohd Rizal Palil
Keyword(s):  
Soybean Oil ◽  
Futures Markets ◽  
Abnormal Returns ◽  
Technical Analysis ◽  
Test Statistics ◽  
Futures Prices ◽  
Oil Futures ◽  
Trading Rules

This paper presents a study of technical analysis trading rules that generate abnormal returns for futures prices.  It reports abnormal returns above that of the passive buy-and-hold policy for FKLI, FCPO, Soybean Oil Futures, Soybean Futures and Corn Futures for year 2008 tested. 

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