The technical analysis method of moving average trading : rules that reduce the number of losing trades

A general issue with moving average trading is the assumption that all buy/sell signals result in a trading action. The argument that such trading rules are representative of trading practice is highly questionable. This thesis proposes two new moving average trading rules designed to capture tradin...

Full description

Bibliographic Details
Main Author: Toms, Marcus Christian
Published: University of Newcastle Upon Tyne 2011
Subjects:
Online Access:http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.556032
id ndltd-bl.uk-oai-ethos.bl.uk-556032
record_format oai_dc
spelling ndltd-bl.uk-oai-ethos.bl.uk-5560322015-03-20T03:33:56ZThe technical analysis method of moving average trading : rules that reduce the number of losing tradesToms, Marcus Christian2011A general issue with moving average trading is the assumption that all buy/sell signals result in a trading action. The argument that such trading rules are representative of trading practice is highly questionable. This thesis proposes two new moving average trading rules designed to capture trading practice. The first trading rule is the trade reduction rule and is based on the idea of allowing a trade to run. The second trading rule is the positive autocorrelation rule and is based on the idea of only trading if it is believed to be profitable to do so. The trading rules are tied to moving average trading via the buy/sell signal generating mechanism and alter the way the price crossover rule responds to the buy/sell signals. Simulations of portfolios of UK equities find that the trading rules uncover information that is missed by the price crossover rule and there is evidence that this information is financially exploitable. This motivates the argument that the information needed for trading to be economically viable is observable in the price. The trading rules also establish a link with the market microstructure literature. The trading rules uncover issues of informed trading (asymmetric information), liquidity, adverse selection and price impact. The strongest interpretation that can be applied to the trading rules in this context is that they are examples of informed trading. Compared to the price crossover rule, the trading rules are better able to extract meaning from or are better able to understand the same price information.332.63228University of Newcastle Upon Tynehttp://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.556032http://hdl.handle.net/10443/1288Electronic Thesis or Dissertation
collection NDLTD
sources NDLTD
topic 332.63228
spellingShingle 332.63228
Toms, Marcus Christian
The technical analysis method of moving average trading : rules that reduce the number of losing trades
description A general issue with moving average trading is the assumption that all buy/sell signals result in a trading action. The argument that such trading rules are representative of trading practice is highly questionable. This thesis proposes two new moving average trading rules designed to capture trading practice. The first trading rule is the trade reduction rule and is based on the idea of allowing a trade to run. The second trading rule is the positive autocorrelation rule and is based on the idea of only trading if it is believed to be profitable to do so. The trading rules are tied to moving average trading via the buy/sell signal generating mechanism and alter the way the price crossover rule responds to the buy/sell signals. Simulations of portfolios of UK equities find that the trading rules uncover information that is missed by the price crossover rule and there is evidence that this information is financially exploitable. This motivates the argument that the information needed for trading to be economically viable is observable in the price. The trading rules also establish a link with the market microstructure literature. The trading rules uncover issues of informed trading (asymmetric information), liquidity, adverse selection and price impact. The strongest interpretation that can be applied to the trading rules in this context is that they are examples of informed trading. Compared to the price crossover rule, the trading rules are better able to extract meaning from or are better able to understand the same price information.
author Toms, Marcus Christian
author_facet Toms, Marcus Christian
author_sort Toms, Marcus Christian
title The technical analysis method of moving average trading : rules that reduce the number of losing trades
title_short The technical analysis method of moving average trading : rules that reduce the number of losing trades
title_full The technical analysis method of moving average trading : rules that reduce the number of losing trades
title_fullStr The technical analysis method of moving average trading : rules that reduce the number of losing trades
title_full_unstemmed The technical analysis method of moving average trading : rules that reduce the number of losing trades
title_sort technical analysis method of moving average trading : rules that reduce the number of losing trades
publisher University of Newcastle Upon Tyne
publishDate 2011
url http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.556032
work_keys_str_mv AT tomsmarcuschristian thetechnicalanalysismethodofmovingaveragetradingrulesthatreducethenumberoflosingtrades
AT tomsmarcuschristian technicalanalysismethodofmovingaveragetradingrulesthatreducethenumberoflosingtrades
_version_ 1716781596406710272