Statistical properties of stochastic processes for moving average trading to work
Statistical properties of stochastic processes for moving average trading to work
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vonjd · External communityPost link
External question — Quantitative Finance Stack Exchange
Author: vonjd
Original post: https://quant.stackexchange.com/questions/348
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Common wisdom holds it that a moving average approach is more successful than buy-and-hold. There is quantitative evidence for that across different asset classes (see e.g.
this book
, or
this paper
from the same author Mebane Faber).
My question takes a different turn: I am trying to generalize these empirical findings to a general class of stochastic processes.
My question:
What properties must a stochastic process have for moving average trading to outperform naive buy-and-hold. At the moment I am only talking about simple moving average strategies like when the process crosses the average from above/below sell/buy. There could also be simplifying assumptions like no trading costs etc.
The plan behind this is to find general properties which are empirically testable on their own. In a way I want to find the building blocks for moving average strategies to work.
Do you have some ideas, papers, references...? Thank you!
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onlyvix.blogspot.com · External communityPost link
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Author: onlyvix.blogspot.com
Original post: https://quant.stackexchange.com/a/356
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These moving strategies are also known as trend-following. If returns have positive autocorrelation, hurst exponent > 0.5 that would be good for these strategies.
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vonjd · External communityPost link
External answer — Quantitative Finance Stack Exchange
Author: vonjd
Original post: https://quant.stackexchange.com/a/1729
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In fact there is an exhaustive paper on this issue available now:
"The Trend is not Your Friend! Why Empirical Timing Success is Determined by the Underlying’s Price Characteristics and Market Efficiency is Irrelevant"
by Peter Scholz and Ursula Walther, Frankfurt School Working Paper, CPQF No. 29, 2011
Fascinating read - highly recommended!
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Quoted from Forex.com.bd-Editorial External question — Quantitative Finance Stack Exchange Author: vonjd Source score (net votes, not local likes): 21 Original post: https://quant.stackexchange.com/questions/348 License: CC BY-SA 2.5 — https://creativecommons.org/licenses/by-sa/2.5/ Adaptation: HTML converted to plain text; contact email addresses removed. Common wisdom holds it that a moving average approach is more successful than buy-and-hold. There is quantitative evidence for that across different asset classes (see e.g. this book , or this paper from the same author Mebane Faber). My question takes a different turn: I am trying to generalize these empirical findings to a general class of stochastic processes. My question: What properties must a stochastic process have for moving average trading to outperform naive buy-and-hold. At the moment I am only talking about simple moving average strategies like when the process crosses the average from above/below sell/buy. There could also be simplifying assumptions like no trading costs etc. The plan behind this is to find general properties which are empirically testable on their own. In a way I want to find the building blocks for moving average strategies to work. Do you have some ideas, papers, references...? Thank you!
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