Building a right trading perspective towards moving averages Part 1: Technical Outlook, Edition #216 (07/06/2022)
Looking to add a new weapon to your trading arsenal? 👀 Read on to find out what Moving Averages are and how to incorporate them into your strategy in this multi-part series 👇
(This is a Qluster guest article written by Vũ Nguyễn and edited by Andy Phung)
Moving Average (MA), especially Exponential Moving Average (EMA), is one of the common indicators in a trader's toolbox for technical analysis.
The comprehensive nature of the indicator and its versatility as it suits both long-term and short-term traders make moving averages so popular among the traders/investors.
Nevertheless, I have observed much confusion and mistakes traders/investors made because of lacking the proper perspective in using it as a trading system.
Let us dive into this topic to have a good overview of this indicator.
Time – a fundamental concept of technical analysis
Along with price and volume, time is one of the three 'pillars' of technical analysis.
We see the time factor deeply entrenched in our daily lives.
The United Nations estimates a global average life expectancy of 72 years for 2019. Memento mori.
We can peer even closer to see how people conduct business and how time is incorporated into the financial market.
The Securities and Exchange Commission (SEC) rules that earnings reports are expected after the end of a company's first three quarters and both quarterly and annual reports after their fiscal year (FY) ends.
We do tax reports every year (don't we love doing them!)
On the other hand, the futures market has the delivery date of physical goods, and the options market has Θ (Theta) to represent time decay for a contract value.
Incorporating the time factor into the charting system is a must for every technical analysis method.
(Unless your trading system is based on a quantum mechanism in another universe, which focuses on the 'state' of the value instead of its linear/exponential development – but that's another story, and you may not need to read this article, do you? Looking at you, Dr Manhattan!)
Just because you’re a omniscient god-like being with the powers over time and space doesn’t mean you’re a god at trading.
And for digital assets like cryptocurrency, we're only just getting started 👇
Why moving average?
There are various ways to present the time factor into your trading/investing system.
However, the most popular way is to incorporate time with price. A price chart is a presentation of the state of price over time like other chaotic systems, price is subject to volatility, and therefore excessive noise could distort its presentation.
Figure 1: S&P 500 1-Month Realised Volatility Index
This index seeks to reflect the 1-Month realised volatility in the daily levels of the S&P 500. Realised volatility measures the variations in the price of a security over a given period.
As a rational investor/trader, the ultimate goal in analysing the market is to identify the current market conditions and to which extent this condition is proved wrong.
For the above to happen, it is necessary to have a system where the development of price can be quickly and accurately summarised, which in turn would allow;
(1) remove the insignificant noise of the market
(2) produce a summarised result that will be used in deductive reasoning to conclude the current market condition.
In this regard, averaging is a viable option in dealing with market data.
Various techniques exist for producing average price data, incorporating different market factors within its calculations.
For the scope of this article, I would focus on the Exponential Moving Average because it is the most popular one (probably because it is easier on the eyes).
Know someone who loves good due diligence? Help us get the word out and refer a friend to Qluster Research now 👇
Formula: Let pt be the price of an asset at the instant t, h be the length of the moving average, i.e., the number of observations from which the standard of the values will be extracted and let N ≥ h be the position of a given observation from which the previous h values will be included in the calculation of the N-th moving average.
EMAN is the Nth exponential moving average and will be calculated as follows: (de Souza et al., 2018)
Figure 2: Formula of EMA. Source: de Souza et al., 2018.
The result is a smooth line that runs along with the price line, and it contains the average value of the price within the specified period.
Figure 3: SPY ETF with 200-period EMA in 3D timeframe and the same EMA without price chart.
Note how easy it is to reach a conclusion about the market from 2008 until now.
If tailored right, the moving average could bring considerable benefits to traders.
Reportedly that Richard Dennis, one of the most successful traders of all time and his Turtle trading group were wildly successful just by following a simple trade-following strategy using EMA.
In his strategy, the price sits above or below the moving average, implying the market's trending condition, and he would long or short the underlying asset accordingly.
What is unique about Richard Dennis is that he gets out very quickly when the price collapses to the opposite side of the moving average. At the same time, he would pyramid his positions aggressively if the market conditions stayed the same.
Thank you for reading Qluster Research. This post is public so feel free to share it.
Exciting findings of moving average
Over the last few years of using moving average, I have had several interesting observations in obtaining insights into the market.
Those findings are selected identical to the way we choose the indicator parameters, the perspectives of the traders, and the way we allocate capital in trading.
⦁ Observation No.1: EMA period is not the problem, but the timeframe is when it comes to indicator accuracy
Let us have a comparison between a 200-period EMA in a 5M chart and a 50-period EMA in a Daily chart:
Figure 4: BTCUSD with 200-period EMA in 5M timeframe and with 50-period EMA in Daily timeframe
Although it is four times greater than the 50-period, the 200-period EMA in the 5M timeframe produces a lot of noise and inaccurate crosses.
Higher timeframes should always be a priority over switching back and forth between different EMA parameters.
⦁ Observation No.2: EMA and Moving Averages are not trading signals, but the measurement tools for the current market conditions
Contrary to popular belief, buying at EMA lines most often does not entail any unique advantage over other situations.
As every trend will eventually reverse, the time you bought when the price touches the EMA' Support' could probably be the last time we could see the price remain above the moving average.
However, a constructive entry approach where traders continuously enter the market as the conditions remain the same would probably be better.
Figure 5: BTCUSD with 200-period EMA in 12H timeframe analysis
Well done! You’ve almost made it to the conclusion so help us share this research before reading on 👇
⦁ Observation No.3: EMA in Ultra-high timeframes give you an overview of the current market and possibly the economic
Figure 6: Dow Jones with 62 and 38-period EMA in Weekly-Monthly-4M (Quarterly) timeframe
A macro overview of the market and good opportunities are also present when we look at ultra-high timeframes EMA (from Daily onwards).
We can see that stocks generally go up with some short-term bear markets and rare opportunities.
It is also reported that Warren Buffet also loaded up Berkshire Hathaway's portfolio around May this year, probably somewhere closer to the Monthly EMA support. (Otani, 2022)
This section may as conclude the first part of this writing.
Then, we will focus on building the right trading/investing perspective toward this fantastic indicator for the next part!
Part 2 - Building the right attitude towards Moving Average
⦁ Basic approaches
⦁ Trend-following: Thinking about the worst-case scenario
⦁ Anti-trend: Being a stubborn opposition (with a limit)
⦁ Advanced approaches: Multi-timeframe EMA and gap consolidation
See you next time!
de Souza, M.J.S., Ramos, D.G.F., Pena, M.G., Sobreiro, V.A. and Kimura, H. (2018). Examination of the profitability of technical analysis based on moving average strategies in BRICS. Financial Innovation, 4(1). doi:10.1186/s40854-018-0087-z.
SP Global (n.d.). S&P 500 1-Month Realised Volatility Index | S&P Dow Jones Indices. [online] www.spglobal.com. Available at: https://www.spglobal.com/spdji/en/indices/indicators/sp-500-1-month-realized-volatility-index/#overview.
Otani, A. (2022). Warren Buffett Spends Big as Stock Market Sells Off. Wall Street Journal. [online] 17 May. Available at: https://www.wsj.com/articles/warren-buffett-spends-big-as-stock-market-sells-off-11652589031 [Accessed 6 Jun. 2022].
We’re on a mission to a Brand New World.
It’s a place where people come to share in the wonderful gifts of trading. Where individuals come to Qluster their knowledge, united by a shared love for learning.
This is Trading Made Social. Help us on our mission by sharing the gift of Trading Made Social to new explorers.
Join our Facebook group and connect with likeminded traders 🚀
Like and Follow our Facebook page for activity updates 📣
Connect with us on LinkedIn for future updates 🤝
The information on this website is for general information purposes only. It is not intended as legal, financial and/or investment advice and should not be construed and/or relied on as such. Before making any commitment of a legal and/or financial nature you should seek advice from a qualified and registered legal practitioner and/or financial and/or investment adviser. No material contained within this website should be construed or relied upon as providing recommendations in relation to any legal and/or financial product. Qluster does not recommend and/or endorse products and does not receive remuneration based upon investment and/or other decisions