The Effectiveness Of The 50 Day MA With This ETF (NYSE:SPY)
Of the myriad of technical indicators available, moving averages have risen as not only one of the most popular, but also one of the most effective. Perhaps their popularity is due in part to their simple yet versatile nature. Traders can use them for anything from identifying trends and reversals to measuring momentum and crossovers. Though moving averages can be measured on any time frame, the 50 day moving average has become a staple for most chartist. Indeed, it comes default on most charting platforms and is often used to aid in identifying the intermediate trend of the market.
I suspect many traders (myself included) took note last Thursday as the SPDR S&P 500 ETF (NYSE:SPY) mustered the strength to breach its declining 50 MA. Those subscribing to the notion that the 50 MA provides quality signals no doubt used this breach as a clarion call to dispense with their bearish aspirations for the time being and perhaps dip their toes in the water on the long side.
As with any strategy or method of analysis, the proof is in the pudding. If breaking the 50 MA has provided profitable signals in the past, then directional traders ignore this signal at their own peril. Thus far the (NYSE:SPY) has seen four different occurrences of breaking the 50 MA in 2010 – all of which proved fruitful.
Admittedly, four signals is too small a sampling size to draw any meaningful conclusions. Suppose we looked at the performance of the 50 MA signal going back to 2000. With ten years of data and 70 plus crosses to learn from, we certainly have enough data to pass judgement on whether this moving average is all hype or worth observing.
I’ll divulge my findings tomorrow. Stay tuned… (We posted the follow up below)
As mentioned yesterday, the 50 MA is a tool of choice for many chartists in determining their outlook on the overall market as well as individual securities. Equipped with a few simple rules and my semi-adequate Excel spreadsheet skills I set out to determine whether or not this moving average is worth its weight or just another indicator cluttering up my chart. Before delving into the results, let’s first establish the gist of the trading plan.
1. Buy the (NYSE:SPY) on a 1+% break above the 50 MA.
2. Sell short the (NYSE:SPY) on a 1+% break below the 50 MA.
As outlined, the system dictates one always has a position (long or short) depending upon whether the (NYSE:SPY) is above or below the 50 MA. For simplicity purposes I assumed one was simply long or short one share of the (NYSE:SPY). To reduce the risk of whipsaw, I required the (NYSE:SPY) to break the 50 MA by at least 1% to generate a signal. Settling on a proper filter for a trading system is always a dilemma as there is an inherent trade-off. Though using a break of .5% instead of 1% would have generated quicker signals and thus better entry prices, it inevitably would have resulted in more false signals. No price filter will work every time, so it’s really a matter of finding what works best the majority of the time.
The graphic below displays the outcome of the trading system from 2000 to 2010.
The table is broken down to the 50 MA’s performance per year with both the best and worst years highlighted. Of the 71 buy/sell signals I found, 30 were winners and 41 were losers. At first blush, that doesn’t look so effective, however, it’s not just about number of wins versus number of losses. To gain a complete picture we must also take into consideration the average gains captured on the winning trades versus the average losses incurred on losing trades. Of the 30 winners, $7 was the average gain. Of the 41 losers, $2.30 was the average loss. Shown in this light, the trading system looks much more appealing.
Given that I did this by hand, I don’t doubt I may have missed a signal here or there. Be that as it may, I’m confident it wouldn’t have changed the conclusions we can draw from this whole exercise. Tomorrow I’ll compare the best and worst performing years to hammer out a few strengths and weaknesses of using moving average signals.
Written By Tyler Craig From Tyler’s Trading
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