This post will introduce several simple day trading strategies using the well know ETF SPY. We'll begin with a simple observation, do some analysis, and then step by step build a model to trade this ETF in a unique way. The original "edge" was discovered quite by accident in previous studies of ETF behavior and modeling. We'll start with a very simple strategy: Buy the Close and Sell the next day's Open. That would seem to be counter-intuitive, but like many things in the stock market and life in general don't be surprised if the conventional wisdom is wrong.

After all the conventional wisdom would say - you're exposing yourself to a great deal of risk, either overnight risk or weekend risk with such a strategy.

However a simple analysis proves that initial reaction wrong; following this simple strategy actually outperforms, by a small margin, a simple buy-and-hold SPY strategy. For this article we'll look at all of the data for the SPY ETF that is available; the inception date for the SPY ETF was Jan 29, and we'll show data in this article through the end of 2Q We'll also neglect the effect of dividends; this is a valid omission since following the simple strategy with the actual ETF will have you as a valid holder of the ETF on each ex-dividend date.

Day Trade, Swing Trade or Invest in Leveraged ETFs? - Tradingsim

When we begin development of a model and look at optimizations we look at a range of data and statistics. Here's the data for the very simple strategy Buy the Close, Sell the Open for SPY from Jan 29, to Jun 30, The total percentage gain for this simple Buy the Close Sell the Open strategy is The first question one might ask is "Can we find a filter to reduce the average loss on losing days? There are a wide range of potential candidates and strategies that one can investigate in that pursuit; for our study here again we'll stick with something very basic - the Simple Moving Average [ SMA ] for SPY.

Here's the hypothesis we'll test: Graph 1 below is a plot of the total percentage gain for a range of simple moving averages where the green line is the percentage gain when SPY is above a given SMA and the red line is the percentage gain when SPY is below a given SMA. So the first thing we notice is that there is indeed an optimal value for a SMA in this study there's actually two distinct peaks on the graph but we'll come back to that later and the optimal value for our SMA is By going Long SPY only when SPY is above its day SMA we can improve the winning percentage and average gain and we can also see that there is a small net overall loss when SPY is below its day SMA, so indeed it would be advantageous to short SPY when that condition is met.

Let's look at the statistics for this new strategy overall and for each Zone:. Now let's compare this with an "adjusted" baseline.

ETF Trading strategies - Simple stock trading

Why do we need to "adjust" the baseline? Because the original data started with the inception of the SPY ETF and the earliest we can begin to use the day MA strategy is after the nd day when we can accurately compute a day SMA.

So a couple of quick observations.

Now let's go back and look at the second peak in the first chart. The 4 zones we'll create and analyze are:.

One possible way to implement a strategy using these zone statistics would be to simply trade Zone 2 Long; you would only be day trading The total percentage gain for Zone 2 alone is Of course, there are also 2X and 3X leveraged SPY ETFs than can be used with this strategy quite effectively.

Last, we'll simply plot the cumulative percentage gain for the three strategies against our "adjusted" baseline, the initial simple strategy, the two or four zone strategy and the Zone 2 Long only strategy. One feature that immediately jumps out from the graph is the significant reduction in volatility, especially for the Zone 2 Long only strategy. In conclusion we've shown a couple of basic strategies that can be used to day trade SPY.

The underlying methodology can also be used to develop more complex strategies. Currently we've developed 8- and zone strategies for several popular ETFs and experimented with and zone strategies.

The author has no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours. Blog posts are not selected, edited or screened by Seeking Alpha editors.

Developing A Simple Model To Day Trade SPY Aug. Let's look at the statistics for this new strategy overall and for each Zone: The 4 zones we'll create and analyze are: