Using market profile to get an edge on the stock market

In the previous articles, we analyzed the return on investment of going long every day on the S&P 500 and found out this would be a profitable strategy. In this article, we will try to see if there are ways to utilize some very basic concepts of market profile to improve this strategy's return.

What is market profile?

Developed by J. Peter Steidlmayer in his book Mind Over Market, market profile displays prices on the vertical axis and time on a horizontal axis of a chart. The approach is very complex, in this article we will use only one concept: the value area. The value area represents the zone in intraday trading where the market spends more than 70% of the time.  If the price reaches at least once during a 30 minutes block, a Time Price Opportunity TPO block is created is added to the chart. Traditionally a letter is used to represent a TPO, but we use a number to make it easier to read (see graph below). Just with a glance by looking at the three long bars on the profile on the left, we can see that the most time spent was between 399.5 and 400. 


Below is another way of representing the market profile. The value area where the market spent 70% of the time is in green on the chart. The point of control or POC is the price where more time has spent, the longest bar closest to the center of the profile.  Both the value area and the POC indicate where the market agrees on value.

Since the value area indicates where the market spent most time in a day, on the following day, when the market opens outside the value area of the previous, this might be a strong signal that the market might be trying to establish a new balance by going higher if above the previous day value area, or lower if below the previous day value area.


Analysis of the relationship of market profile to improve trading odds


1) Setting up a baseline


It has been established in previous articles that the S&P 500 close price has a slightly more than 50% chance of closing above the previous day's close price.

In this article, we used 5 years of ES data, the S&P futures from Nov 2015 to 2020, and analyzed the data just when the market opens at 9:30 to the closing at 16:00.

The baseline consists of just plainly buying going long every day. After few calculations, the optimal setup we came to the conclusion that the optimal setup would be to set a stop loss of 0.28% of ES open price.

For example, if the market opens at 4060, the optimal stop loss would be:
  •  4060 * 0.28% = 11.5 points.
  • Stop loss : 4060 - 11.5 = 4048.5 

We assume that the micro-mini (MES) follows the same price movements as the ES, and used it as a reference for profit calculation. Based on our calculation, for every contract purchased, using the strategy of going long every day at the open, with a stop loss of 0,28% of open price, would generate a profit of 60.67$ per MES contract per month. Assuming an account size of 5000$, the expected ROI is 60.67$ / 5000 = 1.21%




We try to follow the principle that we should not risk more than 1 to 2% of our account per trade. A stop loss of 0.28% equals a weighted amount of 67.26$, assuming an open price of 4060. For an account size of 5000, that would represent a risk profile of 1,35% of the account, which is within our risk profile requirement of not exceeding 1 to 2% of account size. 




2) Using previous day value area to improve trading results

In order to improve the strategy mentioned above, we devised a simple improvement using the value area concept of market profile. The idea is to trade only when the open price lies outside the previous day's value area. The details are as follow:
  • If the open price is above the previous day's value area high, place a long position
  • If the open price is below the previous day's value area long, place a short position. 
  • Sell at the end of the day
For example: if the previous day value range is between i2000 and 2500, we would place a long position if the open value was above 2500, and a short position if the open price was below 2000.

Our analysis showed the values below as optimal for this strategy, based on the 5 years analyzed data. On average, this strategy would generate 178.93$ per month per MES contract invested, with a ROI of 3.58% on a 5000$ account.  



The risk profile for both positions is acceptable, below 1.3%.




Here is an example of stop-loss calculation : 
  • Hypothesis: open price 4060
  • If the open is above previous day VA :
    • Long position on open price: 4060
    • Stop loss : 4060 - 6.25 = 4053.75
    • If not stopped, close position just before the close 
  • Below Previous Day VA : 
    • Short position on open price: 4060
    • Stop loss : 4060 + 10.25 = 4070.25
    • If not stopped, close position just before the close

Conclusion

Even a crude application of market profile theory using only previous day value area shows promise of being 3 times more profitable than just buying a contract at the open. 

More applications of market profile and other optimization ideas will be explored in future articles.



Appendix - Why do we use stop-losses?

A reader asked me the question: Would it be more profitable to not use any stop-loss at all? Intuitively my answer was "of course not", but this is not a fact-based answer, so I ran the numbers. 

It turns out the answer is not as obvious as one would believe.


The approach with stop loss is 30% more profitable than the approach without stop-loss. Nevertheless, the approach without stop-loss seems still very profitable on average.

The problem with the approach without stop-loss is risk management. On average, it is slightly riskier than the approach using stops. But in practice, not using stops causes huge swings in account balance. While using stops limit the risk of taking a position to a fixed amount, for example, 0.15% of the opening price, the approach without risk management can cause a downswing of up to 1 to 2% of the initial position, roughly 4 to 8% of an account balance. Also, the psychological can be devastating. It is very difficult to suffer such big blows in an account without affecting future trades, therefore risking the effect of compounding losses by placing future bad trades because of the cascade effect of big losses.











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