Reason 8 for Using Stock Metadata

Reason 8 for using stock metadata statistics is to learn how to take advantage of clues found to trade long positions in the market.

Reason 8 continues with a controversial stock market topic, the use of stock metadata and its role in trying to time stock market trades.

There are a number of techniques that people use to try and time their stock market trades. Simply put, they try to buy low and sell high. Still others try to take advantage of the fluctuations in the price of the stock by day trading often and making some repeated small but quick profits.

Regardless of which group you belong to, in order to be successful at making any stock market profits, an effective trading strategy is a must.

For those that look to making multiple smaller profits in the market as opposed to one big killing, here’s a strategy that needs to be considered.

It involves using stock metadata. To work it requires the monitoring of the three following pieces of information about a stock’s price:

• Current low price of the stock
• Previous low price of the stock
• Current high price of the stock

For reason 8, references will be made to the following metadata report:

• 15-Minute-Metadata-Detail report as illustrated in figure 8a below
  Click Here for a detailed description of the report layout
  Click Here to see this report with Ford Motor Company data

We will use the following modified screen extract from this report to explain the strategy used for executing a trade based on metadata.

You might find it easier to follow the explanations given by having your own copy of these files populated with the exact same stock price data.
Click here to get them. You can also save yourself a lot of effort by using these files later on as templates for creating your own metadata reports.

This day trading strategy involves following the status of the low price of the stock. A buy signal is given when the current low price is less than the lowest price of the previous 15-minute time period.

As shown in the example above, during the 12:45:00 to 12:59:59 time period, the price of Ford shares fell below the previous price of 7.52 and continued down to 7.47.

If the stock was subsequently sold either during the same period it was bought or during the current 15-minute time period (13:00:00 to 13:14:59), it’s very possible that these shares could have been sold at a modest profit.

In order to make a profit, the best case scenario would have been that the stock was acquired at close to the previous lowest price of 7.47 and then sold at a higher price, somewhere close to the current highest price of 7.59 for a $0.12 profit per share.

This example assumes that the trade is for a block of 1,000 with a total of $20 in brokerage fees. Therefore, 1,000 shares multiplied by the per share profit of $0.12 (7.59 -7.47) minus the $20 commission fee would equal a potential profit of $100.

The most optimistic scenario when using stock metadata would be executing this type of strategy whenever it was presented. Using the all possible transactions in figure 8a above, the best case scenario would translate into a potential cumulative profit of $770 for the day.

This would occur by only day trading 1,000 shares on the eleven occasions when the buy signal criteria were presented. And to ensure the maximum profit, the shares had to be bought at the lowest price and then sold at the highest price.

From reviewing reason 8, we all know that when day trading, the chances of buying the shares at the lowest previous price and then selling at the highest price of the current period would not be realistic. But something in between is possible.

Furthermore, traders that use this type of strategy would typically do so with a larger number of shares in order to make a reasonable profit per trade for the day.

Of course the other option exists to execute a trade every 15 minutes by buying the stock at its low for the previous period and selling it at its high for the current period. The potential maximum profit for the day could reach $1,690 as previous shown in figure 8a above.

For this to have happened would mean that starting during the 9:30:00 to 9:44:59 time period and for each of the subsequent 15-minute time periods that shares can be traded, shares of Ford would have had to be bought at their lowest price during the current time period and then sold at the highest price during the next time period.

The use of this day trading strategy for one of the time periods is illustrated in figure 8b above. We can see that Ford shares were acquired during the 10:15:00 to 10:29:59 time period and then subsequently sold during the 10:30:00 to 10:44:59 time period. The potential profit from executing this transaction for 1,000 shares would have been $130.

But let’s be realistic – we all know that the chances of repeatedly doing this would be impossible. Nonetheless, it may be possible to make at least one profitable trade during the day.

So now here’s the question that everyone is asking:

“Is this strategy in reason 8 one that works 100% of the time?”

The answer is a qualified “Certainly not 100% of the time”. There are related factors that also have to be considered. For example, traders have to consider the overall direction of the market for the day, any good news or bad news announcement that would affect the price of the stock, and so on.

The key point to remember is that all market influences need to be considered before making any trade. Metadata is that extra piece of information that allows you to make an informed day trading decision.

We have now completed the review of reason 8 for using stock metadata when day trading. Let’s continue with reason 9:
Using metadata statistics with more clues on how to time the market for trading short positions

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