List of Futures Symbols & Profit Potential Calculation

“I've got strengths, and I've got weaknesses. I don't work on my weaknesses. I ignore them, and I cultivate my strengths. The level of achievement that we have at anything is a reflection of how well we were able to focus on it. Because the only thing that's holding you back, is the way you're thinking.” - Steve Vai

Below is a list of commonly traded futures and their DTN IQFEED symbol for both current month and continuous contracts.  I have also added the Interactive Brokers symbol for reference.

Over at TradersHelpDesk.com, they posted an interesting article discussing what a beginning trader can hope to take out of the markets.  In general, there steps were as follows:

1.  Determine the Average True Range for a given set of days for the instrument (they used 254 periods – I chose 100 for the chart below).

2.  Determine 10% of the ATR.  This is (likely) what a beginning trader could pull out of the market as a scalper.

3.  Divide the number by 2 to determine your stop for a ½ risk reward profile.

For example, the S&P 500 E-Mini has had an ATR of about 24 points for the last 100 days. 

Since there are 4 ticks for each point, the profit potential is equal to 24/.25*12.50 for a total profit potential of 1,200 or 96 ticks per contract.

10% of this full profit potential would be $120.  Since we want cannot trade partial ticks, we round up to 10 ticks or $125.  We would set our stop at 5 ticks for a ½ risk reward profile.

How likely is it that we would be successful with a 5 tick stop?  Not very.  But this is a good place to start your testing.  

Narrowing the Knowing-Doing Gap

“We often (or even usually) know what we should be doing in both personal and professional life. We also know why we should be doing it and (often) how to do it. Figuring all that out is not too difficult. What is very hard is actually doing what you know to be good for you in the long-run, in spite of short-run temptations.”

- David H. Maister. Strategy and the Fat Smoker; Doing What's Obvious But Not Easy

The Knowing – Doing Gap

In a recent post entitled “There is a Difference Between Knowing and Doing,” Ivan Hoff describes what he refers to as the “Empathy Gap.”  He defines the Empathy Gap as “the difference between how you believe you will act under certain circumstances and how you actually act when the time comes.”  After giving several examples, he concludes:

Most market participants have incredibly short-term memory. Greed and fear have the power to erase even the most well thought out plan and make the smartest people behave silly.

Ignorance is not the main hurdle. A lot of people have excellent understanding of how market works and what their biases are, but yet very few are able to put that knowledge into practice. It is the difference between knowing how to lose weight and doing it, but 10 times harder. This is why so many successful people are not afraid to share everything they know – the “secret” to their success. Most people will never put the efforts and the time to consistently apply that knowledge in their everyday trading/investing process. It is human nature.

In their 2000 book, The Knowing-Doing Gap, Robert Sutton and Jeffrey Pfeffer set out to define and quantitatively analyze why the gap between what we know we should do and what we actually do exists.  They settled on one truth:

[O]ne of the most important insights from our research is that knowledge that is actually implemented is much more likely to be acquired from learning by doing than from learning by reading, listening, or even thinking. . . . . One of our main recommendations is to engage more frequently in thoughtful action. Spend less time just contemplating and talking about organizational problems. Taking action will generate experience from which you can learn.

Sutton and Pfeffer delve deeply into the matter in the book but also point out one important perspective to keep in mind:  their research revealed that, although some people are inherently better at shortening the gap between knowledge and action, ultimately anyone can do more of what they know they should do regardless of personality, ability or self imposed limitations.

In a recent post, Stephen Dodson notes that:

I think the bigger reason for the disconnect between knowing and doing is human nature. This disparity exists in all areas of human activity. Weight-loss books need only three lines: “Eat better food. Less of it. Exercise more.” That there are thousands of books in the genre, and certain to be thousands more written, is because this knowledge-action gap exists. This is exacerbated by our tendency to justify our actions.

***

People tend to see what they want to see. And they often seem more motivated to be proven right than to understand reality. Bridging the gap between knowledge and action means doing things that are uncomfortable, like changing one’s mind and admitting mistakes. No one is right about everything the first time around. It means analyzing past mistakes, thinking about personal shortcomings. In a 1999 New Yorker article, Malcolm Gladwell interviews Charles Bosk, a sociologist who developed a system to evaluate the differences between unsuccessful surgeons and successful ones. It boiled down to one thing: “He [Bosk] concluded that, far more than technical skills or intelligence, what was necessary for success was… a practical-minded obsession with the possibility and the consequences of failure.”

In summary, for a trader, less emphasis should be placed on figuring out what to do, but rather devising ways to ensure that, compared to others, we actually do more of what we should do.

Examples of the Knowing-Doing Gap

Take a moment and think for a second.  Where can we find examples of the Knowing-Doing Gap?  Here are three:

1.  8 out of 10 dieters fail at losing weight for an extended period of time.  The “knowing” is the diet – the steps people take to lose weight.  The “doing” is the execution of the diet itself for a prolonged period of time.  As one clinician puts it, “Diets don’t fail, people do.”

2.  More than 50% of Americans don’t take prescription medication as instructed.  Knowing is that prescriptions will make you better.  Doing is the actual taking of the prescriptions.  As Seinfeld said, it’s not the taking of the reservation but the holding of the reservation.

3.  When patients were told that they had to make changes to their personal lives – diet, exercise, smoking – only 1 in 7 actually make the change.  The knowing is that lifestyle changes will literally save your life.  The doing is making those changes on a repeated basis.

The point of the examples above is that often times people know what they should do but they don’t do it (for a variety of reasons that will discussed below).  When people don’t diet or take their required medication, they accept the real and substantial possibility of getting sick or dying.  If people will so easily disobey something that may save their life, how easy would it be for a trader to diverge from a rule that has, in his or her mind, a slim possibility of being true in the first place?  Stated otherwise, would it be easier to disobey a doctor’s orders that would save your life or widen a stop on a losing position?  I am going to have to chose the latter. 

The Implications of the Knowing-Doing Gap

“The problem is the inability to close the gap between what we genuinely, even passionately, want and what we are actually able to do.” 

-  Kegan, Robert; Lahey, Lisa. Immunity to Change: How to Overcome It and Unlock the Potential in Yourself and Your Organization.

If we are to accept that most traders know what they SHOULD do but don’t do it because of certain limitations, then the next step is to identify each trader’s Knowing – Doing gap and identify ways to overcome this.  To do this, we must first understand the function that prevents us from doing what we should do. 

In the Immunity to Change book, they put it this way:

When we experience the world as “too complex” we are not just experiencing the complexity of the world. We are experiencing a mismatch between the world’s complexity and our own at this moment. There are only two logical ways to mend this mismatch—reduce the world’s complexity or increase our own.

To put it in a trader’s perspective, the market will never be less complex (arguably, it is getting more complex day by day).  The only solution is increase our own mental complexity. 

Any time you experience a resistance to implement a change, it is likely because of a deep-seated and hidden emotion – or a hidden commitment - that is holding you back and protecting you from what you perceive as harm.  Kegan and Lahey describe this as “one foot on the gas and one foot on the brake.”  You may want to execute your trade plan perfectly but you actually have a hidden commitment that is holding you back that, in your mind, is “protecting” you from the outcome you don’t want to experience.

Some of these hidden emotions/commitments that hold you back (unknowingly to the conscious mind) from doing what you should be doing are:

1.  Excuses

2.  Fear

3.  Greed

4.  Need to be Right

5.  Apathy or Laziness

6.  Procrastination

7.  Lack of Discipline

8.  Lack of Vision

9.  Victimization

10.  Self Sabotage

11.  Unrealistic Expectations

12.  Self Doubt

13.  Need to Control the Situation

14.  Approval Seeking/Worrying About What Others Think

The reason that you aren’t doing what you should be doing as a trader is because:

1.  You develop our own inner map of reality and the markets.

2.  You interpret the world (and markets) through this inner map based on your current level of mental complexity.

3.   In accordance with this inner map we have our own inner commitments to our own personal priorities (such as one of the 14 above).

4.  These inner hidden commitments have a high priority and will over-ride any counter intentions that conflict with them

5.  The high priority is assigned because the hidden commitment is inextricably linked to an inner hidden perception of our own physical, psychological, social or emotional safety.

6.  This hidden commitment is (nearly always) outside of our conscious awareness

Steps to Shrink the Knowing-Doing Gap

Kegan and Lahey point to 4 steps to create lasting change:

Step 1

-  Identify a commitment that is important and insufficiently accomplished.

For instance, a losing trader might say, “I am committed to taking every single trade that my system gives me without hesitation.”

Step 2

-  What are you doing or not doing that is keeping you from the commitment.

“Sometimes, I will not take a trade that my system is giving me because I hesitate to execute an entry or exit signal.”

Step 3

-  Identify competing commitments by imagining what it would be like to do the exact opposite of the behaviors listed in Step 2.

“I am committed to controlling the outcome of that specific trade.  I am fearful that I will exit a trade to early, take a loss or miss out on a big move in my direction.”

Step 4

-  Identify the big assumption that is underlying our competing commitment.

“I assume that if I can’t control the outcome of a specific trade, then people will know that I am not very smart and that trading was a big waste of time.  I assume that if I courageously take every signal an exit a trade to early or miss out on a big move, then I won’t make enough money to support my family or be proven a failure in other people’s eyes.”

Step 5

-  Step 5 talks about moving forward, by becoming aware of the big assumption and testing it out in the real world:

-  Observe the big assumption in action.

-  Stay alert to challenge the big assumption.

-  Design a test of our big assumption.

-  Run the test and discuss the data openly

Take the first trade entry and exit signal of the day (in a smaller size than normal) and wait for your feelings in Step 4 to come to the surface.

When you have those feelings, challenge them:  “I don’t need to know what will happen next to be a good trader or to be considered a smart person.  My preparation has helped me get to this point and was not a waste of time.”

For a more detailed approach to these steps, check here.

Conclusion

If the smartest, richest most successful trader walked up to you tomorrow and gave you a winning trading system, would you execute it perfectly?  Probably not.  Every trader has a knowing-doing gap.  Stop focusing so much on the technical changes and more on the adaptive changes. 

Keep ya mind right.

Using Volume Indicators and an Example Trade

“Sorrow is the mere rust of the soul.  Activity will cleanse and brighten it.” – Samuel Johnson.

Definitions:

Volume – number of shares exchanged in an instrument between buyers and sellers during a given time period.

Delta – difference between the volume transacted at the market’s ask price versus the volume transacted at the market’s bid price during a given time period. 

Uptick Volume – The number of shares traded when the price is increasing.  The term "tick" refers to a change in a stock's price from one trade to the next. Really what's going on is that a comparison is made between trades reported on the ticker. If the later trade is at a higher price than the earlier trade, that trade is known as an "uptick" trade because the price went up.

Downtick Volume – The number of shares traded when the price is decreasing.  If the later trade is at a lower price than the earlier trade, that trade is known as a "downtick" trade because the price went down.

Remember for a second that we are in the supply and demand business.  Other traders either (1) really think the security is a bargain at a given price and buy or (2) really think that the security is overvalued at a given price and sell.  This is obviously an oversimplification but will work for our purposes.

Indicators For Volume

Volume Histogram – Simply a histogram showing the volume (total transactions between buyers and sellers in a given time period).

Cumulative Delta - Delta accumulated throughout the day and expressed as “Cumulative Delta” or CD.  Generally, CD will stay at or near the zero line during range bound days and stay solidly positive or negative on trending days.

For a good starting post for cumulative delta, check out this Traderfeed post.  For an in-depth review of cumulative delta, look here.

Cumulative Uptick/Downtick – This is similar to cumulative delta.  First, take the difference in the uptick versus the downtick during a given time period.  Then accumulate this from the beginning of the session.

NYSE TICK Indicator - TICK measures the number of NYSE stocks trading on upticks minus the number trading at on downticks. This captures the short-term sentiment of traders, as they either aggressively lift offers across stocks or hit bids.  It is similar to Delta in that it measures short-term sentiment of aggressive buyers and sellers.

Traderfeed had a great post about the use of a moving average in NYSE tick:

In a rising trend, we'll see successive peaks in the moving average of the TICK correspond to higher price highs in the index over time. In a falling market, we'll see lower price lows with each fresh valley in the TICK. In range markets, we'll see new peaks and valleys in the moving average of the TICK fail to bring either new price highs or lows.

***

A moving average of TICK thus can be thought of as a kind of overbought/oversold index of sentiment. Some of the best selling opportunities occur at TICK moving average peaks that fail to make fresh price highs; some of the best buying opportunities occur at TICK moving average valleys that cannot generate new price lows.

Using Volume Indicators to Enter and Exit Positions

One of the most basic ways to use the Volume Histogram is to look for divergences.  Put simply, a divergence is a difference between price and the underlying indicator.

A bullish divergence would be lower lows in price combine with higher highs in volume.

A bearish divergence would be higher highs in price and lower lows in volume.

Traders Help Desk offers this simple take on volume divergence.  A quick rundown:

1.  Determine whether we are in an uptrend or downtrend.

2.  In an uptrend (price is making higher highs and higher lows), for each subsequent high in price, is volume higher or lower?  If lower volume on higher highs and higher lows in price, you have bearish divergence.  If higher volume, you have a new measuring stick.

3.  In a downtrend (price is making lower lows and lower highs), for each subsequent low in price, is volume higher or lower?  If lower volume on lower highs and lower lows in price, you have bullish divergence.  If higher volume, again you have a new measuring stick.

Exiting a Position on Volume Histogram Divergence

For now, take a look at the ES chart below – it is a four point range bar with the volume histogram shown below.  It also has a 33EMA in green and a 99EMA in red overlaying the chart.  Say you took the entry on the open of the green bar marked with a blue arrow and have determined that we are in a short uptrend based on the short 33EMA being above the longer 99EMA.

1.  For 6 bars, you have higher highs and higher lows on higher volume. No divergence here because volume is tracking price action.

2.  On the 7^th bar, you see price make a lower high BUT we have lower volume to coincide with this.  Because we are in what we define as an uptrend, then we are looking for bullish divergence (price making higher highs and higher lows on lower volume). 

3.  From the 7^th through the 12^th bar, price is making higher highs and higher lows on increasing volume.  Again, no divergence.

4.  On the 13^th bar, we see a higher high and higher low on lower volume.  AHA!  This is what we are looking for.  This would be a good clue to exit sometime on the 14^th bar – when volume continued lower from the 12^th bar, it was a clear sign to get out on the 14^th or at least the 15^th bar.  You can also see price is far away from the 33EMA on the 13^th bar which is a good clue that it will probably start retracing to the 33 EMA (which is what it did).

CHART 1

From a risk perspective, you would enter on the first bar (blue arrow).  If you were long two contracts, you could set your stop somewhere near the 99 EMA (that would show you were clearly wrong about the trend).

Enter:               2 Contracts Long @ 1378.

Stop Loss:        1376.50.

Risk:                1.5 points X 2 = $75 X 2 = $150

If you exited the first contract on the 7^th bar (say at the low), you would have made 1.5 points or $75 on your first contract.  Then move your stop to 1378.50 which is near the 33EMA or breakeven plus 2 ticks.  You are now risk free on your remaining contract.

Exiting your remaining contract on the low of the 14^th bar (where we have clear confirmation of bullish divergence) at 1381.5.  This would have been a 3.5 point gain or $175.  Total gain on both contracts was $225 with an initial risk of $150 or a 1.5 reward to risk ratio.  If you had held both contracts until the bullish divergence at the 14^th bar (and probably moved your stop to 1387.50 on the 7^th bar) you would have made $350 with an initial risk of $150 for a 2.33 reward to risk profile. 

At a 1.5 RR profile, you need a 40% winning percentage for a positive expectancy trading system.

At a 2.33 RR profile, you need about a 30% winning percentage.

More on the other volume indicators to come. 

Keep ya mind right.

Win/Loss Ratio and Winning Percentage: Benchmarks when Designing a Trading System

“You never change things by fighting the existing reality, to change something, build a new model that makes the existing model obsolete.” - Buckminster Fuller.

Having certain benchmarks to attain when designing a trading system are important because they help steer you in the right direction when you come to a sticking point in designing a profitable trading system.  Instead of saying “I want to earn $X per day” or not having a goal at all, focus on 3 important functions:

Win/Loss Ratio (W/L) = Avg Win/Avg Loss

Winning Percentage (WP) = No. Profitable Trades / Total Number of Trades

Expectancy = (Avg Win * WP) – (Avg Loss * (1 – WP)

These three factors can be used to construct the basis for a profitable trading system.

Assume for a second that you have $10,000 of initial capital to fund your account.  A general rule you hear is that you need a system with a W/L ratio of 2 (your average win is 2 times greater than your average loss) and a winning percentage of 40% (out of 100 trades, you will have 40 profitable trades and 60 un-profitable trades or losers).  If you take 400 trades using this system, what will your Expectancy and ending account balance be?

Expectancy = ((W/L + 1) * WP) – 1 = (( 2 + 1 ) * .4 ) - 1 = 0.2

After 400 trades, your account has grown to $18,000.

But what if you know your Win/Loss ratio and want to tweak your system’s Winning Percentage so that you have a positive Expectancy system?  The table below shows you the minimum Winning Percentage to have a positive Expectancy system (an Expectancy at least equal to 0).

Win/Loss Ratio	Min WP to Have Positive Expectancy
0.25	80.00%
0.5	66.67%
0.75	57.14%
1	50.00%
1.25	44.44%
1.5	40.00%
1.75	36.36%
2	33.33%
2.25	30.77%
2.5	28.57%
2.75	26.67%
3	25.00%

For example, if you have a W/L ratio equal to 2, your WP must be equal to 33.33% to have a positive expectancy system. 

The formula to find the minimum WP for a positive expectancy system is:

Min WP = 1 / (W/L + 1).

The Chart below breaks this formula down by some common W/L ratios:

This is a useful exercise because it can immediately identify the weakness in your system.  If your system isn’t performing, either increase your WP or your W/L ratio.  This can usually be achieved by changing your exits:  increasing the profit target or adjusting your trailing or indicator stop (like an ATR stop).  More on exits later.

Say you know your W/L ratio and want to determine the WP required to have a known Expectancy.  For example, assume you want a system with an Expectancy of 0.5 and you have a W/L ratio of 1.0 – what is the required WP?  You can use the chart below:

Looking at the red line, you see you need a WP of 75% to have an Expectancy of 0.5 for a system with a W/L ratio of 1.0.

Or you can use the formula above to solve for the required Expectancy.

Expectancy = ( ( W/L + 1) * WP ) – 1

0.5 = ( ( 1 + 1) * WP ) – 1

Solving for WP shows that you need a WP equal to 75%.

Keep ya mind right and happy trading.

How Can I Blow Out My Account? - Projecting the Maximum Number of Consecutive Losses

“Everyone has a plan til they get punched in the mouth.” – Mike Tyson

Summary

1.  Calculating the maximum number of losers we can sustain before our account drops below a certain minimum is instructive to determine our margin of safety for a trading system.

2.  Risk on a given trade can be loosely defined as your stop loss less any commission and slippage.

3.  We calculate the maximum number of losers our initial account balance can sustain by defining risk in 2 separate ways:

-  Risk on a given trade is equal to a set percentage of our remaining account balance

-  Risk on a given trade is equal to a certain number of ticks per trade

4.  By using a fixed number of ticks per trade as our risk, we calculate the maximum number of losers before our risk exceeds 1% of our remaining account balance.

CALCULATING THE MAXIMUM NUMBER OF LOSERS IN A ROW USING A SET AMOUNT OF RISK DEFINED AS A PERCENTAGE OF ACCOUNT PER TRADE

I was reading an article over on the TradersHelpDesk.com that was discussing risk management.  The premise was:  “if you risked 2% of your account balance on any 1 trade, how many losing trades in a row could you sustain before you blew out your account?”  Their answer was 170 trades.  You can check out the article here.

So I decided to map it out.  Assuming you had a $10,000 account, how many losing trades could you take IN A ROW before you blow out your account?  I modeled out the amount at risk (which can be loosely defined as your stop loss plus commissions and slippage) from 1% to 10%.  This was a bit of a challenge because each account never really goes to zero in this scenario.  Since you are only risking a set amount of the remaining account size after the loss, the account just approaches zero.  For instance, if your risk is 1% and you have an initial account size of $100, you risk $1 and lose then your remaining balance is $99.  You risk 1% again or $.99 and lose then your remaining balance is $98.01.  This can go on to infinity with the account never getting to zero.

But for practical purposes, we can assume that an account is totally “blown out” when the balance gets below $100.  So for different sets of risk on each trade, how many losses in a row can you sustain?

Interpreting the chart, you could have 458 losers in a row if you risk 1% of your remaining account balance on each trade before your account drops below $100.  You could have 227 losers in a row before your account drops below $100 if you risk 2% of your remaining account balance.  This exercise is important not to show you how long you can trade before you lose it all but to show you the importance of sizing your positions.  In the example above, you can take two times as many trades by risking just 1% of your account versus risking 2% of your account on each trade.  This will keep you in the game a lot longer.

From a practical perspective, if you are trading futures or have a margin to satisfy, your account balance cannot drop below a certain level before your broker pulls the plug.  What if we were to assume that an account of $10,000 cannot drop below $5,000.  How many losing trades in a row can we have then?

Again, you can see the 2:1 relationship between risking 1% of your $10,000 account and 2% of your $10,000 account.  For futures traders, risking 1% on a single E-Mini contract means that you are risking $100 or 2 points or 8 ticks.  And this doesn’t include commissions or slippage.  If you are thinking of risking more than 1% on any trade, you need to think long and hard if you only have a $10,000 account.  You can drop below the $5,000 minimum very quickly.  Scary to think that some brokers have a $500 daily minimum account balance for futures.

CALCULATING THE MAXIMUM NUMBER OF LOSERS IN A ROW DEFINING RISK AS A SET AMOUNT OF TICKS PER TRADE

One more point on the E-Mini – because tick sizes are $12.50, it is hard to dial in your risk at exactly 1%.  For example, if you have the $10,000 account, risk 1% and lose, then in our example above, you should only be risking 1% of your remaining account balance of $9,900 or $99.  With a tick size of $12.50, it is not possible to risk exactly $99.  You have three choices at this point (other than starting with an account bigger than $10,000):

1.  Add $100 of your own cash back to the account to get it to $10,000.

2.  Risk less than 1% - say 7 ticks or $87.50.

3.  Risk more than 1%.

A good exercise with this risk model (to keep you within the safety margin of 1%) is to look at how many trades you can have go against you in a row based on a certain tick size.  We can ask two questions then:

1.  How many losers in a row can you have before your account drops below a certain minimum if we are risking X number of ticks on any given trade?

We see that with a stop loss of 6 ticks, our $10,000 account can sustain 66 losers in a row before the account drops below $5,000.  Our account can only sustain 49 losers in a row if we adjust the tick size to 8 ticks or $100 per contract of risk on the E-Mini.

2.  If you are risking X number of ticks on any given trade, how many losers in a row can you have before the risk on any given trade exceeds 1% of your remaining account balance?

This one is an eye opener.  You can’t forget when you are trading with futures the effect that leveraging has on your account.  For the chart above, if we start with $10,000, and we risk 1 tick on each trade (not likely), then we can have 701 losers in a row before our next trade would have a risk greater than 1% of our remaining account balance.  On our 702^nd losing trade risking 1 tick (or $12.50) our remaining account balance is $1225 therefore our risk is $12.50/$1225 which is greater than 1%.

 A more likely scenario is that we risk at least 6 ticks on the trade, which gives us 34 losing trades in a row before we have a risk on our remaining account balance of greater than 1%. On our 35^th losing trade risking 6 ticks (or $75.00) our remaining account balance is $7450 therefore our risk is $75.00/$7450 which is greater than 1%.

The likely answer to this problem is to up the size of our initial account.  It is more likely, considering slippage and commissions, that our risk on a given trade will exceed 6 ticks.  What if we started with an account balance of $20,000?

This is a little better.  If our risk per trade is 6 ticks, then we can have 167 losers in a row before the next trade has a risk that is greater than 1% of our remaining account balance.  If we did have 167 losers in a row, then our remaining account balance would be $7475 (167 Losers X $75 Risk Per Trade = Loss of $12,525).  Our risk on the 168^th trade would be defined as $75/$7475 so our risk would be greater than 1%.

SUMMARY

The point of this exercise is to keep you in the game.  We can’t predict how many losing trades we are going to have in a row.  We can control our risk every time we put on a trade though. As a new trader, you have to give yourself a margin of comfort.  Ask yourself, is it likely that I will have X number of losers in a row?  If I did, how long could I trade my account?  The charts above should help you out as a starting point.