Market Profile and Context

The courses taught today on the traditional Market Profile focus on the bell curve, ‘the Profile’, with little comment on the other aspects.

Peter Steidlmayer taught that there were 5 elements to his traditional approach:

  • Long-term Perspective,
  • Long Term Activity Charts (LTAC),
  • Market Structure,
  • Market Timing and
  • Trade Location.

Each element played its part bringing a trade to a successful conclusion. And although this was not expressly taught, I took the view that Long-Term Perspective and LTAC provided ‘the context’ to Peter’s approach. Nowadays ‘context’ in the Market Profile is provided by the longer-term distributions; but I still find Peter’s way of classifying fundamental events useful.

There are three types of events:

a) Expected events when fundamentals are correctly perceived by the market and as a result, we have range bound markets. In range bound markets we buy the low end of the range (what I call the Primary Buy Zone) and sell the upper end (the Primary Sell Zone)

b) A surprise event which are an ‘act of God’, an event totally unexpected by the market. In such as situation, price moves away from value and then returns to value. Chernobyl (April 26 1986) was such an example. Following a muted response to the disaster on April 28, the S&P fell from 243.55 to 232.25 over 13 trading days. Six days after the low, the S&Ps were trading at 244.75. In such a situation, the strategy is to take a position on the basis that price will return to their original levels.

c) An ‘unexpected event’ where the market fails to recognize a shift in the fundamentals; a shift that signals a move by value away from price. In short, an event that will change the longer-term trend of the market. (In my jargon a change of trend of at least quarterly trend proportions).

I believe that an ‘unexpected’ event occurred in August 2007 when the major Western Central Banks poured liquidity into their respective economies’. We are talking billions of dollars over a very short time. Usually we’ll begin to see reflected in the economy, the effects of excess money reflected within six to nine months time: in this case, say from March 2008 onwards. In other words, inflation figures will start rise. The FEDS will then find themselves between a rock and a hard place (of their own making). The Weekly Leading Indicator published by the Economic Research Institute (http://www.businesscycle.com) shows that the US economy is set to slow down in the months ahead.

So the FEDS will have a climbing inflation with a weak economy and Bernanke is reported to shifting towards an inflation targeting system. Given their charter and stated policy, the probability is the FEDS will have to raise rates. In turn this will have an adverse effect on the US economy and US Stock Market.

Now let’s add another spark to the potential firestorm.

China‘s inflation is said to be running at the highest level in a decade (Financial Times 11-16-2007). So far the half-hearted attempts to stem the rise have done little to alleviate the problem. When the Government starts to take strong measures their stock market will turn down. In addition a slowing US economy will have a severe impact on the Chinese. ‘China‘ central bank estimates that every 1% drop in the US economic growth translates into a 6% fall in Chinese exports (FT 11-16-2007)’. Exports now account for 33% of the Chinese economic growth. So a slump in the US economy will impact the Chinese, and a slowdown in both countries, the rest of S-E Asia.

I see these facts as painting an ‘unexpected event’ portrait for a US stock market downturn. The probability is set to begin from the time the US inflation figures start to rise – this clear and present danger to be present from March 2008 onwards.

Now don’t get me wrong. I am a technical trader and the timing of short entries (if any) will be based on my chart patterns. But my best trades have been when I identified a story not yet heard by other traders e.g. at the ADUS secondary bottom in about September/October 2001.

If this scenario proves correct, we’ll have the usual seasonal strength in 2007 with new highs into March 2008 onwards. From that month onwards, I’ll be looking for evidence of the onset of a downtrend of at least 13-w proportions (i.e. trends in the quarterly time frame).

Managing A Trade

I am going to depart from planned content. I was going to comment on ‘Context and the Market Profile’. Instead I’ll continue with the current thread and write on managing the ES trade.

In The Expectancy of a Trade and Your Trading PIan I argued that the we had total control only over our entries and exits. In the Role of Intuition and Barros Swings – How to Use Them, we saw how the comment applied to the ES’s entry. I determine the size of my position both on the number of contracts I take and the amount of capital I am willing to risk. These are determined by a subjective assessment of the probability of exiting without loss. The risk I am willing to take ranged from 0.5% to 4%. In this case I was willing to risk 1% and take say, 6 contracts (the amount of contracts is for illustrative purposed only)

I found that because of the large stop (below 1535), 6 contracts would have cost me 2%. So I took only 3 at 1539.25. I wanted to add another 3 contracts on a breakout that conformed to my ideal breakout pattern. I treated this as a new pyramid trade. I could have added 6 and risked another 1% because I treat each entry as a separate trade. To prevent overtrading, I do have a maximum portfolio risk.

Although I could have added more than 6 contracts on the breakout – the breakout setup raised the probability of success and hence increased the risk and number of contracts – in this context I had decided to keep to 3. I had 1st resistance at 1496 and last night when the market stalled after reaching 1496, I had a dilemma. If I used the Rule of 3 and exited one third of my position size, I would not break even on the remaining open positions.

If I exited half my position size (the ones taken at 1469), then my risk per contract dropped to 10 points. So I exited half at 1488.5 and held half with stops below 1538.

Today with the CPI due, I decided to raise my stops on half my remaining positions to 1544 and keep the rest below 1538. I then had to work out if I should exit the remaining positions or let the stop take me out.

The inputs were:

a) I had no feel for the CPI figures so I rated the bear and bull response at 50%

b) If bearish, there was a 10% chance of no stops being hit, a 90% of the first stop at 1544 being hit and a 40% chance of the stops below 1538 being hit.

I then worked out the results in points for each secnario and placed the information in a Decision Tree Spreadsheet. Figure 1 shows the results. In this case, given the inputed data, the probabilities favoured letting the stops be hit.

Decision Tree

FIGURE 1 Decision Tree

As an aside, even if I moved all my stops to 1544 (90% of being hit), the matrix still favoured holding the position into the CPI. If I moved them all to below 1538, the matrix still favoured holding the position into the CPI. Based on this, I have reveresed my earlier decision and now my stops are below 1538.

TheMatrix worked out that only probabilities of 96% and above would favour exiting immediately. This would be true even I exited no higher than 1454. I have assessed that for that to happen we would need a headline rate of greater than 4% and a core rate greater than 2%. If the CPI numbers are that bearish, I’ll exit immediately.

The Decision Tree I use is sold by Palisade Tools. You can download a free copy of a Decision Tree matrix from www.visionarytools.com. If all you are after is a decision tree software, then use this. The only drawback with the permanent evaluation copy is you cannot save your work. To overcome this, all you need do is grab a snapshot before exiting.

So let’s stop back and suumarise this post:

a) We adjusted position size to allow for the larger than normal stop.

b) We took addtional positions based on new information,

c) We exited part positions when the market stalled at first resistance

d) We performed a Decision Tree analysis ahead of the CPI and

e) That Decision Tree analysis included a scenario where the CPI exceeded the upper boundaries of the expected range for tonight (bearish scenario).

By the way, the Decision Tree analysis did not stop there. I also did an analysis of what I would do if the lower boundaries (bullish scenario) are exceeded.

The Relative Importance of Your Trading Tools

I was referred to Brett Steenbarger’s blog of Nov 14 ( http://traderfeed.blogspot.com/) . As I read, it struck me that the tools we use in our trading plans are of less importance than having a plan.

Brett’s approach to the markets is very different to mine. He is a short-term trader and to gain his edge, he uses internals backed by statistical testing. I have had the honour and pleasure of meeting Brett and would say that his tools suit his personality.

I too use statistical testing but because I process sensory information visually {and to a much lesser extent kinesthetically (through feelings)}, I use tools that suit my personality: Barros Swings, the Ray Wave and the Market Profile are all used as visual mediums.

A fab example of this difference was Brett’s use of the volume at the bid (as the market moved down) as a target for identifying the end of the move up. I never thought of using volume that way. Incidentally, I also subscribe to Market Delta but what I find important is the shape of the profile at support and resistance areas.

Again last night provided an interesting example.

As you know from my blog, I went long early with a position that was half normal size. I then decided to use the breakout of the 1st hour’s opening range to enter the market for my remaining positions. But, the 30 minute volume profile on the 1st breakout (at 11:30) took the form of a bell curve. This suggested that the market would rotate back into the range and it did, all the way back from 1466 to 1459.

At 13:30 the market took out 1466 but this time the volume profile for the period took the form of a one-timeframe (trending) market. Sure I got filled 3 points worse off, 1469 rather than 1466 but I had an easy exit strategy if I was wrong about the breakout. A failed breakout with one-timeframe characteristics is likely to attempt a move in the opposite direction. This meant I could place my stops at 1457 under the start of the distribution (1459). This exit strategy was unavailable to me if the breakout took the form of a bell curve since that shape said that the probabilities favoured a rotation back into the opening range.

Score another important lesson for Pete Steidlmayer: it’s not the breakout price that is important. What is critical is how the market reaches the price (e.g. the form the breakout takes) and what the market does after reaching the price.

So, you’re probably asking what’s the central point of this posting.

It’s a simple one.

Newbies worry about some secret whiz bang, never fail, tool that will bring them untold riches. But such a tool does not exist. What is more important than the non-existent, never fail tool, is to find a tool or tools that match our personality. Unless we do that, we are likely to second guess our signals; such second guessing will lead to the slippery road of breach of discipline. So, rather than engage in a fruitless search for a non-existent super tool, focus instead on understanding your personality and find the tools that mesh with it.

Barros Swings – How to Use Them?

I have received mail from purchasers of Nature of Trends (Wiley Edition) asking how to use Barros Swings. In fact a large section of the book deals with that topic. In addition, the Appendix shows you how to construct the swings. So, in this post, I’ll only briefly summarise the uses for the Swings

But first let’s outline the problem.

Figure 1 shows a downtrend….Are you sure?

Figure 1 Uses of Barros Swings

FIGURE 1 Uses of Barros Swings

Let’s take a look at Figure 2. Notice that we have at “A” and at “B” higher highs and higher lows.

Aren’t downtrends supposed to have lower lows and lower highs? But since we have higher highs and higher lows, don’t we have  an uptrend? Yet we intuitively say we have a downtrend, don’t we?

FIGURE 2 Possible Uptrend

FIGURE 2: Is this an Uptrend?

This then leads to the first use of the Barros Swing: to identify the trend of a timeframe. Let’s turn to Figure 3 and the solution to the above problem.

Figure 3 shows that each time the 13-w corrects, the 4-week trends up i.e. forms at least a higher high and higher low. In other words, whenever a timeframe corrects, we can usually expect the First Lower Timeframe to try to change its trend. (In this blog, I am using the 4-week as a substitute for the 18-day).

Identifying the Trend of a Timefram using Barros Swings 

FIGURE 3: 13-w and 4-w swings

In addition to identifying the trend, Barros Swings identify the support and resistance areas of a time frame. In Figure (3), for example,  the highs and lows of the blue swings are the 13-w critical support and resistance points; the red swings are the equivalent of the monthly trend and its swing highs and lows identify the monthly support and resistance levels.

The final function of the swings is to identify the patterns that warn of a change in trend.

Yesterday, for example, we spoke about an Upthrust, a pattern that identifies changes of trend from up to down. The swings not only disclose the pattern, they also identify the time frame that is changing its trend.

By knowing that a swing size is changing its trend, we know that the first higher timeframe will probably have a change of line direction.

In Figure 4, we have the monthly S&P (cash). If the Green Line is going to turn down,  its minimum target is 1340.45, the price at which the green line will turn down; of course the 12-m may be making a double-top in which case we can expect a retest of the 800 area.

S&P Cash 12M

FIGURE 4: Double Top?

Well folks, that about covers it: in this post I have covered a short summary of the uses of Barros Swings.

Context – How It Improves Profits

Two important ideas I learned from Peter Steidlmayer:

  1. The use of different timeframes in my trading and
  2. The idea of ‘context’.

As a discretionary trader using technical analysis, ‘context’ has made a great difference to my bottom line. Before I explain what I mean, let me first define some critical terms:

  • By discretionary I mean I have a set of rules that I usually follow; but I also have a rule that says “I don’t have to follow my rules”. I have this rule so I have room for my intuition to come into play – especially when exiting. Thirty (30) years of trading means my subconscious sees patterns that my conscious mind fails to see. The trick is to know when intuition rather than my ‘rat brain’ is in control.
  • By Technical Analysis I mean the use of charts to identify who is in control of the markets, the bulls or the bears, and whether that control likely to continue or end.

I place great store in ‘context’; it’s the filter by which I judge my setups – the patterns that tell me when the probabilities favour a trade. I do test and validate my setups through computer backtesting. I start with the raw idea and if that proves statistically that the setup is robust, I test it real-time with small size. If that proves successful, then I test it within a context. Only when the setup passes that gate do I employ it in my plan.

Let me show you what I mean by reference to the current cash S&P.

I use a pattern called a Change in Trend called an Upthrust (see Nature of Trends, page 38). It is one of my favourites and one of the patterns that has a $win expectancy ($2.87). When you consider that the average historical upper end of expectancy is 2.33:1, you see how profitable the pattern is for me.

The 13w chart below shows a classical Upthrust. Normally I would have sold double size and would have been looking for a move to at least the area bounded by the Blue Horizontal Lines and probably a breach of B followed by a subsequent trend down. I’d also normally have followed the trade management process I call the Rule of 3: I would have covered only two-thirds of my open positions after the market reached the blue lines. One-third of my position size I’d have left open because it would be the start of the positions I start to pyramid in anticipation of the expected downtrend.

Upthrust 13w S&P

13-Week S&P

But in this case, I sold ‘normal size’ and have covered half my size at first support reached on Friday. I also plan to cover the rest either at the zone bounded by the blue lines in the chart above or on a buy signal generated around Friday’s zone.

The reason for this is the ‘context’ that is partially provided by the Ray Wave: because of the nature of Wave [2], I was looking for a one of 2 patterns for Wave [4]: Running or Sideways. The market accepted below the maximum Running Zone on Friday Nov 9; that being the case, I would expect the market to go to the zone bounded by the blue lines. If the market breaches B, then we have the first sign that the current bull market is in difficulties and if we get acceptance below ‘B”, this would confirm the 13w Change in Trend Upthrust signal.

13w Ray Wave Count

13-week Ray Wave Count

(By the way, a Ray Wave count is not an Elliott count although I have borrowed some of Elliott’s ideas).

Context then in this case, caused me to hold a smaller than normal size and has me looking for a buy around the 1400 – 1370 area. Can I be wrong about the context? Sure, but my results say I can also be right and I am happy to give context its due.

Zones

Once we have identified the trend identification of your timeframe, we have your strategy. The next event is for us to identify a low risk entry. I see low risk entry comprised of three factors:

  • Zone

  • Setups

  • Entry and Initial Stop (and/or exit strategy)

Our zone will be a function of whether we are taking a breakout trade or looking to trade responsively (buy on dips in an uptrend, sell on rallies in a downtrend). Here the Barros Swings again play an important role. Breakout zones are the important highs and lows created by your timeframe e.g. the Turtles would buy a breakout above the highest high of the past 20 days and would sell the breakdown of the lowest low of the past 20 days. The problem with this definition is the ‘breakout or breakdown’ zones may not represent critical resistance or support zones.

Figure 1 is a good example of what I mean.

FIGURE 1 AUDUSD 1-m Swings

FIGURE 1 AUDUSD 1-m Swings

(Click on Thumbnail for Full View. Click again for clarity)

Figure 1 shows a 1-period monthly swing (the equivalent of an 18-d swing). I used a 1-m swing for the sake of clarity. Notice that after a prolonged uptrend (Sept 1 2001 to Feb 1 2004), the market formed boundaries of congestion at .8002 to .6771. The breakout occurred 33 months later. During the 33 month period there were numerous breakouts and breakdowns of 20-day highs and lows; these were trades that at best would have resulted in small profits and at worst they would have resulted in losses.

The point is this: if we are to be breakout traders, then the identification of our timeframe’s resistance and support zones is important for our win rate. Barros Swings do the job.

The flip side of breakout trading is responsive trading. The tools I use (in order of priority) to identify the zone where a correction may end are:

  • Statistical Time-Price Zones of the 18-d corrective swings

  • Statistical Time-Price Zones of the 5-d corrective swings

  • MIDAS (download free lectures from www.tradingsuccess/freestuff)

  • Various Fibonacci relations

(See the Nature of Trends, available from Amazon)

The Ray Wave (forthcoming book) indicates whether we should expect a complex correction or simple and thus indicates the boundaries of the Statistical Time Window (i.e. whether we are looking for a price correction greater than mean + 1 stdev or – 0.5 stdev). It also identifies the maximum boundary for the correction. Within the Time Window boundaries, I look for a confluence of support zones.

Notice what I have done. The Statistical Time-Price Windows have two components, an input of corrective data of the swings in my timeframe (18-d) and an impulse input of the first lower timeframe (the 5-d). The reason is a correction in one timeframe is an impulse swing in the first lower timeframe. I then look to other tools to reduce and zoom in on the zones of this window.

The idea that a correction in one timeframe is an impulse move in the first lower timeframe is an important concept for the newbie to grasp.

Once I have my zone, I look for a pattern that tells me a zone will hold (setups). I have three types of patterns:

  • Negative Development

  • Contractions

  • Reversal Bars

I’ll deal with aspects of the patterns in later blogs.

A setup pattern comes with its entry bar. Generically I am looking for evidence that not only has a zone held but also that the market has resumed its trend. If we have only end of day data, I’d be looking at a candlestick bar that shows strength for a buy and weakness for a sell. Again we’ll consider the idea of what denotes strength/weakness in later blogs.

Nowadays I have access to intra-day day data and for this reason I use the information provided by Market Delta (http://www.marketdelta.com). This software identifies buying and selling volume and allows me to enter near the start of a move rather than at the end of the day. In this way, I am able to reduce the size of my stop without substantial adverse effects on my win rate.

All entries require exit strategies. I use two types. A stop placed with my broker: a stop that represents a price beyond which I am not prepared to accept further losses. This stop is technically based.

I also have qualitative stop. Whenever I enter a trade, I ask myself three questions:

  • What does the market have to look like for me to remain in the trade?

  • What does the market have to look like for me to exit the trade?

  • For how long am I prepared to hold the trade without the market moving mean +1.5 Standard Deviations in my favour from entry?

If I am trading well, I’ll exit trades before my stop is hit and most of the time, this will prove to be the right decision in that had I not exited earlier, I’d have been stopped out.

Well we’re almost at the end of this theme.

In the next post, I’ll deal with Subsequent Trade Management, a subject that will complete this section in Trading Plans. After that I’ll have a look at some aspects of Winning Psychology. By the way, one of the better sites for psychology and ideas on trading the e-minis is Dr. Brett Steenbarger’s:

http://traderfeed.blogspot.com/

Pay it a visit, you’ll be well rewarded

Components Of A Trading Plan – A

This is the first in a series on trading plans. In this article, I shall be looking at the elements of a discretionary plan. But before I do that, let’s look at the different types of traders and plans:

  • Subjective: There is no plan as such. The traders use kinesthetic information to enter and exit trades. Subjective traders trade solely (or mainly) by intuition. Successful subjective traders with whom I am acquainted are ex-floor traders (locals). Most locals have had a difficult time making the transition to the screen. Perhaps the scalping screen traders will replace the locals – we’ll see.
  • Mechanical: On the other side of the spectrum lies the Mechanical Trader. The Mechanical Trader has a set of rules to which he always adheres. “See a signal, take a trade” is his mantra.

  • Discretionary: Between the two is the Discretionary Trader. The Discretionary Trader has a set of rules but reserves the right not to follow them. In this way, he makes room for his intuition. Newbies need to understand that intuition is the result of experience and is not to be confused with ‘into-wishing’. ‘Intuition’ in this context is the subconscious recognition of patterns. For the subconscious to amass the patterns, we must first have had the experience of consciously identifying them. Newbies are unlikely to have this experience and more often than not, call label ‘into-wishing’, intuition.

Discretionary plans have either a fundamental or a technical base or have a combination of the two. The better discretionary plan reflects some fundamental idea of the nature of markets. For example, Buffett believes that companies have an intrinsic value and that this value is assessable. The Market Profile believes that the nature of markets is fractal and is best observed via the bell curve with present tense information.

The better technical analysis based plans have certain, specific components:

  • Identification of a Trend of a Timeframe
  • Low Risk Entry

Zone

Setup, Entry and Initial Stop (or initial exit strategy)

  • Trade Management

I am heavily influenced by Pete Steidlmayer’s approach to the markets. Pete used to say that ‘traders succeed, not because of their tools but in spite of them’. I believe that his words are particularly applicable in this area of trend definition of a timeframe.

Most traditional trend definition tools rely on some form of moving average. The tools are great if a market is trending but do a poor job when the market is in a transitional phase. The reason is as a rule markets move from Bull to Sideway to Bear or Bear to Sideways to Bull. Moving Averages do a poor job in sideways markets.

Is there an alternative to moving averages?

I thought so: swing charts. But the traditional swing charts were almost as unsatisfactory as moving averages so I developed my own: a swing chart that had a time component (unlike percentage charts that only have a price component) and a price component (unlike Gann Swing Charts that have only a price component). I called the swing chart Barros Swings.

My book the Nature of Trends (available from Amazon) describes how the swings are drawn. I use on Daily Bars:

  • A 5-period swing to define a weekly trend (5-d)
  • An 18-period swing to define the monthly trend (18-d).

I also use the 13-period swing on Weekly Bars (13-w) to define the quarterly trends and the 12-period swing (12-m) to define the yearly trend.

I call the timeframe that defines our trading strategy the Trader’s Timeframe Trend. The trend of the Trader’s Timeframe is impacted by the trend status of the First and Second Higher Timeframe.

For example, if the Trader’s Timeframe is the 18-d, then the First Higher Timeframe is the 13-w and the Second Higher Timeframe is the 12-m. To know when the 18-d has a high probability to change its trend we need to know the likelihood of the 13-w changing its line direction or trend. The 12-m provides further perspective.

The swings make it easy to define the trend of a timeframe:

  • Uptrend: higher swing highs and higher swing lows
  • Downtrend: lower swing highs and lower swing lows
  • Sideways: almost equal swing highs and almost equal swing lows

Once we have assessed the Trader’s Timeframe trend, we need to ask: continuation or change? Once we answer that question, we have our trading strategy: be a buyer or seller or stand aside. I will trade against the trend only if there is a change in trend pattern. More on that in tomorrow’s post.

VISION and Trading

Yesterday I wrote that VISION, goals etc had their counterpart in out trading.

VISION is found in two components:

Our trading philosophy. Consciously or unconsciously our philosophy, Ayn Rand’s ‘sense of life’, governs our actions. So too with our trading, consciously or unconsciously, our trading philosophy governs our actions from the plans we choose to our position size to the actions we take to execute consistently our trading plan.

I adapted the statement of my philosophy when I first read it in Trader Vic – Methods of a Wall Street Master by Victor Sperandeo. The articulation there of Sperandeo’s philosophy strongly resonated with my values. So with a small amendment, I adopted it:

  • Preservations of Capital
  • Consistent Execution (leading to consistent profitability)
  • Superior Returns

You’ll see the three ideas reflected in all that I do. Our trading philosophy forms one part of our VISION.

The other component is found in the rational for a trading plan. We need a trading plan for two reasons:

  1. Before entry: it tells us when the probabilities favour our trade
  2. After entry: it tells us when the probabilities are no longer in our favour and we should quit a trade.

Both components are essential to our trading success. The key analytical insight to our success is found in the expectancy formula; the formula that tells us we can expect to make, on average, on each trade. Unless the sum is positive, we don’t have an edge i.e. we are doomed to fail in the long run. The most basic formulation of the formula finds its expression in:(Avg$Win x WinRate) – (Avg$Loss x Loss Rate) = Expected Trade Result

Where:

  • Avg$Win = Total $ profits/Total number of Winning Trade
  • WinRate = Total number of Winning Trades/Total Trades taken
  • Avg$Loss = Total $ losses/Total number of Losing Trade
  • LossRate = Total number of Losing Trades/Total Trades taken.

Most newbies focus on the Win and Loss Rate. But in my view, this is the more difficult part of the equation to control. Why this is so is best described by a story I heard about while learning Drummond Geometry (P&L Dot):

One day an ex-floor trader was told by an apprentice he had taken under his wing: ‘The 1-1 support WILL hold this decline”! The market was heading south towards what P&Lers called 1-1 support.

The ex-floor trader replied: “What are the probabilities?”

The apprentice said: “It WILL HOLD, I am certain!”

The ex-floor trader said not a word; instead, he picked up the phone and said: “Sell me 3000 Dec contracts at market”

Needless to say, the market went through the 1-1 support like knife through butter. “Remember this” said the ex-floor trader, “ we think in probabilities not certainties”.

This is a great tale. It tells us that the trading is in the realm of probabilities and as such the win/loss rate is less under our control than the Avg$Win and Avg$Loss. Both of these depend entirely on our decisions to enter and exit.

Notice that the formula explains why someone with a 90% win rate can still lose money. Let’s see why. Let’s say the Avg$Win is $10 and Avg$Loss is $100 and the win rate is 90%. The sum of the formula is:

($10 x .90) – ($100 x .10) =

(S9) – ($10) = -$1.00

So over the long term, over a large sample size, each trade we take will lose -$1.00.

Our VISION allows us to imagine a number of critical events:

  1. What does a trade need to look like – what does it have to do after entry – for me to remain in a trade?
  2. What does a trade need to look like for me to exit a trade?
  3. What does a trade have to look like for me to stop and reverse?

By visualizing the answers to these questions allows me to exit trades BEFORE my stop is hit. The technique allowed me to return 46.64 on capital (ROI) for 2007 an average dollar profit per trade of US$181.00.

By keeping detailed statistics, I am able to CANI (constant and never-ending improvement) my entry and exit. This is not to say I won’t have losses; of course, I will. My loss rate for 2007 of 50.44 attests to that. But by keeping a margin of 2:1 for my Expectancy Ratio (same formula except we divide the Avg$Win component by the Avg$Loss), I was able to return a fabulous 46.64% ROI.

In the next post, I’ll look at a trading plan and its components.