Graeme’s Trading Blog – Review of Van Tharp

Review : Trade your way to financial freedom

Chapter One – The legend of the Holy Grail

Van Tharp makes some great opening remarks and reminds us that:

Life starts out in the neutral position between profits and losses – it neither fears losses nor desires profits. Life just is, and that’s represented by the Grail. However, as a human being develops self-awareness, fear and greed also arise. But when you get rid of the greed(and the fear that comes from lacking), you reach a special unity with all. And that’s where great traders and investors emerge.

I have put in bold the two key points as I see them, life (or the markets)just is, and the sooner we accept that the better for our psyche, sure we can do things that will improve our lot, otherwise to what purpose all our educations and experiences. And that fear is inextricably linked to lacking what we, greedily, seek to achieve!

Van Tharp goes on to explain:

One of the Grail legends starts out with a short poem that states: “every act has both good and evil results.” Thus every act in life has both positive and negative consequences – profits and losses, so to speak. The best we can do is accept both while leaning toward the light.

As a trader therefore we have to accept both positive and negative and from that perspective:

Wins and losses are equally a part of trading. That metaphor, to me, is the real secret of the Holy Grail.

In reality this dis-passion rarely exists and this manifests itself when people fail to kill positions when they know they are wrong for example, in the mistaken belief that “it will turn around”

More importantly, if you cannot accept that losses will occur, then you cannot accept a good trading system that will make a lot of money in the long run but might lose money 60 percent of the time.

You don’t need a 90% success rate, but you do need control of position size and risk and reward for example.

But markets do not create victims; investors turn themselves into victims. Each trader controls his or her own destiny. No trader will find success without understanding this important principle at least subconsciously

This is so true, so many times I have sought to find the best system, the easiest way, and many others have and will, or failed to follow rules, or to curve fit some part of a system instead of religiously following the rules. This is down to a lack of what Van Tharp refers to as Internal Control, it is not down to not finding the right system per se.

Van Tharp proves this by the results of interviewing 50 successful traders where the common thread was not a common system, in fact there was no commonality in systems, rather there was a trait that all involved “low risk ideas”.

The suggestion then is that we need to find out enough about ourselves as traders to be able to find the best form of system that suits our personality.

So what that means is that the Holy Grail

Is not some magical source that is the key to the markets, as most people believe. The metaphor of the “Holy Grail” ………….is all about finding yourself.


The “Holy Grail” is not a magical trading system: it is an inner struggle. Once you’ve discovered that, and resolved the struggle, you can find a trading system that will work for you.

In summary this chapter is actually a great summary of where I have been and where I now know I need to be, to understand myself and what I am trying to achieve – before I can go achieve it!!

Chapter Two: Judgemental Biases: Why Mastering The Markets Is So Difficult For Most People

This second chapter is about self-learning and what may be holding a trader back from fully understanding Internal Control and the search to achieve it and starts with a telling quote:

We typically trade our beliefs about the market and once we’ve made up our minds about those beliefs, we’re not likely to change them. And when we play the markets, we assume that we are considering all of the available information. Instead, our beliefs, through selective perception, may have eliminated the most useful information.

So before I get into this chapter, it is worth sharing what this means to me – how many times have you taken a trade based on “sound” analysis, only to find the trade going against you? I know I have! But more importantly on reviewing the trade and checking your analysis see clear contra-indications that would confirm the alternate view? Again I know I have! What this says to me and first real memo of the book to myself is:

When making trade decisions train my mind to be meticulously objective in my analysis and not carelessly subjective and only seeing what I want to see.

However that simple statement is going to be difficult to achieve because we humans have so much information at our finger tips, and information flow doubles every year so we could have literally millions of pieces of information coming at us at every minute and yet our brains can only realistically process very small amounts at one time. It is no wonder we all find ourselves confused and indecisive at times!

Van Tharp then explains that we filter this information by generalisations and deleting much of it, for example by stating “I am not interested in stock markets” generalises it as “stock market information” and deletes it from consideration. We generalise information we want to see by setting criteria, and set our computers to sort by that information say daily bars meeting such and such, but then distort that generalisation by adding indicators like moving averages or RSI etc and then potentially trade our beliefs about that distortion. Those beliefs may or may not be useful!

Psychologists have looked at these distortions and grouped them into judgemental heuristics which enable us to sort this volume of information, but are dangerous to traders who are not aware they exist and affect the way we develop trading systems. The chapter then goes on to examine the biases we face:

Biases that affect trading system development

Representation bias

This is where we are potentially guilty of judging a book by its cover so to speak, for example assuming a daily bar is a representation of the daily market activity, whereas in reality there is a huge amount of information missing, time and sales, volume, psychological makeup of buyers and sellers, who is buying and selling, at what levels most of the activity took place, how much activity was large transactions, how much activity was retail or commercials etc etc etc. And yet as traders we could all make decisions based on that daily (or other timeframe bar) – scary huh?

Reliability bias

Closely related to representation bias – where we believe what is represented as true.

Lotto bias

Many people do the state lotteries, despite the odds being 1 in 13 million or so, because the stake is so small and the prize potentially so big, the lotto bias is not that, it is more to do with the fact that because people pick their own numbers they somehow improve the odds of success.

Picking the right numbers in trading means knowing what to buy and when, which is why so many focus almost entirely on entry, and not exit and position sizing and why so many so called gurus make vast sums selling the unsuspecting trader their 80% accurate trading system or trading signal service.

Van Tharp sums this up:

I have always felt that this “lotto” bias is a way of dealing with the anxiety of not feeling in control. Most people would rather pretend to be in control (and be wrong) than fear the anxiety of having no control over the environment in which they must exist. The big step is in realising that “I have control over my actions.” And that is enough!

Light bulb moment anybody?

Bias of the law of small numbers

Basically, it doesn’t take may examples of a particular price formation say to jump to a conclusion before making an assumption it is a good entry – William Eckhardt is quoted:

We don’t look at data neutrally – that is, when the human eye scans a chart, it doesn’t give all the data points equal weight. Instead, it will focus on certain outstanding cases. It’s human nature to pick out the stunning successes of a method and to overlook the day-in, day-out losses that grind you to the bone. Thus, even a fairly careful perusal of the charts is prone to leave the researcher with the idea that the system is a lot better than it really is.

Conservatism Bias

In a nutshell the mind is quick to see what you want to see and all too often ignores contra-evidence. I know I have been guilty of this more time than I care to admit!

Randomness Bias

This is an assumption that market movements are random and that traders make erroneous decisions about what such randomness might be, for example looking for chart patterns to predict a particular price movement.

Need To Understand Bias

Where people try to explain market movements (particularly the media) but extends into other forms of technical analysis – Van Tharp uses Elliot Wave as an example – and challenges what rational theory would be capable of explaining why should a market move in waves. I would agree with that as in particular I find EWT particularly subjective and the need to “re-count the waves” comes far too often for my liking (apologies to any IT EWT gurus reading this).

Biases that affect how you test trading systems

Degrees of Freedom Bias

A degree of freedom is for example the number of periods being used with a moving average, 20, 50 etc. People then often want more degrees of freedom i.e. more indicators, to better predict price.

If we add this into the backtest mix and add optimisation, what we end up with is a perfect system that will make money on the data on which It was tested (curve fitting) but will prove to be utterly useless when traded in live market conditions.

Van Tarp suggests only 4/5 degrees of freedom in a trading system as this is the most many minds can handle.

Postdictive Error Bias

Where material information that can only be know after the fact is used as a parameter in the backtest which can lead to skewed results.

Bias of not giving yourself enough protection

This is where traders either deliberately or naively trade at levels that are too high or without protective stops in place.

Biases that affect how you trade your system

Bias of the Gambler’s Fallacy

This is a natural consequence of the randomness bias and a belief that a trend that is established in a random sequence must end at some point. For example after three losses believing that the probabilities of a win are somehow increased. This follows through to betting higher in a losing streak and not in a winning streak and failing to accurately build position size into a trading system and following it.

Conservative With Profits And Risky With Losses Bias

Perhaps the number one rule of trading is to cut your losses short and let your profits run

whereas we will all experience times where we allow a loss to run in the hope it will turn at the next level and grab any profit as soon as we see the slightest re-trace, even when our system does not say we should exit. This one certainly is my largest single nemesis and needs to get under control!

Bias that “My Current Trade or Investment Must Be a Winner”

Closely linked to the last bias and another reason why we grab profits and try to nurse losing trades into winners – the need for our decisions to be right.

In summary I believe chapter 2 neatly sets out a series of biases which we as traders/investors need to come to terms with, or at least recognise when they start to influence our trading, and be able to consider ways of changing our behaviours to deal with them before they become destructive, either to our psychology, or to out trading accounts!

Chapter Three: Setting Your Objectives

This chapter starts with a reality check example of a trader wishing to buy a car for his wife but when challenged over the objective had to come up with a trading plan which consistently produced a 15:1 reward to risk return – hardly realistic – as we move into objective setting any trader would do well to retain realism and temper impatience – otherwise we may face a battle that WILL win the war and our trading life ends!

Designing Objectives is a Major Part of Your System Work

About 25 years ago I started in Financial Services selling Life Assurance etc, and one part of that training I remember still to this day and sits well here and that is the broad concept which has four steps:

Where are you right now
Where do you want to be in the future
What are all the different methods of getting there
Which is the right one for you right now

Essentially this is what Van Tharp is eluding to – how can you achieve anything if you don’t even know what you want to achieve?

SO: First step design your objectives, then see that they are realistic, then design your trading system.

For realism Van Tharp asks how can a trader with $100k and needs $50k to live each year then expect to trade for a living – 50% each and every year – more if he/she wants to increase capital to hedge against inflation – I am not going to pass further comment here as this is but one example and the methodology will vary trader to trader.

Van Tharp then goes on to interview Tom Basso who is a professional money manager and someone interviewed by Jack Schwager in “The New Market Wizards” book and was consider the best personal role model he had interviewed. The interview revolves around:

Part 1 Self-Assessment

This is about understanding yourself and your own strengths and weaknesses in order that you can design a system that best suits you.

Part 2 Define Your Objectives

Probably the most important step as it defines what is real to you and also what parameters you will need to add – for example maximum risk, drawdown etc.

Part 3 Trading Ideas

This is naturally about entry exit position sizing and the mechanics of your trades.

Setting Your Own Objectives

Van Tharp suggest that this step should take at least 50% of the time in developing your system and I agree – it is vital to know exactly what you will do in certain situations – to take out the uncertainty.

He goes on to say that your emotional response to the answers you give to the questions being asked as above will be a good clue to any psychological issue you may have with your system and that if you cannot complete this step then perhaps we should consider if we have the right presence of mind for trading.

In summary, the steps described are so vital and yet so often missed or treated lightly by an aspiring trader. Make no mistake anyone planning to trade, must plan to trade – anything less is more likely to lead to the 95% failure rate statistic.

Chapter Four: Steps to Developing a System

This is a description of Van Tharp’s 12 step model that he has developed through interviewing hundreds of traders and establishing the common steps they all have in common and ignoring the idiosyncrasies.

1/ Take an inventory

This of course is an inventory of yourself much as already discussed in Chapter 3 – of your strengths and weaknesses.

2/ Develop An Open Mind And Gather Market

Here we are shown that facts perhaps could be better viewed as beliefs, and it is the utility or usefulness of the belief that is important. So when something contradicts your current view it is better to ask the question

Is there any chance that this is a more useful belief

Therefore to be truly open minded about the markets, you must first determine your beliefs about the market so you can assess any new beliefs that come your way and assess their usefulness.

3/ Determine your objectives

As Chapter 3

4/ Determine your timeframe

How active do you want to be/can actually be and understanding how psychology plays a very significant part of the ability of a trader to trade successfully in different timeframes.

5/ Determine the best historical moves in that timeframe

Examine 50 – 100 significant market moves from various markets including up and down price movements and try to determine the common criteria, this could be price formations, volume, correlations with general market moves etc Are the moves linked to fundamentals – how do the moves develop and do they end sharply or gradually and how should the move have been exited.

6/ What is the concept behind those moves
and how can you objectively measure your concept

Here we are shown that the previous exercise gives us two parts of our trading system, the set up conditions, and the timing or entry signal. This entry should then be tested across various timeframes and yield results that are better then random entry which would mean probability of better than 55%.

The entry has to yield significantly better than random when tested raw, as when you add stops and transaction costs etc, then clearly profitability reduces in any system.

It is also vital to understand how many false moves the signal would generate as this could reduce the probability to less than random.
Van Tharp believes

The more you understand the real nature of your concept, the less historical testing you will have to do.

This in turn means the temptation to curve fit by optimisation could be reduced or removed.

7/ Add your stops and transaction costs

You will then need to determine how you will exit the market if your trade is not going your way, and what type of stop you will use. You also need to establish transaction and slippage costs and add them into the previous calculations and see what effect this has on reliability. Almost certainly it will drop.

8/ Add your profit taking exits and determine your expectancy.

When looking at exits Van Tharp suggests target have to be realistic to the time frame being traded and that expectancy must be as high as possible. Expectancy is defined as:

The average amount of money you’ll have to make in your system – over many, many trades – per dollar risked

This is dealt with later in more detail

9/ Look for huge reward trades

An alternate to steps 6-8 is to look for ways to capture the high r-multiples i.e. profit many times initial risk. For example breakout from narrow consolidation ranges.

10/ Optimise with position sizing

This is also dealt with in more detail later

11/ Determine how you can improve your system

Vah Tharp explains quite correctly that even when this is all said and done, you should never stop reviewing as markets change and what works with positive expectancy may fail in other markets, for example a trend following strategy in a range bound market period.
Also combining say a long term trend strategy with a range strategy during consolidation may well increase overall profitability.

12/ Worst case scenario mental planning

This is about understanding and planning for the unexpected like pc failures, internet failures, major events such as war etc and understanding what effect this would have on your system.

In summary I thought this chapter was useful in particular I have not really done the sort of wider research on major moves to consider that as a basis of a system and that is one thing I will need to be looking at for sure.

Chapter Five: Selecting a concept that works

Van Tharp believes that about 20% of people that trade actually has a system in the first place, and of them the majority rely on indicators to derive the system, and very few people understand the concept behind what they trade. This chapter describes several trading concepts through articles contributed to by successful traders.

Tom Basso – The Philosophy of Trend Following

Basso defines trend following as someone who awaits a change of direction and then follows the trend – typical of the letting profits run trader who only exits on a reversal signal.

The advantages being lower transaction costs and never missing a major move, and because then risk/reward is potentially significantly better and one trade could make the year, then % accuracy can afford to be lower.

The disadvantages are that many times the potential change in direction will be nothing more than a minor re-trace, and multiple whipsaw losses can hurt the account and trader psychology. Also markets spend most of their time in ranges or consolidation periods, so a successful trend follower must have a backup strategy for these periods, or wider markets being watched.

If the above is true – why follow trends – without them the markets would probably die off as no-one would be interested in them. Trend following is probably one of the easiest techniques for a new trader to understand.

Charles LeBeau – Fundamental Analysis

LeBeau defines fundamental analysis as the use of actual and/or anticipated relationships of supply and demand to forecast the direction and magnitude of future price changes.

Le Beau believes that fundamental analysis

will tell you only the direction and general magnitude of future price movements. It will rarely tell you when the price movement will begin or exactly how far prices will travel.

Obviously that is useful information and when combined with solid technical analysis will go a long way.

LeBeau warns not to confuse fundamentals with news – news follows the price whereas fundamentals can predict price movements. Although pending news may move the market far more than the news itself.

He further warns to be careful of reacting to fundamentals without knowing the market expectations. He cites a 10% crop reduction in soybean which should be bullish, but was bearish as the market expected and priced in a 15% drop.

We are further counselled not to do our own fundamental research but to delegate that to the professionals – subscribe to newsletters etc and look for someone who is precise in their reports, and to now have more than one source per market to remove contradiction and confusions.

Look for demand driven markets to trade as these will be the most sustainable – short term supply concerns may lift the market but will be relatively short lived.

It should be noted that one of the most famous fundamentally based trader is none other than Warren Buffet – and he doesn’t do so bad!

Jerry Toepke – Why Seasonals Work

This is of course where traders seek to take advantage of known, repeatable events such as the climate effects on the cost of heating oil etc and is defined as

a market’s natural rhythm, the established tendency for prices to move in the same direction at a similar time every year.

In some markets this seasonality can be so ingrained it almost becomes a fundamental in its own right as humans are creatures of habit and like to follow proven patterns of behaviour.

One important note is to take regard of options expiry as this often invokes some volatility which can give opportunities to take profits or enter if the initial move is missed.

Needless to say seasonal influences are no more the Holy Grail than the local Gypsy Fortune Teller’s crystal ball! However, once again Van Tharp’s book has reminded me of something I have consciously removed from my trader arsenal simply because up to now I have traded very short timeframes. This will not change as I go into the Prop Firm and indeed I will become much more focussed on daytrading, however I still have a pension which needs to be looked after and my own money I will need to trade, perhaps, just perhaps, this is something I need to research in more detail in due course as longer term trades will need to be made, perhaps based on daily/weekly charts for those funds.

Kevin Thomas – Introduction to Spreading

Spreads is the concept of creating a synthetic position of long and short positions at different dated contracts which create a position which is potentially lower risk and at reduced margin.

This type of trading works best on futures contracts where there is good liquidity in forward contracts. Volatility is likely to be less the closer the expiry dates.

There are a large number of potential forms of spread trading, such as calendar and butterfly which are touched on in the book but falls short of a detailed explanation.

Thomas also explains that commodities are good for spreads due to the backwardation principle.

One of the main advantages of spread trading is the ability to trade intra market relationships that otherwise would be impossible.

Ray Kelly – Arbitrage – What it is and how it is implemented

In essence arbitrage is exploiting differences in price or value or inefficiencies in market pricing, the chapter talks about several examples of arbitrage, but IMO nowadays to exploit inefficiencies to any great extent requires capital and computer algorithms far beyond the average traders remit, so although interesting reading I will comment no further here.

Louis Mendlesohn – Introduction to Neural Networks

OK – hands up – I really really don’t get this!! Essentially the basis is intra-market analysis (so far so good) which is run through computer models that essentially predict market moves with up to 86% accuracy – so says the author who sells the software.

Ooops no stop it – I have to be open-minded here!

There is no doubt that neural networks are extremely clever pieces of software capable of amassing intra-market analysis way beyond that a human mind could even countenance let alone handle and the chapter does a solid job of explaining the methodology.

To me though the more complex the input, the more subjectivity can creep in which in turn leads to the potential for misleading results. The software will have error checking, but this would be based on the same potential flaws.

I believe this is all still too new but I have no doubt will become more mainstream eventually.

Van Tharp – There’s an Order to the Universe

Finally Van Tharp himself offers up three concepts which presume there is an order to the markets;

Human Behaviour Has A Cycle

…markets are a function of human behaviour and that the motives of human beings can be characterised by a certain structure.

Van Tharp then goes on to explain the most obvious example of this being Elliott Wave theory which assumes fear and greed follow a distinct wave pattern. As I have said before there is much subjectivity to EWT, but the rules do if interpreted correctly

allow you to arrive at market turning points that are tradable.

and that it is the trader’s job to determine which wave series was responsible for any turning point.

Physical Systems Influence Human Behaviour in Predictable Patterns

Here Van Tharp cites examples of research that physical systems (Sun, weather etc) can have an impact on the markets. A little difficult to believe but there are correlations being proven, and as such could be tradable. A little out there this one, but each to their own!

There’s a Mysterious Mathematical Order to the Universe

No surprises here as Van Tharp refers to Gann and Fibs etc, and yes they are tradable events if combined with correct position sizing etc.

All three concepts are potential predictors of turning points in the markets which can lead to entry and exit criteria. However trading the levels requires the market to show you the way – perhaps through price structure – volatility breakouts – candle formations etc.

In summary this chapter introduces several trading concepts and for me highlights the not one size fits all concept, some things mentioned I could only swallow with a very large pinch of salt whereas others would epitomise a large juicy steak!

It is for every trader to make themselves aware of the options available to them, and pick the right style or combination of styles to suit their individual personalities.

Chapter Six: Understanding Expectancy and Other Keys to Trading Success

This chapter is key to the book and is the most complex. Van Tharp starts out by explaining 6 variables traders need to consider in their trading:

1/ Reliability or hit rate – the number of times you make the right trade decisions.
2/ Relative size of profits against size of losses which should be expressed as a R-multiple for example a 2-R multiple means a $1,000 gain against an initial risk of $500.
3/ The costs of making your trades (often consolidated in net profit or loss but should be aware of separately)
4/ How often you trade
5/ Size of trading account
6/ Position sizing model

Van Tharp goes on to use a snowball fight analogy which I don’t have space to do justice to here, but imagine hiding behind a wall of snow and snowballs being thrown at you, white snowballs good, black bad – essentially your object is to get the wall (trading account) higher and examines the variables above represented by size and frequency of white and black balls etc. A good analogy which is summarised into variables 1-4 defining expectancy with 5 and 6 being the most important for overall profitability.

We then get to go over the calculation for expectancy which is in its base form:

(PW x AW) – PL X AL) where:

PW is the probability of winning
PL is the probability of losing
AW is average win size
PL is the average loss

Van Tharp uses an excellent example of a marble game drawing different colour marbles from a bag and dependant on how many marbles etc will vary expectancy and confirms what we already know, that account size and position size are critical to longer term success. This is something I can vouch for from bitter experience of an 11 trade losing streak BUT 2% position size saved the day and did not dent my psyche too much!

The actual variables and resultant formula is additive which means that it is adaptable for any amount of variables and gives a formula result of $ earned per $ risked which is the average returns over a LARGE number of trades.

However expectancy in isolation is not enough, we need to also consider opportunity factor i.e. the fourth variable of how often do we trade. The more often you trade the more likely you are to achieve the stated expectancy.

This variable means that a smaller expectancy system traded more frequently than a significantly higher expectancy system may prove to be more profitable.

Of course when we trade markets it is difficult to know exactly what risk and returns will be achieved, so expectancy can only be estimated based on past trades and reviewed with experience, or by using a system with past records available.

We have already been introduced to R-multiples, and Van Tharp goes on to explain the psychology of a run of losing trades and how as traders we must resist the “winning trade is around the corner” syndrome and stay calm and trade our plan, and even with a significant losing streak on a system with correct sizing, can still prove profitable.

Van Tharp then considers a range of trading results and shows us to be on the guard for “outstanding” profits and losses and shows us the need to understand why these occurred and what probability there is that they will be repeated, and how a profitable system in net profit terms could actually have a very low $ gain/$risked.

Van Tharp then goes on to show how expectancy can be compared but warns that such comparisons are only valid if traders are actively trading as such as opportunity factored in will skew results.

In summary this was an eye opening chapter for me – I thought I understood probability and expectancy but in reality I did not to the degree I needed to and has prompted me to review future systems in a different way (I say future as my methodology is likely to change significantly as I develop on the Prop Firm route). It also excited me as the opportunity about to be afforded to me means that I will have a very much increased ability to make trades, and therefore a deeper understanding of expectancy and proof that even a lower hit rate if combined with good position sizing and calmness of mind can lead to profit is exciting to say the least – bring it on!!

Chapter Seven: Using setups

Van Tharp’s opening remarks on this chapter include the quote:

If you learn one critical thing from this book, it should be that a setup is about 10% (or less) of your trading system. Most people will place 90% of their emphasis on finding the right setups, but setups are actually one of the least important part of the system.

Well I don’t know about you – but that was me for a good deal of my early days and on occasion still is when I get a run of losses. In reality we should spend more time on disciplined trading and the rest will follow – unless your chosen system is a real dog that is!

Van Tharp then goes on to describe four phases of entry:

Market Selection

This is about choice of market and what characteristics to look for:

1/ Liquidity – really important – you need to know that you can get into and out of a market with relative ease, especially if trading in any size. Also illiquid markets can move disproportionately when larger trader do enter and are much more likely to be manipulated.

2/ Newness of the market – it is best to keep out of new markets unless that is your speciality as many mistakes on pricing can occur in the early days.

3/ Market Makers and Market Rules – when walking into the den – check for Lions! In other words understand the rules of the exchanges, the ability to get good fills, who makes the market and their reputations etc.

4/ Volatility – is there sufficient volatility in your chosen market to cover two to three times your initial risk in the timeframe you are trading.

5/ Capitalisation – generally the smaller the capitalisation the higher the potential return and associated risk.

6/ Markets and Trading Criteria – how well does the market historically shape up to your chosen style – how often does it trend, conform to EWT etc.

7/ Selection of a Portfolio of Independent Markets – building a portfolio based on independent non-correlated markets increases the probability of a trending market and reduces correlation risks.

Market Direction

We all know markets only go up down or sideways – you need to know what your markets are doing and how they match your system – not much more to say!

Setup Conditions

These are the conditions that should apply for your system to trigger and could consist of fundamental, seasonal, technical or other conditions.

Market Timing

We like to be right, but it is often better to catch the meat of fewer moves than try to get the turn point only to be stopped out on many trades.

Van Tharp then goes on to summarise a number of setups beginning with setups for stalking the market – mainly short term setups with reduced risk.

Failed Test Setups

Basically where a new high, or range high is tested and fails is used as an entry signal.
Climax Reversals or Exhaustion Pattern Setups
Van Tharp describes this as typically chart patterns that are difficult to objectively describe and that many are not “real patterns that can be traded and therefore restricts his discussion to the next topic. Personally I do feel there is some merit in these patterns which tend to come from observation over time, volume also can add its story.

Gap Climax Move

Essentially price gaps to a new extreme but fails to follow through and signals a short term trade in the opposite direction. These are described as dangerous because you are effectively standing in front of an express train going very fast. Again though risk can be reduced by studying past similar actions in that market.

Retracement Setups

Wycoff is quoted as saying

Don’t buy on breakouts. Wait for the retracement test.

Retracement setups are good for trend following systems as they allow tight stops and higher potential risk/reward.

We are then advised of the differences between filters and setups where essentially filters are based on the same data as your system and are often optimised by using back testing but in reality are not of much use in the live market.

Setups based on different data however can provide an edge and the following examples are given:

Time Filter

Giving your trade a time constraint based on other data such as seasonal or cycles etc.
Price Data in Sequence

Requiring price to form in a pre-defined manner based on experience for example a 1-2-3 retracement.

Fundamental Data

Understanding such data as is relevant to your market such as yield of harvest on wheat etc.

Volume data

This is a subject much discussed in IT

Composite Data

Neglecting to look at the component parts of an index when trading that index can be dangerous.


Understanding the volatility or range for your market relative to say the last 50 days can give a heads up for range breakout or volatility breakout trades.

Business Fundamentals

Warren Buffet is probably the best known proponent of this style of trading set up, and the theories are discussed later in the book.

Management Information

If looking at individual stocks or managed instruments, then an understanding of the track record of the management team is critical.

Van Tharp then examines setup formulas that have been known to work – he does not go into detail so I will not either – remember setups are 10% or less of a good system.

Stockmarket setups

William O’Neil’s CANSLIM Model – which is an acronym which describes his model and compares financial data such as current earnings per share, with other factors such as leadership and the general market direction.

Warren Buffett “Value” Model – really Buffett buys to hold and considers the nature and complexity of the business, the management structure and some of the financials.

The Motley Fool “Foolish Four” Approach – essentially allocating capital to the 2nd 3rd 4th and 5th highest yielding stocks in the Dow 30 and buying at a determined date with exit strategies that are discussed later.

Futures Market Setups

Perry Kaufman’s Market Efficiency Model – This is a model that compares speed of movement of a market and the noise it generates and can be used to form an adaptive moving average which gives signals.

William Gallagher’s Fundamental trading Method – this is where you gather all known information about a market and use it to establish a value market where supply conditions are weakening which could give rise to increased prices – often combined with seasonal influences. Van Tharp suggests this is good for bias but less useful for market timing.

Ken Robert’s Method – where you have a major high from the last 9 months or year, the market reverses to form a low, then goes back towards the turning point but not reaching it before falling away and breaking the previous low – a 1-2-3 reversal – reverse for downtrends.

The problem of course is the subjectivity and likelihood of many false positives.

In summary the chapter describes in overview a number of different setups, but none in much detail, but does reference many other sources of information to discover more should the reader do so. He does give enough information to get a flavour and perhaps determine if the concept is at least worthy of further investigation.

Chapter Eight: Entry or Market Timing

Avoiding mistakes makes people stupid and having to be right makes you obsolete.

Van Tharp here quoting Robert Kiyosaki at the head of the chapter is such a great quote. Learning is a process which must encapsulate and relish mistakes – fact – and once you become a “now it all” you are doomed IMO!

We have already learned that good systems come from high positive expectancy and good position sizing and that entry is only a small part. That said it is still important and this chapter confirms the need to find entries that suit your objectives.

There are two basic ways to do this – better reliability signals or to find high R-multiple trades.

Trying to beat random entry

Van Tharp describes some experiments with entry based on the flip of a coin determining then direction of trade with some surprisingly efficient results with profitability achieved even with only 38% reliability, and a trend following exercise that without protective stops was very profitable with predetermined time exits, but the reliability reduced when stops were added which clearly demonstrates why trend following strategies often have reliability of less than 50%.

This really goes to support the theory that good systems benefit from high R-multiples or letting the profits run and a few larger winning trades.

The chapter then goes on to describe some common entries and their effectiveness:

Channel Breakouts

Here Van Tharp is not referring to the diagonal parallel lines we often refer to as channels, he is referring to the high and low points of a pre-determined number of days and entering when that level is breached. This is something the famous Turtles did quite successfully. The downside with this method is the relatively high drawdowns caused by the stop placement outside of the larger ranges.

Visual Entry Based on Charts

We are referring here to more traditional chart pattern technical analysis, however Van Tharp cites that entry on these patterns is not much better then random, although I personally suspect that can be improved upon by experienced eyes and use of confirmations from, say, volume.

Pure Prediction

EWT is one example of predictive method along with support and resistance or fib levels predicting tops and bottoms, but these again are best used when confirmation is seen.

Volatility Breakouts

J Wells Wilder is credited with first describing volatility breakouts and they are effectively sudden price movements in a particular direction. In the example Van Tharp uses he calculates 0.8 times the average true range for the instrument and places markers around the result above and below the close of the previous day, entry being either extreme being breached. However Wilder uses 3 x ATR as a trailing stop which initiates and entry in the opposite direction when hit.

It is suggested that at the very least you should not trade against a strong volatility breakout.

Directional Movement and the Average
Directional Movement

The Directional Movement indicator is designed to show the “trendiness” of your chosen market and the ADX (Average Directional Movement) indicator is designed to show the trend strength.

There are issues with ADX as spikes do not adjust into the indicator well so sustainable trends may show as reversals and the longer period ADX will lag and show a trend only well after it has started.

The most used signal is the DI+ crossing the DX- for longs and vice versa for shorts. Also high ADX indicates solid trend so perhaps retraces in high ADX markets may produce better than random results?

Moving Averages and Adaptive Moving Averages

Most traders will know enough about moving averages, and will be familiar with moving average crossovers with one of the first people to write about a 5 and 20 period crossover being Donchian. Similarly most traders will be aware that this method really only works well in true trends and whipsaws you like crazy in more undecided markets.

There are a number of moving average systems and types of average each attempting to solve the problems such as Weighted, Exponential, Displaced and Adaptive but Van Tharp warns that even the variations have their own issues.

Oscillators and Stochastics

Van Tharp has little faith in the oscillators and believes they offer not much more than chance and I would agree when taken in isolation however there are many posts on IT that show traders using them to great effect, and one way Van Tharp does advocate is to help entry on a retrace in a trending market.

Outside of Van Tharp’s comments, I also wonder if ADX can help filter oscillator signals – but that’s for another day!

Designing your OWN entry signal

It is suggested that designing your own entry system is the only way to get something that works for you as I am sure our very own Larry Folson would agree! But to make a successful system you really need to understand the concept and workings of the system itself.

Van Tharp then goes on to explain the outline of designing a system based on velocity and acceleration as a conceptual exercise. I won’t explain it here as it will muddy the waters and is not a tested system, but it does serve to show how understanding a concept can lead to the makings of a good system.

The book then goes on to evaluate some of the entry systems talked about in the previous chapter:

William O’Neil’s CANSLIM

Entry is timed using patterns such as cup and saucer, double bottom, etc arising from a consolidation period lasting anywhere between 7 weeks and 15 months, but only where volume is at least 50% above average. It is this additional volume which indicates the likelihood of a continuation of the move.

Warren Buffet’s Business Evaluation Model

Van Tharp believes that no entry signal exists beyond finding a Company that ticks all the boxes and that Buffett is less concerned about timing, although doubts if Buffett would buy an overvalued Company.

Motley Fool Foolish-Four Approach

At its simplest entry can be on the first business day of the month or November 1 to May 1 as suggested, but could be improved on by adding channel breakouts etc.

Perry Kaufman’s Adaptive Trading

This uses quite complex formulae to take account of an efficiency ratio based on speed and direction and filtered using % of standard deviation of the change in the resultant adaptive moving average to produce buy and sell signals.

To be fair although I get the principle I would have to do some work to see how advantageous or otherwise this was.

William Gallagher’s Fundamentals

The problem with “funnymentals” is the issue of timing and Gallagher suggests a 10 day channel breakout which Van Tharp disagrees with as it would lead to too many whipsaws, but suggests perhaps a 50 day alternative.

Ken Roberts 1-2-3 Reversal Approach

Whilst the theory is good van Tharp suggests that many times this will result in periods of consolidation before the trend resumes, but with correct stops and position size could be profitable.

In summary, whilst the chapter does not fully explain the setups in detail in most cases, it does serve as a memory jogger/challenge and reminder that you must understand why a signal is relevant and accept the false results.

Chapter Nine: Knowing When to Fold ‘Em: How to Protect Your Capital

Your protective stop is like a red light. You can go through it, but doing so is not very wise. If you go through town running every red light, you probably won’t get to your destination quickly or safely.

I remember it well, my first forays into trading – know it all – 60% down in a short period of time. If only I observed some basic traffic laws! Instead of fearing losses, or ignoring them we need to acknowledge and embrace them as a fact of trading business life and a learning opportunity.

What your stop does

Firstly it sets the maximum loss or risk (R) used as the basis of R-multiples. Secondly it provides a benchmark for gains. Thus a good trader looks to make higher R-multiple trades as much as possible.

One way is to make R as small as possible, but that could entail tight stops which reduce the reliability of a system and Van Tharp goes on to help on that point:

Going beyond the noise

Most stops are placed at technical areas around support and resistance and everyone knows where they are so no wonder that stops “get hunted” which is a major cause of complaint for broker “scams”

By utilising a stop based on Average True Range you can get outside of this market noise (Van Tharp suggests 3 x ATR) and if that gives too wide a stop reduce position size to allow it or move on.

Maximum Adverse Excursion

This is where you look what price movement happens after entry and the worst intraday potential loss usually the high or low of the day. When analysed the results show that winning trades rarely have a MAE of more than 1.5 x ATR whereas almost half losing trades were over 1.5 ATR and thus there is an argument for restricting stops to a lower ATR multiple based on a MAE study of the market you are trading.

Tight stops

Tight stops are better when expecting major turns or on smaller timeframe entries and result in potentially higher R-multiple trades but increase transaction costs and amount of losing trades, and potentially runs of losing trades so the use of tight stops must be a careful balancing act and used by those with larger accounts that can cover the costs more easily and by those with the temperament to withstand the loss impact.

Dollar stops

Simple calculation of stop based on the maximum $ loss acceptable, these have an advantage of being generally unpredictable and even better if beyond the MAE for the market.

Percentage Retracement

Stops are placed beyond a % retracement in the stock/market price, OK if based around MAE or ATR but not if purely a standardised arbitrary amount.

Dev Stops

Or standard deviation on price – for example a standard deviation of ATR adjusted for skew.

Channel Breakout or Moving Average Stops

Breakouts and averages can be used as entry and stops placed the other side, as before probably most effective if outside MAE or ATR.

Support and Resistance

Same principle as above but if worried about stop clusters and obvious location than add a constant factor to the placement.

Time Stops

If a trade does not go your way within x time then get out – needs to be tested for effectiveness for the market and timeframe being traded.

Discretionary Stops and Psychological Stops

Experienced traders can get out of a market based in instinct and others should get out when the psyche is not well balanced – when ill – travelling – divorcing!

In summary stop placement to protect capital is an absolutely vital step in making money from trading and a trader needs to decide on placement that suits his or her market, style of trading and personality. I for one wish I had read this chapter when I first started trading!

Chapter Ten: How to take profits

….exits do control two important variables – whether you will make a profit and how much profit you will make. They are one of the major keys to developing a successful system.

Exits control your losses and your profits and come in many guises and should be tailored for your system and objectives:

Exits That Produce a Loss, But Reduce Your Initial Risk

The initial stop loss (initial risk) should be the worst case scenario, but Van Tharp describes other methods that can be employed to exit at reduced loss:

The Timed Stop

If a market move does not occur in an acceptable timeframe then option exists to close at a loss potentially, but less then initial risk.

The Trailing Stop

…. exits do control two important variables – whether you will make a profit and how much profit you will make. They are one of the major keys to developing a successful system.

Exits control your losses and your profits and come in many guises and should be tailored for your system and objectives:

Exits that produce a loss, but reduce your initial risk

The initial stoploss (initial risk) should be the worst case scenario, but Van Tharp describes other methods that can be employed to exit at a reduced loss:

The timed stop

If a market move does not occur in unacceptable timeframe then the option exists to close at a loss potentially, but less than initial risk.

The trailing stop

Trailing stops can be based on a number of different factors for example volatility, moving averages, breakout ranges or consolidations and so on, and any of these could have a number of different variables.

Whatever the basis of algorithm used to define your trailing stop, the point is that the exit moves in your favour and even though you could still end up at a loss, but at least it will be less than the initial risk.

Care must be exercised using trailing stops as to move your stop too early could lead to an unnecessary loss but there is the advantage of reducing your initial loss in most cases.

Exits that maximise your profits

In order to maximise your profits you must be willing to give some of them back, and as such trailing stops can also have the potential to help you gain large profits but inevitably you’ll give some profit back
There are a number of different variations on the trailing stop theme, but most of them we have come across before, such as trailing stops based on volatility or ATR, or dollar trailing stops, channel breakout stops, moving average stops, or other variations.

The profit retracement stop

Retracement stops should only be put in place once you have gone a certain distance, say 2-R into profit. The percentage can be either random or perhaps based on fib levels. This again would be dependent on your objectives and your system.

Exits that keep you from giving back too much profit.

The book then describes a number of strategies that will stop you from giving back too much of your hard earned profit.

The profit objective

You may have established through backtesting that your system generates profit of say 4R. If you achieve that level you may wish to simply exit or put in a closer stop. This can then be combined with a number of other strategies.

The profit retracement exit

A variation of the stop would be to reduce the percentage you give back the higher your profit goes.

Volatility stops

Essentially coming out of the market on a move against you on some multiple of the ATR. This could be combined with the trailing stop referred to earlier.

Parabolic stops

First described by J. Wells Wilder parabolic stops are a curve starting at a previous low and accelerates in upward moving markets.

Parabolic stops are good for profits, but less efficient for protecting initial loss.

Psychological exits.

Described by Van Tharp as one of the smartest exits anyone can have.

As we described before there can be a variety of psychological exits and it is important that we exit at any point when it is “wrong” to continue trading in such circumstances.

I have lost count of the times in my trading where I have “felt” a trade is to move against me, and could have saved a lot of money if I followed my gut feeling – this is not to be confused with simply running scared!

Just using your stop and a profit objective

The most simple way to control exits is to have one initial risk stop and a profit objective preferably of a multiple of R and backed by a logical reason – say a higher resistance level.

Once set these exits should be left alone, and certainly from a psychological viewpoint this is the simplest of all exit strategies.

This kind of stop and profit strategy is best used aiming for larger profits from tight stops as psychologically it is easier to leave a stop in place where it is a tight stop.

Multiple exits

Any one or more of these exit strategies could be combined into a multiple exit strategy.

For example moving a protective stop to break even when a trade moves to its profit objective and then using the training stop to maximise on your profit.

There are of course any number of potential ways to do this, but it is best to keep things simple for ease of trade management.

What to Avoid

Interestingly van Tharp advocates strongly against scaling out of positions. The rationale Van Tharp uses is why have your largest position guaranteeing loss, and your minimal position exposed to profit? Quite a logical comment really and one to a degree I support.

Finally Van Tharp looks at the exit strategies for some of the systems described earlier:

William O’Neil’s CANSLIM System

The basic set up is 8% stop 20% profit, but then O’Neil has 36 other selling rules and 8 for holding on to a stock – sounds a Tad complicated to me – and Van Tharp does not expand either simply rfering interested readers to O’Neil’s book.

Warren Buffett’s Business Approach

Buffett seems to be a bit of a mystery to Van Tharp, or at least the details of what he does and doesn’t do are unclear to him, and thus not a great deal to add.

Motley Fool Foolish-Four Method

Simply the portfolio is adjusted to reflect the position of the stock each year or cut if it no longer qualifies.

Kaufman’s Adaptive Methods

Two exits, one when the adaptive moving average moves in another direction, and the other when the efficiency exceeds a pre-determined level as he argues that high efficiency is unlikely to be maintained.

I see this as, rightly or wrongly, as a variant of the rubber band theory that extended price will always gravitate towards the median. I can see some merit in this theory, but again would ned to research this a lot more to comment further.

Gallacher’s Fundamental Trading

Designed as an always in system, but trades are only taken in line with the fundamentals, so if a 10 day low is breached on a long position supported by the fundamentals, then Gallacher will exit only re-entering on breaching the 10 day high assuming the fundamentals are still bullish at that point.

Ken Roberts 1-2-3 Methodology

As a trend follower Roberts simply employs a trailing stop below consolidation areas.

In summary, I personally found nothing new in this chapter, and if anything I found it a little weaker than the rest of the book so far. Perhaps it was just the content being familiar to me that made me feel that way.

Chapter Eleven: The Opportunity and Cost Factors

The first part of this chapter refers back to the different types of trader and expectancies, but adds in the opportunity factor and nicely shows how increased trading opportunity can level the expectancy playing field or indeed tip it firmly in the favour of the frequent trader so even a system with very low reliability and expectancy can still be the most profitable.

The Cost of Trading Opportunity

Although cost is part of expectancy, Van Tharp expands on the cost reduction side of things. We already know that frequency of trade increases the relevance of cost as does a lower trading account size so Van Tharp talks about:

Look for Low Commission

Kind of a no brainer here but best execution at lowest price has to be the goal, and from a personal slant don’t be afraid of overseas brokers – US discount brokers do seem to add value over UK ones for example!

One warning though – Van Tharp correctly emphasises speed and availability of execution during high volatility which is an essential pre-requisite and having been on the wrong side of that in the past (UK broker not even discount but with shocking execution) I have to concur!

Execution Costs

Here Van Tharp means bid/ask and slippage. Clearly less of an issue for longer term traders, but anyone trading short term needs to be very clear on the impact of these costs.

Although Van Tharp does not go this far, I would always recommend using instruments with the smaller bid/asks and highest order flow to try and reduce this sneaky cost.

The Cost of Taxes

We are reminded of the cost of taxes but it is out of scope for the book but IMO a very important discussion could be had here – however because of the fear of being sued for giving tax advice I will leave it alone as well lol.

Psychological Costs

We must never forget the psychological toll trading takes, not just on us but our loved ones. The best way to reduce the effects is to plan your trades and trade your plans – without exception – and plan time to enjoy the rewards!

In summary a brief but necessary chapter – lest we forget these important considerations and in particular to remind us of the need to factor opportunity and costs into any system development.

Chapter Twelve: What Do You Mean Position Sizing?

This is probably another pivotal chapter in the book, and Van Tharp quickly defines money management (which he refers to as position sizing).

It is not that part of your system that dictates how much you will lose on a given trade.
It is not how to exit a profitable trade.
It is not diversification.
It is not risk control.
It is not risk avoidance.
It is not that part of your system that maximises performance.
It is not that part of your system that tells you what to invest in.
Money management is that part of your system that answers the question “how much?” throughout the course of a trade.

We may need to consider the above items to help determine position size, but none equate to position size in themselves.

Van Tharp in explaining the issue of account size refers us back to the snowball analogy and explains simply put that, if one black snowball which is bigger than the wall is thrown at the wall, then it doesn’t matter about the ratio of black to white snowballs, the wall WILL be destroyed. Remember that the wall is reflects the account size in the analogy.

Van Tharp goes on to suggest that an account size of under $50,000 or local equivalent is small, and in reality the average account size is nearer $1,000 to $10,000 so the mathematical odds are stacked against them.

I would echo this as I know I have been guilty in the early days of loading up the lot size to get some return that were worthy (psychology of greed), only to nearly devastate the account due to a run of losses, yet every time I risk 1-2%, things seem just to go smoother!

We know that a 50% drawdown actually means you need a 100% return to get back to breakeven so inappropriate position size can lead to the need for improbable returns just to stay in the game.

When I lost 60% in my pension account it has taken me nearly two years but I am still just over 80% of where I started – that’s still 33% return over two years – but it illustrates the point nicely.

Position Sizing Strategies

Van Tharp then describes two main classes of position sizing strategy – Martingale and Anti-Martingale.

Martingale is where you increase your bet size each time you lose, and Anti-Martingale is where you increase bet size when you are winning.

Martingale requires vast capital size to trade effectively, and most people simply don’t have that kind of cash and in any case risk reward would be psychologically difficult to handle on any meaningful run of losses.

Anti-Martingale however works according to Van Tharp – both in the casino, and in trading and Van Tharp then goes on to explain a variety of position sizing strategies, all of which are Anti-Martingale.

In order to demonstrate the systems, Van Tharp uses a single trading system in order to show the effects of each strategy which is a 55 day channel breakout with a 21 day channel trailing stop and is used consistently across a basket of 10 commodities from 1981 through 1991.

Model 1: One Unit Per Fixed Amount of Money

Basically one unit per $50,000 or whatever. This allows you to always take a trade, but if you are trading multiple markets, then the value of that unit will vary whether the unit be a futures contract or lot of shares. When you add volatility then the distortion becomes larger and thus this method whilst allowing all trades, does not give an equal exposure in all trades and distorts dependency on some markets.

Using the standard trade as described earlier, the system broke down completely using one unit per $20,000, and actually needed $70,000 to prevent a 50% drawdown!

Increasing unit size can only be done very slowly and thus Van Tharp considers that this system means no real position sizing for a small account.

Model 2: Equal Value Units for Stock Traders

This strategy is used with non-leveraged instruments and is where your capital is divided into 5-10 parts and the resultant part then purchases x units dependant on the value of the underlying, so for shares valued at $100 per share with $10,000 you buy 100 shares and for a $20 share you buy 500. A similar principle could apply to futures by determining how much of a product you wanted to control and only buying those contracts where this could be achieved.

This system therefore gives equal weighting to any investment and allows you to know what leverage you are carrying. But again has the disadvantage of adding to units very slowly so again is considered as “no” position sizing for a small account.

Model 3: The Percent Risk Model

This is the first system which allows the 1-R principle to be applied equally across investments and is probably the most familiar method of position sizing discussed in trading circles, you will have seen many IT members, including myself counselling against a position size of more than 2% per trade.

Van Tharp adds some twists to the basic formula by suggesting that if a high frequency tight stop trade system with lower reliability exists then perhaps we should halve the acceptable position size.

He also suggests that you should not trade this system with less than $100,000 and even then not use more than 0.5% per trade. (As the book was updated in about 1997 Van Tharp does not appear to consider FX or the relatively recent advent of mini futures contracts so this amount could be lower if written today.)

Model 4: The Percent Volatility Model

Volatility is expressed by the average true range of an instrument and this method adds volatility into the mix. Van Tharp explains this by using gold at $400 an ounce (now that would be a buying opportunity!). In his example ATR was $3, and the per point move was $100, thus daily volatility gives a value of $300. If volatility is allowed to be 2% of $50,000 account then we risk $1,000 which divided by $300 gives 3.3 contracts so we could get 3 contracts.

Running the same model strategy gives the best risk reward using about 2.5% volatility but has a crucifying drawdown of 86%. Most it is suggested would use 0.5 to 1% volatility.

Care has to be exercised on what figures are used as the parameters, but the system is good, many people fail to use it – possibly due to its sophistication / complexity.

Van Tharp summarises the models by saying that any position sizing model that does not treat all trades with equal merit should be disregarded.

The impact of Position Sizing

Van Tharp then goes on to show how the models apply to a series of trades taken over a portfolio of 30 DJIA stocks from January 1992 to June 1997 trading a channel breakout long only entry based on breakout over a 45 day high and 3 x ATR trailing stop to exit.

A $1m portfolio was used with transaction costs of 0.5% – during the period the system took 595 trades of which 273 won and 322 lost so 45.9% were winners.

First series was a baseline of 100 shares whenever the system signalled entry, this showed 0.58% compound annual return (CAR) with maximum drawdown 0.75%.

Next tested was the fixed amount model which returned 5.75% CAR and maximum drawdown 7.13%.

Equal Value returned 3.86% CAR and 3.72% maximum drawdown.

1% model produced 20.92% CAR and maximum drawdown 14.14%.

Lastly a 0.5% volatility model was used which gave 22.93% CAR and maximum drawdown 16.61%.

Again Van Tharp goes back to discuss the position sizing used in the systems previously discussed:

William O’Neil’s CANSLIM System

O’Neil uses a form of the equal value model but modifying the number of equal splits made based on account size.

Warren Buffett’s Business Approach

Buffett just adds when something meets his criteria.

Motley Fool Foolish-Four Method

Again equal value but with a twist in that one stock is twice the share of the rest.

Kaufman’s Adaptive Methods

Kaufman does not talk about position size per se but introduces a variation on risk using standard deviation to determine probability of levels of drawdown and adjusting size to reflect individual considerations.

Gallacher’s Fundamental Trading

Gallagher objects to the percent model as all things are not equal, for example one contract of corn risking 1% or $500 is less risky than trading 2 contracts risking $250 each due to the relative closeness of the stop placement.

He goes on to argue that you should determine the greatest drawdown you can tolerate and that it occurs on day one, and then calculate how much capital is needed to avoid that level of drawdown so this is a variation of one unit per $x of account but varying by volatility.

Ken Roberts 1-2-3 Methodology

Roberts caters for smaller traders and therefore suggests the one contract system and therefore position sizing does not get much coverage and is therefore dangerous.

In summary we can now clearly see the effect of position sizing but Van Tharp is quick to warn that there are potentially millions of permutations available and some serious research lies ahead for those serious in understanding this better.

If like me you have kept a trading journal then the first step may be to see what impact variations of the models would have made to your performance – but that would take some serious excel work so I will have to come back to that after my Prop Firm course – it will be interesting to compare how they approach position sizing.

Chapter Twelve: Conclusion

To be a money master, you must be a self-master. (J. P. Morgan)

In conclusion Van Tharp reminds us that the Holy Grail is inside us all, we just have to find it! To do this we need to know what we want to achieve and plan around those objectives and ensure to cut losses and let profits run which is all about the control of exits as a major part of any system.

We need to understand the relative importance of system reliability, reward to risk ratio, cost of trading, trading opportunity levels, size of equity and position sizing.

In doing so we must then have a good handle on expectancy and how that relates to opportunity and cost and how important size of equity is to anti-martingale position sizing.

Having done all that Van Tharp acknowledges that this is just the start and goes on to touch on several topics that are outside of the scope of the book, but will in turn demand attention:


We are warned that data represents that market and is not the market, he also warns on reliability of the date which we have seen many time here at IT, the last time being the blog entry I referred to at the beginning of my entry Is your broker cheating like this


Unsurprisingly we are warned against the black box type of software that will almost certainly be curve fitted to historical data and this is a subject that has come up many times. That said software is an essential component so choose with care!


Yes we need to test, but we also need to acknowledge that backtesting in particular is fraught with issues not least because of data, or even if visually backtesting, then seeing what we want to see.

Testing needs to be done but we need to accept that effectively nothing is an exact science and steel ourselves accordingly.

Order execution

Things have moved on a tad since the book was written and order execution has too. That said we need to be sure we have the right broker as discussed earlier, but also ensure you have backup plans, the telephone number of your broker in case of internet failure for example. In fact I would say a sensible part of any business plan is a form of business resumption plan, think of all the things that could (and do) go wrong, and plan how you will deal with them and what effects they could have on your system, profitability and psyche.

Multiple systems

Markets change! Always consider having different systems available to you whatever the market conditions, and always give yourself the opportunity to trade.



What do you think the most important thing is that traders or investors can do to improve their performance?

That’s an easy question, but the solution is not easy. Take total responsibility for everything that happens to you – in the market, and in your life.

Last words of wisdom

Van Tharp finishes by briefly talking about beliefs, and how important it is to have a belief system in yourself.

He also points out that even sub-consciously as we read this book, we will filter according to our beliefs – I know I did and reflected that in some of my comments. So with that in mind, read the book several times to ensure you get it all!