What do you see trading as? Do you see it as:

* An exchange, involving the buying or selling of goods or services?
* A game that can be exciting for speculators?
* A tool, for example, one that enables traders to hedge the market?
* A war, albeit one without bloodshed?
* A business that happens to be the most difficult thing in the world?

Depending on the person giving the answer, there are elements of all of these in
trading. However, our answer is that we choose to see trading as a business. There are two basic types of participants in the futures and commodity markets:
hedgers and speculators. The hedgers are those seeking to minimize and manage price risk. Speculators are those willing to take on risk in the hope of making a profit. It doesn’t matter whether you are either a speculator or a hedger. We all need to treat trading as a business.

Why Do You Need a Business Plan for Trading?


In the following, we will reason why you need a business plan and how to compare it with a normal business.

Turning Crisis into Opportunity

In 2008 and 2009, some individuals and mutual funds found that their accounts lost 50 percent of their value. If you had been holding stocks of blue chips—General Motors (GM), AIG, or Citibank (C)—for 20 years, those stock values dropped 90 percent. It’s a very scary situation. To protect what you’ve earned is not an easy job in today’s fast-changing, volatile market. Should you exit or hold tight? Should you buy more shares or take partial profits? Able Trend helps you answer these questions. 

The software allows you to quickly and easily auto-scan the markets in your 401(k) or IRA accounts. You can instantly con- firm that support levels are still in place for your retirement investments. You can place stop orders to ensure that a market crash won’t mean a major setback to your financial security. To prepare for the greatest financial crisis we’ve ever seen in modern times, you need to use an advanced trading tool, such as Able Trend, for a ground-zero look at what’s unfolding globally. You need a more precise view of the markets than has ever before been possible! You need a more coolheaded guide, helping you find early trends around the world that offer the greatest investment opportunity, while helping you manage your risk. Instead of following the crowd, you’ll have a chance to get in ahead of the crowd as you find early trends that most investors don’t even know exist yet.

Zero-Sum Game

Remember, trading is a zero-sum game. Trading doesn’t create wealth, but rather it transfers wealth from one to another. It is peaceful on the surface, but it is a war without guns and bloodshed. Remember, if you win, someone must lose, and vice versa. As we know, the final purpose of any war is to achieve economic or financial goals. Some people view trading as a big gambling game. Many years ago, if you told others that you were a futures trader, people might think you were a risky speculator, and you were not considered as being anything other than a gambler. In fact, trading actually arises from the real needs of the economic and financial activities of society. I don’t need to spend much time explaining this.

 There are libraries of books about what trading and the markets are. The critical point is this: Trading is a business. Since it is a business, we must treat it as a business, and not as a gambling game. Since it has the nature of war, we should be well prepared before jumping into the “war zone” of trading. However, as yet there are no business schools or universities that officially teach the business of trading. There are no such trading-related courses, or majors, or degrees for trading within our school system. Hundreds of billions of dollars exchange hands each year from one to another through the trading business, and yet there is little in the way of education to help people run their trading as a business, rather than a game of chance. Most traders come to the markets without a business plan for trading or even knowing what the basics of their business plan should be.

Beware of Fighting a War without a Plan


Fighting a war without a plan is equivalent to suicide. The only way to succeed is to use a proven winning system and stick to it. You must have a trading plan before you make any trades—and while a trade is under way, you must stick to it. Do not change your plan during the trading session unless you have a very good reason to do so. You can change your plan in future trades based on what you learn, but changing your plan mid-trade is usually based on emotion and leads to more severe losses. Enter the trading battlefield armed with time-tested risk management and money management strategies. This helps to remove guesswork and emotion in trading. The strategies and signals you will use to execute your trade are critical aspects of your overall trading plan.

Summary: Trading Is a Business

As when starting any business, you need a business plan to run your trading business. Table 4.1 is an outline of the basic features you should incorporate into your trading business plan, as they compare to the features that are normally included in any standard business plan.





Price is the balancing point of supply and demand. In order to estimate the future price of any product or explain its historic patterns, it will be necessary to relate the factors of supply and demand and then adjust for inflation, technological improvement, and other indicators common to econometric analysis. The following sections briefly describe these factors.



The demand for a product declines as price increases. The rate of decline is always dependent on the need for the product and its available substitutes at different price levels. In Figure , D represents normal demand for a product over some fixed period. As prices rise, demand declines fairly rapidly. D′ represents increased demand, resulting in higher prices at all levels. Figure  represents the actual demand relationship for potatoes from 1929 to 1939. Although this example is the same as the theoretical relationship in Figure , in most cases the demand relationship is not a straight line. Production costs and minimum demand prevent the curve from going to zero; instead, it approaches a minimum price level.

 This can be seen previously in the frequency distribution for wheat, Figure  where the left side of the distribution falls (lower price) off sharply. On the higher end of the scale, there is a lag in the response to increased prices and a consumer reluctance to reduce purchasing even at higher prices (called “inelastic demand”). Coffee is well-known for having inelastic demand—most coffee drinkers will pay the market price rather than consume less. Figure shows a more representative demand curve, including extremes, where 100 represents the cost of production for a producer. The demand curve therefore, shows the rate at which a change in quantity demanded brings about a change
in price. Note that, although a producer may lose money below 100, lack of demand and the need for income can force sales at a loss.

Elasticity of Demand


Elasticity is the key factor in expressing the relationship between price and demand and defines the shape of the curve. It is the relative change in demand as price increases A market that always consumes the same amount of a product, regardless of price, is called inelastic; as price rises, the demand remains the same, and E D is negatively very small. An elastic market is just the opposite. As demand increases, price remains the same and E D is negatively very large. Figure  shows the demand curve for various levels of demand elasticity. If supply increases for a product that has existed in short supply for many years, consumer purchasing habits will require time to adjust. The demand elasticity will gradually shift from relatively inelastic  to relatively elastic . 


The supply side of the economic equation is the normal counterpart of demand.
Figure  shows that, as price increases, the supplier will respond by offering greater amounts of the product. Figure demonstrates the supply at price extremes. At low levels, below production costs, there is a nominal supply by those producers who must maintain operations due to high fixed costs and diffi- culty restarting after a shutdown (as in mining). At high price levels, supply is erratic. There may be insufficient supply in the short term, followed by the appearance of new supplies or substitutes, as in the case of a location shortage. When there is a shortage of orange juice, South American countries are willing to fill the demand; when there is an oil disruption, other OPEC nations will increase production. In most cases, however, it is reduced demand that brings price down.

Elasticity of Supply

The elasticity of supply E S is the relationship between the change in supply and the change in price The elasticity of supply, the counterpart of demand elasticity, is a positive number because price and quantity move in the same direction at the same time.



The demand for a product and the supply of that product cross at a point of equilibrium. The current price of any product, or any security, represents the point of equilibrium for that product at that moment in time. This is the basis for the technical assessment that the price, at any moment in time, represents the netting of all fundamental information. Figure  shows a constant demand line D and a shifting supply, increasing to the right from S to S ′. The demand line D and the original supply line S meet at the equilibrium price P; after the increase in supply, the supply line shifts to S ′.

 The point of equilibrium P ′ represents a lower price, the consequence of larger supply with unchanged demand. Because supply and demand each have varying elasticities and are best represented by curves, the point of equilibrium can shift in any direction in a market with changing factors. Equilibrium will be an important concept in developing trading strategies. Although the supply and demand balance may not be calculated, in practical terms equilibrium is a balance between buyers and sellers, a price level at which everyone is willing to trade, although not always happy to do so at that price. Equilibrium is associated with lower volatility and often lower volume because the urgency to buy or sell has been removed.Imbalance in the supply-demand-price relationship causes volatility. Readers interested in a practical representation of equilibrium, or price-value relationships, should study “Price Distribution Systems” in Steidlmayer’s Market .

Cobweb Charts


The point at which the supply and demand lines cross is easily translated into a place on a price chart where the direction is sideways. The amount of price volatility during this sideways period (called noise) depends upon the price level, market participation, and various undertones of instability caused by other factors. Very little is discussed about how price patterns reflect the shift in sentiment between the supply and demand lines, yet there is a clear representation of this action using cobweb charts. shows a static (symmetric) supply-demand chart with dotted lines representing the “cobweb.” A shift in the perceived importance of supply and demand factors can cause prices to reflect .

the pattern shown by the direction of the arrows on the cobweb, producing the sideways market represented by Figure. If the cobweb were closer to the intersection of the supply and demand lines, the volatility of the sideways price pattern would be lower; if the cobweb were further away from the intersection, the pattern would be more volatile. 4 Most supply/demand relationships are not static and can be represented by lines that cross at oblique angles. In Figure  the cobweb is shown to begin near the intersection and move outwards, each shift forming a different length strand of the web, moving away from equilibrium. Figure  shows that the corresponding price pattern is one that shifts from equilibrium to increasing volatility. A reversal in the arrows on the cobweb would show decreasing volatility moving toward equilibrium.


 Building a Model


A model can be created to explain or forecast price changes. Most models explain rather than forecast. Explanatory models analyze sets of data at concurrent times: that is, they look for relationships between multiple factors and their effect on price at the same moment in time. They can also look for causal, or lagged relationships, where prices respond to other factors after one or more days. It is possible to use the explanatory model to determine the normal price at a particular moment. Although not considered forecasting, any variation in the actual market price from the normal or expected price could present a trading opportunity. Methods of selecting the best forecasting model can affect its credibility. An analytic approach selects the factors and specifi es the relationships in advance.

Tests are then performed on the data to verify the premise. Many models, though, are refined by fitting the data, using regression analysis or some mass testing process, which applies a broad selection of variables and weighting factors to find the best fit. These models, created with perfect hindsight, are far less likely to be successful at forecasting future price levels. Even an analytic approach that is subsequently fine-tuned could be in danger of losing its forecasting ability. The factors that comprise a model can be both numerous and difficult to obtain. Figure  shows the interrelationship between factors in the cocoa industry. Although this chart is comprehensive in its intra market relationships, it does not emphasize the global influences that have become a major part of price movement since the mid-1970s.

The change in value of the U.S. dollar and the volatility of interest rates have had far greater influence on price than some of the “normal” fundamental factors for many commodities. Companies with high debt may find the price fluctuations in their stock are larger due to interest rate changes than increases or decreases in revenues. Models that explain price movements must be constructed from the primary factors of supply and demand. A simple example for estimating the price of fall potatoes 5 is.

P/PPI = a + bS + cD


P = the average price of fall potatoes received by farmers
PPI = the Producer Price Index
S = the apparent domestic free supply (production less exports and
D = the estimated deliverable supply
a, b, and c = constants determined by regression analysis

This model implies that consumption must be constant (i.e., inelastic demand); demand factors are only implicitly included in the estimated deliverable supply. Exports and diversion represent a small part of the total production. The use of the PPII gives the results in relative terms based on whether the index was used as an inflatorr or deflator of price.

A general model, presented by Weymar, 6 may be written as three behavior-based equations and one identity:


C t = f C ( P t , P t L ) + e C t





Having a trading plan is like having a solid blueprint to build your home, or having a map when traveling to a new location. You already know that a professional trader won’t survive in the markets without a good trading plan.
Now that you’ve defined your goals and created your trading plan, you need to make sure it really works. Thus far, everything might look great, but how can you be sure that the system works when you start trading it with real money?

Evaluating a trading strategy is easier than you think. In this topic you'll find 10 Principles of Successful Trading Strategies that we’ve developed and refined over the last couple of years.You should use these Power Principles to evaluate your trading strategy, whether you developed it on your own or are thinking about purchasing one. By checking a strategy against these principles, you can dramatically increase your chances of success.

 Principle #1: Use Few Rules – Make It Easy to Understand

It may surprise you that the best trading systems have less than ten rules. The more rules you have, the more likely that you’ve "curve-fitted" your trading strategy to past data, and such an over-optimized system is very unlikely to produce profits in real markets. It's important that your rules are easy to understand and execute. The markets can behave very wildly and move very fast, and you won't have time to calculate complicated formulas in order to make a trading decision. Think about successful floor traders: the only tool they use is a calculator, and they make thousands of dollars every day.


Take a look at the trading approaches presented in the section “Popular Trading Approaches.” The easy rules are: buy when the RSI drops below a reading of 20, or, sell when prices move above the upper Bollinger Band.

Avoid a trading strategy that has an entry rule like this:

Buy when the RSI is below 20, and the ADX is between 7 and 12, and the 7-bar moving average is pointing up more than 45 degrees, and there is a convergence between the price bars and the MACD, and, and, and...

Do you really think that you could follow this strategy while you’re watching the markets LIVE?

Principle #2: Trade Electronic and Liquid Markets

I strongly recommend that you trade electronic markets, because commissions are lower and you receive instant fills. You need to know as fast as possible if your order was filled and at what price, because you plan your exit based on this information. You should never place an exit order before you know that your entry order is filled. When you trade open outcry markets (non-electronic), you
might have to wait awhile before you receive your fill. By that time, the market might have already turned and your profitable trade has turned into a loss!

When trading electronic markets, you receive your fills in less than one second and can immediately place your exit orders. Trading liquid markets means you can avoid slippage, which will save you hundreds or even thousands of dollars.
Fortunately, more and more markets are now traded electronically. The recent addition of the grain futures markets in the summer of 2006 was a huge success: in January of 2007, the volume traded in the electronic contracts surpassed the volume traded in the pit markets. In December of 2007, the pit-traded corn contract traded with 621,800 contracts, while the electronic corn contract had a trading volume of 2,444,400 contracts. Most futures markets, all forex currency pairs, and the major U.S. stock markets are trading electronically. So why would you even want to trade Pork Bellies or Lumber?

Principle #3: Have Realistic Expectations

Losses are part of our business. A trading system that doesn't have losses is "too good to be true." Recently, I ran into a trading system with a whopping winning percentage of 91% and a drawdown of less than $500. WOW!

When I looked at the details, though, it turned out that the system was only tested on 87 trades and – of course – it was curve-fitted. If you run across a trading system with numbers too good to be true, then it's probably exactly THAT: too good to be true.

Usually you can expect the following from a robust trading system:

1.) A winning percentage of 60-80%
2.) A profit factor of 1.3-2.5
3.) A maximum drawdown of 10-20% of the yearly profit

Use these numbers as a rough guideline, and you’ll easily identify curve fitted systems.

Principle #4: Maintain a Healthy Balance Between Risk and Reward

Let me give you an example: if you go to a casino and bet everything you have on "red," then you have a 49% chance of doubling your money and a 51% chance of losing everything. The same applies to trading: you can make a lot of money if you’re risking a lot, but if you do, the risk of ruin is also high. You need to find a healthy balance between risk and reward.

Make sure your trading strategy is using small stop losses and that your profit targets are bigger than your stop losses.

Stay away from strategies that have a small profit target of only $100 and a stop loss of $2,000. Sure, the winning percentage will be fantastic, but 2-3 losses in a row can wipe out your trading account.

The perfect balance between risk and reward is 1:1.5 or more – i.e. for every dollar you risk you should be able to make at least $1.50.

In other words, if you apply a stop loss of $100, your profit target should be at least $150.

Principle #5: Find a System That Produces at Least Five Trades per Week

The higher your trading frequency, the smaller your chances of having a losing month. If you have a trading strategy that has a winning percentage of 70%, but only produces one trade per month, then one loser is enough to have a losing month. In this example, you could have several losing months in a row before you finally start making profits.
 In the meantime, how do you pay your bills?
If your trading strategy produces five trades per week, then you have on average 20 trades per month. If you have a winning percentage of 70%, then your chances of a winning month are extremely high.
And that's the goal of all traders: having as many winning months as

Principle #6: Start Small – Grow Big

Your trading system should allow you to start small and grow big. A good trading system allows you to start with one or two contracts, increasing your position as your trading account grows.
This is in contrast to many "martingale" trading systems, which require increasing position sizes when you are in a losing streak. You’ve probably heard about this strategy: double your contracts every time you lose, and one winner will win back all the money you previously lost.

Principle #7: Automate Your Exits

Emotions and human errors are the most common mistakes that traders make. You have to avoid these mistakes by any means necessary, especially when the market starts to move fast. You might experience panic and indecision, but if you give in to those emotions, you’ll suffer a much greater loss than you had originally planned for.

Your exit points should be easy to determine. The best solution for your exit points is the use of “bracket orders.” Most trading platforms offer bracket orders, which allow you to attach a profit target and a stop loss to your entry.

This way, you can put your trade on autopilot, and the trading system will close your position at the specified levels.

Of course, this assumes that you have easy exit rules. A stop loss of $100, or 1%, of the entry price can easily be specified in today’s trading platforms.

Exit rules like “2/3 of the average true range of the past 5 trading days” are more complex to automate. In the beginning, you should keep your trading as simple as possible.

If you can’t make money with simple entry and exit points, you won’t be able to make money with more complex trading rules. Think about driving a car: if you can’t drive a Ford, you definitely won’t be able to drive a Ferrari.

Principle #8: Have a High Percentage of Winning Trades

Your trading strategy should produce more winners than 50%. There's no doubt that trading strategies with smaller winning percentages can be profitable, too, but the psychological pressure is enormous.

Taking 7 losers out of 10 trades, and not doubting that system, takes a great deal of discipline, and many traders can't stand the pressure. After the sixth loser, they’ll start "improving" the strategy, or stop trading it completely.

It’s very helpful for beginning or novice traders to gain confidence in their trading, and if your strategy gives you a high winning percentage, let’s say more than 65%, your confidence will definitely be on the rise.

Principle #9: Test Your Strategy on at Least 200 Trades

The more trades you use in your back-testing (without curve-fitting), the higher the probability that your trading strategy will succeed in the future. Look at the following table:

Number of Trades      50     100     200   300    500
<>Margin of Error    14%   10%     7%    6%     4%

The more trades you have in your back-testing, the smaller the margin of error, and the higher the probability of producing profits in the future.

You need at least 40 trades for a valid performance report. As you can see from the table above, 200 trades are optimal, since the margin of error decreases fast from 14% to 7% with only an addition 150 trades.

If you test your system on more than 200 trades, the margin of error decreases at a slower rate. The next 100 trades only increase the confidence by 2%.

Principle #10: Choose a Valid Back-Testing Period

Take a look at your trading strategy and run it against these 10 Power Principles. How many principles apply?

If your trading strategy doesn’t fulfill all 10 Principles, is there any area in which you can improve it?




Once you’ve determined which markets you want to trade, selected a time frame, and defined your entry and exit rules, it’s time to test and evaluate your trading strategy.
There are three ways to test your trading strategy:


Back-testing is a method of testing which will run your strategy against prior time periods. Basically, you’re performing a simulation: you use your strategy with relevant past data to test its effectiveness. By using the historical data, you’re saving a ton of time; if you tried to test your strategy by applying it to the time periods yet to come, it might take you years. Back-testing is used for a variety of strategies, including those based on technical analysis. The effectiveness of back-testing relies on the theory that what has happened in the past WILL happen again in the future. Also, keep in mind that your backtesting results are quite dependent on the moves that occurred in the tested time period. It’s important to remember that this increases the potential of risk for your strategy.

The Monte-Carlo Simulation

The Monte-Carlo Simulation is a problem-solving technique used to approximate the probability of certain outcomes by running multiple trial runs – called simulations – using random variables. It is a way to account for the randomness in a trading parameter – typically, the sequence of trades. In Monte Carlo simulations, the basic idea is to take a sequence of trades generated by a trading system, randomize the order of trades, and calculate the rate of return and the maximum draw down, assuming that x% of the account is risked on each trade.
The process is repeated several hundred times, each time using a different random sequence of the same trades. 

You can then pose a question such as "If 5% of the account is risked on each trade, what is the probability that the maximum draw down will be less than 25%?" If 1,000 random sequences of trades are simulated with 5% risk, for example, and 940 of them have a maximum draw down of less than 25%, then you could say the probability of achieving a maximum draw down of less than 25% is 94% (940/1,000). Keep in mind that the data used in Monte Carlo Simulations is still historical data; therefore, one could say that this simulation is a more sophisticated way of back-testing.

Paper Trading

Paper trading is a method of “risk-free” trading. Basically, you set up a dummy account, through which you can test your trading strategy with paper money. 

There are two methods to this:

you can either pretend to buy and sell stocks, bonds, commodities, etc., and keep track of your profits and losses on paper, or you can open an account online, usually through your broker (and usually for free). This is a fantastic way for new traders to kill a whole tree full of birds with one stone. First off, you’ll learn the tricks of the trade without putting your own money at risk. Second, you’ll be able to gain some much-needed confidence when it comes to maneuvering in the markets. And third, you’ll be able to test out your trading strategy in real-time simulation. This is probably the best way to test a trading strategy, since it doesn’t rely on historical data. On the other hand, it’s the most time-consuming strategy, since it might take weeks or months until you have enough data for a statistically relevant performance report.


When back-testing, there are definitely things you need to be aware of. It's not enough to just run a strategy on as much data as possible; it's important to know the underlying market conditions. As outlined in previous chapters: in non-trending markets, you need to use trend-fading systems; and, in trending markets, you should use trend following methods.

That's when clever back-testing helps you. If your back-testing tells you that a trend-following method worked in 2011-2013, but doesn't work in 2014 and 2015, then you should not use this strategy right now. And vice versa: when you see that a trend-fading method produced nice profits in 2010 , 2011 and 2012 then trade it.

How to Read and Understand a Performance Report

While testing your trading strategy, you should keep detailed records of the wins and losses in order to produce a performance report. Many software packages can help you with that, but a simple excel sheet will do the trick just as well. If you get in contact with us here at Rockwell Trading®, we can send you an excel sheet that will automatically produce a performance report for you after you’ve entered several trades.

 Total (Net) Profit

The first figure to look for is the total, or net, profit. Obviously you want your system to generate profits, but don’t be frustrated when, during the development stage, your trading system shows a loss; try to reverse your entry signals.

You might have heard that trading is a zero sum game. If you want to buy something (e.g. a certain stock or futures contract), then somebody else needs to sell it to you. And, you can only sell a position if somebody else is willing to buy from you at the price you're asking. This means that if you lose money on a trade, then the person who took the other side of the trade is MAKING money. And vice versa: if you’re making money on a trade, then the other trader is losing money. In the markets, money is not "generated." It just changes hands. So, if you’re going long at a certain price level, and you lose, then try to go short instead. Many times this is the easiest way to turn a losing system into a winning one.

Average Profit per Trade

The next figure you want to look at is the average profit per trade. Make sure this number is greater than slippage and commissions, and that it makes your trading worthwhile. Trading is all about risk and reward, and you want to make sure you get a decent reward for your risk.

Winning Percentage

Many profitable trading systems achieve a nice net profit with a rather small winning percentage, sometimes even below 30%. These systems follow the principle: “Cut your losses short and let your profits run.” However, YOU need to decide whether you can stand 7 losers and only 3 winners in 10 trades. If you want to be “right” most of the time, then you should pick a system with a high winning percentage.

Understanding Winning Percentage

Let's say you purchased or developed a system that has a winning percentage of 70%.

What exactly does that mean?

It means that the probability of having a winning trade is 70% – i.e. it is more likely that the trade you are currently in turns out to be a winner rather than a loser. Does that mean that when you trade 10 times you will have 7 winners? No!
It means that if you trade long enough (i.e. at least 40 trades) then you will have more winners than losers. But it doesn’t guarantee that after 3 losers in a row, you’ll have a winner.


If you toss a coin then you have 2 possible outcomes: heads or tails. The probability for each is 50% – i.e. when you toss the coin 4 times, then you should get 2 heads and 2 tails.

But what if you tossed the coin 3 times and you got heads 3 times?

What is the probability of heads on the fourth coin toss?

50%, or less?

If you answered 'less,' than you fell for a common misconception. The probability of getting heads again is still 50%. No more and no less.

But many traders think that the probability of tails is higher now because the three previous coin tosses resulted in heads. Some traders might even increase their bet because they are convinced that now “tails is overdue.” Statistically, this assumption is nonsense; it’s a dangerous – and many times costly – misconception.

Let's get back to our trading example: if you have a winning percentage of 70%, and you had 9 losers in a row, what’s the probability of having a winner now? It's still 70% (and therefore there's still a 30% chance of a loser).

Average Winning Trade and Average Losing Trade

The average winning trade should be bigger than the average losing trade. If you can keep your wins larger than your losses, then you’ll make money even if you just have a 50% winning percentage. And every trader should be able to achieve that. If you can’t, reverse your entry signals as described previously.

Profit Factor

Take a look at the Profit Factor (Gross Profit / Gross Loss). This will tell you how many dollars you’re likely to win for every dollar you lose. The higher the profit factor, the better the system. A system should have a profit factor of 1.5 or more, but watch out when you see profit factors above 3.0, because it might be that the system is over-optimized.

Maximum Drawdown

The maximum drawdown is the lowest point your account reaches between peaks.

Let me explain:

Imagine that you start your trading account with 10,000, and, after a few trades, you lose 2,000. Your draw down would be 20%. Now, let's say you make more trades and gain 4,000, which brings you to 12,000 (8,000 + 4,000 = 12,000). And after this, on the next trade, you lose 2,000. Your draw down would be 16.7% (12,000 - 2,000). The 12,000 was your equity peak; that was the highest point in the period we looked at. If you started your account with 10,000 and the lowest amount you had in your account over a six-month period was 5,000, then you had a 50% draw down You would need to make 5,000 from the lowest point in order to recoup your losses. Even though you lost 50% from your high of 10,000, you would need to make 100% on the 5,000 to get back to your original amount.

Measuring Drawdown Recovery

Drawdown recovery can confuse many traders. If a trader loses 20% of his account, he thinks he needs to make 20% in order to get back to even. This isn’t true. If you started with 10,000 and lost 2,000 (20%), you would need to make 25% in order to get back to even. The difference between 8,000 and 10,000 is 2,000. If you calculate the 2,000 as a percentage of 8,000 (not the original 10,000) it works out to 25%. A famous trader once said: “If you want your system to double or triple your account, you should expect a drawdown of up to 30% on your way to trading riches.” Not every trader can stand a 30% drawdown. Look at the maximum drawdown that your strategy has produced so far, and double it. If you can stand this drawdown, then you’ve found the right strategy. Why double it? Remember: your worst drawdown is always ahead of you. It’s best to plan for it now.


The above examples provide you with some guidelines, but it’s up to you to decide whether the numbers in the strategy’s performance report work for you or don’t. Ultimately, YOU’RE the one trading the strategy, and YOU’RE the one who has to feel comfortable with the expected results of your strategy.

Action Items:

* Start back-testing your trading plan on at least 40 trades. The more trades the better. You can download an excel sheet to record your trades from our website.

* Analyze the performance report and decide if YOU feel comfortable with the statistics.




to be a good option trader, one must first be a good trader. Sometimes the particular complexities of managing an option position can blind us to this fact. In order to be successful, we have to put ourselves in situations where we can buy low and sell high. Humans have been trading forever. Despite this, there is no consensus about what good trading practices are. Perhaps when it comes to specifics this is to be expected. By its nature successful trading can destroy the anomalies that make it possible. However, at a more general level we can state the essential characteristics that all successful trades must have. Further, it is almost certainly a better idea to improve upon a method that others have found to be successful than to try to find something completely new.

I want to emphasize the place of this chapter. This is meant to complement innate trading skill, which I certainly believe exists. I do think that a solid grasp of the quantitative analysis of probability and strategies can benefit any trader, but knowing all of these things is not enough to make a good trader. Traders already do a lot of quantitative analyses, often subconsciously. Good traders can read patterns and prices in ways that statistical analysis still finds too hard. As I have stated several times, measurements in markets are very context-dependent, and a good trader often has keen insight into what variables are currently important.

Too many quantitatively driven traders dismiss the decisions of intuitive traders as merely arbitrary and little more than guesswork. But at least some intuitive traders make very thorough analyses of the situations they see. That this is subjective is generally because it is the best or only way to quickly amalgamate the data, place it into context and produce a conclusion. Granted, many more traders think they have this skill than actually do, but we should never totally dismiss the idea. Some intuitive traders, like some statisticians or some scientists, are not very good. They are irrational or even just stupid. But for those who are not, I hope this chapter helps them a little. This chapter is about general trading principles. We may use option examples in places, but the concepts are more broadly applicable. The specifics of trading options will be covered in later chapters.


You must have a definite source of edge. This is something that gives your trades positive expected value. Very loosely speaking, for something to be a source of edge it must be correct and not widely known. This second part is often forgotten. If you know only what others know, this is valueless. It will already be priced into the market. This is why, even if I was so inclined, it would be impossible for me to give you a recipe for profitable trades. The publishing of the recipe would render the trades generated from it almost immediately useless.

Looking for positive expected value is not the same as making only trades that we expect to win. This flawed thinking leads to the nonsense, “You only have to win more often than you lose.” This is simply wrong. The winning percentage of a trader is not enough to know if he has been, let alone will be, successful. A similar error is perpetrated by those who refuse to buy options, on the basis that most expire out-of-the-money. This is a mistake made by even the most experienced traders.

You must have some idea why a particular trade has positive expected value. Back-testing an idea will show you that something has worked in the past, but there are an infinite number of combinations of trade ideas, parameters, and products. Obviously some of these will have produced successful trades in the past. We need to know why they will do so in the future. This gives us confidence, but also tells us when to stop a particular trade. If you have no knowledge of why something worked in the first place, it is very tough to know that it has stopped working. Evaluating its diminishing effectiveness just from watching the results can be expensive and is also often difficult, as all trades will go through bad stretches.


A hedge is a trade that we enter in order to somehow offset an existing position. For example, imagine that we buy the 100 call because its implied volatility is cheap. However, this makes us synthetically long the underlying, so we sell some of the underlying short in order to mitigate our directional exposure. This is a hedge. We see in Chapter 4 that this idea is at the core of option pricing, but when should we hedge trades in general? We need to have an understanding of hedging concepts, so we can deal with the complexities that will occur in real trading situations. Ideally, we hedge all of the risks except those that we explicitly want to be exposed to. In practice this is seldom possible. Even most trades that we think of as arbitrages will have some minor difference in contact specifications. This exposes us to risk. Also common is the situation where a hedging instrument is available, but we have to weigh the benefits of hedging a risk against the costs of executing and managing another instrument.

There are a few situations where we should always at least consider hedging.

* We enter a trade that has multiple sources of risk and we only have positive expectation with respect to one of these. Directionally hedging an option trade to isolate the volatility exposure is an example of this situation.

* Our exposure has grown too big. This could happen as a result of losses in other parts of your portfolio, or it could occur when one position performs unexpectedly well. If you originally wanted a position to ac- count for a certain percentage of your risk, you should consider rebalancing when it significantly exceeds this.

* We can enter a hedge for no cost. For example, in times of market turmoil, it has sometimes been possible to enter long put or call spreads for zero cost or even a credit. This is a great situation. These spreads will probably be a long way out of the money. They have a low probability of making money. But they could pay off, and they cost nothing. It is like being given free lottery tickets. Such situations happen less often than they used to, but they still occur, particularly in pit-traded products.

* The hedge was part of the original trade plan. Sometimes we do certain trades because we are reasonably confident that an offsetting trade will present itself before expiration. In 1997, around 11 A . M . London time, a customer would buy several thousand 20 delta DAX puts in clips of one hundred. Once we had noticed this pattern we would have a few hours each morning to work at buying puts on the bid, knowing that our hedge would appear later. These situations occur frequently, and give market makers a significant source of profit.

All hedging decisions need to be made on the basis of a risk-reward tradeoff. And as soon as risk is introduced to a situation, personal preferences matter. What is seen as an unwanted risk by some traders will be welcomed by others. For a market maker, inventory is a source of risk that he will pay to remove, but for a position trader inventory is necessary to make money. But sometimes we just have a bad position. Part of the art of trading is recognizing this case and knowing when it is time to start again. In some types of trading this is all that position management is: merely a matter of knowing when to take profits and when to stop ourselves out of a bad position. Option positions are far more complex as they present us with multiple risks.

In fact the flexibility they offer us in being able to tailor our position to exact views of the market (for example, we might forecast that the underlying will rally slowly, both implied and realized volatilities will decrease, interest rates will remain stable, but a special dividend will be declared) can mean that we are complicit in getting ourselves into overly complex situations. Keeping things as simple as possible is a good idea in most situations. Option traders in particular have a tendency to fall into the trap of over complication. So, no matter what our views are and how certain we are in their correctness, we need always to be absolutely clear what it is we are trying to achieve, when we will admit we are wrong and what we will look to do to adjust our position as circumstances change. By definition, unforeseen circumstances cannot be predicted, however some contingency planning is always possible and the more it is done, the more effective it will become.




We will examine four market outlooks with trading strategies corresponding to each:

Bullish -  The expectation of an increase in price. This category has two subcategories:

* Moderately bullish-Although the outlook is for higher prices, the increase is not likely to be dramatic.

* Extremely bullish  - Expecting a dramatic, explosive increase in price (generally anticipated to occur in the short term)

Bearish -  The expectation of a decrease in price. This category has two subcategories :

* Moderately bearish - Although the outlook is for lower prices, the decrease is not likely to be dramatic.

* Extremely bearish - Expecting a dramatic sell-off in the stock (generally anticipated to occur in the short term)

* Neutral (front spread) - Expecting little price movement over a given time period. Neutral strategies enable the trader to make money in a market where prices remain the same or move little.

* Volatile (back spread) - The anticipation that prices will move dramatically, but the direction of that move is not clear.

Our goal in separating our discussion of strategies into the four general categories of bullish, bearish, neutral, and volatile is to provide our readers (after determining your market outlook) with a reference for the potential strategies. This chapter will also discuss risk-reduction strategies for managing an existing stock portfolio.


A number of these strategies involve option spreads. You construct a spread by being long an option(s) and being short an option(s) of the same type in the same underlying asset. For example, buying a call and selling another call with a different strike or a different expiration is a spread. Buying a put and selling another put with either a different strike or a different expiration is also a spread. In contrast, buying a call and either buying or selling a put is not a spread. 

Spreads offer the investor an array of strategies for attempting to benefit from almost any anticipated market condition while reducing risk. For example, you can use a spread to take a bull position or a bear position, for selling high volatility and buying low volatility, or to finance the purchase of other options. The degree of risk reduction varies among the different types of spreads. While some spreads have limited risk, others have risks that are comparable to buying the underlying security outright. There are several different types of spreads:

1. Calendar spread (in other words, a time or horizontal spread)-With this type of spread, all options are of the same type and have the same strike price and underlying asset, yet they have different expiration dates. The purchase (sale) of one option has a different expiration date from the sale (purchase) of another. Buying one XYZ March 85 call, for example, and selling one XYZ February 85 call would be a calendar spread.

2. Diagonal spreads-This kind of spread is similar to the time spread in that the options are of the same type and underlying asset; however, the expiration date and the strike prices are different. This time spread uses different strike prices. Buying one XYZ March 90 call and selling one XYZ February 85 call is an example of a diagonal spread.

3. Vertical spread-A vertical spread consists of options of the same type, on the same underlying asset, and with the same expiration date, but these options have different strike prices. Buying one XYZ May 90 put and selling one XYZ May 85 put is an example of a vertical spread.

4. Ratio spreads-A ratio spread is any of these types of spreads in which the number of options purchased differs from the number of options sold. Buying one XYZ July 90 call and selling two XYZ July 95 calls is an example of a ratio spread.


Several strategies involve three or more options strikes. As a practical matter, you cannot put on these positions simultaneously at reasonable prices. In order to achieve these positions at prices that produce an acceptable risk/reward profile, you must put on the positions in a series of separate trades. This process is called legging. Although the analysis of these specific positions includes a discussion of how to approach legging, we should give you some general comments concerning legging at this point. Until a position is fully legged into, your ability to complete the position at an acceptable price is subject to the risk of changing prices in the positions that you have not yet executed. The key to legging is knowing which order to execute the trades in order to minimize that risk.

To minimize this risk, we look at the supply and demand factor of each building block in the options strategy. Once we determine the supply and demand for each building block, the trader can leg into the position first from the building block that has the most demand and finish the implementation with the building block that has the most supply. This procedure is called legging the hard side first. The hard side is the trade that is the most difficult to put on. If the stock is rising rapidly in price and the trader wishes to purchase the stock, because the stock is rising, this side is considered the demand side.

The demand side refers to what the majority of traders are doing, whether buying or selling. If a stock is rising quickly, we would say that there is demand for the stock-hence, there would be more buyers than sellers. Selling the stock would be easy; because there are many buyers. We would then call this side the supply side. Because buying the stock in a rising market situation is difficult (getting a good price is difficult because of the high demand), we call this side the hard side.Consider the following example of legging the hard side

first. Assume that you are legging into a covered call in which the stock price is rising. Realizing that it will be harder to purchase the stock at a good price than it will be to sell the call, you should buy stock as the first part of the leg. Selling the call would be the easier of the two sides to fill, because the rising price of the stock should increase the demand for the call. If the trader decides to sell the call first in a rising market, he or she is taking the chance that he or she might not be filled on the stock at his or her price.


When a trader puts on a leg and cannot complete the rest of the position because the price for remaining legs has become unacceptable, the trader is said to be legged out. He or she now has a position that has gone against him or her, and it will be hard to close it without incurring a loss. Some of the option positions that we cover in this book can only be legged into. Do not even bother calling your broker with any fancy spread terminology such as a butterfly or iron butterfly: The market makers on the trading floor will just laugh your broker right out of the trading pit. There is no market maker in the world who will hand over free money, especially to a customer.

Bullish Strategies

Bullish strategies are among the most common strategies that individual investors use, probably resulting from the general view of the market that we acquire through the media and elsewhere is that rising stock prices are good, and falling stock prices are bad. In actuality, your position relative to that market movement-not the movement itself-is either good or bad for you. For example, if you position benefits from a declining market and the market does decline, that is good, while if instead it rallied, that would be bad. Most investors, then, are programmed to buy low and sell high. 

These are bullish investors who want to gain a profit from a rise in value or stock price. In fact, when investors tend to think of bullish strategies, the only thing that typically pops into their head is to purchase stock. To be sure, this strategy is great when the stock rises in price, but when a hefty sum of the investor's capital is committed to the position, this endeavor can be risky: In other words, while long stock purchase is not necessarily the wrong idea, it can be capital intensive and can create risk parameters that the individual investor might not totally understand. 

In this topic, we will show alternatives to purchasing stock, learn how to reduce market directional risk and capital exposure, and discuss the relevance of leverage. The first bullish strategy we will consider is long stock. Because long stock is the most commonly employed strategy and the one with which most traders are familiar, it will offer a good comparison study against the other bullish strategies described in this topic.




Options allow the investor to sculpt the returns in their portfolio. When you buy a stock and the price rises $1, you make $1. You lose $1 if the price declines $1. Your profits are linear and directly related to only the change in the price of the stock. Interest and dividends will make a slight change to the outcome though these factors are also linear. Options blow apart this linearity. Options are called convex instruments because the returns are not linear but curved. We saw that in the previous chapters. You can literally create millions of possible returns through the use of options. You can mix and match options to create just about any return possible.

Selecting a strategy is a multi step process. You should go through a systematic process before initiating a trade. Each step should lead to further refinement of the strategy. It can be very dangerous to your bank account to disregard some or all of the major factors that affect options prices. The most important factor that affects option prices is the price of the underlying instrument. But that is usually not the only thing that most investors look at. Only looking at the underlying instrument price can lead to significant losses for the investor. This strategy assumes that the edge that the investor has in stock selection is so superior that he can withstand a lot of headwinds caused by trading an option or options that have a lot of edges against him.

For example, what if the investor is buying a near dated call on U.S. Widget? But what if the options is overvalued and there is little gamma and the time decay is large. Here are three strikes against the investor. I have seen situations where the investor got the direction of the underlying instrument correct but all the other factors wrong and lost money on the trade. I am reminded of the old admonishment—don’t try this at home, kids. Options have a tremendous amount of power but also a lot of risk. So the design of your strategy should be the most important thing in your arsenal. You need to develop a particular frame of mind to trade options. You need to think multidimensional when you trade options. You must now think about time because options expire and the returns change over time.

 You need to think in terms of distance. By this I mean you must now consider how far the underlying instrument will move. For example, you may buy an out-of-the-money call that expires in three weeks. This means that you must expect the UI to rally at least up to the break-even point by expiration. This is very different from just owning the UI where you are expecting the UI to rally but you don’t need to put a time limit on it. Options require you to consider not only the fact that the underlying instrument will rally but how much and how quickly that rally will occur.

This chapter contains tables that show the main strategies that are the most suitable. One problem with a book like this is that it must, by necessity, simplify. For example, long straddles are usually considered neutral strategies, but they can actually be constructed with a market bias. The tables in this chapter generally refer to strategies as they are usually considered.


The strategies in this book are generally presented in their plain vanilla form. Yet the very nature of options gives greater scope to the creative strategist. For example, one of the interesting aspects of options is that you can combine strategies to create even more attractive opportunities. You could write a straddle and buy an underlying instrument to create a lower break even than by holding the instrument alone or to create greater profits if prices stagnate, but give up some of the upside potential. You should be able to examine a myriad of fascinating strategies after reading this book.

 Another feature of options is the ability to twist the expiration and strike prices to fit your outlook. For example, a straddle is constructed by buying a put and a call with the same strike price. That is the plain vanilla. But you can change the strike prices by, say, buying an out-of-the-money put and an out-of-the-money call and create what is called a strangle. Or why not buy the call for nearby expiration but the put for far expiration? The net effect is that you have a tremendous tool in options for creating exciting trading opportunities. Do not get stuck in the ordinary.


Of course, the selection of any strategy involves trade offs. For every one factor that you gain, you will likely give up another. The choice of one strategy over another largely depends on your personal expectations of the future of the market. For example, you may believe that implied volatility is going to go higher. Any strategy that is long implied volatility is going to be hurt by time decay. You are assuming that implied volatility will increase quickly and strongly enough to offset the drain on your position due to time decay.



There are three main ways to construct a strategy:

1. Use software to filter for different strategies using different criteria.
2. Use a building blocks approach.
3. Use tables such as the ones in this chapter.
We will focus on the latter two. However, we will need to use software to build our strategies using the building blocks approach. The table approach is a rule of thumb or back of the envelope approach.


There are two major techniques to identifying an appropriate strategy:

1. Identify your ideas on the major factors that affect options prices, that is, the greeks. You will need to look at such factors as market opinion, volatility, and time decay. You will then be able to make a statement like, “I think that Widgets will move slightly higher in price, volatility will decline, and time premium will decay rapidly because we are approaching expiration.” You can then start to build the strategy.

2. Systematically rank various option strategies. This technique can easily be used in conjuction with the first. For example, you may have decided that covered call writing fits your outlook. You now want to rank the covered calls on Widget International by their various risk/reward characteristics. For example, you could rank them by expected return or perhaps by the ratio of the return if unchanged to the downside break-even point. The main problem with the use of rankings is that you will need a computer to do all the possible mathematical manipulations.

Once again, the basic way to construct a position is to make a decision on the future of the key greeks and the underlying instrument. This will nearly always lead to a final position that meets your scenario. What this means is that you must have an opinion on the future direction of the UI and on the direction and level of the implied volatility. It is best if you also have an opinion on the other greeks since, although they are usually not as important, sometimes they rise to the highest level of importance. Further, it is advantageous to have an opinion on how quickly these expected changes will occur. 

For example, suppose you are bullish on Widget Life Insurance. You look for the price of the stock to move from its current $50 per share to $60 per share over the coming three months. This means that you should only look at bullish strategies. Suppose you also believe that the options are cheap from the perspective of implied volatility. Maybe you are very bullish, expecting the price to move higher very quickly. You, therefore, should only focus on very bullish strategies where you are a net buyer of calls. This suggests that you should likely buy a call that is out-of-the-money.

Now suppose that all the same conditions apply, but that you are bearish on implied volatility. This means that you should construct a position that is neutral or bearish on volatility. You might want to consider selling a put or buying a bull spread. The point is that your outlook on a given stock, its future price behavior, and the future behavior of the greeks will all have an impact on your construction of a strategy. There are six building blocks that we can use. We can be long or short a call, a put, or the underlying instrument. We can construct any strategy with combinations of those six positions.