Secrets to Profiting From Seasonality:

The Precision Profits

Trading Manual

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SEASONAL patterns define much of our lives. These patterns are based on the calendar — and they exist because of the calendar. We know, for example, that farmers in the Northern Hemisphere plant crops in the spring and harvest

in the fall because the weather dictates those times. In fact, the general growing season is easily tracked with a calendar — and it’s possible to trade based on this tendency.

For instance, every year, when it’s time to harvest, there will be downward pressure on grain prices because supply will be, at least temporarily, greater than demand. For value hunters, that creates a buying opportunity since prices are likely to rise when the harvest is completed.

And that’s the crux of Precision Profits. It underscores precisely why I created a system that utilizes the seasonal calendar to maximize investment

potential. There’s simply a consistent wealth of opportunities to mine within seasonality — you just have to pay attention to the calendar so you know when to buy and when to sell.

Just keep in mind that while farmers’ behavior is driven by seasonal trends, the calendar isn’t making farmers behave this way. Nor does it make seasonal investors like us execute our trades.

The calendar is simply marking a pattern that exists in nature — providing a guide for farmers … and us. Moreover, although farmers have a reason for their actions — the calendar — they might not be able

to explain it. In fact, many would consider it ridiculous to explain why they plant and harvest at the same time each year. Farmers tend to be practical and prefer to make money doing things that work rather than theorizing why they work.

Stock market investors could benefit from similar thinking. Rather than looking for reasons why some investing strategies work, investors would often be better served

by focusing on using the strategy to make money — particularly when it comes to investing in seasonal patterns.

So, in Precision Profits, we will think like farmers and not overanalyze a certain seasonal trend. Of course, we will also think like hedge fund managers or any other group of market participants who consistently make money. Our goal is to quantitatively apply seasonality to the markets to generate consistent profits.

In short, we aim to make money and enrich our futures. To that end, we will apply a four-step process for finding profits:

Secrets to Profiting From Seasonality:

The Precision Profits Trading ManualBy Michael Carr, CMT

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1. Find Strong Seasonality: Each month, our system will identify the best trading candidates. These will be stocks that have historically delivered profits at least 70% of the time. 2. Analyze the Price Data: Then I will review the seasonal trends of these stocks. Seasonal trends are found with a mathematical technique based on a periodogram, a technique I will explain shortly.3. Analyze the Momentum: Once we have a seasonal trend defined, we can measure the momentum of that trend to determine the ideal time to enter it. 4. Visualize the Trend: Finally, I’ll review all of the possible trading strategies to select the one that minimizes risk while offering the best potential rewards.In this guide, I’ll explain that process and tell you exactly what to expect from the Precision Profits service. I may explain more than you want to know at times. But by the time you finish reading this manual, you’ll

understand the math involved in our strategy — and you will know why you never have to look at the math again. I’ll also show you an example of my trade alerts — dispatches that mean you’ll never have to find the seasonal trends yourself.

That’s what I’m here for. In fact, I created this trading manual so you could essentially look over my shoulder at my proprietary

system. That way, you’ll be prepared to trade seasonality and be right at the forefront as new profit opportunities unfold.

So let’s get started…

What Is Seasonality?There are definite seasonal patterns in the markets, but many investors argue they simply can’t exist. Academic researchers almost uniformly deny the existence of seasonal patterns in the markets. They believe

if those recurring patterns existed, someone would have jumped in and traded the profits away. So seasonal patterns simply cannot exist.

A popular joke among economists explains this argument:A respected economist is walking down the street with his new grad student. The younger economist looks down and sees a $20 bill on the street. He calls his mentor’s attention to the money on the ground saying, “Look at that $20 bill on the sidewalk.” Without even looking, the older economist says, “That’s ridiculous. If there was really a $20 bill lying on the sidewalk, someone would have already picked it up by now.”You might not be laughing, but among economists, this actually gets chuckles at conferences. That joke also

summarizes the efficient market hypothesis (EMH) in a nutshell. The EMH basically says it’s impossible for money to really be lying around somewhere because someone else

would have already picked it up. But in the trading world, there are opportunities to essentially pick $20 bills off the sidewalk because skeptics — like those economists — ignore the money.

Many of these opportunities involve seasonal patterns that occur predictably in the market. Just as the location of Earth in its orbit around the sun explains seasonal patterns in farming, human behavior explains many seasonal patterns in the markets.

Let’s look at a trading pattern to see what I mean… Soybean prices decline almost 70% of the time in the first week of the year. Economists would argue this is

just a random piece of data, but many economists haven’t spent time with farmers. If they did, they would know farmers often store the beans in grain elevators after harvest. When the new

tax year begins in January, they sell some of their holdings to generate cash for the winter months. Thus, the price drops as a large supply hits the market.

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From an economist’s perspective, this might seem irrational, but farmers are often averse to paying taxes. By deferring income in December, they feel like they are lowering their tax bill. In the first week of January, they know they have 51 weeks to figure out ways to lower this year’s taxes.

As traders, we can benefit from this by simply shorting soybean futures the first week of January. We would have a winning trade 70% of the time, based on history. That’s not exactly the same thing as picking up a $20 bill on the street, but seasonal patterns might be the closest thing to picking up free money that traders will ever be able to do.

That’s why seasonal patterns are the concept behind Precision Profits. These are the types of behaviors I will look to uncover.

I do that by, essentially, completing a large number of calculations and analyses. While some of that might be a bit dull, I plan to explain that math here. I believe it’s important to understand why concepts like this work so that you can trade the patterns with confidence.

That philosophy comes from over 20 years of experience — so to start, let me introduce myself a bit more...

My History With Precision Calculations

The financial markets are my second career. Before working in the markets, I spent 20 years in the U.S. Air Force.

In the military, following a disciplined process is important to success. And understanding that process provides military members with the confidence they need to succeed.

I learned that after years of working with nuclear missiles, the most destructive weapons in history. Missiles are intended to maintain peace by presenting an alternative too horrible to contemplate. In order

to meet their objective, they must be 100% reliable. After all, potential adversaries need to know the weapons can be launched on a moment’s notice and with complete accuracy under any conditions. So my job included ensuring the missiles were programmed to hit their targets — 100% of the time.

I won’t sugarcoat it; this is difficult. The missile’s path could be altered by wind, for example. So there needs to be something built into the system to make sure that doesn’t happen. The programming required is actually boring, but I learned a great deal from that process.

Among the lessons I learned was to think of everything that could possibly go wrong — and prepare for it.I also learned the principles of programming are the same, whether you are looking at missiles or stocks.

And so it was a natural progression for me to start designing trading systems.Early in my career, I realized that stocks provided a unique opportunity. Simply put, investing could

increase your wealth. In military terms, it was the “strategic mission.” And I realized that by compounding small gains over many years, you could end up with millions of dollars.

It was such a clear way to improve your finances … if you did it the right way. With that thought, I went to work, and I decided to reframe the period for compounding.

Instead of thinking about earning, say, 8% to 10% a year, I realized earning a couple percent a month would increase wealth faster. To do that, I turned to the study of technical analysis.

I spent countless hours reading hundreds of books and articles to learn about how and why prices move. And in the end, it paid off. That’s why I was conferred the honor of Chartered Market Technician (CMT) by the Market Technicians Association (MTA). And why I earned positions such as chief market strategist for Dunn Warren Investment Advisors LLC and as the subadviser to the CIFG All Weather and Strategic Opportunities mutual funds family, where I managed more than $200 million.

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Just to give you a little more background, I’ve also edited the MTA’s newsletter since 2004 and led the effort to revise the code of ethics for the MTA — making sure we adopted the strongest ethics in the industry.

But among my most interesting, and profitable, discoveries is that stocks often follow seasonal patterns — and that’s what we’ll focus on in this service.

A Seasonal Strategy Beats the Market

I first discovered the power of seasonality in an old book. I want to lay out the process of this discovery because it illustrates the power of stock trends … if you know what to look for.

While we won’t be using this exact strategy, it was the basis for my own journey into seasonality, and I think it’s important to understand.

See, in 1976, Norman Fosback described the “end of month” strategy in Stock Market Logic. This strategy requires you to own stocks just five days a month. It’s often referred to as the “beginning of the month” trading strategy.

The rules, as explained in that book, are simple:• Buy at the open on the last trading day of the month.• Sell at the close on the fourth trading day of the month.With this strategy, you are invested just five days a month, or 60 days a year. There are typically about

252 trading days in a year, so you are invested about 24% of the time. The published results show this strategy beats the market, even though it is only invested about a quarter

of the time. That’s an important point because it means we can use the money for other strategies 75% of the time.

This will help shorten the compounding period and help us grow wealth faster.From 1927 to 1975, Fosback showed that $10,000 would have grown to $572,020 with this trading

strategy. In contrast, an investor owning stocks on the other days of the month would have seen their $10,000 shrink to $899. In fact, Fosback’s results showed that his strategy also outperformed the “buy and hold” one with an average annual gain of 8.8%, while the market gained an average of 3.47% a year.

Those are impressive findings, so let’s dig a little deeper into Fosback’s results because there’s something here that can be applied to our own trading.

First of all, Fosback tested a 48-year time period, a time frame any investor would consider to be long-term.

Over that time, the broad stock market delivered an average annual return of 3.47%. This is significantly less than the lofty 8% to 10% annual returns most investors believe are possible in the stock market. Those lofty expectations are based on the high returns achieved from 1982 to 2000.

Without those years, most long-term holding periods provide average annual returns of around 5%. Over the past 100 years, for example, the Dow Jones Industrial Average provides an average annual gain of 5.6% a year over 10-year holding periods.

That tells me 1982 to 2000 was a unique period in market history. As investors hoping to retire one day, we should plan on the market delivering more typical returns averaging about 5% a year in the long run.

And this demonstrates why we need to follow active investment strategies — such as our Precision Profits system — to beat the market. Most of us won’t be able to retire on returns averaging 5%.

With that in mind, let’s get back to seasonal strategies.

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To see if we should follow Fosback’s strategy in our seasonal trading, let’s look at some historical data. The chart below shows the “end of month” performance from 1975 to 2000.

End of Month Trading Strategy: 1975 – 2000

The results were not great from 1975 through 1987: For 12 years, there were no profits. Then the system began working again and easily beat the stock market.

The next chart shows the performance since 2000.

End of Month Trading Strategy: 2000 – 2017

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As you can see, based on those years, the system doesn’t appear to be tradable anymore. Rather than steady gains, we see wild equity swings with large losses following large gains. However, there are still gains to be seen here. In fact, by digging deeper into the performance, we might be

able to fix this strategy.

The Nuts and Bolts of Market Trends

Fosback’s original study began in 1927 and ran through 1975. So why was it so profitable during that time?Well, this was during a time when individual investors owned most stocks in their own name.

Institutional investors played a smaller role in the stock market because stocks were considered risky, so they allocated more funds to bonds than they do today.

Moreover, institutions at that time included insurance companies who collected premiums through the month and then invested the assets at the beginning of the next month. Pension funds were relatively small at that time, but they also usually followed a rigid monthly investment schedule.

This pattern explains why stocks had a tendency to move higher in the first week of the month during this time. And why capturing that seasonality was so profitable.

Then came the period from 1975 through 1987, when the “end of the month” strategy disappointed. That’s because stocks were largely despised by individual investors and institutions then. Interest rates

were high, and managers were able to collect 10% coupons on bonds. Even Treasurys offered double-digit rates at this time.

So with little money flowing into stocks, we don’t see the beginning of the month bounce we saw earlier.Of course, from 1987 through 2000, we had a steady bull market with individuals participating through

mutual funds. They often invested in the funds throughout the month, using dollar-cost averaging strategies to buy a few shares on a regular basis. This led to fairly predictable cash inflows that managers could then deploy at the beginning of the month, after the previous month’s deposits were in. So Fosback’s strategy worked well.

Remember, investing was more difficult and expensive at this time, so waiting for the first week of the month was also an efficient way for managers to put money to work, buying in bulk to hold down commissions and other trading costs.

Since 2000, however, computers have changed the way money moves through the economy and how portfolio managers allocate investments. Costs have come down, and managers can invest at any time during the month. Thus, 2000 to 2017 hasn’t seen the same trend.

I lay all of this out because it is a great example of how trends are shaped by cyclical market functions. Which is something I take into account when selecting our trades.

And there’s more to it. Back to Fosback’s research…See, one thing hasn’t changed that much since 2000: Investment managers often face restrictions on how

much cash they can hold. Consider Fidelity Investments as an example. The company has more than $2 trillion under management,

with at least $700 billion of that invested in U.S. stocks. Managers of stock funds are only allowed to hold enough cash to meet redemptions and pay expenses.

They are usually restricted from holding more than about 5% in cash — although some funds may have higher limits. If they have more than that, they need to invest it in stocks.

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Investment managers have no choice other than to buy stocks before management reviews cash holdings at the end of the month. For example, if a manager has been bearish all month, hoping for a pullback, they will have built up cash and be forced to invest that cash at the end of the month.

This is different than how the markets worked in the 1970s, when managers could invest the cash they received at the beginning of the month.

Knowing this, we can see the best time for owning stocks has shifted to the end of the month instead of at the beginning of the month.

This is powerful information to take into account when trading.In fact, here’s a look at the amount of money you could have made by buying on the open with four days

left in the month and selling at the close on the first trading day of the following month.

New End of Month Strategy: 2000 – 2017

We’re still holding stocks for just five days, just as we were in the original strategy. But we shifted the five days from the beginning to the end of the month — and clearly, there’s a much stronger performance. Note the steady climb without the outrageous swings we saw in the previous chart.

You can mark this strategy on your calendar to trade every month years in advance. But remember, as we saw, seasonal tendencies can, and do, change over time. That was a crucial lesson for me while studying technical analysis, and it’s part of why I make sure that I don’t blindly follow a system.

Trends can change, and I need to account for that in each analysis. Like I said, in the military, I learned to think of everything that could possibly go wrong — and prepare for it.

Now, knowing all of this — that trends do in fact work but that they can shift — let’s move on to the heart of our Precision Profits strategy.

Profit From the Precision Profits Strategy

In Precision Profits, we will use a more sophisticated strategy. As I mentioned above, we are applying a four-step process for finding profits.

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1. Find Strong Seasonality: The first step involves finding stocks with a strong seasonal trend in the current month. Each month, I will run a trading system to identify the stocks that have delivered the best performance in that

month over the past 10 to 15 years. For example, at the end of February, I will search for the stocks that have the best performance in March.

Generally, I will be looking for stocks that have delivered gains at least 70% of the time.Then, I will construct charts, showing the average seasonal trend in those stocks. This is important because we

want to visualize the typical pattern of the stock. An example of that type of chart is shown below:

This is a chart of Pool Corporation, a company that specializes in supplying pool products. We would expect a strong seasonal pattern in a stock like this (pools are used more often in the spring/summer), and the blue line shows that trend. As you can see, the stock’s pattern shows we should expect an uptrend from January through April.

Before explaining how I use that line, I want to explain how I find the seasonal pattern in the data — which brings us to Phase 2…

2. Analyze the Price Data: The second step involves building the periodogram. To begin, I start with a long series of price data. Monthly price data works well, provided I have at least 200 months — or about 16.5 years’ worth of price

data. Weekly data should be avoided since there are variations in the sequence of annual events. For example, holidays can fall on different weeks every year and distort the seasonal pattern, or there could be a different number of weeks in a month from year to year. Daily data could be used, as long as you have at least 16.5 years of the data.

After collecting the price data, I transform prices from dollars to log values. This step is needed to avoid overemphasizing large jumps in the values of the data and factors out the impact of secular trends (usually upward in stock prices). Using logs means each data point is equally important, whether the share price is $1 or $1,000.

Essentially, I smooth out the outliers with this step.The charts below show the difference. The chart of Pool Corp. shown earlier uses log-transformed data. The

one below uses untransformed price data.

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As you can see, the chart without the transformation simply moves up. Log values, on the other hand, identify the seasonal pattern. Otherwise, you’d simply see a line moving

almost straight up or down, depending on whether the stock has been in a long-term bull or bear market. That doesn’t give me the information I need to determine the complete seasonality.

Now on to Phase 3…3. Analyze the Momentum: We know these seasonal tendencies can change. This can help us reduce risk by limiting trades to stocks whose seasonality has remained strong in recent years. So, for this step, I will be applying an analysis to the seasonal pattern. This will involve measuring the

momentum of the most recent trend. I do this by creating a periodogram.This step can be done with software (although the software tools tend to be expensive) or in Excel, where

the required steps tend to be tedious. I will use Excel for our example, just so you can see the type of analysis I put into each one of our recommendations.

To transform closing prices to logs in Excel, use the LOG function.

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Base 10 should be used. If you have all the closing prices in Column E, for example, you could point to that cell for the “number” in the LOG function and then type in “10” for “base.”

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec1995 1.005395 1.005395 1.0192471996 1.088137 1.101231 1.161368 1.224015 1.278753 1.255272 1.273 1.278753 1.306425 1.255272 1.278753 1.3170161997 1.332438 1.380211 1.327358 1.332438 1.389165 1.324797 1.356981 1.361726 1.236788 1.380211 1.295567 1.2844311998 1.317018 1.359362 1.352182 1.373372 1.38134 1.389166 1.172457 1.088136 1.113943 1.142233 1.190332 1.1796951999 1.18327 1.157608 1.146128 1.264227 1.281602 1.41288 1.359361 1.361728 1.371068 1.355786 1.373372 1.4139282000 1.413928 1.39467 1.486076 1.565995 1.529879 1.371068 1.42042 1.467053 1.471658 1.412881 1.431364 1.4780252001 1.525854 1.521792 1.511883 1.49831 1.530968 1.537063 1.594392 1.578869 1.329398 1.366236 1.411788 1.4385422002 1.453012 1.473487 1.49693 1.500922 1.466274 1.44342 1.395326 1.441224 1.437909 1.454845 1.498448 1.4653832003 1.44295 1.437751 1.472903 1.518645 1.507991 1.536432 1.588496 1.612572 1.444513 1.54506 1.554126 1.5142822004 1.505828 1.559308 1.571243 1.604334 1.604766 1.653213 1.615213 1.62521 1.427161 1.465234 1.498724 1.5037912005 1.473049 1.53199 1.503246 1.512951 1.554247 1.545183 1.561578 1.563481 1.543199 1.55594 1.590284 1.5707762006 1.600755 1.63819 1.671265 1.669503 1.635383 1.639785 1.590284 1.580583 1.585461 1.612572 1.612466 1.5929542007 1.563481 1.545307 1.553883 1.603469 1.612254 1.591399 1.526469 1.513883 1.397592 1.372544 1.328787 1.2973232008 1.391641 1.279895 1.276232 1.339054 1.314078 1.249443 1.343999 1.384891 1.367915 1.240799 1.236285 1.2545482009 1.200029 1.122871 1.127105 1.251881 1.241297 1.21906 1.374015 1.376942 1.346744 1.291813 1.256718 1.2805782010 1.263873 1.300595 1.354876 1.389698 1.38003 1.340841 1.344981 1.265996 1.302547 1.304059 1.326131 1.3529542011 1.387034 1.397245 1.382197 1.480869 1.480582 1.474362 1.427324 1.413803 1.41797 1.46568 1.4843 1.4785662012 1.531607 1.561101 1.573104 1.567144 1.567849 1.607026 1.566555 1.595386 1.618885 1.623869 1.62211 1.6265462013 1.661055 1.660106 1.681241 1.690373 1.711385 1.719414 1.722469 1.716754 1.748731 1.735439 1.748498 1.7644752014 1.733839 1.766859 1.787602 1.770999 1.761402 1.752509 1.738463 1.753277 1.73175 1.775974 1.77386 1.8023632015 1.79386 1.839918 1.843606 1.812178 1.821382 1.846213 1.847696 1.843108 1.859138 1.911371 1.914026 1.9073042016 1.926857 1.904553 1.943198 1.941561 1.961753 1.973266 2.009791 2.003762 1.975524 1.966517 2.002641 2.0184512017 2.023499 2.068742

Average 1.491501 1.500127 1.486839 1.519616 1.524399 1.518182 1.51568 1.515578 1.477825 1.487349 1.474272 1.480054

You could then pull this cell down to copy it into the rest of the column and quickly transform your price data into logs. This would be the case if you downloaded monthly data from a web site like Yahoo, for example.

Now, you need to move the data from columns to a table with the years in separate rows and the monthly price data in each column. An example is shown below. The data can be set up in this way with the “paste special, transpose” function. (And this is an example of how the process becomes tedious.)

Example of Pool Prices as Log Data

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Then Phase 4 comes into play…4. Visualize the Trend: Finally, it’s time to put the calculations into a view that’s usable.To do this, after formatting the data, I take the average of each column as shown at the bottom of the figure.

Then I plot the averages into a line chart as shown below.

Pool’s Seasonal Trend

Peaks show when seasonal uptrends are expected to end. Troughs (lows on the plotted line) show when seasonal downtrends are expected to end. In the case of Pool, we have a trough in September and peak in May. This should be the ideal time to own this stock.

What about the other six months of the year when the seasonal trend is bearish? Here, traders have two options. They could simply own other stocks. Or they could buy put options or

sell shares short to benefit. Bear in mind that short sellers can face unlimited risk, while put buyers are able to limit their risks.

That’s why we’ll use put options for downtrends, but I’ll get to our options details later.The reason for Pool’s pattern is easy to understand. Most of Pool’s revenue is likely to be booked in the

summer months, about May through September. Traders are buying and selling on what they expect the future to hold. So, in October and through the winter months, they are buying Pool in anticipation of the summer revenue. Then traders take profits by selling in May through the summer because they expect lackluster performance from the company six months in the future.

Traders who look ahead — rather than at the present or the past — are driving this seasonal cycle. Many stocks have patterns like this. We might not be able to readily explain the pattern as we can with

Pool. (Which is fine. As I said in the beginning, sometimes we just need to accept that a trend works and not overanalyze it.) Trends could also be related to earnings reports that occur at the same time every year, the introduction of new products at trade shows that occur at the same time every year, a release of test data for pharmaceutical companies that occurs at medical conferences held at the same time every year, seasonal trends in sales that unfold in the same way every year — or one of many other reasons.

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How We Will Trade Seasonality

Now that you’ve seen the process I’ll use to select our companies, let’s turn our attention to the tactics of trading.

We’ll be capitalizing on seasonality by buying simple put and call options — and we’ll likely never hold them for longer than three months. There is a detailed Options 101 manual available for you to review if you are unfamiliar with options. But, in general, buying options is a low-cost, defined-risk way to benefit from price moves. Plus, it maximizes our gains.

A call option gives you the right, but not the obligation, to buy a stock at a predetermined price for a predetermined amount of time. The call will usually sell for about 3% to 5% of the stock’s price.

So, for a stock trading at $60, we might find a call trading at $2. Each call contract covers 100 shares, so the total cost per contract will be $200 in this example — and that is the maximum risk on the trade. We can never lose more than we paid to buy the option. If the stock falls $5, an investor with 100 shares would lose $500, while the call buyer would lose just $200.

If the stock gained $5, the owner of the stock would have a $500 profit while the call buyer might generate just $300 in gains. (The Options 101 guide goes into detail on how options prices are determined.) In percentage terms, the shareholder would have an 8% gain, while the call buyer would have a 150% gain.

Put options provide the right to sell a stock and deliver gains when the price of a stock falls. We will use them to benefit from downtrends. This is important because prices fall faster than they rise. Benefiting from price declines allows us to potentially generate wealth rapidly in bear markets.

To trade options, you will need to open an account with options permissions at your broker. This usually involves completing a one- or two-page form requesting information about your assets and investment experience. We will only be buying (or going long) options, so this is the least risky options strategy.

When it comes time to trade, I will tell you exactly what to do so you will have no problem placing the trades.

Here is an example of one of my trade alerts. As you can see, I provide all of the instructions for your ease of use.

Example Trade Alert (Please Do Not Trade This Example)

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If you are new to options, consider opening an account at one of the brokers listed below. Interactive Brokers has the lowest costs, and low costs mean you keep more of your profits.

You will most likely find Interactive Brokers has the lowest commission rates, but they also have the lowest level of customer service.

If you need help placing trades or processing other transactions, you may find one of the other brokers is a better choice, and recent price cuts in the discount brokerage industry make any of these firms affordable.

We will trade up to 10 positions at one time, so you should allocate 10% of the money you’ve allocated to this strategy to each recommendation.

As for the rest of what you can expect from me, the trade alerts will be just one part of the service. These alerts will be sent whenever action is required of us and will include detailed instructions on what to do. You should expect to see at least two trades a month.

Your service also includes weekly updates. Every Thursday, I’ll send an update on the portfolio, discuss what I’m looking at in the market and answer any of your questions that come up. I’ll also send a mailbag issue every now and then to make sure your questions are answered and that you are comfortable and confident trading the service.

When you have questions, please send them to me at precisionprofits@banyanhill.com. I will always do my best to provide clear ideas to you, but don’t ever hesitate to ask me anything about the service, the trades I recommend or the market in general.

Regards,

Michael Carr, CMTEditor, Precision Profits

Interactive Brokers www.interactivebrokers.com 1-844-4IB-BRKR

Options House www.optionshouse.com 1-877-653-2500

Fidelity www.fidelity.com 1-800-343-3548

E*Trade www.etrade.com 1-800-ETRADE-1

Options Xpress www.optionsxpress.com 1-888-280-8020

eOption www.eoption.com 1-888-793-5333

TradeKing www.tradeking.com 1-877-495-5464

Broker Contact Information

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Banyan HillP.O. Box 8378 Delray Beach, FL 33482 USAUSA Toll Free Tel.: (866) 584-4096

Email: http://banyanhill.com/contact-us

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