How to Use the New Symbol Details Page on TradingMarkets

One of the many new features in the new TradingMarkets Analytics section is our Symbol Detail page. On the Symbol Detail Page you can receive live readings on ConnorsRSI which allows you to see how overbought or oversold a stock or ETF is at that moment.

Another great feature can be found here by doing the following:

1. Go to the Analytics Section at http://analytics.tradingmarkets.com/

2. Type in a symbol

3. Scroll down and you’re able to see the dollar return of the stock (or ETF) over the past 3 month, 6 month, 1 year, 2 year, 3 year, and 5 year period of time.

For example, type in VXX. Then click 5 years. You will see that VXX started trading in January 2009. A $10,000 investment in VXX would today be worth $126 (many of you who have taken our courses saw this coming a long time ago).

A more upbeat picture can been seen in Google.

1. Go to the top of the page type in GOOG in the quote box.

2. An investment made three months ago is now up almost 20%. One made 5 years ago is now up over 75%. And that includes most of the bear market of 2008!

Now scroll down further. You can see the monthly returns of Google all the way back from its first day of trading.

The advantage of looking at the monthly returns of a stock is to give you a good long term historical view of the stocks volatility. The best example of seeing this in action is with Apple (AAPL). Great company? Yes. Safe stock? Not a chance. Down 34% in 2002. Down 56% in 2008 (!). And down 20% so far this year. Few people realize or know this.

The Symbol Detail Page within TradingMarkets Analytics is a great place to get your live overbought and oversold readings during the day along with the historical returns on stocks. As we move ahead, I’ll show you additional features we’ve built into this.

Also, look out for the new TradingMarkets website coming later this month. Not only is it redesigned for you, it’s going to include “how to” articles from some of the best and brightest traders in the business for you to learn from.

Trading Beyond the Matrix

I’d like to recommend a new book on trading psychology just published by Van Tharp. I began reading it Sunday night and the book goes far deeper than any trading psychology book I’ve ever read.

Also, one of our Chairman’s Club Members is featured in Chapter 2 and it’s always great to see success like this gentleman is having.
If you are looking to improve your trading, buy this book.

Trading Beyond the Matrix: The Red Pill for Traders and Investors
Van Tharp

http://www.amazon.com/Trading-Beyond-Matrix-Traders-Investors/dp/1118525…

The Death of Intra-day Reversals?

If you speak to enough traders, you’ll hear a general consensus that the market has changed the past few years, especially last year.

High volatility securities which used to mean revert, didn’t do so as much last year. Rotational strategies in S&P stocks and high quality stocks, like the Rotational strategies found in The Machine had extraordinary years in 2012, far surpassing the index averages. I can list more examples of this but as many people have seen, it was a year which buy and hold returned, bonds were king, quality was in, and trading reversals was not.

One of the metrics I’d like to share with you to further understand the market over the past year is the following.

We ran the following test. We looked at SPY every day from 1995 -2011 and asked, how many times was SPY up (down) ½% intraday and then reversed and close down (up) for the day. Here are the statistics:

Symbol Start Date End Date Intraday Reversals- Down (%) Intraday Reversals- Up (%)
SPY 1995-01-01 2011-12-31 12.56 12.84

On average over the 17 year period, whenever SPY had moved at least 1/2 % intra-day versus the previous days close, it then reversed to close in the opposite direction just over 12.5% of the time.

We then looked at the same data from 2012. And now you’ll see why so many traders are saying “2012 felt different”. In fact it was.

Symbol Start Date End Date Intraday Reversals- Down (%) Intraday Reversals- Up (%)
SPY 2012-01-01 2012-12-31 6.00 8.00

As you can see, intra-day reversals to the downside were cut in half. To the upside it was appoximately 40% lower.

There are three possible reasons for this.

1. Volatility was down.

Yes, volatility was down but if there were many years volatility was as low or lower. 2005 and 2006 are examples.

2. Markets have changed. Intra-day reversals have been squeezed by less leverage in the marketplace, high-frequency trading, an abundance of cash in the system caused by Fed easing, etc.

At this point, I’m not buying into this. In early 2007 we heard the same excuses as to why low volatility was permanent. That lasted until everyone bought into this and the last dollar got levered up. And then reality set-in.

3. 2012 was different but in the long run, market behavior evens out.

If you look at markets over many years, behavior tends to average itself out. The best example is the outsized gains of the 90’s were averaged out by the lack of gains in the 2000’s. Combining them together looked more in line with historical returns. And the same will likely occur when it comes to intra-day reversals. Eventually, (possibly very soon) you’ll see an abundance of them.

Obviously those traders who said 2012 felt different are right. It was different. Intra-day reversals are just one of many things that were different. But, if you buy into belief that market behavior eventually averages itself out (it reverts to its long term mean) then over time the market will again move back to its ways of swinging intra-day. And strategies which rely upon this behavior will again be the big winners. If you have strategies which trade intra-day and rely upon intra-day reversals, you may want to keep an eye on them. Because if their behavior begins reverting to its mean, they’re going to potentially have a big run sometime in the near future.

How to Use The TradingMarkets Screener – A Live Class with Larry Connors

The newly released TradingMarkets Screener offers an easy way to search and sort for specific stocks and ETFs that meet distinct criteria that you select by using key technical indicators.

In this special online webinar, Larry Connors will walk you through using The TradingMarkets Screener and detail how you can use this powerful tool to find high-probability trading setups every single day.

Click here to register now for this free class on using the TradingMarkets Screener. This is a rare chance to learn first-hand how to find the best trading opportunities directly from Larry Connors.

By combining content licensed from financial data providers with our exclusive set of technical indicators, we provide a comprehensive set of financial information that you can find nowhere else on the web including:

  • Exclusive Customizable Filters
  • Interactive Sortable Data Tables
  • Company Search
  • Premium Technical Indicators
  • And More…

We’ve also recently released the first and only quantified oscillator for traders – ConnorsRSI – which is built into the TradingMarkets Screener and can be used to sort and filter to find the most overbought and oversold securities on a daily basis.

This powerful tool is constantly evolving as we develop new ways to enhance its capabilities. We’ve made several updates to the TradingMarkets Screener since its original release, including customized Watchlists, filter sets, sharing features, and daily lists to help point out high-probability trading setups.

Take advantage of this opportunity to learn how the TradingMarkets Screener can provide you with exactly the data you need to meet your personal trading needs. Click here to register today.

4 Reasons to Zealously Track Your Trading Activity

Recording all of your trading activity can seem rather tedious at times. After all, you can easily check your brokerage account balance online anytime you want to, and your broker keeps a ledger of all your trade entries and exits. So why spend your precious time creating your own log? Here’s a short list of obvious and not-so-obvious reasons.

 

Learn the essential skills you need to succeed in your swing trading by attending the upcoming 2013 Swing Trading College. Click here to find out more about the quantified research, strategies, and techniques you’ll have the opportunity to learn in a live webinar with Larry Connors.

 

  1. Distinguish account deposits and withdrawals from trading profits and losses.
    When we’re trying to determine how well our investing has been going lately, the first number that many of us focus on is our account balance. But is your balance higher this month than last because of your trading prowess, or is it because you deposited more cash into your account?

    By recording all of your deposits and withdrawals as well as your monthly account balance, you will be able to calculate the ratio of your current account balance to your net deposits. If this percentage is greater than 100%, you’ve made money overall. If the percentage is higher now than it was X months ago, then you’ve probably generated profits over that time period. Be careful though… withdrawals can reduce the denominator in your equation and thus increase the result. Similarly, deposits can reduce the result. If your deposits and withdrawals are small compared to your overall account size, this probably won’t have a major effect, but it’s something to be aware of.

  2. Evaluate Your Strategies.
    We all know that following a set of quantified trading rules helps provide consistency in our results. Unfortunately, most of us have also experienced a time when some of those strategies become less productive, or even downright unprofitable.

    If you’re trading with a strict set of rules, it doesn’t really make sense to judge the performance of those rules by letting your gut tell you when “things don’t seem to be working”. Instead, record the name of the strategy with each and every trade you make. That way, you can evaluate the strategy over any relevant time period, and compare the recent performance to longer-term metrics. This, in turn, will allow you to objectively determine whether it might be time to put a strategy aside for awhile.

  3. Quantify Your Discretionary Decisions.
    How many times have you decided to “bend” your strategy rules a bit? Does adding an element of discretion help or hurt your overall results? It’s human nature to remember the times when breaking the rules was wildly profitable for us, and to conveniently forget all the times that it was not.

    By adding a comment field (and possibly a data column as well) to your trading log, you can keep track of when you executed your quantified rules to perfection, and when you did not. You may be surprised to find that all of those “clever” decisions to override the rules were not actually as beneficial as you had thought or hoped. On the flip side, you might discover that every time you add a particular entry or exit filter to your rules, the trade works out better than when you don’t use that filter.

  4. Appraise Advisory Services.
    For every investment vehicle in existence, there are services available to tell you what to buy and when to buy it. From Forex day trades to weekly options to monthly stock picks to multi-year buy-and-hold strategies on precious metals, there is someone available to “help” you… for a fee. The problem is, most of them seem to be a testament to the standard disclaimer that “past performance does not guarantee future results”, because somehow your real account containing your hard-earned cash never seems to grow by the same leaps and bounds as the model portfolio shown on their web site!

    Assign an “idea source” for every trade you make, whether that source is your own research, a trade alert from a paid service, or an informal recommendation from a friend, newsletter or other publication. That way you’ll have hard data to help you decide whether or not to renew your subscription to XYZ Wealth Advisory, or continue spending time every week reading ABC Market Insights.

 

As with everything we do at Connors Research, we believe that the more you are able to quantify your results, the better data you will have for making decisions about how to proceed. Start simple. Start small. But start today. You may be surprised by where the data leads you.

The Power of TPS

In 2008 we introduced a concept that we labeled TPS, which stands for:

  • Time
  • Price
  • Scale-In

Originally presented as a stand-alone strategy, the core ideas behind TPS have turned into a methodology that can be applied to a variety of different mean reversion strategies. Since the overall concept has held up incredibly well over the intervening years, it’s worth a quick review.

With TPS, we’re trying to get all three components – time, price, and scale-in – working in our favor. At a high level, here’s how it works for a long mean-reversion strategy:

  1. When a pullback occurs and the strategy signals an entry, buy a small initial position.
  2. If the stock or ETF becomes more oversold (more on this in a minute), then increase your position size by scaling in, i.e. purchasing more shares.
  3. Step 2 may be repeated multiple times if the price continues to pull back and the scale-in rules allow it.

Typically the criterion for scaling is simply a closing price that’s lower than the previous entry price. However, other rules may be used to determine when a stock has become more oversold. For example, we might enter a trade when ConnorsRSI is less than 20, and then scale in if ConnorsRSI drops lower. If the first scale-in occurs when ConnorsRSI is 17.8, then we would scale in a second time if ConnorsRSI closed lower than 17.8 at any time before we exited the trade.

Different strategies utilize different scale-in ratios. Common ratios include 1-1, 2-3-5, 1-2-3-4 and 1-2-3-4-5. The ratio is created by using each digit as the numerator, and the total of the digits as the denominator. For example, with 2-3-5 scaling, we can have an initial entry plus two additional scale-ins. The initial entry would be 2/10 (20%) of a full position, the first scale-in would be an additional 3/10 (30%) of a full position, and the second/final scale-in would be 5/10 (50%) of a full position.

The biggest advantage to this approach is that by scaling in at lower and lower prices, we are lowering our average entry price. This, in turn, increases our chances of a profitable exit.

A less obvious benefit of TPS is that it can allow us to enter trades using less stringent entry criteria. In many cases, this will increase both the number of trade signals generated and the average gain per trade.

Consider a very simple strategy with the following rules:

  1. Buy a stock that has an RSI(2) value below X, where X = 10, 20, or 30.
  2. Sell the stock when it closes above the 5-day moving average, MA(5)

Here are the results when the strategy is applied to a universe of liquid stocks and TPS is not used:

Here are the results when the strategy is applied to a universe of liquid stocks and TPS is not used:

Var # # Trades Avg % P/L % Winners RSI(2) Threshold Scaling
1 58463 0.42 66.80 10 1/0
2 81917 0.34 66.33 15 1/0
3 102258 0.29 66.21 20 1/0

As we would expect, as the entry criteria becomes more stringent (lower RSI(2) threshold), we generate fewer trade signals but a higher average gain per trade.

Now let’s see what happens when we use 2/3/5 or 1/2/3/4 scaling. In all cases, we scale in further when the price closes below the previous entry price.

Var # # Trades Avg % P/L % Winners RSI(2) Threshold Scaling
4 58463 1.38 80.02 10 2/3/5
5 81917 1.30 79.65 15 2/3/5
6 102258 1.24 79.61 20 2/3/5
7 58434 1.62 83.46 10 1/2/3/4
8 81917 1.54 83.21 15 1/2/3/4
9 102005 1.49 83.21 20 1/2/3/4

Notice that if we keep the RSI(2) threshold the same, then the number of trades remains stable, but the average gain per trade rises by a factor of 3 to 5. Alternatively, we can use a higher RSI(2) threshold to increase both the number of trades and the Average % P/L. For example, consider Variation 1, which uses no scaling and an RSI(2) threshold of 10. In back testing, this strategy variation generated 58,463 entry signals, and an average gain per trade of 0.42%. Variation 5 uses an RSI(2) threshold of 15 and 2/3/5 scaling, and generated 81,917 trade signals and an average gain of 1.30%. Using 1/2/3/4 scaling (Variation 8) increased the gain per trade to 1.54%.

As you can see, TPS is a powerful tool that can potentially increase the returns of many existing trading strategies. TPS is just one of many topics that will be covered in detail during the upcoming 2013 Swing Trading College.

Trading Option Straddles and Strangles: Part 2

In the previous newsletter, we introduced two non-directional option strategies: straddles and strangles. Today we’ll discuss when to use these strategies, and how to evaluate their potential for success.

Long straddles and strangles are useful tools when you think that a stock will undergo a large move, but you’re not sure whether the move will be up or down. Short straddles and strangles are simply the opposite side of this trade, and are essentially a bet that the stock price will not change significantly before expiration.

Some traders like to use the long version of these strategies when a company is announcing earnings or introducing a new product to the marketplace. However, it’s always hard to know how much of the news is already “priced in”, i.e. reflected in the current price of the stock. So how can we tell if the change in stock price is likely to be large enough for a long straddle or strangle to be profitable?

There are at least three ways to gauge our chances of success with a straddle or strangle:

  1. Use a quantified, back-tested strategy.
    Obviously this is our preferred method. Developing a well-defined strategy with precise entry and exit rules and then back-testing that strategy with reliable data across a variety of market conditions gives us an excellent perspective of how the strategy has performed in the past, and therefore provides some reasonable (though certainly not infallible) expectations of how it will perform in the future.The challenge here lies with the “reliable data” aspect of back-testing. While there are many, many sources for high-quality historical stock and ETF data, good options data is much more difficult to obtain. This is partly due to its volume (consider that a single stock may have dozens or even hundreds of strike prices for each of several active expirations), and partly due to its transience (most traders don’t care about the price of an option that expired three years ago).
  2. Use stock prices as a proxy for option prices.
    If you don’t have access to option data, you may be able to gain some insight by looking at historical stock prices. With AAPL earnings being announced this week, you may have thought that last Friday would be a good time to purchase a straddle using weekly options. However, the ATM straddle had a price of around $36 on Friday, which is 7.2% of AAPL’s $500 stock price. Recall that for a long straddle to be profitable, the stock price needs to move up or down by more than the cost of the straddle. Assuming you’d like to make at least a 10% profit on your trade, you could check how many times AAPL has moved by 8% or more during earnings week. Over the past three years, it’s happened 5 out of 12 times. Do you want to place $3600 on a bet that’s been a winner less than 50% of the time in recent years?
  3. Apply an option pricing model to current option data
    This is the most complicated of the three solutions, but is not as intimidating as it sounds because your trading platform will do most of the work for you.Theoretically, the price of an option is determined by a number of factors. The four most influential ones are:

    • Price of the underlying stock
    • Strike price of the option
    • Time until expiration of the option contract
    • Implied (expected) volatility of the stock price

    The actual option price and all the values above except implied volatility are easily obtained. Because we have all the other elements, we can algebraically solve for implied volatility, which in turn allows us to calculate delta (one of the option Greeks) and the probability that the option will expire in the money (ITM). All platforms will have a way to report delta and the other Greeks. Some platforms will also report the probability of the option expiring ITM. For example, here was the weekly option chain for AAPL as of Friday, January 18th, as shown on TD Ameritrade’s thinkorswim platform. Calls are on the left, puts are on the right, and strike prices are in the blue section in the middle.

    Notice that the value of delta is quite close to “Prob ITM”, which is the probability that the option will expire in the money. Therefore, delta is a reasonable substitute for probability of expiring in the money if your platform doesn’t provide the latter value.

    How does that help us? Well, we know that the 500 strike straddle would have cost just under $36 last Friday. Therefore, to profit we need AAPL to move by more than that amount, so let’s say we’d like at least a $40 move. The current AAPL price of $500 plus a $40 move would be $540. Looking at the option data above, we see that the 540 call has a 17.68% chance of expiring in the money, i.e. there’s a 17.68% chance that the price of AAPL will be above $540 by expiration. Similarly, the OTM option that is $40 below the current stock price is the 460 put, which has an 18.49% chance of expiring in the money. Therefore, the combined wisdom of the marketplace, as encapsulated in the price of the options, is that there’s less than a 20% chance that the price of AAPL will move sufficiently to make the straddle profitable.
    Obviously the market is not always correct, and sometimes the market participants get surprised. Would you be willing to bet your money that this is one of those times?

You now have several tools to help you evaluate whether a straddle or strangle is likely to be profitable. The same tools can be used whether you’re considering a short position or a long one. We hope you have found this information helpful!

Hedgehogging

Somehow along the way I didn’t get a chance to read Barton Biggs classic book Hedgehogging until this past week. What a gem. If you’re interested in getting inside the minds of one of the great market strategists of all time, this book is for you. What’s amazing, in hindsight, is that this diary starts with him opening his own hedge fund…at the age of 70!

Highly recommended.

http://www.amazon.com/Hedgehogging-ebook/dp/B0086I1Z2U/ref=tmm_kin_title…

Trading Option Straddles and Strangles: Part 1

One of the most powerful aspects of trading with options is that there’s an option strategy for almost any situation. Today we’re going to introduce two of those strategies: straddles and strangles. Both straddles and strangles are non-directional strategies, meaning that they have the ability to profit whether the price of the underlying security moves up or down.

A long straddle involves buying a call and a put on the same underlying security. Both options have the same expiration date and the same strike price. The risk profile for a long straddle is shown in the box to the left.

A risk profile, sometimes called a profit diagram, shows how much the option strategy will gain or lose based on the stock price at expiration. All long straddles have a risk profile shaped like a V, with the base of the V falling $C below the horizontal breakeven line, where $C is the total cost of entering the straddle. In terms of the stock price, the base of the V coincides with the strike used for the call and put. In other words, if buying a 125 strike straddle costs $7/share ($700/contract), then the maximum loss will occur if the stock expires at a price of exactly $125, making both options worthless at expiration.

The breakeven points for a long straddle fall $C above and below the strike price. Continuing the example from above, the stock price needs to be below $118 or above $132 at expiration for the straddle to be profitable. The further below $118 or above $132 the stock price is, the more profitable the straddle will be. Therefore, we can see that buying a long straddle is a bet that the stock price will move significantly by expiration.

Not surprisingly, a short straddle is a bet that the stock price will not move significantly before expiration. A short straddle is created by selling (shorting) a call and a put with the same expiration date and the same strike price. The short straddle risk profile is shown in the box to the left. As with all short option strategies, the profit is capped at the amount of premium collected ($P) when the position was entered. With a short straddle, that occurs when the stock price is exactly at the strike price at expiration. If the stock moves more than $P above or below the strike, the position will incur losses, and those potential losses are theoretically unlimited.

Strangles are close cousins of straddles. The difference is that strangles are created by buying (long strangle) or selling (short strangle) a call and a put with the same expiration date and different strike prices. The risk profiles are shown below.

A long strangle is less expensive to establish than a long straddle, because it uses an out of the money (OTM) call and put, rather than the pricier at the money (ATM) options used by the strangle. The disadvantage of the strangle is that the stock price has to move further before the position becomes profitable. For a long straddle with a cost of $C, the lower breakeven point occurs when the stock price expires $C below the put strike, and the upper breakeven point is $C above the call strike. Once the stock price moves outside this range, there is unlimited profit potential.

Similarly, the short strangle garners a smaller premium (max profit) than the short straddle. However, you get to keep the entire premium ($P) as long as the stock price stays between the call and put strikes, so there’s a larger margin of error with short strangles as compared to short straddles. As with the long strangle, breakeven occurs $P below the put strike and $P above the call strike.

In the next newsletter, we’ll discuss ways to evaluate straddles and strangles.

Click here to read Part 2.

How to Pairs Trade

If you’ve been trading for any length of time, you’ve probably noticed that the stocks you own have a tendency to move with the overall market. That’s great when the market goes in the direction that you want your stock to move, but rather irritating when the market moves against your position.

A common way to eliminate some of the market risk is through the use of pairs trading. You can find plenty of information on this style of trading on the internet, but the basic concept is that you own a long position in one security while simultaneously going short another security. In many cases the two securities will be stocks in the same sector, like Ford and GM, or Coke and Pepsi. But you can also pair a stock with a market-tracking index, like GE and SPY, which more directly addresses the problem of market risk.

The key question, of course, is how to know when you should be long the stock and short the index, and when you should be short the stock and long the index. Many people use a ratio of the prices of the two securities as a guideline. For example, the chart below plots the ratio of the price of GE over the price of SPY. The ratio has been multiplied by 100 just to bring it into a more typical range for prices.

When the price ratio is rising, you want to be long the numerator in the ratio (in this case, GE), and short the denominator (SPY). Conversely, when the ratio is falling, you want to be short GE and long SPY. The relative position sizes are also of great importance, but delving into that topic is beyond the scope of this newsletter.

Again, there are plenty of ways to determine which direction the ratio is likely to move. However, one that you may not have run into before is to apply our old friend the 2-period RSI, or RSI(2), to the price ratio. The chart below is identical to the one above, but with RSI(2) shown in red in the lower pane:

As you can see, when the RSI(2) value dips below 10, it is often a signal that the price ratio is about to rise. RSI(2) values above 90 often signal an upcoming decline in the ratio. However, if you look closely you will also notice that RSI(2) alone is not a perfect predictor of changes in the ratio. For example, in mid-June the RSI(2) peaks above 90 twice. After the first time, the ratio falls slightly but then makes a strong move upward.

It’s not surprising that RSI(2) might need a little help from some additional filters to make this strategy more robust. In fact, very few strategies rely on a single indicator. The important thing is that RSI(2) does a great job of identifying potential entry points for a pairs trade, and also allows you to quickly filter out a lot of the noise in the price ratio plot.

If you already include pair strategies in your trading toolbox, consider adding RSI(2) (or even ConnorsRSI if your platform supports it) to your other indicators to help you evaluate your trades. If pairs trading is new to you, it’s an area worthy of some further exploration.