Chips Ahoy!!

In Aug 2007 LSI Logic Corp. announced it would sell off its mobility products business unit to Infineon Technologies AG, and in September of the same year the number of baseband suppliers was further reduced when MediaTek Inc. purchased Analog Devices Inc.'s baseband chip product line.

Infineon now has the main stake in this business with 25% of the revenues coming from it.

In the rankings in the baseband market the main players were QCOM, MediaTek, Texas Instruments, STMicroelectronics, Infineon Technologies, Broadcom, Renesas, Marvell Technology Group and Spreadtrum Communications, according to iSuppli.

Data Visualization Tools

1) Ruby -- for data munging;
2) Postgres -- for database management;
3) World Programming System (WPS) -- for SAS legacy data programming;
4) Tibco -- for data visualization;
5) R -- for predictive modeling/data mining.

The developing interface between Tibco and R is very promising. 

http://www.tableausoftware.com/ 
http://www.panopticon.com/ 
http://www.qlikview.com/us/explore/products

WEKA

http://www.gapminder.org/ 

http://projects.flowingdata.com/walmart/

QCOM Snapdragon

The Qualcomm Snapdragon platform continues to generate robust industry attention to accompany its steadily expanding customer base. The Snapdragon platform is already incorporated into over 140 device designs that include mobile devices that range from HTC's Droid Incredible and Nexus One smartphones to Huawei's S7 tablet to name a few. 

The Snapdragon platform can be viewed as competing within the mobile application processor market segment (also referred to as the mobile multimedia processor market segment). Today the mobile application processor segment includes integrated circuit platforms that typically integrate the application processor core along with additional functions such as baseband modem and wireless connectivity functions onto a single system-on-a-chip; this includes the Qualcomm Snapdragon. 

The mobile application processor market also consists of IC platforms that exclude integration of baseband modems (e.g., Texas Instrument's OMAP 4). The mobile application processor platform segment addresses a wide range of mobile devices including smartphones, mobile Internet devices, netbooks and portable media devices. By its nature, the mobile application processor market segment attracts a wide swath of competition from the top-tier mobile silicon players, including Samsung, Apple, Intel and TI. 

Due to Qualcomm's historically solid competitive foundation, based heavily on its CDMA chipset royalties, and the burgeoning traction of the Snapdragon platform (in over 140 device designs), it presents a mounting competitive challenge and thus generates the key issue of how the competition can position against the overall Snapdragon platform. At the recent COMPUTEX 2010 show, Qualcomm unveiled the sampling of the third generation of its Snapdragon platform – namely its first dual-CPU Snapdragon chipsets consisting of the MSM8260, MSM8660 and QSD8672 products that feature enhanced dual cores that can run at up to 1.2 GHz and 1.5 GHz respectively, and are targeted at the high-end smartphone market area (the third generation Snapdragon platform is expected to support commercial products by the end of 2010). The new third-generation Snapdragon products complement its first-generation QSD8x50 1GHz core product and the second-generation MSM8x55 and QSD8x50A products with 1 GHz enhanced core, including multimedia optimizations and 1.3 GHz enhanced core respectively.

The Snapdragon platform has been commercially available since Q4 2008 through the QSD8650 and QSD8250 first generation product offerings. From its inception, Qualcomm positioned the Snapdragon platform as an innovative breakthrough offering since it uses the in-house custom developed Scorpion CPU as the core application processor based on the ARMv7-based Cortex-A8 core. This approach has enabled Qualcomm to engineer improvements over standard off-the-shelf ARMv7-based Cortex-A8 processors in areas such as power consumption (e.g., the first Scorpion processor required 150 milliwatts less power consumption at 600 MHz than the non-customized ARM equivalent and so on) as well as optimizing the processor design for the low-power process. As a result, the Snapdragon platform has proven a stalwart in the smartphone and tablet application processor market, as evidenced by the Snapdragon platform's multiple high-profile mobile device OEM selections. 

For the first generation Snapdragon QSD82x0 products and the second generation Snapdragon MSM8x55 and QSD8x50A products, Qualcomm shares platform and product metrics in areas such as core processor clock speed/performance, flexible wireless connectivity functions, HD video/3D/display/camera support and operating system versatility. This gives rivals a wide range of product areas to seek selective differentiation against the Qualcomm Snapdragon platform, although Qualcomm is hardly unique in that regard. 

The topic of core processor clock speed and performance, for example, represents a straightforward and intuitive product area for rivals to assert competitive differentiation. The Snapdragon platform's first-generation QSD8x50 supports a 1 GHz core processor while the second-generation MSM8x55 and QSD8x50A products support a 1 GHz enhanced core, including multimedia optimizations and a 1.3 GHz enhanced core respectively. 

In contrast, Intel asserts that its x86 processor-based Moorestown platform via the Atom Z6xx processor series can support up to 1.5 GHz clock speed for smartphone devices and up to 1.9 GHz clock speed for tablet devices. Such metrics will still match the third generation Snapdragon QSD8672 product that is designed to run dual cores that operate at 1.5 GHz (this product should appear in mobile devices at retail by the end of 2010). This complements Intel's overall efforts to position its Moorestown platform as prime time ready for smartphone technology due to the improvements realized in areas such as power consumption advances in battery life spans (based on 1500 mAh batteries) in support of 1080p/720p video (e..g, up to four hours for 1080p video) and browsing applications as well as multi-fold improvements gained in Java script, Web page, graphics and video performance. This includes up to fourfold Java script performance improvement and at least a doubling of Web page download performance and graphic performance in relation to the Qualcomm Snapdragon platform as well as wielding the industry's only across-the-board support of 1080 HP/MP/BP 30 fps and 720 HP/MP/BP 30 fps video capabilities. 

Intel's overall R&D investment and marketing blitz on behalf of the Moorestown platform is certainly targeted at Snapdragon, as well as advancing Intel's longstanding ambition to promote the x86 processor architecture as a viable alternative to the ARM processor architecture that dominates the mobile device silicon market today. Intel hopes to play a more prominent role within the overall mobile device silicon market beyond netbook silicon. There is a bit of irony here as Intel is looking to use the Intel Moorestown platform to attack the ARM-centric Snapdragon platform in Qualcomm's backyard of smartphone and tablet silicon, while Qualcomm is developing the Snapdragon platform to help more directly challenge Intel's prominence within the netbook silicon segment.

Apple, Samsung and TI are Qualcomm rivals that also use the customization of the ARMv7-based Cortex-A8 processor to achieve select advancements over the standard ARM offering. Samsung and Apple currently have a strange bedfellow arrangement that can influence how they position their respective platforms against the Snapdragon platform. Samsung collaborated with Intrinsity in developing and introducing its 45nm-based Hummingbird platform during 2009. In April 2010, it was revealed that Apple acquired Intrinsity in stealth mode to lock up the FastCore intellectual property that was instrumental in realizing the iPad A4 processor's enhancements to standard issue ARM Cortex-8 core processor technology (e.g., achieving 1 Ghz clock speed on a 45nm process). 

Through the acquisition, Apple can promote that its A4 processor development efforts are dedicated exclusively to the support of Apple products such as the iPad and iPhone, and the company can avoid the dissipation of processor engineering resources that its rivals, such as Qualcomm, are obliged to perform through the open-ended support of multiple OEM products. 

Samsung should look to further elucidate its plans to license the Hummingbird technology to other mobile device vendors and what if any impact this has on its Apple relationship. The Apple acquisition of Intrinsity does not change the fact that Apple's A4 technology remains based on Samsung's 45nm SoC technology and Samsung continues to have access and wield the Hummingbird IP gained from its joint collaboration with Intrinsity prior to the Apple acquisition of Intrinsity.

Samsung continues to register significant product development and marketing advances with its Hummingbird SC5PC110 processor. The Hummingbird S5PC110 runs the Samsung Galaxy S smartphone, which Samsung asserts will launch in an astonishing 110 countries. One area the Samsung can assert clear product differentiation against Qualcomm is in the area of 3D graphics. The S5PC110 processor can scale up to support 90 million triangles per second. In contrast, the Qualcomm QSD8650 delivers only 22 million triangles per second while the pending QSD8672 will do up to 80 million triangles per second. Additionally, in the related area of 2D graphics rendering, Samsung's S5PC110 product can support up to one billion pixels per second while Qualcomm's QSD8650 supports only 133 million pixels per second and the upcoming QSD8672 product still comes up short against Samsung with an improved 500 million pixels per second. 

TI's OMAP 4 platform using the OMAP4440 processor is slated to support mobile device products that will hit retail in late 2010/early 2011. The OMAP processor series is already found in well-known mobile handset products such as the Nokia N-series, the Motorola Droid, and the Palm Pre. However, OMAP 4 dual core clock speeds are limited to just 1 GHz, and that's for a product that is not yet in generally available mobile products. In this regard, OMAP 4 only ties the Qualcomm Snapdragon's first generation 1 GHz product and trails both the second and third generation 1.2 GHz/1.5GHz products. 

However, TI has already staked out a competitive position against Qualcomm in this area showing how apples-to-apples comparisons can prove dicey at times in the mobile silicon space. TI asserts that the OMAP 4 can deliver improved resolution display and still image metrics in relation to the Snapdragon platform, despite the core processor clock speed differentials. For example, the OMAP 4 can deliver 20-megapixel camera support while the QSD8x50 product can only handle 12-megapixel cameras. Moreover, TI advocates the OMAP 4 platform will prove more flexible in hardware support of future video codecs in relation to the Snapdragon platform. TI will also invoke that its OMAP4440 processor will use the ARM Cortex-9 architecture, which can yield performance improvements over ARM Cortex-A8 products (up to 30% according to ARM) and more flexible dual core power management arrangements.

Overall the most serious long-term competitive threats to the Qualcomm Snapdragon platform within the smartphone and tablet application processor market will prove to be the major mobile silicon players such as Samsung, Apple and TI, as well as Intel, who already possess competitive application processor platforms targeted specifically at smartphone, MID and tablet products. Mobile silicon rivals such as Marvell, Freescale, Nvidia and ST-Ericsson all sport viable mobile application processor platforms but need to prove they can move the market needle more within the mobile application processor market segment to mount a serious challenge to Qualcomm in the evolving smartphone/tablet silicon market segment. Marvell and Freescale have achieved market distinction within the eReader niche, for example, but are not able to match the Snapdragon's presence in over 140 device design wins. 

Samsung, Apple, Intel and TI all possess the product differentiators in areas such as core processor clock speed/performance, power consumption metrics, and HD video/3D/display/camera video performance and the global channels to challenge the Snapdragon's early market prominence in this area into the foreseeable future.

Ron Westfall is the Research Director of Silicon at Current Analysis and is responsible for tracking the evolution and the competitive landscape within the global chipset market, including mobile device chipsets. Westfall brings over twelve years of analytical experience to the overall telecommunications and silicon market, including specialization in mobile silicon, regulatory issues, and telecom infrastructure technologies. Contact Westfall at rwestfall@currentanalysis.com or follow him on Twitter @sirronsilicon.

Questions Every Investor Should Ask

Do you know whether?

Was the start of the year bullish or bearish, and how did the year progress quarterly?

How is domestic doing vs international?

How is value doing vs growth?

How is developed doing vs EM?

What are the numbers like Employment, CPI, WPI, Trade Balance, ISM, Retail sales and Housing?

How much is the corporate bond yield?

How much is the municipal bond yield?

If not then we can help you sort these things.

Bullish Strategies

These options strategies can be great ways to invest or leverage existing positions for investors with a bullish market sentiment.

LONG CALL

For aggressive investors who are bullish about the short-term prospects for a stock, buying calls can be an excellent way to capture the upside potential with limited downside risk.

COVERED CALL

For conservative investors, selling calls against a long stock position can be an excellent way to generate income without assuming the risks associated with uncovered calls. In this case, investors would sell one call contract for each 100 shares of stock they own.

PROTECTIVE PUT

For investors who want to protect the stocks in their portfolio from falling prices, protective puts provide a relatively low-cost form of portfolio insurance. In this case, investors would purchase one put contract for each 100 shares of stock they own.

BULL CALL SPREAD

For bullish investors who want a nice low risk, limited return strategy without buying or selling the underlying stock, bull call spreads are a great alternative.

BULL PUT SPREAD

For bullish investors who want a nice low risk, limited return strategy, bull put spreads are another alternative. Like the bull call spread, the bull put spread involves buying and selling the same number of put options at different strike prices.

CALL BACK SPREAD

For bullish investors who expect big moves in already volatile stocks, call back spreads are a great limited risk, unlimited reward strategy. The trade itself involves selling a call (or calls) at a lower strike and buying a greater number of calls at a higher strike price.

NAKED PUT

For bullish investors who are interested in buying a stock at a price below the current market price, selling naked puts can be an excellent strategy. In this case, however, the risk is substantial because the writer of the option is obligated to purchase the stock at the strike price regardless of where the stock is trading.

Bearish Strategies

These options strategies can be great ways to invest or leverage existing positions for investors with a bearish market sentiment.

LONG PUT

For aggressive investors who have a strong feeling that a particular stock is about to move lower, long puts are an excellent low risk, high reward strategy. Rather than opening yourself to enormous risk of short selling stock, you could buy puts (the right to sell the stock).

NAKED CALL

Selling naked calls is a very risky strategy which should be utilized with extreme caution. By selling calls without owning the underlying stock, you collect the option premium and hope the stock either stays steady or declines in value. If the stock increases in value this strategy has unlimited risk.

PUT BACK SPREAD

For aggressive investors who expect big downward moves in already volatile stocks, backspreads are great strategies. The trade itself involves selling a put at a higher strike and buying a greater number of puts at a lower strike price.

BEAR CALL SPREAD

For investors who maintain a generally negative feeling about a stock, bear spreads are a nice low risk, low reward strategies. This trade involves selling a lower strike call, usually at or near the current stock price, and buying a higher strike, out-of-the-money call.

BEAR PUT SPREAD

For investors who maintain a generally negative feeling about a stock, bear spreads are another nice low risk, low reward strategy. This trade involves buying a put at a higher strike and selling another put at a lower strike. Like bear call spreads, bear put spreads profit when the price of the underlying stock decreases.

Neutral Strategies

These options strategies can be great ways to invest or leverage existing positions for investors with a neutral market sentiment.

REVERSAL

Primarily used by floor traders, a reversal is an arbitrage strategy that allows traders to profit when options are underpriced. To put on a reversal, a trader would sell stock and use options to buy an equivalent position that offsets the short stock.

CONVERSION

Primarily used by floor traders, a conversion is an arbitrage strategy that allows traders to profit when options are overpriced. To put on a conversion, a trader would buy stock and use options to sell an equivalent position that offsets the long stock.

COLLAR

Bullish investors seeking a low-risk strategy to use in conjunction with a long stock position may want to try a Collar. In the example here, a collar is created by combining covered calls and protective puts.

BUTTERFLY

Ideal for investors who prefer limited risk, limited reward strategies. When investors expect stable prices, they can buy the butterfly by selling two options at the middle strike and buying one option at the higher and lower strikes. The options, which must be all calls or all puts, must also have the same expiration and underlying.

CONDOR

Ideal for investors who prefer limited risk, limited reward strategies. The condor takes the body of the butterfly - two options at the middle strike 0 and splits between two middle strikes. In this sense, the condor is basically a butterfly stretched over four strike prices instead of three.

LONG STRADDLE

For aggressive investors who expect short-term volatility yet have no bias up or down (i.e., a neutral bias), the long straddle is an excellent strategy. This position involves buying both a put and a call with the same strike price, expiration, and underlying.

SHORT STRADDLE

For aggressive investors who don't expect much short-term volatility, the short straddle can be a risky, but profitable strategy. This strategy involves selling a put and a call with the same strike price, expiration, and underlying.

LONG STRANGLE

For aggressive investors who expect short-term volatility yet have no bias up or down (i.e., a neutral bias), the long strangle is another excellent strategy. This strategy typically involves buying out-of-the-money calls and puts with the same strike price, expiration, and underlying.

SHORT STRANGLE

For aggressive investors who don't expect much short-term volatility, the short strangle can be a risky, but profitable strategy. This strategy typically involves selling out-of-the-money puts and calls with the same strike price, expiration, and underlying. The profit is limited to the credit received by selling options. The potential loss is unlimited as the market moves up or down.

PUT RATIO SPREAD

For aggressive investors who don't expect much short-term volatility, ratio spreads are a limited reward, unlimited risk strategy. Put ratio spreads, which involve buying puts at a higher strike and selling a greater number of puts at a lower strike, are neutral in the sense that they are hurt by market movement.

CALENDAR SPREAD

Calendar spreads are also known as time or horizontal spreads because they involve options with different expiration months. Because they are not exceptionally profitable on their own, calendar spreads are often used by traders who maintain large positions. Typically, a long calendar spread involves buying an option with a long-term expiration and selling an option with the same strike price and a short-term expiration.

Option Strategies

http://www.optionsxpress.com/free_education/strategies/bullish.aspx

Thoughts on flash

http://www.apple.com/hotnews/thoughts-on-flash/

Part 2 from Brett on Price Targets

This will be my second and final bonus post on the topic. As with the
earlier one, I will be keeping it on the site for a limited time as a
thanks to current readers. If the ideas interest you, you might want
to print the post out or jot down the relevant ideas.

In this post, I will explain how I calculate the daily price targets
that I post each morning via Twitter. I'm in the process of tweaking
my weekly target calculations and will wait for a future occasion to
share those.

CALCULATIONS

The calculations begin with the day's pivot level, as I define it:

Pivot = (H + L +2C)/4

Today's pivot price is defined as the average of yesterday's high
price plus yesterday's low price plus two times yesterday's closing
price. That gives us an approximation of yesterday's average trading
price.

Going back to late 2002, we touch the pivot level during today's trade
on 70% of all trading days. This is a useful "reversion" target if we
open above the pivot, but cannot sustain buying or if we open below
pivot and cannot sustain selling. (The current day's VWAP for the
index futures contracts is generally my first reversion target).

As mentioned in the earlier post, the overnight high and low price and
the prior day's high and low are generally my first price targets.
Along with the pivot level and VWAP, those are generally targets for
the first trades I will place during the day. Once I know those
targets, it's a matter of: 1) discerning the balance between buying
and selling sentiment, as well as sector and intermarket dynamics, to
gauge direction; 2) assessing today's volume relative to yesterday's
(and the prior five days' average volume) to gauge evolving
volatility; 3) executing the trade in the identified direction at a
price that provides a favorable level of reward relative to risk; and
4) holding the trade to the price target most likely to be hit given
the market's current strength and volatility.

(The above paragraph is a concise description of how I trade on the
day time frame).

The price targets above the prior day's high are identified as R1, R2,
and R3. The price targets below the prior day's low are identified as
S1, S2, and S3.

To calculate this levels, we need an estimate of recent volatility.
That estimate in my calculations is the median daily price range for
the past five trading sessions in SPY. Thus, each day we calculate the
Daily Range: DR=((H-L)/O)*100. That is the difference between the
day's high and low prices divided by the opening price multiplied
times 100 (to give us a percentage). The Volatility estimate (V) for
our calculations is the median of the prior five days' DR values.

As I mentioned earlier, going back to 2002, the median volatility for
the prior five days correlates with today's volatility by .80. Knowing
V gives us a good idea for today's DR.

So now we can define our R and S price targets:

R1 = Pivot + (.60*V)
S1 = Pivot - (.60*V)

Going back to 2002, we touch R1 or S1 about 84% of the time. If the
volume today is anything like yesterday's volume, R1 or S1 should be
hit during the day.

R2 = Pivot + (.80*V)
S2 = Pivot - (.80*V)

Going back to 2002, we touch R2 or S2 about 66% of the time. If
today's volume is above average, we should hit R2 or S2 during the
day.

R3 = Pivot + V
S3 = Pivot - V

Going back to 2002, we touch R3 or S3 about 50% of the time. If
today's volume is meaningfully above average, we should hit R3 or S3
during the day.

R4 = Pivot + 1.2 V
S4 = Pivot - 1.2 V

Going back to 2002, we touch R4 or S4 about 36% of the time. We need
to see volume today much greater than the recent average volume to
have confidence in hitting R4 or S4.

Obviously, you could define R5 and S5 levels (and beyond) accordingly
for relatively rare occasions of high volume trending and range
breakouts.

NOTES ON THE CALCULATIONS

These price levels were calculated and tested empirically in Excel
using historical data. They are not based on any Fib or any other
numerical scheme.

A worthwhile tweak on the above methodology would be to use today's
Open price in lieu of the Pivot for the calculations.

Another tweak substitutes weekly data for daily data to use for swing trading.

Another tweak is to adapt the formulas to different trading markets.

Knowing how far a market is likely to move in a direction is
invaluable in guiding the placement of stop and exit levels and
calculating the risk/reward parameters of a trade. By adjusting price
targets for recent volatility, traders can adapt quickly to faster and
slower market conditions. The price targets are not necessarily hard
exit levels; rather, they provide anticipation of where those proper
exits are likely to occur.

Brett's Formula

As I mentioned earlier today, in appreciation of the generous
readership, I thought I would share some of my ideas and methods for
calculating price targets. If you're new to this topic, it would be
helpful to review my prior posts on hidden volatility assumptions
anddefining effective price targets with the previous day's data.

What we saw in that latter post was that using the previous day's
high, low, and average prices provides us with relatively high
probability targets for the current trading day.

In my own work, I do not use the average price as defined in the post
(H+L/2). Rather, I use (H+L+2C/4). This is the "pivot" level that I
post each morning for SPY via Twitter. This overweights the closing
price relative to the prior day's high and low, so that--on
average--the pivot price will be closer to the current day's open.
Going back to late 2002 (N=1894 trading days), my Excel calculations
show that we have touched the previous day's pivot on 70% of all
trading days.

For this reason, the previous day's high, low, and pivot prices are
key near-term price targets for my trading. As I mentioned previously,
even closer price targets are the overnight high and low prices from
the ES futures.

If I anticipate a slow trading day with a narrow price range and we
open in the middle of the overnight and prior day's ranges, I will
look for trades to take out the overnight high or low price and then
the previous day's high or low. If I anticipate a slow trading day and
we open nicely above or below the overnight and prior day's pivot
levels (for overnight "pivot" I use the day's VWAP), I look for a move
back to VWAP and then the previous day's pivot if buying or selling
can't be sustained.

If I anticipate an average or busier trading day, I look toward more
distant profit targets. Below is one way of calculating those that
builds on the previous post.

FORMULAS FOR CALCULATING PRICE TARGETS

* Let us call the difference between yesterday's high and low prices
R, for range. That means that the difference between yesterday's
average price and yesterday's high is 1/2 R and the difference between
yesterday's average price and yesterday's low is 1/2 R. (We're using
average price, not the pivot level, for this calculation. More on
pivot-based calculations in the next post in the series).

* If we calculate (yesterday's average price + 3/4 R), we will get a
price level above yesterday's high that we'll call R1. If we calculate
(yesterday's average price - 3/4 R), we will get a price level below
yesterday's low that we'll call S1.

* Going back to late 2002, the odds of hitting R1 or S1 during today's
trade are 67%. Two-thirds of the time, we'll hit R1 or S1. It's a high
probability target if volume is average or better.

* If we calculate (yesterday's average price + R), we will get a price
level above R1 that we'll call R2. If we calculate (yesterday's
average price - R), we will get a price level below S1 that we'll call
S2.

* Going back to late 2002, the odds of hitting R2 or S2 during today's
trade are 41%. We want to see above average relative volume (and
today's volume > yesterday's volume) to assume that we'll touch R2 or
S2.

* If we calculate (yesterday's average price + 5/4R), we will get a
price level above R2 that we'll call R3. If we calculate (yesterday's
average price - 5/4R), we will get a price level below S2 that we'll
call S3.

* Going back to late 2002, the odds of hitting R3 or S3 during today's
trade are 26%. We would need to see significantly above average
relative volume (and today's volume significantly > yesterday's
volume) to assume that we'll touch R3 or S3.

VARIATIONS OF THE ABOVE WORTH RESEARCHING:

* Instead of using yesterday's average price as a base for
calculation, you can use the traditional pivot formula of (H+L+C)/3.

* Instead of using yesterday's average price as a base for
calculation, you can use today's open. That is especially helpful when
the overnight session leads to an opening price far from yesterday's
average price.

* Instead of using R values based on yesterday's trading range, use
the average trading range from the prior N days. My research shows
some benefit to going out several days, but returns are diminishing
out to a five-day lookback.

Regardless of your calculation method, you will find that R increases
as the market's volatility increases and decreases as the market's
volatility wanes. This automatically adjusts your price targets for
the market's most recent volatility.

Going back to late 2002, yesterday's volatility correlates with
today's volatility by a whopping .75. That means that we can predict
more than half of the variance in today's volatility simply by knowing
the prior day's trading range. If we go out to a five-day period, the
correlation between the prior five-day's average range and today's
range has been .80.

Once you become good at tracking today's volume relative to
yesterday's (or the prior five days'), you can make very reasoned
estimates as to which levels we're likely to hit during the day. That
considerably strengthens our exits and helps us maximize our
risk/reward.

This post and the next one (tomorrow) will remain on the blog for a
limited time. If the research is of interest, you might want to print
out the post or copy the relevant data.

Thanks again for all the interest and support--

Brett
.

Things to look for after a breakout

What I find among short-term traders is that they often will presume that breakouts will continue in their direction without actively planning for the possibility of retracement. When we see that stocks have broken to new highs (as we did this morning), but that other asset classes aren't participating significantly and that the number of stocks making new highs has been waning, we want to actively build a scenario for a possible reversion trade. Once the correlated asset classes begin to retreat, stock prices stall out, and we see NYSE TICK pulling back, we're then prepared to act on the scenario we've built.

It is much easier to act on market action if you've visualized and planned for it in advance.

Birth of a trade - Selling a Call

For the current month the underlying expired on high volume near some price say 40.

So the underlying has shown some strength recently and the first thing you would be to get the volatility envelope from your volatility package for the last 60 days.

Underlying at 40.27 and if you sell a 41 call on the underlying and see that right now it is trading for 77cents. That means you would get a 4% return in 30 days if called.

Also note that earnings of the underlying are 2 days after the month's expiry so the price will continue to move up towards the earning date.

The three goddesses have revealed the following numbers for this month's expiry.

39 41

38 42

37 43

March 25th 2010,

It is just 2 days after the above post and here we see a jump in the underlying towards the three SD price level. So should we sell a call now as the volatility is very high indeed....

41 calls have now climbed from .77 to 2.90

44 calls @95

and 45 calls @56

Whoa.......

Let us see what happens.....

Mar 30th 2010

Underlying is pulling back from the breakout towards 42.00 expect it to stay there for 2-3 days and then move higher as we head into earnings.....but since the broad market is topping out we dont know for sure

41 calls at 1.61

44 calls at .25

45 calls at .12

BroadMarket showing weakness at 117 being the resistance and 115 a support

Identifying Breakouts

http://traderfeed.blogspot.com/2010/03/identifying-breakout-moves-in-stock.html

Coaching a Trader

Trading Fundamentals

Executing a trade countertrend

The resolution of this issue represents what has been, for me, the
single best contributor to the profitability of my trading in the last
couple of years.

And here it is, in all its simplicity:

I trade with the trend.

I execute the trade countertrend.

That is, if I identify an uptrend at time frame X, I wait for a
pullback at time frame (X-1) to enter the market on the long side. If
I identify a downtrend at time frame X, I wait for a bounce at time
frame (X-1) to enter the market on the short side.

If I'm a buyer, I wait for the sellers to take their turn in the
market and show me what they've got. If they cannot push the market
below a prior low reference point, I'll buy and use that reference
point as a stop.

If I'm a seller, I let the buyers rally the market and show me how far
they can take it. If the buying dries up below a reference prior high,
I'll sell and use that reference area as a stop.

If we have a good trending move and a weak countertrend dip or bounce,
we'll usually at least test the prior highs or lows. That means that
even a trade that doesn't roar to new highs or lows can often be
exited with some profit.

That execution edge can make all the difference in terms of
profitability; it has for me.

Best of the Reads

Best of Trader Feed Posts

Why is trading difficult?

Markets change their behavior faster than people can change their
minds. And that is why intraday trading is so difficult.

Mistakes of a Scientific Trader

In the first two posts in this series, we examined a scientific mindset and how it affects trading practice. Let's now turn the tables and view three common trading mistakes through the scientific lens:

1) Mistake #1: Trading Without Understanding - Sometimes traders put their capital at risk without taking the time to observe market patterns and integrate these into a concrete explanation of what is happening in the marketplace. A number of traders I work with observed the recent rise in interest rates very early in the move and formulated ideas of shorting rate-sensitive sectors. They tested their understandings with initial positions and scaled into the idea as markets confirmed their views. How different this is from simply putting a position on because a market is making a new high or low! 

2) Mistake #2: Oversizing Positions - Many psychological problems in trading can be traced back to excessive position sizing. Traders trade too large for their account size in order to make windfalls, not in order to test their ideas. Scientists conduct many tests before any hypothesis is truly supported, and they test many hypotheses before they accept theories as versions of truth. If you were a lab scientist, would you risk your entire grant funding on a single experiment? Of course not; a single study could fail for a variety of reasons, including experimenter error. Similarly, any single trade or idea can fail for a variety of reasons. A true scientist knows that his or her understanding will always fall short of reality. That is why scientists will conduct doable experiments to refine their ideas before they dedicate significant resources to large investigations.

3) Mistake #3: Not Knowing When You're Wrong - A scientist does not actually test his or her hypotheses. Rather, each experiment is framed as a test of the "null hypothesis": the proposition that variables of interest do *not* affect the outcomes under study. Scientists thus never accept their hypotheses; they at best only reject null hypotheses. Embedded in this perspective is the idea that it is crucial to know when it is necessary to accept that mull hypothesis and conclude that a view is not supported. Can you imagine a qualified scientist becoming emotional because an experiment produces no significant differences and then conducting numerous revenge studies?! Traders, however, sometimes do just that. They don't have rational stop losses identified and so can't terminate their "experiment" at a prudent time. That leads them to take on excessive losses and react out of frustration rather than understanding.

A simple checklist would aid many traders who would become their own performance coaches:

1) What is my understanding of this market and what is the evidence behind it?

2) How much of my capital am I initially willing to devote to my understanding of this market?

3) What outcome(s) would lead me to devote more capital to my idea and what is the maximum portion of my portfolio I'm willing to put at risk on this idea?

4) What outcome(s) would lead me to abandon my idea and how much am I willing to lose on this idea?

Many bad trades could be avoided simply by requiring oneself to answer these questions aloud prior to any trade.

A Trader Scientist

A theme I emphasize with new traders is that it is important to trade like a scientist. The scientific mindset is one that can be rehearsed and cultivated--and eventually internalized.

What do scientists do? First, they observe regularities in nature. They look for patterns: repeated sequences of events and commonalities among structures. Those regularities differentiate what is meaningful from what is random.

After observing regularities, scientists attempt to explain these. Explanation is the role of theory. The theory is the scientist's way of making sense of the world. Theory is not truth; it is a first approximation at truth.

Scientists gain confidence in their explanations by testing them. If a theory is meaningful and accurate, we should be able to use it to generate future observations. These predictions are hypotheses for the scientist. By testing hypotheses, we keep an open mind with respect to our observations and explanations.

Finally, once empirical tests provide fresh observations, scientistsrevise their explanations of nature and use these to generate further hypotheses, observations, and revisions. Knowledge, for a true scientist, is always provisional: that is what separates science from dogma.

The scientific mindset is one of humility: a recognition that our best theories are only approximations and that many of our tests of hypotheses are apt to fail. When we trade, we have an implicit or explicit theory about the current market, and our trade tests a hypothesis that we frame around our explanation. That is why a scientific trader never wagers too much on any single trade. Nature will always be more complex than our science, and our understanding will always be partial. Such a perspective is a powerful antidote to overtrading and overconfidence.

If I am trading like a scientist, I am carefully observing the market and watching for patterns. I already have observed many markets in many conditions and have some theoretical understanding of what makes markets move across different time frames--from interest rates and liquidity at longer periods to the aggressiveness of large traders at short ones.

Perhaps I notice that, as selling hits the market, volume is declining and fewer individual stocks are making fresh price lows. I also notice that one sector of stocks, the semiconductors, are actually moving higher and gaining money flow. Bonds, which had been falling with stocks, are now catching a bid. I hypothesize that the market is running out of sellers, that we are in the process of bottoming, and that we will likely see short covering as a result. That should propel the market higher.

Having formed this hypothesis, I make note of a recent short-term high price in the semiconductors and the low price. I say to myself, in essence, "I think we will hit this price (prior high) before we touch that price (recent low)." In other words, I am willing to risk a possible move back to the low in order to participate in the hypothesized move to the high.

This is only a hypothesis, however; it is not truth. For that reason, as a scientist, I must remain open to data that tell me my hypothesis is not supported. A fresh influx of sellers hitting bids; a fresh drop in bonds--many factors could alert me to a potential problem with my hypothesis. I also must keep my bet on this hypothesis modest: to risk much of my capital on the idea is to treat the tentative formulation as absolute truth.

It is in this context that every good trade tests a hypothesis. When we observe a pattern, frame an idea, test the idea with a trade, and actually profit, our idea--our theory--is supported. That may lead us to another trade that extends this idea. Conversely, if we do not profit from our theory, we may need to go back to observation mode and revise our explanations.

Thus it is that a scientific trader will gain confidence and become a bit more aggressive when his or her ideas are confirmed; a bit more cautious when ideas do not pan out. When you trade like a scientist, every good trade provides you with information, because every good trade is a solid test of your market understanding. For this reason, the scientific trader values losing trades. They, no less than the winners, are data to be assimilated and can push you to further market insight.

A quality of excellent trader

The failing trader does not set or honor stops and is left with a deteriorating position. The good trader sets a stop and limits his loss. The excellent trader extracts information from the losing trade to generate profits.

Finding Opportunity in a loss

Let's say I think stocks will break to the upside and I take a long position. The market goes my way initially, but then reverses. What looks like a valid breakout now shows itself to be a false breakout. I stop out of the position and take a modest loss.

That is good trading.

One trader I recently talked with took exactly those actions--and one more. He saw that the breakout was false, stopped out of his position, and took a modest loss. But he had mentally rehearsed what he would do under just such a scenario. He had told himself that if this long trade didn't work out, the market could retrace the entire prior day's range.

So he stopped out, took his loss, and flipped his position to be short.

He made money on the day.

That is great trading.

The losing trade set him up for a winning day, and all because he was prepared to act on opportunity, not just prepared to limit risk.

A few more Quotes

We can't grow if we stay in the comfort zone.Best strategy is to follow your anxiety and take that ride beyond the comfort zone.

Happiness Begest Success...When we're happy, we become forward-looking which energizes us to achieve stretch goals.