Why Use Historical Charts

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Why Use Historical Charts

Historical charts, or just charts, are the means by which we do what we do. Trade. Charts of historical price action are incredibly valuable and there is no question of there importance to technical analysis. However, there is widespread debate over the importance of using historical data to back test and its reliability on future results. Well, I’m here to tell you that it is important and it is a reliable means of predicting future results. Seriously, if you doubt it then why are you even considering using technical analysis? Technical analysis is nothing but charts, past price action and its bearing on future price movements. One of the pillars of TA is that the market always repeats itself and those repetitions are measurable and predictable. As for back testing goes, hindsight is 20/20 as the saying goes. It’s easy to look back on a chart and see where a signal formed just so, leading to profits.

An Invaluable Educational And Trading Tool

Historical charts are important for a number of reasons. First and foremost is education. You have to learn in order to be good and using past examples is a well recognized method of teaching. It’s one thing to read about rising and declining triangles, support and resistance, pin bars, retracements, cross overs and oversold levels but it is something else to see it, on a chart, and to see how price action behaved before and after. Think about naturalists for example. There are millions of varieties of insects on the planet. In order to recognize and differentiate the myriad variety of ants from each other and other ant-like insects scientists study examples in the laboratory. For us as traders our lab is the charts. We go to the lab, examine known examples of past price patterns in order to become familiar with them and hone our skills and then we look for those patterns as they begin to appear in order to make trades. The more familiar you are with past price patterns the better you will be at recognizing them as they happen.

The second reason, and equally important, is that historical data has great bearing on current price action. Past highs and lows are often key areas of support and/or resistance that provide targets for entries. These highs and or lows represent areas where past buyers are either able to recoup losses or to get into new trades at ideal prices. They can be areas that attract new buyers or prove to current bears that the market is indeed truly weak. At the same time past price action can also be indicative of direction and duration of a move. A break out from a bull flag has an easily predictable target level, important for binary traders because that is a crucial factor in determining expiry. I have found over the ten plus years I have been trading that a line drawn on my charts never ceases to be valid. If I draw it and prices come back to it tomorrow, next week, next year or many years down the line it will affect price action.

Look at the chart above of the CBOE Gold Index. This is a ten year chart of monthly candlesticks, a very long term chart indeed. It is easy to see that the lows of 2008 are acting as a support level for the index at the current time, 5 years later. This support level has a strong implication than a shorter term level of support or resistance and could adversely affect a trade if not accounted for. This same theory applies down through all the time frames. A trader could use this chart and then drill down to one of weekly prices in order to more closely watch support and then use charts of daily and hourly prices to pinpoint trades based on bounces and breaks of the long term support line. I have also used Fibonacci Retracements on this chart as a means of predicting other areas of support and resistance, all based on past price action. In the end, all recognizable past price movements can have an impact on current price action.

The Hard Right Edge

The part of the chart where new price action happens be it weekly, daily, hourly or shorter is often referred to as the “hard right edge”. This is because, obviously, it is the right side of the chart but also because this is where the hard decisions have to be made. Whether or not to buy, sell or hold. Making a trading decision can be very hard, so hard in fact that it keeps many from ever pulling the trigger. This is why using the historical charts, knowing the historical charts and using past price action is so important. It will help you learn what to look for, boost your confidence level so you know what to expect when you see what you have learned begin to unfold and pave the way to a life of successful trading. Knowing exactly what prices will do once you reach the hard right edge is impossible to do but you can still trade with confidence knowing that you will be right more times than you are wrong.

Why to use also historical stock charts

It is a big mistake done by investors who have never checked historical stock charts. Also plenty of traders who concentrate to short-term stock market price chart analysis and omit making analysis of long-term stock charts will make more errors in their trading.

Checking the historical chart stock market situation, actions and important price levels could provide valuable information for today’s stock market trading and investing decisions.

Historical stock charts could provide several important pieces of information about how a stock acted in specific situations like a bad earnings release, increase of major interest rate by central bank, decrease of such rate, debt problems, major bankruptcy and much more.

Here are tips how to maximize returns using historical charts in your analysis.

Check long term stock charts regularly

Do you check historical price charts regularly? I think that every trading or investing decision should be based on knowledge of historical share price development.

Why? There are plenty of reasons, but most important is to compare today’s market situation with the historical charts of the market situation back then.

It is old knowledge that should be imprinted into the head of every investor and trader that says: history repeats and repeats, and forget it at your peril.

Set up multi time frames for long term stock charts

So, based on this knowledge it pays to check the history of trading a few months or years back. Technical traders especially should use these methods and implement multiple periods into their chart analysis and use the historical chart type more often than not.

Historical price charts will help you identify major levels of support and resistance. I personally use three basic charts when I study historical share price market data.

Monthly stock market historical charts

Monthly is the longest time period used by swing and position traders. Here you should monitor most critical levels of support and resistance only on the historical stock charts.

Weekly historical stock price charts

This mid-term period helps you identify good trading opportunities. Here you can see how share price acts near an important support or resistance level. It also signals the best possible values for a stop loss.

Daily time frame

This is shortest time frame for swing traders and position traders. Use it for precise selection of the entry point.

You should place all three charts together on one or more monitors to see all the periods together. It is always important to know major support and resistance levels from a larger time frame. Historical price charts are valuable tools for such analysis.

The types of historical price charts could also be determined by type of stock trading you want to use. If you are daytrader, it is probably not necessary to have monthly graphs but your long-term chart could be daily – if your main trade frame is one minute or an hourly chart.

But all these charts should be based on simple chart reading. If you want to use several indicator please organize them.

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Why Use Control Charts?

Can they help to do a better job?

Published: Wednesday, June 26, 2020 – 12:03

I n everyday language, “in control” and “under control” are synonymous with “in specification.” Requirements have been met. Things are OK. No trouble.

“Out of control,” on the other hand, is synonymous with “out of specification.” Requirements have not been met. Things are not OK. Trouble.

Using this language, an obvious axiom would be: Take action when the process is out of control.

The everyday use of in and out of control is, however, unfortunate for control charts, the major tool of statistical process control (SPC). Why? Because in SPC these terms speak of processes as being stable or unstable. To characterize a process as stable or unstable, process limits, from process data, are needed. Specification limits are not needed.

Given the easy-to-understand basis for the action of meeting or not meeting requirements, coupled with the risk of confusion over the terms in control and out of control, why use control charts? If you are curious to see some of the benefits in doing so, read on. Two case studies are used.

Case one: Part thickness

During a regular review meeting in Plant 17, in- and out-of-specification data on the thickness of part 64 were reviewed.

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About The Author

Scott A. Hindle

Scott Hindle supports R&D and factory operations on process capability studies for new products and processes, statistical process control (SPC) for use in routine production, and the use of on-line measurement devices as a part of both SPC and engineering process control.

Comments

Why Use Control Charts

I found this article especially useful. The Florida Department of Transportation is working with our crushed stone industry to implement statistical process charts. The industry uses a common commercial software with the capabilities, but SPC is not a familiar tool.

We are teaming to develop a system that is logical and works for both FDOT and Industry. A common case we have come across and are trying to assess is what happens when products are within spec, but the Natural Process Limits are outside the specifications. That is Cpk 08/27/2020 – 06:12 am — Marcal Plans Pujolras (not verified)

Excellent material and detailed explanation of two cases

Thank you for our article. it is a great publication on two cases that brought the opportunity to discuss between the voice of the customer and voice of the process. Unfortunately, there are too many cases that there is no action until the trouble is already on our plate. As you mention, there is some missed opportunity to do not implement control charts and use them to translate this information to dollars.

I look forward to your next article!

Why Use Control Charts?

Another great article, Scott. It is kind of sad there is still so much confusion about statistical control versus within specifications. Hopefully this article will be a helpful remedy. The Shewhart control charts put us at a crossroads and enable us to answer a very broad question: What problems will be best solved by workers (unstable) close to the process and what problems will be charged to management (stable)? Without this knowledge, management in general believes faults are on the factory floor and improvements are for someone else, not me. In The New Economics, Dr. Deming estimated 94% of problems belong to management and only 6% are special.

The big gains are in management awakening:

“Causes of nonrandom variation are called assignable causes or special causes. And those are usually chargeable to particular, local conditions that the workers can recognize and eliminate. And then you have left random variation that defines the system, and from then on only the management can improve it. That was Shewhart’s great contribution.” – W. Edwards Deming

THE EARLY INFLUENCE OF W. EDWARDS DEM1NG ON THE DEVELOPMENT OF STATISTICAL QUALITY CONTROL IN THE UNITED STATES AND IN JAPAN, Nancy R. Mann

Why Use Control Charts?

Thanks for writing the article, Scott.

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It is unusual to see an article that is set in the real world and not the theoretical of SPC. Your approach is very practical. If only we can get more employers to see that SPC is meant to be used in realtime for defect prevention, rather than after the fact for process improvement, the world would be a better place. Fortunately, my employer firmly supports the former.

Control versus Predictable

Nice article Scott! You have articulated what is needed in production operations of every type.

I too ran up against the thought that “in control” meant within specifications. That is when I started using predictable and unpredictable to describe the behavior of a process. It has less emotional baggage than in control and out of control.

The problems in production are like fog or smog, and process behavior charts (control charts) can spotlight what needs attention and where we need to work. Moreover, without the framework of an approach such as control charts it is difficult to get the most out of any process. The problems of production are greater than those of research, where we spend a lot of time on developing techniques for learning. Moreover, the problems of production change with time, and this is why we need a time-oriented technique such as the control chart.

Thanks for this article.

Why use control charts

Very, very detailed article; shall need time to go through fully.

I only wish to express my surprise at two points of your article (as far as I have gone).

Sentence 3 i.e “Out of control,” on the other hand, is synonymous with “out of specification.”

Whether figure 2 –plot of individual values of a parameter ‘should’ and ‘can’ be called a “CONTROL CHART”.

With due regards; I venture to disagree with both.

PS I shall read the article fully and try to give more comments.

Virendra, See my comments

Virendra, See my comments below on why I believe there a common language usage of out of control in relation to out of specification.

Understanding and reducing variation

A nice article by Scott.

Little’s Law guarantees that if we reduce the variation in flow of materials through a process that either volume throughput will rise, or work-in-progress will fall, or some combination of both. This is a law.

Scott’s article shows how using control charts helps us to understand and reduce variation.

Better quality, increased throughput, recuded cycle time . we can have it all if we know how to reduce variation.

Hi John, I’ve had your books

I’ve had your books for decades.

I’ve added a variation slider in the Lean Simulation in Q-Skills3D, together with a graphical output. I’ve been rather surprised by the results. Variation has much less impact than I would have thought. The simulation variation slider varies the processing speeds randomly at either station. It would be interesting to see a mathematical analysis. Small changes in the mean at either station have an obvious effect. The sim also shows Little’s Law graphically. It takes a long time to settle down.

Thanks for such a detailed ,though simple way of presenting, today’s most important topic of manufacturing processs-Why use control Charts!

I think, adjusting the average to the centre of the specification doesn’t demand much effort in the process lines but manier times the reality is that we try to be too safer!

Am sure this article will help many of the factory guys to produce compliant product with stable process by operating at full potential.

Well done Scott. Nice to see

Well done Scott.

Nice to see histograms without the all too common and meaningless normal distributions drawn over them

Your Fig 6 also shows how the WE Rule 4 (8 point below CL) is superfluous, as Dr Wheeler describes here: https://www.qualitydigest.com/inside/statistics-column/when-should-we-use-extra-detection-rules-100917.html “Rule one has been the key to process improvement for more than 90 years. Use it and learn about the dominant assignable causes affecting your process. In practice, rule one will usually generate all the signals that most people can realistically investigate.”

Keep it simple. KISS. There’s plenty of free software to draw control charts.

“In control” does not mean you are meeting specifications

Good article except for your opening statement: “In everyday language, “in control” and “under control” are synonymous with ‘in specification.’ Requirements have been met.”

Control charts tell us if the process is stable and predictable, not if requirements have been met. I’ve seen a lot of processes that are stable but not within specifications.

Once you have a stable process (determined by control charts), you can then use capability analysis to determine if the process is meeting specifications. Cp and Cpk can tell you if you’re meeting specifications or not, as shown in this article.

Stable isn’t always capable.

Two different meanings of in and out of control

Thanks for the comment. Fully agree that stable doesn’t mean capable: In SPC, stable (in control) or unstable (out of control) tells us nothing about whether specs have been met or not.

The control chart meaning of in and out of control is different to the colloquial, everyday usage. I picked up on the potential obstacle of terminology some years back (e.g. https://www.spcpress.com/pdf/DJW129.pdf). My experience is that in control and out of control as terminology risks confusion, which can only reduce the expectation of successful control chart usage.

As an example, in training classes it typically works out that after breaks the sessions restart a few minutes late. I noticed it to be a pretty stable situation, repeating itself year after year and in different locations. I plan for it.

I learnt to make an analogy of re-start time as a “process”, where the goal is stated as an on-time start. This goal isn’t met. When asked, a sizeable number of people tend to say this “process” is out of control (not in control). Yet, it is pretty stable, only far from capable. In Figure 10 this “process” would be in the Threshold State.

My emphasis at the start of the article is how in control and out of control are used in everyday, colloquial language. In everyday language, I believe “in control” and “under control” are synonymous with specs/targets having been met.

One set of terms and two meanings is a likely source of confusion. My point in the paper is that the colloquial use of in control / out of control has a meaning that is different to the “SPC meaning”.

Controlling understanding

In discussions with engineers, I’ve been careful to make a distinction between engineering and statistical control. Which, of course, uses the word “statistical”, but one thing at a time.

I have a couple of canned charts showing how engineering control (being in spec, controlled by a feedback loop, etc.) is different from being predictable. We have lots of examples of weeding out half of a lot through inspection and high variation despite tight control of the wrong parameter to control to achieve quality to make my case. But it takes time and an engineer or a manager willing to stand with me in an elevator and talk about something besides the weather!

In these discussions, I’ve been forcing a connection between statistical control and predictability. Maybe it’s time to rename statistical control to . predictably controlled? Just predictable?

Thanks, Scott.

Nice article. Working with a couple of colleagues responsible for incoming quality of subassemblies. This says what I’ve been trying to say much more cogently and interestingly.

We work for what’s essentially been a huge job shop. Production articles have rarely been repeatedly produced, so we’ve been relying on engineering control (meeting spec) to assure we get what we want. Yes, yes, it would have been easy and helpful to use SPC and similar, but what we’ve done has mostly worked.

We’ve recently begun working with larger-volume manufacturers, working toward regular purchases involving significant numbers of the same parts, subassemblies, finished assemblies and even services. We’ve taken our usual approach of certifying an original design, then inspecting the bejeezus out of what comes to us and comparing that to specs. Many of the managers, engineers and others I’ve been working with are recognizing that we could get even more value if we make sure the manufacturing and operation processes going forward is the same as what got certified in the first place – that the process is predictable, in statistical control.

I’m from heavy industry. I know this will work. It’s unfamiliar to my present employer and our suppliers, though. Time will tell whether it catches on in any meaningful way, but so far, the simplicity and head-smackingly visually obvious methods of SPC are piquing interest.

Keep writing. btw – really appreciate the relevant links to other articles.

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