Max Pain Nifty

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Max Pain Nifty

What is maximum pain in Nifty?

Key Takeaways –

  • Max pain, or the max pain price, is the strike price with the most open contract puts and calls and the price at which the stock would cause financial losses for the largest number of option holders at expiration.
  • The Maximum Pain theory states that an option’s price will gravitate towards a max pain price, in some cases equal to the strike price for an option, that causes the maximum number of options to expire worthless.
  • Max pain calculation involves the summation of the dollar values of outstanding put and call options for each in-the-money strike price.

What is the max pain index?

The max pain is the price at which the stock can cause the highest level of financial losses for all the options buyers who have the contracts at that strike price at the time of expiration.

What is the max pain theory in options?

How to determine the Point of Maximum Pain? – Max pain point takes a lot of time for calculation yet it is a simple process to calculate the same. It is computed by aggregating the value of the put and call options outstanding for all the strike prices.

Step 1: Ascertain the difference between the current market price of the stock and the strike price.

Step 2: Find the open interest at that strike price and multiply it with the result from Step 1.

Step 3: Perform this computation for both, call and put options.

Step 4: Take the sum of values derived from the call and put open interests.

Step 5: Carry out the same drill for all the available strike prices.

Step 6: Ascertain which strike price has the highest value.

That strike price is the point where the options traders will have the maximum pain of bearing the monetary loss.

What is the maximum pain for SPX option chain?

The Max Pain for $SPX options expiring on Jun 22, 2023 (1 days) is $4,350.00.

Is Max pain theory real?

Can traders actually rely on the Max Pain theory? – Broadly, it is true that option sellers have a better understanding and therefore better control over option prices compare to the retail traders who are essentially buyers of the options. That means you can take advantage of the max pain theory.

The theory believes that as options expiration approaches, stock price will get pushed toward the price at which the greatest number of options (in terms of rupee value) will expire worthless. In other words, the theory holds that when expiration approaches, stock or index price will gravitate toward the price that will cause maximum pain to both call and put buyers.

In short, option pain is the point at which buyers lose the most and sellers gain the most. If you understand this concept, then even as an option buyer, you can profit from this knowledge.

What is the highest Nifty of all-time?

Nifty hits all-time high as markets gain momentum : Benchmark index Nifty 50 opened at an all-time high on Wednesday as domestic markets gained momentum, tracking positive global cues and a strong uptick in Adani Group stocks. In pre-open trade, the Nifty 50 rose 0.48 per cent to 18,908.15, surpassing its previous all-time high of 18,887.30.

Today’s milestone comes after several sessions where the Nifty, By 9:55 am, the Nifty 50 was trading 200.70 points higher at 18,891.90, while the S&P BSE Sensex was up 681.94 points at 63,651.94. Swapnil Shah, Director of Research, StoxBox, said, “Nifty has crossed the previous ATH (all-time high) and moved beyond the crucial 18,900 levels for the first time in history as market sentiment remained buoyed by the progressive news about the HDFC-HDFC Bank merger and strong current account deficit data for the fourth quarter.” “Yesterday’s closing in the green of the US markets also supported gains in today’s trading session.

We believe that a rapid and widespread progress of the monsoon, albeit with delay, should keep investors interested in the markets in the short term,” he said.

What is a level 10 pain?

Using the Pain Scale If you want your pain to be taken seriously, It is important that you take the pain scale seriously. Because pain is subjective, it is difficult to explain what you’re feeling to another person—even your own doctor. To effectively use the pain scale, familiarize yourself with the levels before your procedure, identifying what key levels are indicative to your pain level.

  • Following a surgery or procedure, typically we tell patients to continue to take medications that allow them to maintain a level of “5 or below.” 0 – Pain Free Mild Pain – Nagging, annoying, but doesn’t really interfere with daily living activities.1 – Pain is very mild, barely noticeable.
  • Most of the time you don’t think about it.2 – Minor pain.

Annoying and may have occasional stronger twinges.3 – Pain is noticeable and distracting, however, you can get used to it and adapt. Moderate Pain – Interferes significantly with daily living activities.4 – Moderate pain. If you are deeply involved in an activity, it can be ignored for a period of time, but is still distracting.5 – Moderately strong pain.

It can’t be ignored for more than a few minutes, but with effort you still can manage to work or participate in some social activities.6 – Moderately strong pain that interferes with normal daily activities. Difficulty concentrating. Severe Pain – Disabling; unable to perform daily living activities.7 – Severe pain that dominates your senses and significantly limits your ability to perform normal daily activities or maintain social relationships.

Interferes with sleep.8 – Intense pain. Physical activity is severely limited. Conversing requires great effort.9 – Excruciating pain. Unable to converse. Crying out and/or moaning uncontrollably.10 – Unspeakable pain. Bedridden and possibly delirious. Very few people will ever experience this level of pain.

What is max pain metric?

What is max pain? – Max pain is a calculation that shows at what price level option holders (buyers) would as a whole suffer the maximum amount of financial pain. This is calculated based on all open interest for the given expiry date, and is not concerned with any individual trader’s specific position.

To calculate maximum pain a strike price is chosen, then for all options currently still open (at all strikes), the intrinsic value of each option is calculated as if the price had already expired at the chosen strike. This process is repeated for every available strike price, giving a total intrinsic value of all options if price were to expire at each strike price.

The strike price with the lowest intrinsic value, is max pain. So for example let’s assume a particular expiry has only three available strikes of $8,000, $9,000, and $10,000. First we would calculate the intrinsic value of all options assuming an expiration price of $8,000.

Then we calculate the intrinsic value of all options assuming an expiration price of $9,000. Then the same assuming a price of $10,000. Whichever of these three calculations gives the lowest figure, that strike is said to be ‘max pain’ for option buyers. Of course in the real world there will be many more strikes than this with varying levels of OI for both the puts and calls, so the calculation would be rather tedious to do by hand.

Thankfully it is relatively simple to do using a spreadsheet. You can download a premade excel spreadsheet I made here, Once you download a copy, with this spreadsheet you’ll just need to enter the expiry date and strikes, then the sheet will do the rest for you.

What is the pain scale 7?

Cut-Off Points for Mild, Moderate, and Severe Pain on the Numeric Rating Scale for Pain in Patients with Chronic Musculoskeletal Pain: Variability and Influence of Sex and Catastrophizing 1 ‘Revalidatie Friesland’ Centre for Rehabilitation, Beetsterzwaag, Netherlands Find articles by 2 Department of Health Sciences, Community and Occupational Medicine, University Medical Centre Groningen, University of Groningen, Groningen, Netherlands Find articles by

  • 3 Adelante Centre of Expertise in Rehabilitation and Audiology, Hoensbroek, Netherlands
  • 4 Department of Rehabilitation Medicine, CAPHRI Research School, Maastricht University, Maastricht, Netherlands
  • 5 Faculty of Health and Technology, Zuyd University for Applied Sciences, Heerlen, Netherlands

Find articles by 6 Department of Rehabilitation Medicine, MGG Medical Centre Alkmaar and Gemini Hospital Den Helder, Alkmaar, Netherlands Find articles by 7 Rijndam Rehabilitation Institute, Rotterdam, Netherlands Find articles by 8 Roessingh Research and Development, University of Twente, Enschede, Netherlands Find articles by 9 Department of Rehabilitation, Centre for Rehabilitation, University Medical Centre Groningen, University of Groningen, Groningen, Netherlands Find articles by

  1. 1 ‘Revalidatie Friesland’ Centre for Rehabilitation, Beetsterzwaag, Netherlands
  2. 2 Department of Health Sciences, Community and Occupational Medicine, University Medical Centre Groningen, University of Groningen, Groningen, Netherlands
  3. 3 Adelante Centre of Expertise in Rehabilitation and Audiology, Hoensbroek, Netherlands
  4. 4 Department of Rehabilitation Medicine, CAPHRI Research School, Maastricht University, Maastricht, Netherlands
  5. 5 Faculty of Health and Technology, Zuyd University for Applied Sciences, Heerlen, Netherlands
  6. 6 Department of Rehabilitation Medicine, MGG Medical Centre Alkmaar and Gemini Hospital Den Helder, Alkmaar, Netherlands
  7. 7 Rijndam Rehabilitation Institute, Rotterdam, Netherlands
  8. 8 Roessingh Research and Development, University of Twente, Enschede, Netherlands
  9. 9 Department of Rehabilitation, Centre for Rehabilitation, University Medical Centre Groningen, University of Groningen, Groningen, Netherlands
  10. Edited by: Lorys Castelli, University of Turin, Italy

Reviewed by: Diana M.E. Torta, Université catholique de Louvain, Belgium; Gerrit Hirschfeld, Osnabrück University of Applied Sciences, Germany *Correspondence: Anne M. Boonstra This article was submitted to Psychology for Clinical Settings, a section of the journal Frontiers in Psychology Received 2016 May 31; Accepted 2016 Sep 12.

  • © 2016 Boonstra, Stewart, Köke, Oosterwijk, Swaan, Schreurs and Schiphorst Preuper.
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY).
  • The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice.

No use, distribution or reproduction is permitted which does not comply with these terms. Objectives: The 0–10 Numeric Rating Scale (NRS) is often used in pain management. The aims of our study were to determine the cut-off points for mild, moderate, and severe pain in terms of pain-related interference with functioning in patients with chronic musculoskeletal pain, to measure the variability of the optimal cut-off points, and to determine the influence of patients’ catastrophizing and their sex on these cut-off points.

Methods: 2854 patients were included. Pain was assessed by the NRS, functioning by the Pain Disability Index (PDI) and catastrophizing by the Pain Catastrophizing Scale (PCS). Cut-off point schemes were tested using ANOVAs with and without using the PSC scores or sex as co-variates and with the interaction between CP scheme and PCS score and sex, respectively.

The variability of the optimal cut-off point schemes was quantified using bootstrapping procedure. Results and conclusion: The study showed that NRS scores ≤ 5 correspond to mild, scores of 6–7 to moderate and scores ≥8 to severe pain in terms of pain-related interference with functioning.

  1. Bootstrapping analysis identified this optimal NRS cut-off point scheme in 90% of the bootstrapping samples.
  2. The interpretation of the NRS is independent of sex, but seems to depend on catastrophizing.
  3. In patients with high catastrophizing tendency, the optimal cut-off point scheme equals that for the total study sample, but in patients with a low catastrophizing tendency, NRS scores ≤ 3 correspond to mild, scores of 4–6 to moderate and scores ≥7 to severe pain in terms of interference with functioning.

In these optimal cut-off schemes, NRS scores of 4 and 5 correspond to moderate interference with functioning for patients with low catastrophizing tendency and to mild interference for patients with high catastrophizing tendency. Theoretically one would therefore expect that among the patients with NRS scores 4 and 5 there would be a higher average PDI score for those with low catastrophizing than for those with high catastrophizing.

However, we found the opposite. The fact that we did not find the same optimal CP scheme in the subgroups with lower and higher catastrophizing tendency may be due to chance variability. Keywords: musculoskeletal pain, numeric rating scale, pain interference, classification, chronic pain Assessment of pain intensity is considered one of the core outcome domains in clinical pain research (Dworkin et al., ), and is thus very commonly applied.

The Numeric Rating Scale (NRS) is regarded as one of the best single-item methods available to estimate the intensity of pain (Jensen et al., ; Breivik et al., ). The NRS assesses pain intensity using a 0–10 ranking scale with 0 representing “no pain” and 10 “unbearable pain” or comparable statement.

Clinicians, including psychologists, often use the categories of mild, moderate, and severe to simplify communication between patients and health care professionals. However, translating continuous measures such as NRS into discrete categories is not straightforward. Simply dividing an NRS into mild, moderate, and severe pain by dividing the scale into three equal parts is not a valid method (Serlin et al., ).

Serlin et al. () tried to solve this problem by correlating pain intensity to the level of interference of the pain with the daily functioning of patients with pain due to cancer, using a specific statistical technique, i.e., estimating how much of the variance in pain-related disability can be explained by different possible pain intensity classifications.

Their statistical approach has been repeated for the same patient population, i.e., cancer patients (Paul et al., ) as well as being applied to other patient populations (e.g., Zelman et al., ; Hirschfeld and Zernikow, ; Oldenmenger et al., ; Boonstra et al., ). Results from the literature (Hirschfeld and Zernikow, ; Oldenmenger et al., ) show that the cut-off between mild and moderate pain, in terms of pain-related interference with functioning, is mostly placed between 3 and 4, and the cut-off between moderate and severe pain between 6 and 8.

The differences may be caused by differences in study samples, pain definitions, and/or measures of functioning. Difference in diagnoses is generally accepted as one of the main causes of differences in cut-off points between studies (Zelman et al., ), while differences between study samples may also be explained by chance variation (Hirschfeld and Zernikow, ).

  • An unresolved issue is the influence of psychological factors on cut-off points.
  • Catastrophizing (expecting or worrying about major negative consequences from a situation, even one of minor importance) is associated with pain severity and disability in patients with several chronic pain conditions (Wertli et al.,,).
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Another issue is the influence of the patient’s sex on the cut-off points. There are clear, though incompletely understood, differences in pain perception between men and women (Rollman and Lautenbacher, ; Racine et al., ). Only Fejer et al. () have studied the association between sex and the cut-off points for interference with functioning in individuals with neck pain, and found a small difference between male and female patients.

Most studies have classified pain intensity using the statistical method described by Serlin et al. () to estimate how much of the variance in pain-related disability can be explained by different possible pain intensity classifications. The cut-off point scheme explaining the highest proportion of the variance is then chosen as the optimal scheme.

Although this method may have shortcomings, its use facilitates comparisons between studies. Hirschfeld and Zernikow () used a bootstrap resampling procedure and found a very large variability in the cut-off points in their sample of children and adolescents with chronic pain.

  1. They recommended that studies to define cut-off points include measures of variability for the optimal cut-off points.
  2. The aims of the present study were to determine the optimal cut-off points for mild, moderate, and severe pain in terms of pain-related interference with functioning for patients with chronic musculoskeletal pain, as well as to measure the variability of the optimal cut-off points, and to determine the association between these cut-off points and patients’ catastrophizing tendency and their sex.

The patients included in the study participated in a nationwide survey of patients with musculoskeletal pain, who were referred or admitted to rehabilitation treatment in one of the cooperating rehabilitation centers. The patients were included when they first consulted their rehabilitation physician or started multidisciplinary inpatient or outpatient rehabilitation treatment.

The study included patients from five rehabilitation centers, each with one (rehabilitation centers a, b, e), two (rehabilitation center d), or five (rehabilitation center c) treatment sites in the Netherlands. Some of these centers were departments of a university or general hospital, others were stand-alone rehabilitation centers.

The centers are located in different parts of the Netherlands, with patients from rural or semi-industrialized areas, living in villages or medium-sized to large towns and cities. Patients were included between the early months of 2012 and mid-2014; the exact time of inclusion differed between the participating rehabilitation centers.

  • Inclusion criteria were: age over 18 years and having had musculoskeletal pain for longer than 3 months.
  • Exclusion criteria were inability to understand Dutch, current major psychiatric disorder (active psychosis, severe depression with risk of suicide attempt, addiction, etc.), unwillingness to provide data for research purposes, a score of “no pain” or missing data on the NRS and more than 3 missing values on the Pain Disability Index (PDI-DV, see measurements).

All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000. The data were collected in a setting of usual care, in order to measure the outcome of the treatment.

  • The patients were asked to indicate if they did not allow their anonymous data to be used for the nationwide survey and/or for scientific studies.
  • Because the data were collected during usual care, no approval of a Medical Ethics Committee was needed.
  • Cross-sectional study in the context of care as usual.

The following background characteristics were assessed: age, sex, marital status, duration of current pain period, and localization of pain (mainly back pain, neck pain including cervicobrachialgia, widespread pain including fibromyalgia, pain in an extremity including shoulder pain, other).

The NRS for pain is an 11-point numeric rating scale, with 0 representing “no pain” and 10 “unbearable pain.” The patients were asked to assign a number to their average pain in the last week. We decided to ask the patients to report their average pain, as two studies found no differences in the cut-off point schemes of the NRS for average and worst pain (Paul et al., ; Zelman et al., ) and one study found only a small difference (Fejer et al., ).

Zelman et al. () also preferred the average pain measure for cut-off point derivation, because in their view average pain better reflects the experiences regarding the interference of pain with daily activities and is more stable than worst pain. Catastrophizing was evaluated by the Pain Catastrophizing Scale (PCS; Osman et al., ).

  1. In this questionnaire the patients were asked to reflect on past painful experiences and indicate the degree to which they experienced each of 13 thoughts or feelings when in pain, on a 5-point scale from 0 (not at all) to 4 (all the time).
  2. Three or less missing values per patient were replaced by the mean score of the other values.

Pain catastrophizing affects how individuals experience pain: ruminating about their pain (e.g., “I can’t stop thinking about how much it hurts”), magnifying their pain (e.g., “I’m afraid that something serious might happen”), or feeling helpless to manage their pain (e.g., “There is nothing I can do to reduce the intensity of my pain”).

  • A higher score means greater dominance of the subscale.
  • The total score on the PCS was used in the analyses.
  • Interference with functioning was assessed with the Pain Disability Index, Dutch Version (PDI-DV; Soer et al., ).
  • The PDI is a 7-item questionnaire to investigate the magnitude of self-reported disability in different situations such as work, leisure time, self-care, and social activities.

Each item is scored on an 11-item numeric rating scale in which 0 means no disability and 10 maximum disability. Three or less missing values per patient were replaced by the mean score of the other values. A higher score means greater disability and therefore greater interference with functioning.

All data were collected prior to the start or in the first 2 weeks of the rehabilitation program. Descriptive statistics were used to analyze the characteristics of the study sample. Marital status was dichotomized into living alone vs. being married or living with a partner. Each patient’s pain intensity rating on the NRS was classified into three categories, viz.

mild, moderate, and severe interference. We analyzed all 28 possible classification schemes, ranging from 2,3 to 8,9. The cut-off points in these classification schemes were named after the upper values for the mild and moderate categories, in accordance with Serlin et al.

For example, a 3,7 CP scheme means that the first category ranges from 1 to 3, the second from 4 to 7 and the third from 8 to 10. The first number, i.e., 3, is thus the upper value of the mild category and the second number, i.e., 7, the upper value of the moderate category. Other examples of schemes are: the 2,5 CP scheme with 1–2 classified as mild, 3–5 as moderate, and 6–10 as severe; the 3,5 CP scheme with 1–3 classified as mild, 4–5 as moderate, and 6–10 as severe; the 5,6 CP scheme with 1–5 classified as mild, 6 as moderate, and 7–10 as severe; and the 5,8 CP scheme with 1–5 classified as mild, 6–8 as moderate, and 9–10 as severe.

In order to determine which CP scheme best distinguished between mild, moderate and severe pain, we used the method introduced by Serlin et al. (). We conducted one-way ANOVAs (using the Generalized Linear Model in SPSS, version 22) for each of the 28 classification schemes, using NRS scores recoded as 1, 2, or 3 (depending on the CP scheme) as the independent variable and PDI-DV scores as the dependent variables.

A significant F -value of the CP scheme indicated that there were significant differences between the three pain severity categories in terms of pain-related interference. In accordance with Serlin et al. (), we interpreted the highest F -value as indicating the classification scheme that maximized the differences between the groups and was therefore the most useful for distinguishing between mild, moderate, and severe pain-related interference.

The variability of the optimal CP scheme was quantified using a bootstrap resampling procedure (STATA, version 13.1). In this procedure the distribution is estimated using the information based on a number of resamples from the total sample. One thousand (1000) repetitions of samples of the patients were used to yield sufficiently stable estimates for the variability of the optimal cut-off points.

  • The optimal CP scheme for each of the 1000 randomly chosen samples was determined, using the above-mentioned method introduced by Serlin et al. ().
  • The associations between the cut-off point schemes and the patients’ catastrophizing tendency and sex were determined by once again conducting ANOVAs (using the Generalized Linear Model in SPSS, version 22) for each of the 28 CP schemes.

In the two series of additional analyses (i.e., with PCS total score and sex), the NRS (recoded as 1–3) was again used as the independent variable and the PDI-DV score as the dependent variable, while the total score on the PSC and the patient’s sex were respectively included as co-variates, as was the interaction between CP scheme and PCS score and sex, respectively.

In view of the results of the analyses with the PCS score, we decided to conduct separate analyses, firstly for the patients with a PCS score equal to or lower than the median of the PCS scores and the patients with a PCS score higher than the median of the PCS scores (dividing the population into two groups by the median split method), and secondly for patients in the lower and higher quartiles and the middle group of scores (dividing the population into three groups by the quartile split method).

In total, therefore, 7 times 28 (196) ANOVAs were conducted. Again, the F -values of the CP schemes were used to determine which scheme fitted best. In these two (median split method) and three (quartile split method) patient subgroups we also conducted the bootstrap resampling procedure described above.

  • A total of 2854 patients enrolled in the study.
  • Patient characteristics are presented in Table,
  • The results of the ANOVAs for the total population are presented in Table, which lists only the mid-range of CP schemes.
  • The F -values of the CP schemes not presented here were lower than the F -value with ranking 6 as indicated in Table,

The 5,7 CP scheme had the highest F -value, indicating that this scheme provided the best fit for distinguishing pain into three categories, i.e., mild, moderate, or severe pain, in terms of interference with functioning. This means that an NRS score in the 1–5 range corresponds to mild interference with functioning, while scores of 6 and 7 represent moderate interference and a score in the 8–10 range corresponds to severe interference with functioning.

All patients Rehab center a Rehab center b Rehab center c Rehab center d Rehab center e
n n n n n n
CHARACTERISTICS
Age (years, mean ( SD )) 2794 43 (12.5) 435 44 (11.5) 539 42 (12.2) 840 43 (12.8) 679 43 (13.1) 301 43 (12.2)
Sex (% male) 2789 28 431 30 539 24 840 31 678 28 301 29
Marital status (% single) 2746 30 434 29 535 35 817 29 674 30 286 30
Work (%) 2657 319 531 835 673 299
• Employed or self-employed 51 47 62 50 50 43
• Student 4 2 6 5 4 4
• Without work, or homemaker 29 28 24 28 31 40
• Retired 4 4 2 4 5 4
• Other/mixed 12 19 7 14 10 10
Location of pain (%) 2854 435 539 840 683 357
• Widespread pain 18 10 36 26 7
• Neck pain 8 1 21 13 2
• Back pain 18 4 24 35 10
• Pain in extremity 7 9 18 2
• Others 4 1 4 7 4
• Unknown 45 84 6 1 75 100
Duration of complaints (%) 2503 154 533 836 679 301
• 3–6 months 5 1 8 4 5 3
• 6–12 months 11 9 12 12 12 10
• 1–2 years 20 20 18 24 18 19
• 2–5 years 25 19 25 23 27 27
•>5 years 39 52 37 38 38 42
FUNCTIONING
PDI (mean, SD ) 2854 39 (12.6) 435 37 (12.7) 539 41 (11.8) 840 37 (12.7) 683 36 (13.2) 357 40 (12.4)
PAIN
NRS (median, quartiles) 2854 7 (5–8) 435 6 (5–7) 539 7 (6–8) 840 6 (5–7) 683 6 (5–7) 357 7 (6–8)
CATASTROPHIZING
PCS 2846 435 535 840 679 357
• Total score
Median, quartiles 29 (21–37) 22 (13–30) 21 (14–30) 31 (25–38) 33 (25–41) 35 (27–43)
Mean, SD 30 (11.9) 22 (10.8) 22 (10.9) 32 (9.6) 34 (10.6) 36 (11.2)

Comparison of different cut-off point (CP) schemes for classifying Numeric Rating Scale (NRS) scores as mild, moderate or severe pain in terms of interference with functioning: F -value in ANOVA using the CP scheme as independent variable and the Pain Disability Index (PDI) scores as dependent variables, for all patients and for the subgroups with low and high catastrophizing tendency (i.e., Pain Catastrophizing Scale (PCS) scores ≤ or > the median of the scores, 29),

CP 3,6 CP 3,7 CP 4,5 CP 4,6 CP 4,7 CP 4,8 CP 5,6 CP 5,7 CP 5,8 CP 5,9 CP 6,7
ALL PATIENTS ( N = 2854)
CP scheme–PDI 332.63 306.15 317.17 337.60 334.67 253.48 337.63 369.65 324.08 306.96 291.35
Ranking 5 3 4 2 1 6
PATIENTS WITH PCS TOTAL SCORE ≤ 29 ( N = 1461)
CP scheme–PDI 173.14 140.30 163.10 172.20 152.79 122.50 170.00 172.34 157.38 154.46 136.35
Ranking 1 5 3 4 2 6
PATIENTS WITH PCS TOTAL SCORE > 29 ( N = 1385)
CP scheme–PDI 124,57 129.58 121.62 130.02 143.46 101.41 132.35 156.76 130.55 121.63 123.61
Ranking 6 5 2 3 1 4

Bootstrapping analysis identified the optimal CP scheme (5,7) in 90.2% of the bootstrapping samples. The 3,6 scheme was identified as the optimal CP scheme in 3.4% of the samples and the 4,6 scheme in 3.3%. The patients’ sex did not influence the optimal CP scheme: in the analyses in which sex and the interaction variable sex * CP scheme were entered as co-variates, neither of these covariates contributed significantly to the model. In the analyses in which the PCS score and the interaction variable PCS score * CP scheme were entered as co-variates in catastrophizing, the PCS score contributed significantly to the model in all analyses, while the interaction variable PCS score * CP scheme contributed sometimes (i.e., in 2 of the 28 analyses). The latter finding was explained as chance variation because only 2 of the analyses found a significant contribution. To explore the finding of the significant contribution of the PCS scores to the models, we conducted more analyses, as described above. First we split the total group into patients with low and with high catastrophizing tendency, and since the median of the PCS score was 29, we performed the analyses separately for patients with a PCS score equal or lower than 29 and for those with a PCS score higher than 29. For the patients with low catastrophizing tendency, i.e., a PCS score ≤ 29, the optimal CP scheme proved to be 3,6 and for the patients with high catastrophizing tendency, i.e., a PCS score > 29, the optimal CP scheme was 5,7 (see Table ). In the subgroup with low catastrophizing tendency, bootstrapping analysis identified the optimal CP scheme as 3,6 in 29% of the bootstrapping samples, while the 5,7 scheme was identified as the optimal CP scheme in 23% of the samples and the 4,6 scheme in 21%. In the subgroup with high catastrophizing tendency, bootstrapping analysis identified the optimal CP scheme as 5,7 in 87% of the bootstrapping samples, while the 4,7 scheme was identified as the optimal CP scheme in 11% of the samples and the 4,6 scheme in 10%. Secondly, we split the total group into patients with low, moderate, and high catastrophizing tendencies, and since the lower quartile of the PCS score was below 21 and the higher quartile was above 37, we performed the analyses separately for patients with a PCS score equal to or lower than 21, for PCS scores between 21 and 37, and for those with a PCS score higher than 37. For the patients with low catastrophizing tendency, i.e., a PCS score ≤ 21, the optimal CP scheme proved to be 3,6. For the patients with moderate catastrophizing tendency, i.e., > 21 and ≤ 37, and for those with high catastrophizing tendency, i.e., a PCS score > 37, the optimal CP scheme was 5,7 in both cases. In the subgroup with low catastrophizing tendency, bootstrap analysis identified the optimal CP scheme as 3,6 in 42% of the bootstrapping samples, while the 4,6 scheme was identified as the optimal CP scheme in 19% of the samples and the 5,7 scheme in 18%. In the subgroup with moderate catastrophizing tendency, bootstrapping analysis identified the optimal CP scheme as 5,7 in 87% of the bootstrapping samples, while the 4,6 scheme was identified as the optimal CP scheme in 3% of the samples and the 4,7 scheme also in 3%. In the subgroup with high catastrophizing tendency, bootstrapping analysis identified the optimal CP scheme as 5,7 in 35% of the bootstrapping samples, while the 2,6 scheme was identified as the optimal CP scheme in 22% of the samples and the 2,5 scheme in 12%. The aim of the current study was to find the optimal cut-off points for mild, moderate, and severe pain in terms of pain-related interference with functioning in patients with chronic musculoskeletal pain, as well as to measure the variability of the optimal cut-off points and determine the association between these cut-off points and patients’ catastrophizing tendency and sex. The NRS score cut-off points (CPs) of 5 and 7 (i.e., a 5,7 CP scheme) were found to provide the best model fit, indicating that an NRS score ≤ 5 corresponds to mild interference of pain with functioning, 6 and 7 to moderate interference and 8–10 to severe interference. The variability of the optimal CP scheme was low, as bootstrapping found the 5,7 CP scheme to be optimal in ~90% of the samples. This makes it unlikely that our findings were due to chance fluctuations. No clear association was found between the cut-off points and patients’ sex. In clinical practice, therefore, interpreting the NRS as mild, moderate or severe pain in terms of interference with functioning is independent of the patient’s sex. By contrast, the level of catastrophizing influenced the optimal CP scheme: the optimal scheme for patients with low catastrophizing tendency was 3,6, indicating that an NRS score ≤ 3 corresponds to mild interference of pain with functioning, 4–6 to moderate interference, and 7–10 to severe interference, whereas the optimal scheme for patients with high catastrophizing tendency was the same as for the total patient sample, i.e., 5,7, indicating that an NRS score ≤ 5 corresponds to mild interference of pain with functioning, 6 and 7 to moderate interference and 8–10 to severe interference. In terms of the cut-off points between mild and moderate, this finding implies the following: among patients with low catastrophizing tendency, the interpretation of an NRS score of 4 or 5 is that the patients with these scores experience moderate interference of their pain with functioning, while among patients with high catastrophizing tendency, the interpretation of the NRS score 4 or 5 is that the patients with these scores experience mild interference of their pain with functioning. Moderate interference with functioning would theoretically imply a higher PDI score than mild interference. However, as can be seen in Figure, the PDI scores of the patients with low catastrophizing tendency were lower for each NRS score than those of the patients with high catastrophizing tendency, thus including the group of patients with NRS scores 4 and 5. This contradicts the cut-off point schemes and their interpretation. Two possible explanations may be given. Firstly, the optimal CP scheme for patients with a low catastrophizing tendency may actually also be 5,7 and our finding of the 3,6 scheme was a matter of chance variability. In the subgroup with lower catastrophizing tendency (both the subgroup with a PCS score lower than the median and the subgroup with PCS scores in the lower quartile), the variability was much higher than in the subgroup with higher catastrophizing tendency. The probability that the correct optimal CP scheme was not found is therefore rather high (type 1 error). Secondly, the statistical method introduced by Serlin et al. (), which uses the highest F -value to indicate the classification scheme that maximizes the differences between the groups and is therefore the most useful for distinguishing between mild, moderate, and severe pain-related interference, may not be the best method for finding the optimal CP scheme. Boxplots of the Pain Disability Index (PDI) scores by Numeric Rating Scale (NRS) score for average pain during the last week for the patients with low and high catastrophizing tendency (i.e., lower or higher than the median of the total scorer on the Pain Catastrophizing Scale (PCS), viz.29), Optimal cut-off points of 5 and 7 were only mentioned in the literature by Zelman et al. (), for patients with osteoarthritis. That this particular CP scheme was found in only one other study may be due to the fact that it was not assessed by most other authors (see Table ). Our previous study (Boonstra et al., ) in a comparable population (not including patients of the present study), but with a smaller sample, found 3 and 6 to be the optimal cut-off points between mild, moderate, and severe interference with functioning, whereas the present study found this 3,6 scheme to be only the fifth best CP scheme. Our previous study used domains of the SF-36 (Aaronson et al., ) to measure interference with functioning, and the Visual Analogue Scale (VAS) for pain, instead of the PDI and NRS, respectively. These different measures may be the reason why we found a different CP scheme in the present study. Other reasons may be chance variability and a possible difference in the distribution of the PCS scores, as the CP scheme is the same as that found in the subgroup of patients with low catastrophizing tendency. Published studies about optimal cut-off point schemes for mild, moderate, and severe pain in terms of interference with functioning,

Study, authors Type of pain/diagnosis Pain measurement n Optimal cut-off points found in the study Range of values studied by the authors for the lower cut-off point (between mild and moderate), and the higher cut-off point (between moderate and severe)
Lower Higher
Serlin et al., Cancer pain NRS, worst pain 470 4 6 Lower cut-off point: 3–4
Higher cut-off point: 6–7
Jensen et al., Leg amputation patients: NRS, average pain
Phantom pain 74 4 7 Lower cut-off point: 3–4
Back pain 29 4 6 Higher cut-off point: 6–7
General pain 102 3 6
Zelman et al., Low back pain NRS, average pain 96 5 8 Lower cut-off point: 4–6
Osteoarthritis 98 5 7 Higher cut-off point: 6–8
Turner et al., CTS NRS, average pain No superior Lower cut-off point: 3–5
Low back injuries scheme 6 Higher cut-off point: 6–7
4
Zelman et al., Diabetic peripheral neuropathy NRS, worst and average pain 255 4 7 Lower cut-off point: 4–6
Higher cut-off point: 6–8
Paul et al., Cancer pain NRS, average pain 160 4 7 Lower cut-off point: 3–5
Higher cut-off point: 5–7
Fejer et al., Neck pain NRS, average, worst, and characteristic pain 1385 4 7 14 categories between 3 and 8
Hanley et al., Spinal cord injury NRS, (a) overall pain or (b) current pain at worst location a: 307 b: 174 a and b: 3 a: 7 Lower cut-off point: 3–4
b: 6 Higher cut-off point: 6–7
Li et al., Cancer pain, patients with bone metastases NRS, (a) worst, (b) average, and (c) current 199 a and b: 4, c: 2 a, b, and c: 6 Lower cut-off point: 2–8
Higher cut-off point: 3–9
Kapstad et al., Osteoarthritis of the hip NRS, average pain 224 4 6 Lower cut-off point: 3–5
Osteoarthritis of the knee 94 4 7 Higher cut-off point: 5–7
Kalyadina et al., Cancer pain, hematological malignancies or solid tumors NRS, worst pain 221 4 6 Lower cut-off point: 3–4
Higher cut-off point: 6–7
Ferreira et al., Cancer pain NRS, worst pain 143 4 7 Lower cut-off point: 3–5
Higher cut-off point: 5–7
Hoffman et al., Diabetic peripheral neuropathy NRS, average pain 401 3 6 Not mentioned
Hirschfeld and Zernikow, Children and adolescents with chronic pain NRS, maximum pain Lower cut-off point: 2–7
Higher cut-off point: 3–8
Whole sample 2249 4 8
Constant pain 650 5 8
Chronic headache 430 4 8
Musculoskeletal pain 295 2 8
Boonstra et al., Musculoskeletal pain VAS, average pain 456 3 6 Lower cut-off point: 3–5
Higher cut-off point: 5–7
Brailo and Zakrzewska, Nondental orofacial pain NRS, average pain 245 4 7 Lower cut-off point: 3–5
Higher cut-off point: 5–9
Present study Musculoskeletal pain NRS, average pain 2854 5 7 Lower cut-off point: 2–8
Higher cut-off point: 3–9

The association between catastrophizing and cut-off points has not been studied before, so no comparison with other studies is possible. As far as we are aware, only Fejer et al. () studied the influence of patients’ sex on the cut-off points for interference with functioning, and their analysis of CP schemes for average pain found a small difference between the sexes, viz.

a lower cut-off point between mild and moderate pain interference for women (4) than for men (6). Their other analyses, with the worst and what they called characteristic pain as independent variables, found no or other differences between women and men, and they finally concluded that the differences were small.

The main strength of our study was the large study sample, the largest sample used until now in studies of this topic. It was also the first study taking patient’s catastrophizing into account and the second to examine the influence of sex on the CP schemes.

  • One weakness of our study is the way the patients were included, i.e., using data from a nationwide survey, which meant that response rate and hence selection bias were unknown.
  • In some rehabilitation centers, the localization of pain complaints was not recorded in the survey questionnaire for most patients (see Table ).

Moreover, none of the rehabilitation centers comprehensively recorded the diagnoses in the survey. Secondly, our study used the PDI to measure interference with functioning. It is possible that other instruments, such as the BPI, would have given different results.

Finally, we explored the effect of catastrophizing by splitting the population using the median split and quartile split methods. Although these are common methods to split a population, they may have influenced the results. In conclusion, we found that NRS scores ≤ 5 correspond to mild pain-related interference with functioning, scores of 6 and 7 to moderate interference and scores ≥8 to severe interference.

This interpretation of the NRS in terms of mild, moderate and severe interference with functioning is independent of the patient’s sex, but seems to be influenced by their catastrophizing tendency. However, the difference in CP schemes we found for patients with lower and higher catastrophizing tendencies contradicts what is theoretically plausible.

The reason why we did not find the same optimal CP scheme in the subgroups of patients with lower and higher catastrophizing tendencies may be chance variability. AB, contributed to the design of the work; and the acquisition, analysis, and interpretation of data; drafted the work, approves final version to be published; agrees to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

RS contributed to design of the work; analysis, and interpretation of data for the work; revised the work critically for important intellectual content; approved final version to be published; agrees to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

HS, AK, RO, JS, KS, contributed to design of the work; and interpretation of data for the work; revised the work critically for important intellectual content; approved final version to be published; and agrees to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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: Cut-Off Points for Mild, Moderate, and Severe Pain on the Numeric Rating Scale for Pain in Patients with Chronic Musculoskeletal Pain: Variability and Influence of Sex and Catastrophizing

How often does Max pain change?

Since the stock price constantly changes and open interest in the options market rises and falls, the max pain price can change daily.

What are the 4 pain theories?

The four most influential theories of pain perception include the Specificity (or Labeled Line), Intensity, Pattern, and Gate Control Theories of Pain (Fig.1).

Do we have a pain limit?

Some people can handle more pain than others – We feel pain because of the signals that are sent from our sensory receptors, via the nerve fibres, to our brain. Everyone’s pain tolerance is different and can depend on a range of factors including your age, gender, genetics, culture and social environment. Our sensory receptors send signals to our brain, via the nerve fibres

What is rule of 20 SPX?

The beginning of a new decade is one of those personal milestones that often prompts reflection and introspection. Where am I in life’s journey? How do I feel about the decade that just ended? What lies ahead? Investors are no different and may have posed the same questions about the financial markets at the end of last year. Their review of the past decade was quite likely positive and upbeat. Stocks and bonds both had a remarkable run in this period. The S&P 500 index soared by an annualized 13.6% in the 2010s and the Barclays Aggregate Bond index rose by 3.7% on an annual basis.U.S.

  • Investors in particular were perhaps also gratified to see the dominant performance of their domestic stock market relative to the rest of the world.U.S.
  • Stocks generated cumulative returns of over 200% in the last ten years and outpaced stocks in both the developed and emerging foreign markets by over 150% in aggregate, based on the S&P 500, MSCI EAFE and MSCI EM indexes.

As the stock market gets off to a strong start this year, concerns about valuations are now starting to grow. During a year of virtually no earnings growth, how could stocks perform so well? As Price-to-Earnings (P/E) multiples rise, are stocks expensive now or even overvalued? The symmetry and numerology of the year 2020 brings to mind the good old “Rule of 20” as a useful way to think about these questions.

  • A tried and tested heuristic in the stock market has been derived from the combined levels of the P/E ratio and the rate of inflation.
  • Over the years, markets have shown a distinct tendency to revert back to a sum of 20 for these two metrics.
  • In other words, the Rule of 20 suggests that markets may be fairly valued when the sum of the P/E ratio and the inflation rate equals 20.

P/E + Inflation = 20 The stock market is deemed to be undervalued when the sum is below 20 and overvalued when the sum is above 20. This seemingly simplified insight has nonetheless been surprisingly effective. Here are some historical observations from Evercore ISI for the Rule of 20.

Markets rarely trade at equilibrium, so it’s no surprise that the Rule of 20 is also rarely achieved in precision. The combined P/E ratio and inflation rate have ranged from a low of 14 to a high of 34. Over the last 50 years or so, the average P/E is just below 16, average inflation is 4% and the average sum of P/E and inflation, as expected, is close to 20.

Let’s compare recent valuation and inflation trends against this historical backdrop. Valuations in the last 5 years have trended higher. The average P/E in this period is measured at 18.1, which is admittedly higher than the 50-year average of 15.8. However, the upward drift in P/E ratios is rooted in the fundamental drivers of low inflation and low interest rates, and not in speculation or euphoria as some might fear.

Inflation in this period has come in significantly below its 50-year average at just 2.0%. Muted levels of inflation have been one of the most remarkable outcomes of this lengthy economic cycle. As a result, the sum of P/E and inflation in the last 5 years registers at 20.1 which is almost surgically aligned with the Rule of 20.

It also provides us with a key insight and takeaway. Higher-than-normal P/E ratios in recent years are being supported by lower-than-average inflation, and consequently, lower-than-average interest rates. The P/E ratio, both forward and trailing, and inflation rate so far in 2020 are a notch higher than the 5-year average shown above.

  1. The average P/E this year is close to 19, inflation is around 2.5% and the sum of P/E + Inflation is just above 21.0.a.
  2. These levels are only slightly higher than the Rule of 20 norm and still close to fair valuations.b.
  3. We also attribute this small uptick in the P/E ratio to expectations of higher normalized growth in the second half of 2020, triggered by the recent truce in the trade war and concerted global central bank easing.

Any discussion of valuations or growth at this point would be incomplete without reference to the current concerns about the coronavirus. In this regard, we observe that geopolitical or “geomedical” events rarely have a lasting impact on the markets even though they inflict significant human pain and suffering.

At this point, we hold a similar view that the current fears of a pandemic will also pass without meaningful permanent economic damage. We, therefore, believe that our valuation views discussed above in the context of the Rule of 20 still remain intact. We believe that the U.S. stock market is fairly valued at these prices.

We also believe that a U.S. recession is unlikely in the near future based upon the health of the consumer and the job market. We nevertheless remain vigilant to changing sources of risk and guard against them through a focus on high quality investments.

Investment and Wealth Management Services are provided by Whittier Trust Company and The Whittier Trust Company of Nevada, Inc., state-chartered trust companies, which are wholly owned by Whittier Holdings, Inc., a closely held holding company. All of said companies are referred to herein, individually and collectively, as “Whittier.” This document is provided for informational purposes only and is not intended, and should not be construed, as investment, tax or legal advice.

Please consult your own legal and/or tax advisors in connection with financial decisions. Although the information provided is carefully reviewed, Whittier cannot be held responsible for any direct or incidental loss resulting from applying any of the information provided.

Is trading SPX risky?

The Bottom Line – With SPX Weeklys options expiring every day of the week, you could have potential trading opportunities daily. But they can be risky—you either make or lose money. Trading weekly options could be a good test of your risk management skills.

Can I trade SPX options 24 hours?

Cboe Extends Options Trading Hours To Fit Traders Of All-Time Zones Chicago, Illinois -News Direct- Cboe Global Markets, Inc. Cboe Global Markets Inc. (BATS: CBOE), a leading provider of global market infrastructure and tradeable products, offers extended global trading hours (GTH) for the S&P 500 Index () and Mini-SPX Index () options.

  1. SPX and XSP trades can be traded nearly 24 hours a day, five days a week.
  2. In the published last week, Cboe reported a number of growth metrics for its U.S.
  3. Products in January 2023, including 291.8 million contracts traded and 1.2 million average daily value traded (ADV) for same-day SPX options.
  4. Despite geopolitical tensions and fears of impending recessions, Cboe’s European clients have contributed significantly to Cboe’s volume tallies in January 2023, breaking records in the process.

The Cboe report found that:

  1. SPX options volume during global trading hours (GTH) posted the second-best month ever in January with an ADV of 58,000 contracts, a 55% growth compared to 2022 levels;
  2. Cboe Europe Equities had an overall market share of 25.1% in January, making it Europe’s largest stock exchange.
  3. Cboe BIDS Europe, Cboe’s European block trading platform, had a 36% share of the large in-scale market, making it the largest platform of its type for the tenth consecutive month.
  4. Cboe Europe Derivatives traded 3,824 contracts, a record monthly figure and beating the previous high of 3,647 contracts in December 2022.

In response to a global interest in its products, Cboe offers extended GTH so that traders from all over the world can participate in options trading. The chart below depicts adjusted trading hours in London, Hong Kong and Sydney. Global trading hours (GTH) regime began on April 25, 2022, and incorporates a brief “curb trading session,” a time period following regular trading hours where market participants can adjust, unwind, or close trades.

  • All electronic trading between 4:15 PM and 5:00 PM Eastern Time (ET) Monday through Friday.
  • Limited to SPX and XSP options only.
  • SPX FLEX options can be initiated.
  • Activity during the Curb session will have the same Trade Date as the preceding RTH session.
  • Maximizes the time overlap with related futures contracts.

Cboe’s extended GTH hours now allow traders to promptly react to global macroeconomic events, economic report announcements, and geopolitical risks regardless of where traders are located around the world. Additionally, SPX and XSP options can grant a list of benefits to users, including better tax treatment and a European settlement style.

What is the backtest max pain theory?

Page 2 – Max pain theory postulates that the price of underlying has a tendency to gravitate towards a point where the maximum number of options expire worthless. Using historical open interest data, we are backtesting to see if we can identify companies where the max pain theory holds true.

Why is Nifty 50 the best?

Bottom Line – By investing in the NIFTY 50 index, you get to invest in 50 leaders in their sectors. So you give yourself a great chance to accumulate enormous wealth in the long run. And investing in the NIFTY 50 index can be convenient, easy, and cost-effective if you invest through index Mutual Funds.

What is Nifty 50 lifetime high?

After many attempts, the Nifty50 finally succeeded in surpassing its previous all-time high and hit a new high of 19,011.25 on June 28, the monthly expiry day for June futures & options contracts, backed by buying across sectors.

What is the maximum PCR of Nifty 50?

PCR – The Contrarian Indicator – Traders generally use the Put Call Ratio (PCR) as a contrarian indicator when the values touch extremely high levels. What this implies is, traders might consider a high Put Call ratio of say 1.4 as a great opportunity for buying because they believe that the market sentiment is extremely bearish and will soon adjust, when those having short positions switch places to cover and the market will eventually face a downturn.

  1. However, there is no specific number that indicates that the market has created a bottom or a top, but traders generally anticipate this by looking for jumps in the ratio or for when the ratio reaches outside of the normal trading range levels.
  2. Generally, NIFTY Put call ratio follows a trend in which it seems to oscillate between 0.8 and 1.3 with 0.8 being the lower band and 1.3 being the upper band.

: Put Call Ratio (PCR) – Definition, Formula and Calculation

What is the circuit limit for Nifty?

Daily Market Wide Circuit Filter –

NIFTY 50 Closing As on 28-Jun-2023 18,972.10
Index Circuit Filter Trigger Limit Equivalent Point (+/-) for 30-Jun-2023
10% 1,897.20
15% 2,845.80
20% 3,794.40

What is high IV for Nifty?

A high IV indicates that the market anticipates significant changes in the current stock price over the following 12 months. A bearish market occurs when equity prices fall over time, making long-term bullish investors more vulnerable. Implied volatility is expected to rise in this type of market.