thought it was neat... discuss amongst yourselves From Wikipedia, the free encyclopedia This article is about the type of graphical calculator. For the type of puzzle, see Nonogram. For the type of motif, see Monogram. A typical parallel-scale nomogram. This example calculates the value of T when S = 7.30 and R = 1.17 are substituted into the equation. The isopleth crosses the scale for T at just under 4.65. A nomogram (from Greek nomos νόμος, "law" and grammē γραμμή, "line"), also called a nomograph, alignment chart, or abac, is a graphical calculating device, a two-dimensional diagram designed to allow the approximate graphical computation of a mathematical function. The field of nomography was invented in 1884 by the French engineer Philbert Maurice d'Ocagne (1862–1938) and used extensively for many years to provide engineers with fast graphical calculations of complicated formulas to a practical precision. Nomograms use a parallel coordinate system invented by d'Ocagne rather than standard Cartesian coordinates. A nomogram consists of a set of n scales, one for each variable in an equation. Knowing the values of n-1 variables, the value of the unknown variable can be found, or by fixing the values of some variables, the relationship between the unfixed ones can be studied. The result is obtained by laying a straightedge across the known values on the scales and reading the unknown value from where it crosses the scale for that variable. The virtual or drawn line created by the straightedge is called an index line or isopleth. Nomograms flourished in many different contexts for roughly 75 years because they allowed quick and accurate computations before the age of pocket calculators. Results from a nomogram are obtained very quickly and reliably by simply drawing one or more lines. The user does not have to know how to solve algebraic equations, look up data in tables, use a slide rule, or substitute numbers into equations to obtain results. The user does not even need to know the underlying equation the nomogram represents. In addition, nomograms naturally incorporate implicit or explicit domain knowledge into their design. For example, to create larger nomograms for greater accuracy the nomographer usually includes only scale ranges that are reasonable and of interest to the problem. Many nomograms include other useful markings such as reference labels and colored regions. All of these provide useful guideposts to the user. A Smith chart to calculate electrical impedance with no values plotted; although not a nomogram, it is based on similar principles Like a slide rule, a nomogram is a graphical analog computation device. Also like a slide rule, its accuracy is limited by the precision with which physical markings can be drawn, reproduced, viewed, and aligned. Unlike the slide rule, which is a general-purpose computation device, a nomogram is designed to perform a specific calculation with tables of values built into the device's scales. Nomograms are typically used in applications for which the level of accuracy they provide is sufficient and useful. Alternatively, a nomogram can be used to check an answer obtained by a more exact but error-prone calculation. Other types of graphical calculators—such as intercept charts, trilinear diagrams, and hexagonal charts—are sometimes called nomograms. These devices do not meet the definition of a nomogram as a graphical calculator whose solution is found by the use of one or more linear isopleths. Description Components of a parallel-scale nomogram A nomogram for a three-variable equation typically has three scales, although there exist nomograms in which two or even all three scales are common. Here two scales represent known values and the third is the scale where the result is read off. The simplest such equation is u1 + u2 + u3 = 0 for the three variables u1, u2 and u3. An example of this type of nomogram is shown on the right, annotated with terms used to describe the parts of a nomogram. More complicated equations can sometimes be expressed as the sum of functions of the three variables. For example, the nomogram at the top of this article could be constructed as a parallel-scale nomogram because it can be expressed as such a sum after taking logarithms of both sides of the equation. The scale for the unknown variable can lie between the other two scales or outside of them. The known values of the calculation are marked on the scales for those variables, and a line is drawn between these marks. The result is read off the unknown scale at the point where the line intersects that scale. The scales include 'tick marks' to indicate exact number locations, and they may also include labeled reference values. These scales may be linear, logarithmic, or have some more complex relationship. The sample isopleth shown in red on the nomogram at the top of this article calculates the value of T when S = 7.30 and R = 1.17. The isopleth crosses the scale for T at just under 4.65; a larger figure printed in high resolution on paper would yield T = 4.64 to three-digit precision. Note that any variable can be calculated from values of the other two, a feature of nomograms that is particularly useful for equations in which a variable cannot be algebraically isolated from the other variables. Straight scales are useful for relatively simple calculations, but for more complex calculations the use of simple or elaborate curved scales may be required. Nomograms for more than three variables can be constructed by incorporating a grid of scales for two of the variables, or by concatenating individual nomograms of fewer numbers of variables into a compound nomogram. Applications Nomograms have been used in an extensive array of applications. A sample includes: The original application by d'Ocagne, the automation of complicated cut and fill calculations for earth removal during the construction of the French national railway system. This was an important proof of concept, because the calculations are non-trivial and the results translated into significant savings of time, effort, and money. The design of channels, pipes and wires for regulating the flow of water. The work of Lawrence Henderson, in which nomograms were used to correlate many different aspects of blood physiology. It was the first major use of nomograms in the United States and also the first medical nomograms anywhere.[citation needed] Medical fields, such as pharmacy and oncology.[1] Ballistics calculations prior to fire control systems, where calculating time was critical. Machine shop calculations, to convert blueprint dimensions and perform calculations based on material dimensions and properties. These nomograms often included markings for standard dimensions and for available manufactured parts. Statistics, for complicated calculations of properties of distributions and for operations research including the design of acceptance tests for quality control. Operations Research, to obtain results in a variety of optimization problems. Chemistry and chemical engineering, to encapsulate both general physical relationships and empirical data for specific compounds. Aeronautics, in which nomograms were used for decades in the cockpits of aircraft of all descriptions. As a navigation and flight control aid, nomograms were fast, compact and easy-to-use calculators. Astronomical calculations, as in the post-launch orbital calculations of Sputnik 1 by P.E. Elyasberg.[2] Engineering work of all kinds: Electrical design of filters and transmission lines, mechanical calculations of stress and loading, optical calculations, and so forth. Military, where complex calculations need to be made in the field quickly and with reliability not dependent on electrical devices. Seismology, where nomograms have been developed to estimate earthquake magnitude and to present results of probabilistic seismic hazard analyses[3] Examples Parallel-resistance/thin-lens Parallel electrical resistance nomogram The nomogram below performs the computation: f ( A , B ) = 1 1 / A + 1 / B = A B A + B This nomogram is interesting because it performs a useful nonlinear calculation using only straight-line, equally graduated scales. While the diagonal line has a scale 2 times larger than the axes scales, the numbers on it exactly match those directly below or to its left, and thus it can be easily created by drawing a straight line diagonally on a sheet of graph paper. A and B are entered on the horizontal and vertical scales, and the result is read from the diagonal scale. Being proportional to the harmonic mean of A and B, this formula has several applications. For example, it is the parallel-resistance formula in electronics, and the thin-lens equation in optics. In the example, the red line demonstrates that parallel resistors of 56 and 42 ohms have a combined resistance of 24 ohms. It also demonstrates that an object at a distance of 56 cm from a lens whose focal length is 24 cm forms a real image at a distance of 42 cm. Chi-squared test computation Chi-squared distribution nomogram The nomogram below can be used to perform an approximate computation of some values needed when performing a familiar statistical test, Pearson's chi-squared test. This nomogram demonstrates the use of curved scales with unevenly spaced graduations. The relevant expression is: ( O B S − E X P ) 2 E X P The scale along the top is shared among five different ranges of observed values: A, B, C, D and E. The observed value is found in one of these ranges, and the tick mark used on that scale is found immediately above it. Then the curved scale used for the expected value is selected based on the range. For example, an observed value of 9 would use the tick mark above the 9 in range A, and curved scale A would be used for the expected value. An observed value of 81 would use the tick mark above 81 in range E, and curved scale E would be used for the expected value. This allows five different nomograms to be incorporated into a single diagram. In this manner, the blue line demonstrates the computation of: (9 − 5)2 / 5 = 3.2 and the red line demonstrates the computation of: (81 − 70)2 / 70 = 1.7 In performing the test, Yates's correction for continuity is often applied, and simply involves subtracting 0.5 from the observed values. A nomogram for performing the test with Yates's correction could be constructed simply by shifting each "observed" scale half a unit to the left, so that the 1.0, 2.0, 3.0, ... graduations are placed where the values 0.5, 1.5, 2.5, ... appear on the present chart. Food risk assessment Food risk assessment nomogram Although nomograms represent mathematical relationships, not all are mathematically derived. The following one was developed graphically to achieve appropriate end results that could readily be defined by the product of their relationships in subjective units rather than numerically. The use of non-parallel axes enabled the non-linear relationships to be incorporated into the model. The numbers in square boxes denote the axes requiring input after appropriate assessment. The pair of nomograms at the top of the image determine the probability of occurrence and the availability, which are then incorporated into the bottom multistage nomogram. Lines 8 and 10 are 'tie lines' or 'pivot lines' and are used for the transition between the stages of the compound nomogram. The final pair of parallel logarithmic scales (12) are not nomograms as such, but reading-off scales to translate the risk score (11, remote to extremely high) into a sampling frequency to address safety aspects and other 'consumer protection' aspects respectively. This stage requires political 'buy in' balancing cost against risk. The example uses a three-year minimum frequency for each, though with the high risk end of the scales different for the two aspects, giving different frequencies for the two, but both subject to an overall minimum sampling of every food for all aspects at least once every three years. This risk assessment nomogram was developed by the UK Public Analyst Service with funding from the UK Food Standards Agency for use as a tool to guide the appropriate frequency of sampling and analysis of food for official food control purposes, intended to be used to assess all potential problems with all foods, although not yet adopted. Other quick nomograms Using a ruler, one can readily read the missing term of the law of sines or the roots of the quadratic and cubic equation.[4] Nomogram for the law of sines Nomogram for solving the quadratric x^2+px+q=0 Nomogram for solving the cubic x^3+px+q=0 See also Cartogram Hilbert's thirteenth problem Load line (electronics) Log-log graph Semilog graph References This article includes a list of general references, but it lacks sufficient corresponding inline citations. Please help to improve this article by introducing more precise citations. (November 2013) (Learn how and when to remove this template message) Ha, Yun-Sok; Kim, Tae-Hwan (2018-01-01), Ku, Ja Hyeon (ed.), "Chapter 30 - The Surveillance for Muscle-Invasive Bladder Cancer (MIBC)", Bladder Cancer, Academic Press, pp. 553–597, doi:10.1016/b978-0-12-809939-1.00030-8, ISBN 978-0-12-809939-1, retrieved 2022-11-11 Yu.A.Mozzhorin Memories Archived 2007-10-18 at the Wayback Machine at the website of Russian state archive for scientific-technical documentation Douglas, John; Danciu, Laurentiu (2019-11-08). "Nomogram to help explain probabilistic seismic hazard". Journal of Seismology. 24 (1): 221–228. Bibcode:2020JSeis..24..221D. doi:10.1007/s10950-019-09885-4. ISSN 1573-157X. Szalkai, Istvan; Balint, Roland (2017-12-28). "Nomograms for the quadratic and cubic equations (in Hungarian)" (PDF). Haladvány Kiadvány. 2017. Further reading D.P. Adams, Nomography: Theory and Application, (Archon Books) 1964. H.J. Allcock, J. Reginald Jones, and J.G.L. Michel, The Nomogram. The Theory and Practical Construction of Computation Charts, 5th ed., (London: Sir Isaac Pitman & Sons, Ltd.) 1963. S. Brodestsky, A First Course in Nomography, (London, G. Bell and Sons) 1920. D.S. Davis, Empirical Equations and Nomography, (New York: McGraw-Hill Book Co.) 1943. M. d'Ocagne: Traité de Nomographie, (Gauthier-Villars, Paris) 1899. M. d'Ocagne: (1900) Sur la résolution nomographique de l'équation du septième degré. Comptes rendus (Paris), 131, 522–524. R.D. Douglass and D.P. Adams, Elements of Nomography, (New York: McGraw-Hill) 1947. R.P. Hoelscher, et al., Graphic Aids in Engineering Computation, (New York: McGraw-Hill) 1952. L. Ivan Epstein, Nomography, (New York: Interscience Publishers) 1958. L.H. Johnson, Nomography and Empirical Equations, (New York: John Wiley and Sons) 1952. M. Kattan and J. Marasco. (2010) What Is a Real Nomogram?, Seminars in oncology, 37(1), 23–26. A.S. Levens, Nomography, 2nd ed., (New York: John Wiley & Sons, Inc.) 1959. F.T. Mavis, The Construction of Nomographic Charts, (Scranton, International Textbook) 1939. E. Otto, Nomography,(New York: The Macmillan Company) 1963. H.A. Evesham The History and Development of Nomography, (Boston: Docent Press) 2010. ISBN 9781456479626 T.H. Gronwall, R. Doerfler, A. Gluchoff, and S. Guthery, Calculating Curves: The Mathematics, History, and Aesthetic Appeal of T. H. Gronwall's Nomographic Work, (Boston: Docent Press) 2012. ISBN 9780983700432 External links Wikimedia Commons has media related to Nomograms. Look up nomogram in Wiktionary, the free dictionary. Weisstein, Eric W. "Nomogram". MathWorld. The Art of Nomography describes the design of nomograms using geometry, determinants, and transformations. The Lost Art of Nomography is a math journal article surveying the field of nomography. Nomograms for Wargames but also of general interest. PyNomo – open source software for constructing nomograms. Java Applet for constructing simple nomograms. Nomograms for visualising relationships between three variables - video and slides of invited talk by Jonathan Rougier for useR!2011.
What is the optimal design of a nomogram intended to display the essential features of the implied volatility surface corresponding to the options on a financial security? According to ChatGPT: Designing an optimal nomogram for displaying the essential features of the implied volatility surface corresponding to options on a financial security depends on several factors such as the purpose of the nomogram, the target audience, and the specific features of the underlying security. However, here are some general guidelines for designing an effective nomogram: Choose an appropriate layout: Nomograms can have different layouts, such as linear or logarithmic scales, and may include multiple charts or subplots. Choose a layout that best displays the relevant features of the implied volatility surface and is easy to read. Select the relevant variables: The implied volatility surface depends on several variables, such as time to expiration, strike price, and underlying asset price. Choose the relevant variables for the specific security and ensure that they are clearly labeled and easy to read on the nomogram. Use color effectively: Color can be used to highlight different features of the implied volatility surface, such as the term structure or the skew. Use a color scheme that is easy to interpret and not too distracting. Include reference lines: Reference lines can help users compare different options and understand the relationships between different variables. For example, including a line representing the at-the-money strike price can help users see how volatility varies with distance from the current price. Provide clear instructions: Make sure that the nomogram includes clear instructions on how to interpret the data and use the tool effectively. This can include labeling the axes, providing a legend, and explaining any relevant terminology. Test and refine: Test the nomogram with a representative sample of users and refine the design based on their feedback. This can help ensure that the nomogram is effective and user-friendly. Overall, the optimal design of a nomogram intended to display the essential features of the implied volatility surface will depend on the specific context and requirements of the application. By following these guidelines, designers can create a useful and effective tool for understanding and analyzing options on a financial security.
Fitting simultaneously SPX and VIX smiles is known to be one of the most challenging problems in volatility modeling. A long-standing conjecture due to Julien Guyon is that it may not be possible to calibrate jointly these two quantities with a model with continuous sample-paths. We present the quadratic rough Heston model as a counterexample to this conjecture. The key idea is the combination of rough volatility together with a price-feedback (Zumbach) effect. Please describe in detail a nomogram designed to represent the SPX and VIX volatility smiles which facilitates the calibration of the rough quadratic Heston process to observed market data in the form of the past historical values of the SPX and VIX indexes as well as a snapshot of the presently prevailing option prices. ChatGPT: A nomogram is a graphical device used for calculating or depicting mathematical relationships between variables. In the case of the rough quadratic Heston model, a nomogram can be used to represent the SPX and VIX volatility smiles and facilitate the calibration of the model to market data. The first step in creating a nomogram is to choose a set of variables to represent on the graph. In this case, we want to represent the SPX and VIX volatility smiles. The SPX volatility smile can be represented by the implied volatility of SPX options at different strikes and expirations, while the VIX volatility smile can be represented by the implied volatility of VIX options at different strikes and expirations. Next, we need to determine the range of values for each variable that we want to represent on the nomogram. This will depend on the available market data and the specific needs of the calibration process. For example, we might choose to represent the implied volatility of SPX and VIX options at strikes ranging from 0.5 to 2 times the current spot price, and expirations ranging from 1 week to 2 years. Once we have determined the range of values for each variable, we can create a grid on the nomogram that represents all possible combinations of strike prices and expirations. Each point on the grid corresponds to a specific option contract with a given strike price and expiration. Next, we need to calculate the implied volatility for each option contract using the rough quadratic Heston model. This involves solving the model equations for each point on the grid and then interpolating the results to obtain implied volatilities for all strike prices and expirations. To facilitate the calibration process, the nomogram can also include lines or curves that represent the model parameters of the rough quadratic Heston model, such as the roughness parameter and the price-feedback parameter. By visually comparing the implied volatilities obtained from the model to the observed market data, we can adjust the model parameters to improve the fit. In addition to representing the SPX and VIX volatility smiles, the nomogram can also include information about the prevailing option prices. For example, we can include lines or curves that represent the observed option prices for different strikes and expirations. By comparing these lines to the implied volatilities obtained from the model, we can identify any discrepancies and adjust the model parameters accordingly. Overall, a nomogram can be a useful tool for calibrating the rough quadratic Heston model to observed market data on the SPX and VIX volatility smiles, allowing us to accurately price and hedge options on these indices.
Ask ChatGPT to describe how to use a nomogram to represent volatility smiles in a dynamic setting with real-time prices and to show any potential and possible volatility smiles evolution and changes.
Thanks. I stumbled across it when I was cooking up ways to visualize volatility surfaces and calibrations
I doubt its that smart. This thing is more like a mid-level mediocre nondescript "business analyst" who only wears out chairs