Lectures: 2 hours weekly
Responsible for the subject: Prof. Zoltán Noszticzius, Department of Physics
Lecturer: Dr.Ferenc Márkus, Department of Physics
vector calculus, differential and integral calculus, basis of the ordinary differential equations.
Compulsory: Mathematics A1
Introduction. Models, theories and laws. Units, standards, SI system. Reference frames. Coordinate systems. Vectors and scalars. Kinematics: speed, displacement, average velocity, instantaneous velocity, acceleration. Uniform motion, uniformly accelerated motion, falling bodies projectile motion. Circular motions. Dynamics: interactions, force, Newton’s laws of motion, mass. Applications of Newton’s laws. Gravitation and Newton’s synthesis. Weight and weightlessness. Kepler’s laws. Work and energy. Work-energy theorem. Translational energy. Conservative forces. Potential energy. Mechanical energy and its conservation. Non-conservative forces. Law of energy conservation. Linear momentum and its relation to force. Conservation of the linear momentum. Many bodies problem. Center of mass. Conservation of momentum and the energy in collisions. Oscillations. Simple harmonic motion. Damped harmonic motion. Forced vibrations. Resonance. Simple pendulum. Rotational motion. Angular quantities. Moment of the force: torque. Angular momentum. Conservation of angular momentum. Rotational dynamics. Rigid bodies. Angular momentum and torque for a rigid body. Moment of inertia. Elasticity and elastic moduli. Stress and strain. Fluids at rest. Pressure. Pascal’s principle. Fluids in gravitational field. Archimedes’ principle. Characteristics of flow. Flow rate and equations of continuity. Laminar flow. Bernoulli’s equation. Viscosity. Turbulent flow. Drag force. Dynamical lift.
Compulsory of the presence, compulsory for the signature: at least 70% presence on the lectures.
Exam: oral exam; working out the answers for two summarizing questions from the list of themes.
Consultations: 14-16 on Tuesdays (in Semester 2007/2008 spring)
Literature: Douglas C. Giancoli: Physics for Scientists and Engineers (Prentice-Hall International Editions).
Last modification of the subject program: 11 May 2007.


smoothScatter with ggplot2
The motivation for this plot is the function:
graphics::smoothScatter, basically a plot of a two-dimensional density estimator. In the following, I want to reproduce the features with ggplot2.
To have some data I draw some random numbers from a two-dimensional normal distribution:
library(ggplot2) library(MASS) set.seed(2) dat <- data.frame( mvrnorm(n = 1000, mu = c(0, 0), Sigma = matrix(rep(c(1, 0.2), 2), nrow = 2, ncol = 2))) names(dat) <- c("x", "y")
smoothScatter is basically a scatter plot with a two-dimensional density estimation. This is nice especially in the case of a lot of observations and for outlier detection.
par(mfrow = c(1,2)) plot(dat$x, dat$y) smoothScatter(dat$x, dat$y)
OK, very pretty, let's reproduce this feature in ggplot2. First thing is to add the necessary layers, which I already mentioned is a two-dimensional density estimation, combined with the
geom called ‘tile’. Also, I use the fill aesthetic to add colour and a different palette:
ggplot(data = dat, aes(x, y)) + stat_density2d(aes(fill = ..density..^0.25), geom = "tile", contour = FALSE, n = 200) + scale_fill_continuous(low = "white", high = "dodgerblue4")
I add one additional layer; a simple scatter plot. To make the points transparent I choose alpha to be 1/10 which is a relative quantity with respect to the number of observations.
last_plot() + geom_point(alpha = 0.1, shape = 20)
A similar approach is also discussed on StackOverflow. Actually that version is closer to
The last step is to tweak the theme-elements. Not that the following adds to any form of information but it looks nice. Starting from a standard theme,
theme_classic, which is close to where I want to get, I get rid of all labels, axis and the legend.
last_plot() + theme_classic() + theme( legend.position = "none", axis.line = element_blank(), axis.ticks = element_blank(), axis.text = element_blank(), text = element_blank(), plot.margin = unit(c(-1, -1, -1, -1), "cm") )
The last thing is to save the plot in the correct format for display:
ggsave( "scatterFinal.png", plot = last_plot(), width = 14, height = 8, dpi = 300, units = "in" )
And that’s it, a nice picture which used to be a statistical graph.


A few days ago, I rediscovered a very interesting paper written by J. L. Kelly, who in the fifties was an associate of professor Claude Shannon (the father of Information Theory) at the famous Bell Labs (later AT&T Bell Labs).
The paper is titled A New Interpretation of Information Rate and was released on March 21, 1956. Let's take a look at the introduction:
"If the input symbols to a communication channel represent the outcomes of a chance event on which bets are available at odds consistent with their probabilities (i.e., fair odds), a gambler can use the knowledge given him by the received symbols to cause his money to grow exponentially. The maximum exponential rate of growth of the gamblers capital is equal to the rate of transmission of information over the channel."
While the intention of Professor Kelly was not that of delving into the basics of gambling (indeed he only wanted to find an alternative scenario for which the transmission rate was significant even in absence of any coding on the transmission channel), I think that the conclusions of this study can be used to (mathematically) confirm some very important investing concepts.
What gambling and investing have in common
Before looking at the paper content, I'll explain the meaning of the title I used for this article.
As Value Investors, we can be annoyed (and sometimes even offended) by whoever tries to associate our investing endeavors to gambling. A gambler (or a speculator) is in our mind someone who intends to earn money trying to guess the outcome of a probabilistic event, and the guess is not an educated one but rather one based on hope or other arcane reasons. Investing on the basis of technical analysis, or betting at a race track, are some examples of such a speculative attitude.
I think that investors and gamblers do have something in common, and that is the act of guessing or trying to imagine the outcome of a chance event or series of events.
We can name it as we prefer, but every investor must deal with uncertainty and therefore with the need of guessing. The difference only lies in the methodology used to produce that guess.
A Value Investor simply tries to minimize the probability of capital loss and to maximize that of capital appreciation. Our biggest effort is that of increasing the probability of success by replacing (as much as possible) the uncertainty with an educated guess.
Game results sent on a private channel
Lets now go back to Kelly's paper. Here's how he introduces the problem:
"Let us consider a communication channel which is used to transmit the results of a chance situation before those results become common knowledge, so that a gambler may still place bets at the original odds."
Let's also make the hypothesis of a symmetric bet: that means that in case of loss, we lose the whole capital we bet, and if we win, we'll double our money.
In the trivial case of a perfect transmission channel, we could simply bet all our capital and fully reinvest it all the time, so that after N bets our initial capital would be multiplied by two to the power of N. For example, if the initial capital is $10 and we place N=10 bets, our final capital would be $10 * 2^10 = $10240.
We can also notice that in this case, as there's no way we can lose the bet, the speed of growth of our capital is equal to the transmission rate, that is to the number of game results we receive within a certain amount of time (e.g. once per week).
The paper then continues with a more interesting scenario:
"Consider the case now of a noisy binary channel, where each transmitted symbol has probability, p, of error and q of correct transmission. Now the gambler could still bet his entire capital each time, and, in fact, this would maximize the expected value of his capital (...) This would be little comfort, however, since when N was large he would be probably be broke and, in fact, would be broke with probability one if he continued indefinitely."
If betting the entire capital each time is a sure recipe for failure, we must necessarily be more conservative and invest only a part of it. The main question the scientist poses is: which is the fraction of our budget we should reinvest each time in order to maximize the exponential rate of growth?
Kelly mathematically demonstrated that, in order to maximize the exponential rate of growth (that is, the compounding power of our investment outcomes), the fraction of the budget we should invest is equal to L = q p, with L being the above mentioned fraction and q and p being the probabilities of a positive and a negative outcome, respectively.
For example, we could have q=0.6 (60% chance of positive results) and p=0.4 (40% chance of negative results), so L=0.2, which means that, in the case of a 60/40 distribution (a positive outcome being here more probable than a negative one), we should invest 20% of our budget if we want our capital to grow as fast as possible. If the distribution is more favorable, lets say 80/20, we should invest 60% of it.
How is Kelly's thesis linked to the investment concepts we're already familiar with? Here are a few considerations directly derived from his simple formula:
- Never invest all your money on a single idea (unless you are absolutely certain about it, but that's usually not the case with investing).
- Allocate your capital accordingly with the estimated probabilities of success and failure. Hope, random guesses and speculation in general are not wise approaches and do not produce good results in the long run.
- The fraction of our budget to invest depends on the difference between the probabilities of success and failure: the bigger the difference, the greater the amount to invest. This means that we should have the courage of allocating greater amounts of capital to our best ideas.
Kelly's paper practically demonstrates that we can take advantage of a specific situation (in our case, an investment scenario) if we have an edge. In investing, having an edge is always the result of a sound investment thesis.
"The wise ones bet heavily when the world offers them that opportunity. They bet big when they have the odds. And the rest of the time, they dont. Its just that simple."
In the next article on this topic, I will extend the discussion to the case of asymmetric bets, describing what is commonly known as the Kelly Formula (which is a generalization of the simple one described in this article), how to practically use it and how this and other studies have been used in the past to profit off of both asymmetric outcomes and gain/loss probabilities.
Read more here:
- Garrett Motion: A Margin of Safety and a Turbo-Catalyst
- Why Berkshire Hathaway's Future Is Safe
- Downside Protection: How Do We Handle It?
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The Fascinating World of Right Triangles
Right triangles are a fundamental concept in geometry, and understanding the sides that form the right angle is crucial in various mathematical and practical applications. In blog post, explore definition sides right triangle form right angle delve significance concept different fields.
Defining the Sides of a Right Triangle
In right triangle, The side opposite the right angle called hypotenuse, while other two sides form right angle known legs. Relationship between sides described Pythagorean theorem, which states square length hypotenuse equal sum squares lengths legs.
Table: Comparison Sides Right Triangle
|The side adjacent to the right angle
|The side adjacent to the right angle
|The side opposite the right angle
|Connected to the right angle
|Connected to the right angle
|Opposite right angle
Importance of Understanding the Sides of a Right Triangle
The concept of the sides of a right triangle is not only crucial in mathematics but also has practical applications in various fields. For example, in architecture, engineers use the principles of right triangles to design and construct buildings with stable and strong structures. Additionally, in navigation and surveying, understanding right triangles helps in calculating distances, angles, and elevations accurately.
Case Study: Application Engineering
In a recent study conducted by a team of civil engineers, the use of right triangles in determining the stability of bridge structures was highlighted. By analyzing the relationship between the sides of the triangles formed by the bridge supports, the engineers were able to make precise calculations that led to the successful construction of a new bridge with enhanced strength and durability.
Exploring the Wonders of Right Triangles
The beauty of right triangles lies in their simplicity and yet their profound impact on various aspects of our lives. By understanding the sides that form the right angle, we gain insights into the intricate connections between geometry, physics, and engineering, paving the way for innovative advancements and practical solutions.
Top 10 Legal Questions About Defining the Sides of a Right Triangle
|1. What is the legal definition of the hypotenuse of a right triangle?
|The hypotenuse, my dear reader, is the side of a right triangle that is opposite the right angle. Longest side makes right triangle special. It`s like the guardian of the right angle, always ensuring harmony and balance in the triangle. It`s a true hero in the world of geometry.
|2. Are there any legal implications of incorrectly identifying the hypotenuse in a right triangle?
|Oh, absolutely! If you mislabel the hypotenuse, you`re essentially misrepresenting the fundamental nature of the right triangle. It`s like calling a square a circle – it`s just not right. In legal terms, it could lead to misunderstandings, misinterpretations, and a general lack of mathematical integrity.
|3. Can the lengths of the sides of a right triangle have legal significance?
|Indeed, the lengths of the sides are crucial in determining the properties and relationships within the right triangle. Just like in the legal world, where every detail matters, the lengths of the sides can have profound implications on the application of the Pythagorean theorem and other mathematical principles.
|4. Is there a legal requirement to accurately measure the sides of a right triangle?
|Well, there may not be a specific law mandating it, but in the court of mathematics, accuracy is paramount. Just as in the legal system, where evidence must be precise and reliable, the measurement of the sides in a right triangle should be done with utmost care and precision.
|5. What legal considerations should be taken into account when discussing the base and height of a right triangle?
|Ah, the base and height, the dynamic duo of the right triangle! When it comes to legal considerations, these two sides play a crucial role in determining the area of the triangle. Much like legal arguments, the base and height must be well-defined and properly presented to make a compelling case for the triangle`s area.
|6. Can the legal concept of “burden of proof” be applied to the sides of a right triangle?
|Interesting question! In a way, the sides of a right triangle do carry a burden of proof – they must satisfy the Pythagorean theorem to be considered legitimate. If they fail to do so, they`re simply not up to par, much like a weak legal argument that lacks sufficient evidence.
|7. Are there any legal precedents involving disputes over the sides of a right triangle?
|While there may not be infamous court cases specifically about right triangles, disputes over mathematical principles have arisen in legal contexts. Just as in law, the sides of a right triangle must adhere to established rules and principles to avoid any disputes over their validity and integrity.
|8. Can the sides of a right triangle be legally patented or copyrighted?
|Now that`s an intriguing thought! While the sides of a right triangle cannot be patented or copyrighted in a traditional sense, their unique properties and relationships are indeed protected by the laws of mathematics and geometry. They are timeless treasures, free for all to admire and utilize.
|9. What legal ramifications exist for using the sides of a right triangle in real-world applications?
|When it comes to real-world applications, the sides of a right triangle must be deployed with utmost accuracy and precision, much like legal precedents in court. Any misuse or misrepresentation of the sides could lead to flawed calculations and misinformed decisions, which is a risk not worth taking.
|10. Are there any legal guidelines for resolving disputes related to the sides of a right triangle?
|While not specifically outlined in legal statutes, resolving disputes related to the sides of a right triangle requires a fair and objective application of mathematical principles. Much like in the legal system, disputes should be approached with reason, evidence, and a commitment to upholding the integrity of the right triangle.
Legal Contract: Definition of the Sides of a Right Triangle
This contract, entered into on this day, by and between the undersigned parties, seeks to establish and define the sides of a right triangle that form the right angle in accordance with applicable laws and regulations.
|Clause 1. Definitions
|1.1 “Right Triangle” shall refer to a triangle with one angle measuring 90 degrees.
|1.2 “Sides” shall pertain to the line segments that form the right angle in a right triangle.
|1.3 “Right Angle” shall mean an angle of 90 degrees formed by the sides of the right triangle.
|Clause 2. Obligations Parties
|2.1 The Party A shall accurately measure and identify the sides of the right triangle.
|2.2 The Party A shall ensure that the measurement of the sides conforms to the principles of trigonometry and geometry.
|2.3 The Party B shall acknowledge and accept the measurement and identification of the sides of the right triangle by Party A.
|Clause 3. Governing Law
|3.1 This contract shall governed laws jurisdiction right triangle defined.
|3.2 Any disputes arising from or relating to this contract shall be resolved in accordance with the laws of the jurisdiction.
In witness whereof, the Parties have executed this contract as of the date first above written.


Inspired by Think Twice
It is a simulation of a double pendulum where two mass are attached with each other in swing motion. It is interesting because when there is only one mass (a single pendulum), the motion of the system is well-predicted as it is just swing back and forth. However, when another mass is attached, it exhibits chaotic motions where a tiny change in the initial setting will dramatically change the overall motion.
Please see Double Pendulum by Erik Neumann for more detail.
I found out later that the way I implemented is called `Euler's Method`. It is a numerical method to determine values in a differential equation system.for each step t: v = v + at x = x + vt
After playing around for a while, I observed strange behaviour as it was also reported here. It seems that the Euler's method works just fine when `t` is very small and the equations are quite simple. Because it "does not take into account the curvature of the solution, so it tends to give different results depending on the step size" . A better solution to this issue is to implement Runge-Kutta Method. Aim of the method is similar to the Euler's but it takes into account the curvature so it results in a significantly accurate motion.
Even though I didn't fully understand how Runge-Kutta Method works, but my pendulum seems to run smoothly without the strange behaviour.
Open world to the Physics Simulation.


Looking for engaging first week of school activities that will get your students up and moving? Check out this mental math review scavenger hunt that will have your kids collaborating to be the first to crack the code!
— ABOUT THIS RESOURCE —
✔ Low prep activity – just print, copy and hide a treat!
✔ Encourages students to interact with new classmates
✔ Includes addition, subtraction, multiplication and division up to 12×12
✔ Students learn a little about the classroom while searching for the ‘treasure’ (prize)
✔ Students are motivated to work with a partner and solve the questions
✔ Gets students up and moving
— WHAT’S INCLUDED? —
✔ Two-page printable math treasure hunt for students
• Page 1 – 30 question clues to be solved
• Page 2 – the code and answer key to find the treasure
✔ Answer key
Want to accommodate? Allow students to use pencil and paper, or a calculator.
NEED HELP? Before leaving feedback:
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Mass of Higgs Boson predicted by Homer Simpson!!!!!
Homer Simpson seems to have discovered the equation to calculate the weight of the elusive God Particle, Higgs Boson as back as a decade
Many of the episodes of the cult show “The Simpsons” are laced with mathematics. It is said the many people involved in the making of this show are mathematicians
In one such episode called “The Wizard of Terrace” in 1998, Homer Simpson turns into a mathematician and is shown pondering over a equation in front of the blackboard.
The equation is written as shown in the picture below.
If you put the values of all the constants in the equation, you come up with the mass as 13.8169×10-25 kilograms.
The latest value as reported in the respected magazine is of the order of 10-25 kilograms which is remarkably close to the value derived from the formula.
So is it a coincidence or something else? The observation was made by science author and presenter Simon Singh in his forthcoming book.


The quantitative finance track is designed to develop students' analytical skills and prepare them for quantitatively focused careers in finance the track is. Wbs training are delighted to announce our new conference for 2018: women in quantitative finance conference (wqf. This book series on quantitative finance will consist of cutting-edge research books on new subjects of financial mathematics, excellent textbooks that present .
The advanced master in quantitative finance offers a unique set of quantitative tools in finance through a well-selected set of courses in. Home about program program delivery program structure program preparation program modules lifelong learning accreditations affiliates. Quantitative finance, also known as mathematical finance, is a complex field of applied mathematics that is primarily concerned with the financial markets. The latest tweets from quantitative finance (@qfinancepapers) new quantitative finance submissions to (not affiliated with.
The course equips you with the necessary theoretical, mathematical and computational skills needed to pursue a career in quantitative finance if you are a. The quantitative finance major is highly quantitative and computer intensive, and is designed to prepare students for careers in financial engineering, structured. The quantitative finance summer program is an intensive 10-week program that provides summer analysts the opportunity to work alongside full-time. Mathematical finance, also known as quantitative finance, is a field of applied mathematics, concerned with mathematical modeling of financial markets.
Math for quantitative finance tour the mathematics used to model the chaos of the financial markets see why math is the new hero of finance 0/3 start. List of issues latest articles volume 18 2018 volume 17 2017 volume 16 2016 volume 15 2015 volume 14 2014 volume 13 2013 volume 12 2012. Contact schools directly - compare 20 master of science degrees in quantitative finance 2018/2019.
The encyclopedia of quantitative finance is a major reference work designed to provide a comprehensive coverage of essential topics related to the quantitative . Master's degree programme in quantitative finance theoretical and applied questions in financial economics are not only important key. The university of maryland robert h smith school of business offers two premier finance masters programs -- the master in finance and the master in.
Study an msc in quantitative finance at the multi-award-winning university of strathclyde join over 22000 students from 100+ countries. Find out more about the msc quantitative finance in the business school at the university of glasgow, uk, this programme draws on recent developments in. As financial securities become increasingly complex, demand has grown steadily for compensation in the field of finance tends to be very high, and quantitative analysis follows this trend it is not uncommon to find positions. You have an interest in quantitative finance you want a career in areas such as trading, quantitative portfolio management, data analytics, risk management and .
Our quantitative finance and risk management msc will develop your understanding of generalist finance issues you'll also develop specialist practical skills. The focus of research at quantitative finance group is the investigation by means of quantitative methodologies, both analytical and empirical, of several. The quantitative finance graduate certificate program at njit explores these concepts to prepares quantitative analysts to use these tools for investment.


Our College Mathematics Department Profile
The department of Mathematics was established in the academic year 1976-1977. It has been upgraded as P. G. department in the academic year 2005-2006. Research Programme M. Phil., Mathematics was introduced in the year 2016. The department offers B. Sc., Mathematics (Tamil Medium) also from the academic year 2017-2018.
|Number of Teaching Post Sanctioned : 10|
|Designation||Teaching Post Filled|
|Guest Lecturer (Full Time)||04|
|Parent Teacher Association (Full Time)||01|


Effective Advice For Finding Good Math Homework Answers
Doing Math homework was considered to be quite a complicated task decade’s back. Majority of students consider this subject to be quite time consuming and dreadful also. But students of this era are quite privileged to avail help from diverse online sites pertaining to math problems.
It has become so simple to get the math assignment answers in just no time courtesy those websites. All you need to do is to place it on search engine and will come across various sites offering the answers instantly. Few other sites will provide the answers of the textbook straightaway.
Know more about the online sources offering good answers to math homework
- Some websites provide you with the answers available in the books. You are surely assigned with problems to solve from math books for the purpose of practising. There are few such sites that provide you with an instant solution to the problems given in the textbooks.
- Another sort of website provide you with solutions on their respective web pages. They are well equipped with problem solver to render solution to any type of equations. Those are diversified into different sections that enable you to select the type of math for which you are looking for the answer.
- There are certain unique sites, where from you can avail solution one by one basis. From such websites you can get the benefit of interacting with experts and receiving the answers at free of cost. These specialized math sites render solution to various problems in this domain.
- Are you aware of the fact that your much used cell phone may also assist you in performing your math assignment skillfully? There are certain specialized mobile apps which may permit you to take picture of the problem and then take the necessary step to complete your assignment on your behalf. Now getting answers has got so simplified and fast due to these advanced apps.
Obviously technological advancement has eased the life of students to a great extent. Getting solution to such critical mathematics assignment is such a smooth and hassle free task! But one pitfall is the fact that while you appear for exams then you need to gain the requisite expertise to solve your problems on your own, without depending on those technological assistance.
Even then with this online help you can easily deal with your day to day tension. You can track the answers for different problems just in a jiffy. You may get an idea about the step by step mode of proceeding with it and ultimately solving the same in a matter of few seconds.
- Help with math problems
- How to manage geometry homework
- Places to find assignment help online
- Finding free calculus checkers
- Find help online
- Homework in kindergarten
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On Tuesday, April 16, the Seventeenth Annual CBU Student Research Poster Session will be held in the Sabbatini Lounge of the Thomas Center. Here are pictures and information from last year’s session.
On Tuesday, April 16, the CBU Math Department will be hosting part of the Tennessee Mathematics Teachers Association (TMTA) High School Math Tests. We expect about 160 students this year.
On April 27, the senior Chemistry and Biochemistry majors will present the results of their undergraduate research at the 36th Annual Area Collegiate Chemistry Meeting to be held at Murray State University in Murray, Kentucky.
Monday, April 29, is the last day of classes for the day program.
Final exams go from Wednesday, May 1, through Tuesday, May 7.
On Saturday, May 11, we will hold graduation!


Calculation of Yarn English Count
English count indicates how many hanks of 840 yards length weigh one pound. That means if count 40 Ne Than it means 40 hanks(bundle) of 840 yards will give 1 pound weight.
(Note: So, for gaining 1 pound weight, 840 yards long how many yarn bundle we will in need, this require a number of bundles is the English count of this yarn.)
- Why calculation: Most of us are fear from count calculation. But we should have a common sense of calculation to be good textile personnel.
Let’s try to solve the following problem of English count
On one cone there are 9800 m yarns which weigh 490 gm. What is the English count of this yarn?
For Ne(English count),
So, Here count 12 Ne means, 12 bundles of yarn with 840 yards length will be required to get 1 pound weight.
So, wish it was helpful for you to understand English count properly. If you like it doesn’t forget to put down your valuable comments and share on facebook
Engineer Sheikh Nurja
B.Sc engineer of textile
Merchandiser at buying house
Facebook: Sheikh Nurja


Dear colleagues and friends
We are happy to announce that the 18th Applied Statistics Conference will take place on 19-21 September 2022 in Ljubljana. The event will be hosted at the Faculty of Social Sciences.
The International Applied Statistics conference is organised by Statistical Society of Slovenia and Faculties of University of Ljubljana (main supporters are Faculty of Social sciences and Faculty of Medicine).
The registration to the Applied Statistics conference is free of charge but registration to the event is required. The deadline for abstract submission is July 25. Please visit the web page of the conference https://stat-d.si/applied-statistics-conference/as2022/ to submit your abstract and to register for the Conference.
The programme of the first two days will include two invited speakers, invited sessions and contributed oral and poster sessions. Wednesday September 22 will be devoted to the Workshop.
The invited speakers will be:
|Peter Filzmoser |
Vienna University of Technology, Austria
|Robust linear and logistic regression for high-dimensional compositional data|
|Matthias Schmid |
University of Bonn, Germany
|Competing risks methods for discrete time-to-event data|
The workshop “Generalized blockmodeling in R using blockmodeling package” will be held by Aleš Žiberna and Marjan Cugmas from University of Ljubljana on Wednesday 21 September.
We are looking forward to meeting in person again, bringing together leading experts in statistics, data analysts and other professionals from various statistical and related fields to present their research, discuss presentations online and learn from each other.
Lara Lusa and Irena Vipavc Brvar
for the scientific and organizing committees of the Applied Statistics Conference
|Abstract submission deadline||July 25|
|Notification of acceptance||August 13|
|Registration deadline for presenting authors||August 23|
|Final registration||September 18|


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Thats why we use the len function while defining the array. 17 Other optimization strategies that focus on minimizing tail-risk (e.g., value at risk, conditional value at risk ) in investment portfolios are popular amongst risk averse investors. Higher the number of iterations, higher will be the accuracy of the optimization but at the cost of computation and time. To reflect a preference for higher rather than lower returns, this objective function is increasing in wealth, and to reflect risk aversion it is concave. The Maximum Calculated Cycles of 8 is a number used in the drawdown probability calculation. For portfolios that meet this criterion, known as efficient portfolios, achieving a higher expected return requires taking on more risk, so investors are faced with a trade-off between risk and expected return.
"The optimization of a quadratic function subject to linear constraints". First Impressions This is a bit of an extended post (probably the longest on the blog so far) but it hopefully provides a decent step-by-step the evaluation and optimization of trading strategies pdf illustration of some of the concepts and how to apply them practically (there are more. I will not detail the formula here (Ill refer you to the book again) but Vince presents a way of calculating the probability of a specific drawdown. 12 Regulation and taxes edit Investors may be forbidden by law to hold some assets. "The Myth of Diversification". These constraints can lead to portfolio weights that focus on a small sub-sample of assets within the portfolio.
However short-selling can be forbidden. The ImpairmentCalc software provides expected loss impairment calculations, incorporating data and scenario analysis for forward-looking evaluation under ifrs 9 and cecl guidance. After the first month, the equity would have increased.9 to 122.9M, which would then be re-allocated according to the same leverage ratios. I will describe the concepts using the simple two-coin toss example and draw a parallel with the real-world application on the four Trend Following Wizards. Head (5) print sim_frame.
Tail (5) The above output shows some rows of the simulation results. By using such a two-step procedure one eliminates non-systematic risks both on the individual asset and the asset class level. "Is diversification always optimal?". Following the, risk-Opportunity Analysis conference, i attended earlier this month, I decided to test the model and the software used to implement it (. The meat of the leverage space model code is contained in the R implementation by Joshua Ulrich (from foss Trading ). You can perform scenario and what-if analyses using a bottom-up approach to measure the impact of adverse events on obligors, or sets of obligors, with significant exposures in the credit portfolio. Harry Markowitz 5 developed the "critical line method a general procedure for quadratic programming that can handle additional linear constraints and upper and lower bounds on holdings. However, too frequent trading would incur too-frequent transactions costs; so the optimal strategy is to find the frequency of re-optimization and trading that appropriately trades off the avoidance of transaction costs with the avoidance of sticking with an out-of-date set of portfolio proportions. This is really just a notation. The Journal of Finance.
Factors being considered may range from tangible (such as assets, liabilities, earnings or other fundamentals ) to intangible (such as selective divestment ). Computational Statistics Data Analysis. 1 2, it assumes that an investor wants to maximize a portfolio's expected return contingent on any given amount of risk. 19 More recently, hedge fund managers have been applying "full-scale optimization" whereby any investor utility function can be used to optimize a portfolio. Let us consider a portfolio consisting of four stocks in banking/financial services sector, namely: Bank of America (BAC Goldman Sachs (GS JP Morgan Chase Co (JPM) and Morgan Stanley (MS). Improve portfolio structure and address concentrations while generating revenue. Kim, Young Shin; Giacometti, Rosella; Rachev, Svetlozar; Fabozzi, Frank.; Mignacca, Domenico. "Multi-agent investment in incomplete markets". Browse Moodys Analytics Learning Solutions and Certifications.
In this simulation, we will assign random weights to the stocks. Central to this optimization is the construction of the covariance matrix for the rates of return on the assets in the portfolio. See Copula (probability theory Quantitative finance. The lspm uses another R package: snow, in order to leverage multi-processors with parallel computing to speed things. Cooperation in portfolio optimization edit A group of investors, instead of investing individually, may choose to invest their total capital into the joint portfolio, and then divide the (uncertain) investment profit in a way which suits best their utility /risk preferences. The n-dimensional curve is constructed in the exact same way, but any f-values that result in a probability of drawdown over the constraint threshold are ignored this would usually result in all values around the peak being discarded. The model is really an alternative portfolio allocation method and I can not see how it could be applied directly to determine position sizing for a trading system. Multi-Component Scenarios with Coin Tosses Following on with our coin-toss example, lets now consider the case of two simultaneous coin-tosses. Specific approaches edit Portfolio optimization often takes place in two stages: optimizing weights of asset classes to hold, and optimizing weights of assets within the same asset class. After 25 years of repeating the same process monthly, the 100M would become a theoretical figure of 411.4 Billion thanks to a monthly geometric mean return.81 (whereas an unleveraged equal-split across four managers with monthly rebalancing would result in a paltry.9 Billion). The Leverage Space Model caters for this, with the possibility of adding margin constraints (I have not looked into this yet but this post on foss trading talks about it). By portfolio optimization, we mean getting a portfolio that meets any of the three conditions based on the investors requirements.
#Calculate mean returns and covariances of all four the stocks mean_returns stock_an cov_matrix stock_v print (mean_returns) print (cov_matrix) Let us define an array to hold the result of each iteration. Annals of Operations Research. This effectively means that an investor would have achieved the highest possible final equity investing in Dunn by resetting the evaluation and optimization of trading strategies pdf the notional account size to 163 of the actual account size, every month (this is theoretical as it ignores the. Optimal f relates. Shapiro, Alexander; Dentcheva, Darinka; Ruszczyski, Andrzej (2009).
Info for the techies: I am running an Intel Core 2 Quad Processor @2.40GHz and I allocated three processors to the optimization process but the running time came at a disappointing three hours for 100 iterations. "Measuring financial risk and portfolio optimization with a non-Gaussian multivariate model". A genetic algorithm is used for the optimization; and after a specific number of iterations, the optimal set of f-values is output by the program. Of course, this improvement is only possible in hindsight. The main point is that.25 is the Optimal f (meaning, in that case, that staking 25 of the largest loss on each bet will maximize the growth of the trading stake over time any other value would be sub-optimal). In case of the simple two-coin toss example, these are easy to identify: 2 Tails: lose 2, 25 probability 1 Tail and 1 Head: gain 1, 50 probability 2 Heads: gain 4, 25 probability Using this set. Conditions of Portfolio Optimization, a portfolio which has the minimum risk for the desired level of expected return. Monte Carlo Simulation, this simulation is extensively used in portfolio optimization. Since the optimal portfolio changes with time, there is an incentive to re-optimize frequently.
The first run is a straight optimal f calculation with 100 iterations. Adding a third simultaneous coin toss would simply generate a 4-dimensional curve (with each point representing the growth rate output of the f-triplet) and so on: the curve is always N1-dimensional, where N is the number of components. Take your career to the next level. #Set the number of iterations to 10000 and define an array to hold the simulation results; initially set to all zeros num_iterations 10000 simulation_res Lets now move on to the iterations. Our solutions enable you to rapidly measure and benchmark portfolio-level credit risk and return across your entire organization. Grechuk,., Molyboha,., Zabarankin,. This is primarily because all component returns have to be split across identical periods, whereas trades from a single system do overlap. In a practical trading example, I have decided to look at the four. Loop through each period and: For each component, determine which bin the periods return fall into; and assign the bin outcome to that component, for that period. When the portfolio optimization process is subject to other constraints such as taxes, transaction costs, and management fees, the optimization process may result in an under-diversified portfolio. We quantify diversification benefits across portfolios, and define risk types that inform risk management and active asset allocation decisions.
Journal of Banking Finance. Improve the performance drivers of your portfolio models with economic, demographic, and financial data, forecasts. However, the files attached at the end of this post in the technical appendix should help you retrace this logic. Whereas the first optimization for the simple growth-optimal f values took seconds for 100 or 1,000 iterations of the algorithm, adding the drawdown constraint has a significant impact on the computation time. Most of the mathematical formulas supporting the model are in the book. Pct_change print (stock_und(4 100) We will now calculate the mean return of all stocks and the covariance matrix. Ang, Andrew; Chen, Joseph; Xing, Yuhang (2006). 21 Where such methodologies involve the use of higher-moment utility functions, it is necessary to use a methodology that allows for forecasting of a joint distribution that accounts for asymmetric dependence. (reprinted by Yale University Press, 1970, isbn ; 2nd. Leverage our industry-leading models, software, and exceptional services to effectively measure, monitor, and manage credit risk within your portfolios. Xlim(0.0075,0.012) #Plot a red star to highlight position of the portfolio with highest Sharpe Ratio #Plot a blue star to highlight position of the portfolio with minimum Variance ow In the output, the red star shows the portfolio. Multi-Component Scenarios with Trading Data Lets now look at our test case with the four Trend Following Wizards.
Summary Just to summarize our complete analysis, we first downloaded the stock price data for one month and computed the mean return of all the stocks and the covariance matrix (which the evaluation and optimization of trading strategies pdf is used in computing the standard deviation of the portfolio). Update We have noticed that some users are facing challenges while downloading the market data from Yahoo and Google Finance platforms. #Compute stock returns and print the returns in percentage format stock_ret data. This would obviously be dependent on how stable the component returns are over time (like for any aspect of back-testing). Optimal f, for a single stream of returns or betting outcomes/probabilities, there is a specific level of leverage, or fraction of capital, to risk on each event, which maximizes the geometric growth of the equity.
The number of columns will change with the number of stocks in the portfolio as we have to store the weights for all the stocks. To minimize exposure to tail risk, forecasts of asset returns using Monte-Carlo simulation with vine copulas 18 to allow for lower (left) tail dependence (e.g., Clayton, Rotated Gumbel) across large portfolios of assets are most suitable. Note that Josh has a blog post on how to create the JPT, so you might be able to only use R, should you want to experiment with the Leverage Space Model (I am not sure the java app is freely available). At every particular combination of these weights, we will compute the return and standard deviation of the portfolio and save. It might well be possible to use each instruments equity curve when traded through a specific system. Below is a file containing the R session that I used to run the example in the posts. Most investors, traders or managers would happily give up some return to stay in their acceptable levels of volatility and drawdown. I will not paraphrase the book and reproduce all the formulas here but I will refer to some of them. It starts with why evaluation and measurement are necessary. Annual Returns and Standard Deviation, to simplify our analysis in this blog, we will deal with daily returns and standard deviation and will consider only 1 month of stock data (Dec 2017). 4, optimization methods edit, the portfolio optimization problem is specified as a constrained utility-maximization problem. Leverage Space Trading Model.
Any other value, higher or lower would have resulted in a lower equity curve. Naval Research Logistics Quarterly. For this, we need to bin the data distribution and create the Joint-Probability Table (which holds each possible outcome combination and its associated probability similarly to the 3 possible outcomes identified above for the coin-toss example). For example: Find the optimal f values for which the probability of a 30 drawdown over 12 periods does not exceed. Some recent studies explore information other than price history, such as market sentiment 13 and business classification 14 to enable the forecast. The fact that the java app generates the R commands directly was helpful, but you can probably learn by example by checking the R session file at the end of the post (there is more doc available.
"Mean-Variance versus Full-Scale Optimization: In and Out of Sample". On the other hand, I can see how the model might be useful to the manager running a programme made up of several systems and wanting to optimize the allocation to each system. Our models, research, software, and credit risk expertise help firms improve portfolio performance and meet Basel requirements. Leverage Space Trading Model: Optimizing f with R The java app developed by Vince creates the Joint-Probability Table from the import of the equity curve for each component. In case you are looking for an alternative source for market data, you can use Quandl for the same. Then explains how to compute and analyse the returns generated by the portfolio after a particular time period. Lectures on stochastic programming: Modeling and theory (PDF). Trend Following Wizards with the longest track records (that I have Campbell, Dunn, John Henry and Millburn. We can now compute the portfolios having maximum Sharpe ratio or minimum risk. Investment is a forward-looking activity, and thus the covariances of returns must be forecast rather than observed. The actual leverage amount is independent of the biggest loss, but expressing it that way bounds the value for f between 0 and. "Cooperative games with general deviation measures", Mathematical Finance, 23(2 339365). At 100 (no leverage the monthly geometric mean return.11; at 163 leverage, the mean return becomes.29 (which is the maximum value possible).
Around 83 the evaluation and optimization of trading strategies pdf MaxDD at 163 leverage). We can support you in defining credit risk strategies aligned with portfolio profitability and pricing objectives. Org/bin/, and the R lspm package. Note that here, the optimal f does not represent the actual leverage or fraction of capital to apply. Of course the drawdown would also increase (around 60 MaxDD at 100 leverage. In the case of the two-coin toss, the optimal f-combination is (0.23,.23) meaning that staking 23 of the capital on each simultaneous coin toss (46 in total for each period) would result in the highest growth rate (over time). The second run is the same with 1,000 iterations and the third run is the optimization with drawdown constraint. Basil Blackwell, 1991, isbn ) Cvitani, Jaka; Polimenis, Vassilis; Zapatero, Fernando. It was later explicated by William Sharpe. The number of iterations depends on the error that the trader is willing to accept. The data looks as shown: We will then convert these stock prices into returns and will save this under the name stock_ret.
Maybe a less costly risk computation might make the running time more manageable. "Optimal portfolio allocation with higher moments". Portfolio optimization is the process of selecting the best portfolio ( asset distribution out of the set of all portfolios being considered, according to some objective. The other implication from this sample application is that the optimal f value can dictate a leverage value which can be higher than the maximum allowed (be it the evaluation and optimization of trading strategies pdf by margin requirements or stock trading in a cash account, etc.). The trading strategies or related information mentioned in this article is for informational purposes only. Talebi, Arash; Molaei, Sheikh (17 September 2010). Drawdown Constraints One of the main problem usually raised with the concept of optimal f is that trading for growth rate optimization is often not realistic, as it generates untenable levels of drawdown and volatility. The R button generates the R instructions to run with the lspm package.
GCorr Macro EL Calculator addresses regulatory requirements for stress testing and assists in strategic portfolio credit risk management. The objective typically maximizes factors such as expected return, and minimizes costs like financial risk. I understand that this is mostly due to the heavy computational costs of evaluating the probability of drawdown. In addition to the traditional measure, standard deviation, or its square ( variance which are not robust risk measures, other measures include the Sortino ratio, CVaR (Conditional Value at Risk), and statistical dispersion. Quantitative techniques that use Monte-Carlo simulation with the Gaussian copula and well-specified marginal distributions are effective. A portfolio which gives the maximum expected return at the desired level of risk (risk as measured in terms of standard deviation or variance). Improving portfolio optimization edit Correlations and risk evaluation edit Different approaches to portfolio optimization measure risk differently. Record the combination of all bin outcomes (ie for all components) for that period and assign it the probability: 1 / number of periods If different periods have the same combination, these can be grouped together (by summing the individual. Techniques include: Optimization constraints edit Portfolio optimization is usually done subject to constraints, such as regulatory constraints, or illiquidity. Each combination generates its corresponding growth rate (which is related to the Terminal Wealth Relative, TWR). Continued emphasis on revenue generation and meeting business objectives brings ongoing pressures for growth, specifically in ways that meet desired return thresholds. "An analytic derivation of the efficient portfolio frontier Journal of Financial and Quantitative Analysis 7, 18511872.
Chua,.; Krizman,.; Page,. RiskFrontier software is an industry-leading credit portfolio risk management solution, trusted by financial institutions globally to improve business performance. However, in practice, we work with annual returns and the evaluation and optimization of trading strategies pdf standard deviation. In the example of the coin-toss with the following parameters: Risk 1 unit for each bet. #Spot the position of the portfolio with highest Sharpe Ratio max_sharpe sim_xmax #Spot the position of the portfolio with minimum Standard Deviation min_std sim_xmin print "The portfolio for max Sharpe Ratio:n max_sharpe print "The portfolio for min risk:n. Random.random(4) weights / m(weights) #Calculate the return and standard deviation for every step portfolio_return m(mean_returns * weights) portfolio_std_dev t(t(cov_matrix, weights) #Store all the results in a defined array simulation_res0,i portfolio_return simulation_res1,i portfolio_std_dev #Calculate Sharpe ratio and store it in the array simulation_res2,i. You can use different inputs and model assumptions to determine losses and assess capital adequacy under changing economic conditions. Another aspect worth looking into is how useful the model is in a forward-looking mode (ie to determine optimal f/leverage to apply to each component for the next periods) and how this can be used/configured (over the whole. The Review of Financial Studies. Similarly, we need a discrete set of outcomes and associated probabilities for our input. See also edit References edit Markowitz,.M.
For realistic utility functions in the presence of many assets that can be held, this approach, while theoretically the most defensible, can be computationally intensive. Note that here the largest loss is equal to 100 of the bet size and therefore the Optimal f and the fraction of capital to stake are equal. #Import relevant libraries import pandas as pd import numpy as np import pandas_datareader. The method requires a discrete set of outcomes and associated probabilities. Tails: lose 1, heads: win 2, the fraction of capital staked on each bet will alter the expected growth rate as per this curve: This has been covered extensively elsewhere (as a simple application of the Kelly formula). To start with, well assign random weights to all four stocks, keeping the sum of the weights to. With ongoing pressures to comply with regulatory stress testing guidelines, institutions are challenged to stay ahead of strategic business objectives, including setting and refining limits, defining contingency plans, and planning for liquidity. Low,.K.Y.; Faff,.; Aas,. Any decisions to place trades in the financial markets, including trading in stock or options or other financial instruments is a personal decision that should only be made after thorough research, including a personal risk and financial assessment and the.
The app requires a file per component, containing the equity curve with constant position sizing (ie. The JPT is the full list of outcome combination and associated probability. All track records go back to 1985 (up to end 2009). Our solutions can help improve revenue growth, balance revenue versus return against evolving capital measures, and manage exposure strategies among lines of business. The main idea is to introduce a risk constraint to the model, so that instead of solely optimizing for maximum growth rate, one can optimize with a constraint on drawdown. Portfolio Optimization For Maximum Return-To-Risk Ratio Using PythonClick To Tweet. Data as web import plot as plt #Fetch data from yahoo and save under DataFrame named 'data' stock 'BAC 'GS 'JPM 'MS' data Close' #Arrange the data in ascending order oc:-1 print und(2).


This is interesting. Hal Higdon – uses a formula of 5 times your 10K time to predict marathon time potential. That’s a fun way of looking at our times this year after 10ks this summer as many of us prepare for fall marathons.
This turned out to be in the ballpark for me last year. I ran a 10k in 1 hr 2 min in June and did my first marathon in October in 4:57. (1:02 x 5 = 5:10 marathon prediction.) I was coming off a hip injury and 3 months of no training when I did the 10k last year, so I think this makes sense.
It’ll be fun to see how things go on Saturday.


There are three different ways that NBA odds can be written; fraction, decimal and American. When you are reading NBA odds, they will be in the American format. For a full explanation of how each three formats work, including how to work out how much you will profit and what the odds mean for the probability of your betting winning, check out our how to read odds page.
American odds are used for moneyline, point spread, total over/under and prop bets as well as NBA futures odds.
When NBA betting, the favourite of a contest will have negative odds, for example -175, meaning you must risk/bet $175 to be able to profit $100, if your bet wins. The underdog of a contest will have positive odds, for example +150, meaning if you risk/bet $100, you will profit +150, if your bet wins.
Are you still wondering how to bet on the NBA? The following table explains what would happen if you bet on a team in a particular game and they went on to win:
The Denver Nuggets are -250 favourites in this game and a $50 bet would return $70 ($50 stake + $20 profit) if they win. The Miami Heat are +210 underdogs and a $50 bet would return $155 ($50 stake + $105 profit) if they win. Underdogs have much better odds as their probability of winning is less than the favourites.
Using the formula to convert odds into probability of winning on our how to read odds page, the odds of this Nuggets v Heat game represent the following probabilities of winning:
|Team||Odds||Probability of Winning|
The odds provided represent Denver having a 71.43% chance of winning and Miami having a 32.26% chance of winning.
You may notice that those odds add up to more than 100%, but how is that possible? Sportsbooks always make the odds so that they end up making a profit, and by making the odds so that the probability adds to 100%, theoretically if there was even money bet on both sides of the game, they would profit overall regardless of the outcome.
Our experts explain how NBA picks work and ensure that you are getting the best odds available on all of your bets.
One NBA betting strategy often used is betting on NBA future markets. NBA future odds allow you to bet on an event where the outcome won’t happen for a period of time. You can bet on individual and team awards, with most markets opening soon after the previous season finishes!
Using an example from the 2020 Eastern Conference Finals betting odds:
The Milwaukee Bucks are -117 favourites to win the East and advance to the NBA Finals. These odds mean that you would have to bet $117 in order to profit $100, for a total return of $217 (stake + profit). Based on the above odds, the Bucks have a 53.92% chance of winning the Eastern Conference Finals, with the Celtics behind them with a 28.17% chance.
The odds for this market, and most other future markets are inflated due to the different number of teams with the possibility of winning. When you actually get to the Eastern Conference Finals, there are only two teams left who can win, so the probability of them winning increases and the odds decrease.
If you are chasing value and want to bet on a futures market, our NBA experts have made their best picks, predictions and analysis for every playoff series, as well as the NBA Finals and NBA Draft, as well as analysing team’s win totals for the regular season.
How do odds work in NBA?
The odds in NBA work appear in an American format. A negative number means that team is the favourite and indicates how much you would have to wager to profit $100, while a positive number means that team is the underdog and shows what you will profit from a $100 wager.
Some of the NBA odds and predictions you’ll find include:
How often do NBA odds change?
With games being played every night during the season and frequent injuries and changes in form, odds change all the time. Sportsbooks update the odds with every new piece of information that comes from the players, teams and media.
It is important to keep up to date with all of the information before you place your bets, and here at SportsTips, we have all of that information for you. As soon as we hear it, we will pass it right along to you, so continue to check in and also keep up to date with our social media pages.
Which team has the best odds to win the Finals?
After winning the 2020 NBA Championship, the Los Angeles Lakers have opened betting for the 2021 title as +350 favourites. They are followed by the Los Angeles Clippers (+450) and the Milwaukee Bucks (+550).
How do you find the best NBA odds today?
At SportsTips, our NBA experts study the form of every team playing, whilst looking at the different markets that sportsbooks provide to come up with the best NBA picks and predictions for all of today’s games.
Who has the best value odds for the NBA?
The answer here varies by each pick. Our team at SportsTips will check all of the sportsbooks, including PointsBet, DraftKings, BetMGM, FanDuel, BetAmerica, and many other high-profile sportsbooks. We will list all the top NBA odds and predictions for these games to help you get the most profit available on the market.


Gene expression values are pulled from
anndata.X. These feed into the histograms, scatterplot, colorscale, and differential expression calculations. We’re working on ways to incorporate
anndata.raw and other
Categorical (e.g., cluster labels) and continuous (e.g., pseudotime) metadata are pulled from
anndata.obs. Any column added here will be available for visualization in cellxgene. You can also create new categorical annotations within the application.
cellxgene looks for embeddings (e.g., tSNE, UMAP, PCA, spatial coordinates) in
anndata.obsm. These fields must follow the scanpy convention of starting with
anndata.obsm['X_umap']. If an embedding has more than two components, the first two will be used for visualization.
We’re actively working on how to improve differential expression within the app. N.B.: the current implementation assumes normally distributed values on a linear scale.
Currently, we use a Welch’s t-test, which assumes that the two populations are each normally distributed, but may have unequal variance. We use a two-sided t-test against the null hypothesis that the two populations have equal means. P-values are adjusted with the Bonferroni corrrection.
To help avoid spurious results, we use the log fold change to filter genes, retaining those where
|log2( mean(set1) / mean(set2) )| > 0.01; this threshold can be configured with the
--diffexp-lfc-cutoff command. We then sort genes by their associated
|t value| and return the top 15 genes.


How to write acceleration
How to Calculate Acceleration: The 3 Formulas You Need Acceleration Calculator | Definition | Formula How to Calculate Acceleration: The 3 Formulas You Need How to Calculate Acceleration: The 3 Formulas You Need Δ t. where Δ v is the change in velocity and Δ t is the change in time. You can also write the acceleration equation like this: a =. v ( f) − v ( i) t ( f) − t ( i) In this acceleration equation, v ( f) is the final velocity while is the v ( i) initial velocity. T ( f) is the final time and t. Formula for Acceleration. There are two formulas for acceleration. The first formula is from Newton’s second law relates force, mass, and acceleration in an equation. Thus, the formula is: F= ma.
Over here: F refers to the force. m is the mass. a is the acceleration You can rearrange this equation with a little algebra to solve for acceleration; just divide both sides by t2 and multiply by 2 to get Great. Plugging in the numbers, you get the following: Okay, the acceleration is approximately 27 meters per second 2. What’s that in more understandable terms? To be specific, acceleration is defined to be the rate of change of the velocity. The above equation says that the acceleration, , is equal to the difference between the initial and final velocities, , divided by the time, , it took for the velocity to change from to . [Really?] 1 a : the act or process of moving faster or happening more quickly : the act or process of accelerating rapid acceleration the acceleration of economic growth. b : ability to accelerate a. The average acceleration ( a) of any object over a given interval of time ( t) can be calculated using the equation This equation can be used to calculate the acceleration of the object whose motion is depicted by the velocity-time data table above. The velocity-time data in the table shows that the object has an acceleration of 10 m/s/s. Velocity Force Displacement Motion Newton's Laws of Motion


After tax cost of debt formula
The cost of debt formula is the before tax cost of debt multiplied by 1 minus the company’s tax rate.
A-T Cd = Cd * (1 – t)
In the cost of debt formula you have two variables that must be inputted in order to solve the after tax cost of debt.
The tax rate can be found on a public company’s annual reports. The best way to find the tax rate that is representative of the company’s future tax rate is by using more than one year of historical data. 5 to 10 years of data should be enough to estimate a company’s future tax rate. Therefore, finding the tax rate of a company is quite simple.
Cost of Debt
However, finding a company’s cost of debt can be more challenging. In theory, there are three ways to find a company’s cost of debt (before tax cost of debt).
Cost of Debt Strategy 1
The first, and usually the most accurate estimate of a company’s before tax cost of debt is it’s average cost of its current outstanding debt. A company’s outstanding debt (bonds issued) will give a strong estimate of a company’s average cost of debt
For example, if Company A has the three following bonds outstanding: Bond A $100M @ 5% interest rate, Bond B $200M @ 7% interest rate and Bond C $200M @ 6% interest rate. In order to calculate the cost of debt for Company A use a weighted average of the outstanding debt. Here is cost of debt of Company A, using the data above: ((100/500) * 5%)+((200/500) * 7%)+((200/500)*6%) = 6.2%. Using this technique, the cost of debt for Company A would be 6.2%.
Cost of Debt Strategy 2
The second way to estimate a company’s cost of debt is by looking at the company’s historical income statements and balance sheet in order to calculate their historical interest payment to debt ratio. This strategy to calculate the cost of debt is acceptable and used widely by students and professional analyst.
Let’s look at an example! Company A has historically paid the following interest (income statement 2017: 300,000, 2016: 200,000, 2015: 250,000, 2014: 100,000, 2013: 180,000. Over the same years, Company A has had the following debt outstanding (long-term debt on balance sheet). 2017: 7M, 2016: 4M, 2015: 5M, 2014: 3M, 2013: 3.5M. Please see the steps to calculate the cost of debt below.
Step 1, calculate the interest rate paid for every year:
2017: 300,000/7,000,000 = 4.28%
2016: 200/4,000 = 5%
2015: 250/5,000 = 5%
2014: 100/3,000 = 3.3%
2013: 180/3,500 = 5.14%
Step 2, calculate the average rate over the 5 years:
Cost of debt = (4.28% + 5% + 5% + 3.3% + 5.14%)/5
Cost of debt = 4.54%
As we can see from the calculation above, the historical interest rate calculation to solve the cost of debt is simple and easy to understand.
Cost of Debt Strategy 3
Finally, the third strategy t that allows us to solve for cost of debt in the after tax cost of debt formula is using a government rate plus corporate debt premium. This strategy uses the current government risk free interest rate and adds a premium for the risk of the company. The rate is then used in the cost of debt formula. For example, if Company A is expected to pay a 3% premium above the current government risk free rate of 3%, their estimated cost of debt is 6% (3% + 3%). This strategy is simple but it is not very accurate since only one data point is being used to solve for the cost of debt.
After Tax Cost of Debt Formula in Action
Now, we know how to find the tax rate and the cost of debt we can use the after tax cost of debt formula to solve for a company’s after tax cost of debt. Once again, the after tax cost of debt formula is:
A-T Cd = Cd * (1 – t)
For example, you find out using the historical interest rate strategy that Company A’s cost of debt is 4.54%. You also know from historical data that there average marginal tax rate over the last 5 years has been 35%. Use this information to calculate the after tax cost of debt of Company A. In this case, A-T Cd = 4.54% * (1-35%), A-T Cd = 2.95%. Therefore, Company A’s after tax cost of debt is 2.95%, which is much lower than the 4.54% before tax cost of debt.
The tax advantage to using debt is immense and very beneficial for a company who is looking to add value and pay the least amount of money possible to its capital providers. This should tell you that most companies should use debt to fund their expansion projects. By paying less to its capital providers the company will be able to add more value to its shareholders and continue to grow at a faster rate. However, we know that debt increases a company’s risk to go bankrupt. For this reason, having too much debt can be very dangerous. Finding the optimal debt to equity ratio (capital structure) of your company is essential. This will be discussed in other pages of this website.
In conclusion, leverage is important for both companies and individuals. Leverage is an optimal way to access cheap capital and expand a growing business. Many successful entrepreneurs and business man have used leverage throughout their career as a way to fund risky projects. Why use your money when you can use someone else’s at a very low cost?


Wavelet(ishape, axes=None, wave_name='db4', level=None)¶
Wavelet transform linear operator.
Currently only has CPU implementation. GPU inputs will be copied to CPU, and back to compute on CPU.
- ishape (tuple of int) – Input shape.
- axes (None or tuple of int) – Axes to perform wavelet transform.
- wave_name (str) – Wavelet name.
- level (None or int) – Number of wavelet levels.
__init__(ishape, axes=None, wave_name='db4', level=None)¶
Initialize self. See help(type(self)) for accurate signature.
__init__(ishape[, axes, wave_name, level])
Apply linear operation on input.
Return adjoint linear operator.
Return normal linear operator.


Note that positions can also be counted from left, in which case the check digit is multiplied by 10, to check validity: It may need to have the value 10, which is represented as the letter X. Which of the following best describes the primary purpose of your visit? Axicon barcode verifiers are used to measure the quality of linear and matrix barcodes, on all levels of product packaging. What is a barcode verifier. Use our check digit calculator below to calculate a check digit. The check digit result is calculated using the information submitted.
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Check Digit Calculator
The check digit is a key control in the accuracy of the GTIN. It consists of one or more digits computed by an algorithm from the other digits or letters in the sequence input.
Other GS1 identifiers also need a check digit to complete them, and this calculator can also provide these for the following GS1 keys. Global Shipment Identification Number.
Access the GS1 General Specifications A very simple check digit method would be to take the sum of all digits digital sum modulo Archived from the original on This section does not cite any sources. Check digit calculator The last digit of a barcode number is a computer check digit which makes sure the barcode is correctly composed.
Check digit calculator > GS1
The last digit is the check digit “7”, and if the other numbers are correct then the check digit cueck must produce 7. The last digit of all fixed-length, numeric GS1 Identification Keys is a check digit that ensures the integrity of the key. In other projects Wikimedia Commons. All GTINs need a check digit, and this is the last digit of the number.
Please help improve this article by adding citations to reliable sources. Were you able to find diggit information you were looking for on our website?
Check Digit Calculation
The digit the farthest to the right which is multiplied by 1 is the check digit, chosen to make the sum correct. This would catch any single-digit error, as such an error would always change the sum, but does not catch any transposition dihit switching two digits as re-ordering does not change the sum.
Check who owns a barcode. Wikimedia Commons has media related to Check digit.
For instance, the UPC-A barcode for a box of tissues is “”. This allows variable length g1 to be used and the length to be changed.
Check digit calculator – Services | GS1
This page was last edited on 20 Septemberat You can know about the owner of a barcode thanks to our tool. What is a barcode verifier.
It is analogous to a binary parity bit used to check for errors in computer-generated data.
In this way the scanner knows it has read all the digits of the number correctly. Note that positions can also be counted from left, in which case the check digit is multiplied by 10, to check validity: Check Digit Calculation The Check Digit is the last, rightmost digit of the number and is based on a mathematical algorithm called the Modulo The complete number is 5 3 9 1 2 3 4 5 6 7 8 9 2 If you are generating many GTINs you may wish to use the online check digit calculator which is available on this website.
Similar is another abstract algebra -based method, the Damm algorithmthat too detects all single-digit errors and all adjacent transposition errors. Please help improve this section by adding citations to reliable sources. The check digit result is calculated using the information submitted. The Axicon barcode verifier is designed to verify large linear barcodes up to mm.
Retrieved from ” https: Its check digit is generated the checck way as the UPC except that the even calculatod are multiplied by 3 instead of the odd digits. This is a 17 digit number.


Sunday, February 1, 2009
International Schools using blogs
Kilmarnock Scotland, local schools have set up a Chinese summer school for one week. The school has set up a website called PiE Chinese Summer School. This interactive website enables students to learn the basics of Chinese language and the Chinese culture. Resources and exercises are put on this blog for the students. Including games, test, podcast, Audio, videos, and much more to help students.Parents and teachers are able to follow the progress of the students as they take this course. This blog site is linked/ organized by the Partners in Excellence, a project in the west of Scotland.
The second international school was a secondary Church School in Malta. The school teamed up with a maths teacher in Poland to make the subject relevant to the everyday life of students. The blog they used was to post students' project on symmetry.Students used camera and took pictures of everyday objects showing symmetry. The blog is from blogger also, so it is very simple to use. Other math teachers even post blogs replying to ideas, and lessons. View it at Mathematics in Everyday Life.


Learn Math with Fun Games: Download Coolmath Games App Now
Download Fun Math Games: How to Make Learning Math Fun and Easy
Do you want to learn math in a fun and easy way? Do you want to improve your math skills without getting bored or frustrated? Do you want to enjoy math as much as you enjoy playing games? If you answered yes to any of these questions, then you should download fun math games!
download fun math games
Fun math games are games that use math as a core element of gameplay. They can help you learn math concepts, practice math skills, train your brain, and have fun at the same time. Whether you are a kid or an adult, a beginner or an expert, a casual or a serious gamer, there is a fun math game for you.
In this article, we will show you how to download fun math games that suit your needs and preferences. We will also give you some tips and tricks on how to play them effectively and enjoyably. By the end of this article, you will be ready to download fun math games and start learning math in a fun and easy way.
Types of Fun Math Games You Can Download
There are many types of fun math games that you can download. Here are some of the most popular ones:
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Puzzle games are games that require you to solve puzzles using logic, reasoning, and problem-solving skills. Some examples of puzzle games that use math are Sudoku, Kakuro, KenKen, and 2048. These games can help you train your logic and problem-solving skills, as well as your arithmetic and algebra skills. They can also challenge your memory and concentration. Puzzle games are great for relaxing and stimulating your mind at the same time.
Arcade games are games that require you to perform fast and accurate actions using your reflexes and mental math skills. Some examples of arcade games that use math are Tetris, Pac-Man, Math Blaster, and Math Invaders. These games can help you improve your reflexes and mental math skills, as well as your spatial awareness and coordination. They can also test your speed and accuracy. Arcade games are great for having fun and getting adrenaline rush at the same time.
Strategy games are games that require you to plan and execute strategies using your planning and decision-making skills. Some examples of strategy games that use math are Chess, Checkers, Risk, and Civilization. These games can help you develop your planning and decision-making skills, as well as your logic and reasoning skills. They can also teach you about history, geography, and culture. Strategy games are great for learning and competing at the same time.
Educational games are games that are designed to teach you math concepts and practice math skills in a fun and interactive way. Some examples of educational games that use math are Math Bingo, Math Playground, Prodigy, and DragonBox. These games can help you learn math concepts and practice math skills, such as addition, subtraction, multiplication, division, fractions, decimals, percentages, geometry, algebra, calculus, and more. They can also provide feedback and rewards to motivate you. Educational games are great for studying and improving at the same time.
Where to Find Fun Math Games to Download
There are many places where you can find fun math games to download. Here are some of the most common ones:
Websites are online platforms where you can browse and download games from reputable sources. Some examples of websites that offer fun math games are Coolmath Games, Math Games, Funbrain, and Hooda Math. These websites have a large collection of fun math games that you can play online or download for free or for a small fee. They also have ratings, reviews, categories, and filters to help you find the best games for you.
Apps are software applications that you can install and play on your mobile devices, such as smartphones and tablets. Some examples of apps that offer fun math games are Math vs Zombies, Math Riddles, King of Math, and Math Master. These apps have a variety of fun math games that you can play offline or online with friends or strangers. They also have features such as levels, achievements, leaderboards, and customization to enhance your gaming experience.
Software is a set of programs that you can download and run on your computer. Some examples of software that offer fun math games are TuxMath, Math Blaster, MathType, and GeoGebra. These software have a range of fun math games that you can play on your desktop or laptop. They also have functions such as tutorials, quizzes, worksheets, graphs, and calculators to support your learning process.
How to Choose Fun Math Games to Download
There are many factors that you should consider when choosing fun math games to download. Here are some of the most important ones:
Age is a factor that determines the suitability of a game for your age group. You should select games that are appropriate for your age group in terms of content, difficulty, language, and graphics. For example, if you are a kid, you should choose games that have simple content, easy difficulty, friendly language, and colorful graphics. If you are an adult, you should choose games that have complex content, challenging difficulty, sophisticated language, and realistic graphics.
Level is a factor that determines the compatibility of a game with your skill level. You should choose games that match your skill level in terms of knowledge, ability, and experience. For example, if you are a beginner, you should choose games that have basic knowledge, easy ability, and low experience requirements. If you are an expert, you should choose games that have advanced knowledge, hard ability, and high experience requirements.
Interest is a factor that determines the attractiveness of a game for your preferences and hobbies. You should choose games that appeal to your preferences and hobbies in terms of theme, genre, style, and features. For example, if you like animals, you should choose games that have animal themes, such as Math vs Zombies or Math Bingo. If you like puzzles, you should choose games that have puzzle genres, such as Sudoku or 2048. If you like cartoons, you should choose games that have cartoon styles, such as Math Blaster or Math Playground. If you like socializing, you should choose games that have social features, such as multiplayer or chat.
Goal is a factor that determines the purpose of a game for your learning objectives. You should choose games that align with your learning objectives in terms of concept, skill, topic, and grade. For example, if you want to learn fractions, you should choose games that teach fractions as a concept, such as DragonBox or MathType. If you want to practice multiplication, you should choose games that practice multiplication as a skill, such as Math Riddles or King of Math. If you want to study geometry, you should choose games that cover geometry as a topic, such as GeoGebra or Math Playground. If you want to improve your grade, you should choose games that correspond to your grade level, such as Prodigy or Math Games.
Tips and Tricks for Playing Fun Math Games
There are some tips and tricks that you can use to play fun math games effectively and enjoyably. Here are some of the most useful ones:
Time is a tip that helps you manage your time and avoid distractions when playing math games. You should set a specific time and duration for playing math games every day or week. You should also limit the number of games and levels that you play in each session. You should also turn o


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Best of John Marchel
Each die (that's singular for dice) in the game of craps has six sides, so there are 36 possible numerical combinations when you throw a pair of dice (6 x 6 = 36). While there is only one combination that results in a 2 (1 and 1) and one that results in a 12 (6 and 6), the number of possible combinations increases as you move forward from 2 or backward from 12 until you reach 7, which has six possible combinations (1 and 6, 2 and 5, 3 and 4, and so on).
Your odds of rolling a particular number in craps are based entirely on the number of possible ways you can roll that specific number. For example, to determine your chances of rolling a 4, divide 36 by 3. (You use 3 because there are only 3 ways to throw a 4.) The result is 12, which means you have a 1 in 12 chance of rolling a 4. This is very important. The odds are 12 to 1 against you, but the house only pays 11 to 1. This is how the casino wins even when you win. Another way to say it is: "When you lose the house wins, when you win the house also wins."
Still, craps is a fun and exciting game. You can be a winner in the short run, but in the end the house will win more often in the long run. So, one good strategy would be to play, win and run.
Bet You Didn't Know
This article is provided by the Frank Scoblete Network. Melissa A. Kaplan is the network's managing editor. If you would like to use this article on your website, please contact Casino City Press, the exclusive web syndication outlet for the Frank Scoblete Network. To contact Frank, please e-mail him at firstname.lastname@example.org.


See the C++ API documentation for the namespace pose_cov_ops.
This module provides implementations for the four main operations between poses (p,p1,p2) and points (a), which are the following (using the "o plus" and "o minus" notation):
p1 ⊕ p2 : Composition of two poses p1 and p2: the resulting pose is p2 "as if" p1 was the new origin of coordinates for p2.
p2 ⊖ p1 : Inverse composition of two poses p1 and p2: the resulting pose is p2 "as seen from" p1.
p ⊕ a : Composition of a pose p and a point a: the resulting point is a "as if" p was the new origin of coordinates of a.
a ⊖ p : Inverse composition of a pose p and a point a: the resulting point is a "as seen from" p.
Is better to illustrate these operations graphically:
Examples of usage
1 #include <mrpt_cov_ops/mrpt_cov_ops.h> 2 3 ... 4 geometry_msgs::PoseWithCovariance p1, p2, p; 5 6 // p = p1 (+) p2 7 // Pose composition, including uncertainty in both p1 and p2: 8 pose_cov_ops::compose(p1,p2, p); 9 10 ... 11 geometry_msgs::Pose p1; 12 geometry_msgs::PoseWithCovariance p2, p; 13 14 // p = p1 (+) p2 15 // Pose composition, including uncertainty only in p2 (and in the output, obviously!): 16 pose_cov_ops::compose(p1,p2, p);
Further references on the geometry and the maths behind these functions:
A tutorial on SE(3) transformation parameterizations and on-manifold optimization, J.L. Blanco, Technical report, 2010 PDF.


Poker statistics you should know
There are 20 Hold'em statistics you should know if you want to improve your game. Each one is remarkably simple but effective - learn more here.
You can become a better poker player by viewing your poker stats on the Internet casino that you are playing on. You can look at your stats in what you have done in real time and it can help you make better decisions when playing poker. Donk Bet - Poker Statistics A guide to using and understanding donk bets in online poker statistics. Blind Stealing - Poker Statistics A guide to using and understanding blind stealing in online poker statistics.
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Mathematics Texas Holdem - 20 Texas Hold'em Poker Odds ... Poker Math and Probability | Pokerology.com Poker Mathematics | Using Math In Poker - Poker Bank Texas Hold'em Poker Mathematics of Texas Hold'em (a modeling project) - Math@TAMU Poker Math of Texas Holdem Poker - YouTube The Reality of Poker Mathematics - YouTube 20 Texas Hold'em Poker Odds & Statistics You Should Know ..
The Paul Phua Poker School chart of common poker odds will dramatically improve your game. Paul Phua gives tips on how they should affect your strategy.
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Poker Mathematics | Using Math In Poker If you have no concrete evidence from the way the hand played out about whether or not your opponent has a better hand than you, you can use mathematics to determine whether or not you should call. Example of using mathematics in poker. First of all you should estimate that probability that your opponent is bluffing and holds a worse hand than you.
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Welcome!! This year I am teaching fifth grade math, and elementary resource. I can't wait to meet all the new fifth graders!--See you in August!
Monday- Lesson 2.2
Tuesday- Lesson 2.5
Wednesday- Lesson 2.6
Thursday- Lesson 2.7
Friday- TEACHER INSERVICE--NO SCHOOL!
Chapter 1 math test will be on September, 13.
Important Upcoming Dates:
Pink Mass: Thursday, October 11
Field Trip to KC Symphony: Tuesday, October 16
Vocation Day: Tuesday, October 23
Science Expo: Thursday, October 25
Scholastic Book Orders:
Please use this link for online orders: orders.scholastic.com/Q7BVH
Class Code: Q7BVH
Feel free to email me at firstname.lastname@example.org with any questions!