Search results “Continuous time in finance”

Views: 4262
Daniel Junior

MIT 18.S096 Topics in Mathematics with Applications in Finance, Fall 2013
View the complete course: http://ocw.mit.edu/18-S096F13
Instructor: Choongbum Lee
This lecture covers stochastic processes, including continuous-time stochastic processes and standard Brownian motion.
License: Creative Commons BY-NC-SA
More information at http://ocw.mit.edu/terms
More courses at http://ocw.mit.edu

Views: 102994
MIT OpenCourseWare

Views: 16
Francis Forster

Visit http://ilectureonline.com for more math and science lectures!
In this video I will find the accumulated amount of a $2000 investment compounded continuously.
Next video in this series can be seen at:
http://youtu.be/jztNjV3vo4o

Views: 24269
Michel van Biezen

Learn about the basics of compound interest, with examples of basic compound interest calculations. Created by Sal Khan.
Watch the next lesson: https://www.khanacademy.org/economics-finance-domain/core-finance/interest-tutorial/compound-interest-tutorial/v/the-rule-of-72-for-compound-interest?utm_source=YT&utm_medium=Desc&utm_campaign=financeandcapitalmarkets
Finance and capital markets on Khan Academy: Interest is the basis of modern capital markets. Depending on whether you are lending or borrowing, it can be viewed as a return on an asset (lending) or the cost of capital (borrowing). This tutorial gives an introduction to this fundamental concept, including what it means to compound. It also gives a rule of thumb that might make it easy to do some rough interest calculations in your head.
About Khan Academy: Khan Academy offers practice exercises, instructional videos, and a personalized learning dashboard that empower learners to study at their own pace in and outside of the classroom. We tackle math, science, computer programming, history, art history, economics, and more. Our math missions guide learners from kindergarten to calculus using state-of-the-art, adaptive technology that identifies strengths and learning gaps. We've also partnered with institutions like NASA, The Museum of Modern Art, The California Academy of Sciences, and MIT to offer specialized content.
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Views: 979055
Khan Academy

In this video, I show how to solve an infinite horizon constrained optimization problem in continuous time. I also show how the Hamiltonian approach works and why the first order condition are equal to what they are equal to. This allows viewers to solve more complicated problems as well.

Views: 5725
Constantin Bürgi

Views: 18
Sarah Laroche

Views: 19
Tori Harrison

Using log continuous growth rates with time-series financial data.

Views: 362
ProfGREvans

Stopping time, hitting time and other times.

Views: 11354
stepbil

Views: 23993
Probability and Stochastics for finance

MIT 18.S096 Topics in Mathematics with Applications in Finance, Fall 2013
View the complete course: http://ocw.mit.edu/18-S096F13
Instructor: Choongbum Lee
*NOTE: Lecture 4 was not recorded.
This lecture introduces stochastic processes, including random walks and Markov chains.
License: Creative Commons BY-NC-SA
More information at http://ocw.mit.edu/terms
More courses at http://ocw.mit.edu

Views: 261529
MIT OpenCourseWare

Financial Markets (2011) (ECON 252)
After introducing the core terms and main ideas of options in the beginning of the lecture, Professor Shiller emphasizes two purposes of options, a theoretical and a behavioral purpose. Subsequently, he provides a graphical representation for the value of a call and a put option, and, in this context, addresses the put-call parity for European options. Within the framework of the Binomial Asset Pricing model, he derives the value of a call-option from the no-arbitrage-principle, and, as a continuous-time analogue to this formula, he presents the Black-Scholes Option Pricing formula. He contrasts implied volatility, as represented by the VIX index of the Chicago Board Options Exchange, which uses a different formula in the spirit of Black-Scholes, with the actual S&P Composite volatility from 1986 until 2010. Professor Shiller concludes the lecture with some thoughts about options on single-family homes that he launched with his colleagues of the Chicago Mercantile Exchange in 2006.
00:00 - Chapter 1. Examples of Options Markets and Core Terms
07:11 - Chapter 2. Purposes of Option Contracts
17:11 - Chapter 3. Quoted Prices of Options and the Role of Derivatives Markets
24:54 - Chapter 4. Call and Put Options and the Put-Call Parity
34:56 - Chapter 5. Boundaries on the Price of a Call Option
39:07 - Chapter 6. Pricing Options with the Binomial Asset Pricing Model
51:02 - Chapter 7. The Black-Scholes Option Pricing Formula
55:49 - Chapter 8. Implied Volatility - The VIX Index in Comparison to Actual Market Volatility
01:09:33 - Chapter 9. The Potential for Options in the Housing Market
Complete course materials are available at the Yale Online website: online.yale.edu
This course was recorded in Spring 2011.

Views: 122153
YaleCourses

Playlist for problems on valuation of annuities: https://www.youtube.com/watch?v=nKtowv5gZwE&list=PLmU0FIlJY-MnsjhWSCBsXQit9lN8_x1cj

Views: 5875
Bill Kinney

This is a quick tutorial on how to use HP 10bII+. The tutorial covers how to calculate: future value, present value, annuity, and net present value (NPV).
You can find web-based practice problems at http://tinyurl.com/hp10biiplus.
I recorded this faceless tutorial as a Teaching Assistant for ACC 312 (Fundamentals of Managerial Accounting) in Spring 2014.

Views: 140432
Daehyun Kim

Finance and accounting leaders are expected to deliver accurate and real time analysis of their organization’s financial performance at all times. Yet many still wrestle with decades-old accounting processes that can only provide a view into the past, where the organization was, not where it is now. Continuous Accounting is a modern approach that empowers real time financial intelligence and allows finance and accounting teams to provide unprecedented value to the larger business.

Views: 4504
BlackLine

Learn about the time to double when compounding continuously in this free math video tutorial by Mario's Math Tutoring.
0:12 Formula for Compounding Continuously
0:41 Example 1 Finding the Time to Double When Compounding Continuously
1:32 Using Natural Logs to Solve For t
Related Videos:
Time to Triple Compounding Continuously
https://youtu.be/VFkHNsjyZys
Compounding Continuously Pert Formula
https://youtu.be/dFsBfi9W7sQ
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For online 1-to-1 tutoring or more information about me see my website at:
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* Organized List of My Video Lessons to Help You Raise Your Scores & Pass Your Class. Videos Arranged by Math Subject as well as by Chapter/Topic. (Bookmark the Link Below)
http://www.mariosmathtutoring.com/free-math-videos.html

Views: 6232
Mario's Math Tutoring

http://lapasserelle.com/finance in practice time is a continous variable. We show the formula for continuously compounded interests. However, for the sake of simplicity of explanations, in elementary finance time is treated as a discrete variable progressing in steps of one year.

Views: 129
andyfrc08

In Chapter 3 I learned how to model asset prices using normal returns, both for discrete time and for continuous time using a Wiener process. The first stochastic differential equation!

Views: 51301
Nathan Whitehead

Free Online Textbook @ https://businessfinanceessentials.pressbooks.com/
This video introduces the HP10BII and walks through multiple examples of using the 5-key approach to solving basic Time Value of Money Examples. Includes changing periods per year, beginning vs. end of period payments, changing decimals displayed, solving for FV, PMT and rate of return.

Views: 221371
Kevin Bracker

option valuation, option-pricing model, Black-Scholes Model, Black-Scholes-Merton Model, Robert Brown, Brownian Motion, random walk, stochastics, stochastic process, Bachelier, probability theory, stochasticv theory, Kiyoshi Ito, Ito Calculus, Stochastic Calculus, Continuous Time Finance, Robert Merton, Black-Scholes Value, tick, uptick., downtick, price jump, lognormal distribution, model assumptions, transaction costs,

Views: 1573
Krassimir Petrov

Educational video for all :)
Credits to:
My teammates
-Aiman
-Ihsan
-Naja
-Hamizah
CS112 3C
and everyone who made this video a success!

Views: 260
Mohamad Aiman

Financial Mathematics 3.0 - Brownian Motion (Wiener process) applied to Finance

Views: 100663
profbillbyrne

What is MATHEMATICAL FINANCE? What does MATHEMATICAL FINANCE mean? MATHEMATICAL FINANCE meaning - MATHEMATICAL FINANCE definition - MATHEMATICAL FINANCE explanation.
Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license.
Mathematical finance, also known as quantitative finance, is a field of applied mathematics, concerned with financial markets. Generally, mathematical finance will derive and extend the mathematical or numerical models without necessarily establishing a link to financial theory, taking observed market prices as input. Mathematical consistency is required, not compatibility with economic theory. Thus, for example, while a financial economist might study the structural reasons why a company may have a certain share price, a financial mathematician may take the share price as a given, and attempt to use stochastic calculus to obtain the corresponding value of derivatives of the stock (see: Valuation of options; Financial modeling). The fundamental theorem of arbitrage-free pricing is one of the key theorems in mathematical finance, while the Black–Scholes equation and formula are amongst the key results.
Mathematical finance also overlaps heavily with the fields of computational finance and financial engineering. The latter focuses on applications and modeling, often by help of stochastic asset models (see: Quantitative analyst), while the former focuses, in addition to analysis, on building tools of implementation for the models. In general, there exist two separate branches of finance that require advanced quantitative techniques: derivatives pricing on the one hand, and risk- and portfolio management on the other.
There exist two separate branches of finance that require advanced quantitative techniques: derivatives pricing, and risk and portfolio management. One of the main differences is that they use different probabilities, namely the risk-neutral probability (or arbitrage-pricing probability), denoted by "Q", and the actual (or actuarial) probability, denoted by "P".
Derivatives pricing: the Q world:
The goal of derivatives pricing is to determine the fair price of a given security in terms of more liquid securities whose price is determined by the law of supply and demand. The meaning of "fair" depends, of course, on whether one considers buying or selling the security. Examples of securities being priced are plain vanilla and exotic options, convertible bonds, etc.
Once a fair price has been determined, the sell-side trader can make a market on the security. Therefore, derivatives pricing is a complex "extrapolation" exercise to define the current market value of a security, which is then used by the sell-side community. Quantitative derivatives pricing was initiated by Louis Bachelier in The Theory of Speculation (published 1900), with the introduction of the most basic and most influential of processes, the Brownian motion, and its applications to the pricing of options. Bachelier modeled the time series of changes in the logarithm of stock prices as a random walk in which the short-term changes had a finite variance. This causes longer-term changes to follow a Gaussian distribution.
The theory remained dormant until Fischer Black and Myron Scholes, along with fundamental contributions by Robert C. Merton, applied the second most influential process, the geometric Brownian motion, to option pricing. For this M. Scholes and R. Merton were awarded the 1997 Nobel Memorial Prize in Economic Sciences. Black was ineligible for the prize because of his death in 1995.
A process satisfying (1) is called a "martingale". A martingale does not reward risk. Thus the probability of the normalized security price process is called "risk-neutral" and is typically denoted by the blackboard font letter " Q {\displaystyle \mathbb {Q} } \mathbb {Q} ".
The relationship (1) must hold for all times t: therefore the processes used for derivatives pricing are naturally set in continuous time.
The quants who operate in the Q world of derivatives pricing are specialists with deep knowledge of the specific products they model.
Securities are priced individually, and thus the problems in the Q world are low-dimensional in nature. Calibration is one of the main challenges of the Q world: once a continuous-time parametric process has been calibrated to a set of traded securities through a relationship such as (1), a similar relationship is used to define the price of new derivatives.
The main quantitative tools necessary to handle continuous-time Q-processes are Ito’s stochastic calculus and partial differential equations (PDE’s).

Views: 1493
The Audiopedia

Homework assignment tutorial from Pyzdek Institute Six Sigma Black Belt Training.

Views: 18454
ThomasPyzdek

Continuous Accounting embeds automation, control, and period-end tasks within day-to-day activities, allowing the rigid accounting calendar to more closely mirror the broader business. Continuous Accounting transforms the way business process works by emphasizing real-time processing, especially skilled employees, and deep analysis. The result is a more efficient close, more accurate financials, and a more effective organization.

Views: 1338
BlackLine

One of the best habits that you can develop is the habit of continuous learning. The most successful people including Bill Gates and Warren Buffett all praise the importance of reading. Today, I give you my 3 favorite books for personal and financial success. http://bit.ly/2EqflqR
Also, if you'd like to enter my free giveaway, click the link above!
“We live in the richest society in all of human history; are you getting your fair share?” @BrianTracy (Click to Tweet: https://ctt.ec/5cwfQ)
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Views: 275311
Brian Tracy

This introductory video covers what wavelets are and how you can use them to explore your data in MATLAB®.
•Try Wavelet Toolbox: https://goo.gl/m0ms9d
•Ready to Buy: https://goo.gl/sMfoDr
The video focuses on two important wavelet transform concepts: scaling and shifting. The concepts can be applied to 2D data such as images.
Video Transcript:
Hello, everyone. In this introductory session, I will cover some basic wavelet concepts. I will be primarily using a 1-D example, but the same concepts can be applied to images, as well. First, let's review what a wavelet is. Real world data or signals frequently exhibit slowly changing trends or oscillations punctuated with transients. On the other hand, images have smooth regions interrupted by edges or abrupt changes in contrast. These abrupt changes are often the most interesting parts of the data, both perceptually and in terms of the information they provide. The Fourier transform is a powerful tool for data analysis. However, it does not represent abrupt changes efficiently.
The reason for this is that the Fourier transform represents data as sum of sine waves, which are not localized in time or space. These sine waves oscillate forever. Therefore, to accurately analyze signals and images that have abrupt changes, we need to use a new class of functions that are well localized in time and frequency: This brings us to the topic of Wavelets. A wavelet is a rapidly decaying, wave-like oscillation that has zero mean. Unlike sinusoids, which extend to infinity, a wavelet exists for a finite duration. Wavelets come in different sizes and shapes. Here are some of the well-known ones. The availability of a wide range of wavelets is a key strength of wavelet analysis.
To choose the right wavelet, you'll need to consider the application you'll use it for. We will discuss this in more detail in a subsequent session. For now, let's focus on two important wavelet transform concepts: scaling and shifting. Let' start with scaling. Say you have a signal PSI(t). Scaling refers to the process of stretching or shrinking the signal in time, which can be expressed using this equation [on screen]. S is the scaling factor, which is a positive value and corresponds to how much a signal is scaled in time. The scale factor is inversely proportional to frequency. For example, scaling a sine wave by 2 results in reducing its original frequency by half or by an octave. For a wavelet, there is a reciprocal relationship between scale and frequency with a constant of proportionality. This constant of proportionality is called the "center frequency" of the wavelet. This is because, unlike the sinewave, the wavelet has a band pass characteristic in the frequency domain. Mathematically, the equivalent frequency is defined using this equation [on screen], where Cf is center frequency of the wavelet, s is the wavelet scale, and delta t is the sampling interval. Therefore when you scale a wavelet by a factor of 2, it results in reducing the equivalent frequency by an octave.
For instance, here is how a sym4 wavelet with center frequency 0.71 Hz corresponds to a sine wave of same frequency. A larger scale factor results in a stretched wavelet, which corresponds to a lower frequency. A smaller scale factor results in a shrunken wavelet, which corresponds to a high frequency. A stretched wavelet helps in capturing the slowly varying changes in a signal while a compressed wavelet helps in capturing abrupt changes.
You can construct different scales that inversely correspond the equivalent frequencies, as mentioned earlier. Next, we'll discuss shifting. Shifting a wavelet simply means delaying or advancing the onset of the wavelet along the length of the signal. A shifted wavelet represented using this notation [on screen] means that the wavelet is shifted and centered at k. We need to shift the wavelet to align with the feature we are looking for in a signal.The two major transforms in wavelet analysis are Continuous and Discrete Wavelet Transforms. These transforms differ based on how the wavelets are scaled and shifted. More on this in the next session. But for now, you've got the basic concepts behind wavelets.

Views: 183140
MATLAB

Attract Abundance of Money Prosperity Luck & Wealth★Jupiter's Spin Frequency★Theta Binaural Beats by Binaural Beats Meditation (Good Vibes)
Listen in a low volume but clearly audible.
Having a mindset of gratitude will make you happier, healthier, more satisfied, you'll attract abundance and magnetize better experiences.
Listen before sleep for 4 weeks-90 days.
Headphones required.
Affirmations:
I feel Rich
I love money. Money loves me.
I attract money now
I am very happy & grateful that money comes to me in increasing quantities from many sources on a continuous basis
I am receiving money now
I have more than enough money
I am willing, ready and able to receive money
I see abundance everywhere
I am a money magnet
I am grateful for what I already have and for all that I receive now.
I have more than what I need
Money now comes to me from unexpected sources & I am grateful
My income is growing higher and higher
I am a rich child of a loving universe
I have the power to attract money
I receive money happily now
Money flows to me easily
I am sensible with money and manage it wisely.
I allow my income to constantly expand and I always live in comfort and joy.
© Good Vibes all rights reserved.

Views: 8355872
Good Vibes - Binaural Beats

Two ways to look at this: start with a given rate (10% in this example) and use different compound frequencies, which gives different final (terminal values). Or, assume the same terminal value, and translate into different discrete interest rates (e.g., monthly, daily). But, the discrete rates can be translated to continuous and vice-versa.

Views: 7700
Bionic Turtle

Connection issues windows 8

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Backtrack for windows phone 8

© 2019 How to start mobile phone business

Divide and Conquer. This is another area that is very industry-dependent, but it is highly unlikely that any company can afford to have an entire contract team devoted to managing one portfolio. More than likely, it is more realistic to divvy up the team and the contracts so that there is a leader for each relevant sphere. The entire team will obviously have to coordinate and communicate, but resources must be allocated in the most efficient manner possible. In turn, this will allow for several individuals to keep an eye on a smaller batch of contracts, thereby facilitating those periodic reviews. Outsource the Tedium to Technology.