In finance, tracking error or active risk is a measure of the risk in an investment portfolio that is due to active management decisions made by the portfolio manager; it indicates how closely a portfolio follows the index to which it is benchmarked. The best measure is the standard deviation of the difference between the portfolio and index returns. Many portfolios are managed to a benchmark, typically an index. Some portfolios are expected to replicate, before trading and other costs, the returns of an index exactly (e.g., an index fund), while others are expected to 'actively manage' the portfolio by deviating slightly from the index in order to generate active returns. Tracking error is a measure of the deviation from the benchmark; the aforementioned index fund would have a tracking error close to zero, while an actively managed portfolio would normally have a higher tracking error. Thus the tracking error does not include any risk (return) that is merely a function of the market's movement. In addition to risk (return) from specific stock selection or industry and factor "betas", it can also include risk (return) from market timing decisions. Dividing portfolio active return by portfolio tracking error gives the information ratio, which is a risk adjusted performance measure. (Wikipedia).
GCSE Science Revision "Systematic Errors"
In this video, we look at systematic errors. First we explore what is meant by a systematic error. We then look at what can cause a systematic error, including a zero error. Image Credits Thermometer https://commons.wikimedia.org/wiki/File:Laboratory_thermometer-03.jpg Lilly_M, CC BY-SA
From playlist GCSE Working Scientifically
Comparison of systematic and random error. Types of systematic error, including offset error and scale factor error/
From playlist Experimental Design
Tracking error (TE) is the standard deviation of the difference between portfolio returns and benchmark returns. The review ex ante and ex post TE and (briefly) TE VaR. For more financial risk videos, visit our website! http://www.bionicturtle.com
From playlist Performance measures
This is how Google is spying on everything you do
Google is spying on everything you. Literally everything. If you are not protecting yourself, Google is after your personal life whether you like it or it. Google spies on you and it's not just a conspiracy theory anymore. Google’s presence is literally everywhere and it wants to play go
From playlist Decrypted Lies
How To Identify Type I and Type II Errors In Statistics
This statistics video tutorial provides a basic introduction into Type I errors and Type II errors. A type I error occurs when a true null hypothesis is rejected. A type II error occurs when a false null hypothesis is not rejected. This video contains a few examples and practice problem
From playlist Statistics
What Are Error Intervals? GCSE Maths Revision
What are error Intervals and how do we find them - that's the mission in this episode of GCSE Maths minis! Error Intervals appear on both foundation and higher tier GCSE maths and IGCSE maths exam papers, so this is excellent revision for everyone! DOWNLOAD THE QUESTIONS HERE: https://d
From playlist Error Intervals & Bounds GCSE Maths Revision
Statistics: Ch 7 Sample Variability (11 of 14) What is "The Standard Error of the Mean"?
Visit http://ilectureonline.com for more math and science lectures! To donate: http://www.ilectureonline.com/donate https://www.patreon.com/user?u=3236071 What is “the standard error of the mean”? It is the standard deviation (of the sampling distribution) of the sample means. Previous
From playlist STATISTICS CH 7 SAMPLE VARIABILILTY
Vlog: CIC News 28-2-2012: Hidden browser flaw threatens iOS Android
Hidden browser flaw threatens iOS, Android: http://on.msnbc.com/recart_280212
From playlist Vlogs
Anomaly Detection for JavaScript Apps
Watch this video to learn about the anomaly detection tools which will enable you to monitor and detect abnormalities in your JavaScript apps. PUBLICATION PERMISSIONS: Original video was published with the Creative Commons Attribution license (reuse allowed). Link: https://www.youtube.com
From playlist JavaScript
Metrics for System Assessment | Autonomous Navigation, Part 6
See the other videos in this series: https://www.youtube.com/playlist?list=PLn8PRpmsu08rLRGrnF-S6TyGrmcA2X7kg Now that you understand the overall system, see how you can use the different kinds of metrics to characterize the autonomous navigation system. Take a systems engineering approa
From playlist Autonomous Navigation
Control Bootcamp: Cruise Control Example with Proportional-Integral (PI) control
In this video, we show that introducing integral control reduces the steady-state tracking error to zero in the cruise control example. We also use a more sophisticated model for the automobile. Code available at: faculty.washington.edu/sbrunton/control_bootcamp_code.zip These lecture
From playlist Control Bootcamp
Sylvia Herbert: "Scalability for Hamilton-Jacobi Reachability Analysis: Decomposition, Warm-Star..."
High Dimensional Hamilton-Jacobi PDEs 2020 Workshop I: High Dimensional Hamilton-Jacobi Methods in Control and Differential Games "Scalability for Hamilton-Jacobi Reachability Analysis: Decomposition, Warm-Start Initialization, and Model Reduction" Sylvia Herbert - University of Californi
From playlist High Dimensional Hamilton-Jacobi PDEs 2020
Special Topics - The Kalman Filter (7 of 55) The Multi-Dimension Model 1
Visit http://ilectureonline.com for more math and science lectures! In this video I will explain the overview of the Kalman filter on a multi dimension model. Next video in this series can be seen at: https://youtu.be/F7vQXNro7pE
From playlist SPECIAL TOPICS 1 - THE KALMAN FILTER
GUIDE: Gaze-Enhanced User Interface Design
April 13, 2007 lecture by Manu Kumar for the Stanford University Human-Computer Interaction Seminar (CS 547). A series of novel prototypes that explore the use of gaze and an augmented input to perform everyday computing tasks are presented. In particular, the use of gaze-based input for
From playlist Course | Human-Computer Interaction Seminar (2006-2007)
Claire Tomlin: "Towards Real-Time Reachability (Part 2/2)"
Watch part 1/2 here: https://youtu.be/f_BTMott6NY High Dimensional Hamilton-Jacobi PDEs Tutorials 2020 "Towards Real-Time Reachability (Part 2)" Claire Tomlin - University of California, Berkeley Institute for Pure and Applied Mathematics, UCLA March 10, 2020 For more information: http
From playlist High Dimensional Hamilton-Jacobi PDEs 2020
At-Home Physics Labs with Mathematica and Your Phone
COVID-19 and social distancing requirements make in-person physics labs difficult, if not impossible. I will describe my efforts to provide "at-home" labs for our second-year physics majors using Mathematica, smartphones and cheap kits that we have shipped to our students. Mathem
From playlist Wolfram Technology Conference 2020
🔥Learn The MERN Stack Full Tutorial 2022 | MERN Stack MongoDB, Express, React, Node.js | Simplilearn
🔥Post Graduate Program In Full Stack Web Development: https://www.simplilearn.com/pgp-full-stack-web-development-certification-training-course?utm_campaign=MERNStackFC11Mar23&utm_medium=Descriptionff&utm_source=youtube 🔥Caltech Coding Bootcamp (US Only): https://www.simplilearn.com/coding
From playlist Simplilearn Live
Yes. I make mistakes ... rarely. http://www.flippingphysics.com
From playlist Miscellaneous
Towards a multi-satellite radiance assimilation in regional models - Chakravarthy Balaji
PROGRAM: Data Assimilation Research Program Venue: Centre for Applicable Mathematics-TIFR and Indian Institute of Science Dates: 04 - 23 July, 2011 DESCRIPTION: Data assimilation (DA) is a powerful and versatile method for combining observational data of a system with its dynamical mod
From playlist Data Assimilation Research Program