The bias ratio is an indicator used in finance to analyze the returns of investment portfolios, and in performing due diligence. The bias ratio is a concrete metric that detects valuation bias or deliberate price manipulation of portfolio assets by a manager of a hedge fund, mutual fund or similar investment vehicle, without requiring disclosure (transparency) of the actual holdings. This metric measures abnormalities in the distribution of returns that indicate the presence of bias in subjective pricing. The formulation of the Bias Ratio stems from an insight into the behavior of asset managers as they address the expectations of investors with the valuation of assets that determine their performance. The bias ratio measures how far the returns from an investment portfolio – e.g. one managed by a hedge fund – are from an unbiased distribution. Thus the bias ratio of a pure equity index will usually be close to 1. However, if a fund smooths its returns using subjective pricing of illiquid assets the bias ratio will be higher. As such, it can help identify the presence of illiquid securities where they are not expected. The bias ratio was first defined by Adil Abdulali, a risk manager at the investment firm Protégé Partners. The concepts behind the bias ratio were formulated between 2001 and 2003 and privately used to screen money managers. The first public discussions on the subject took place in 2004 at New York University's Courant Institute and in 2006 at Columbia University. The bias ratio has since been used by a number of Risk Management professionals to spot suspicious funds that subsequently turned out to be frauds. The most spectacular example of this was reported in the Financial Times on 22 January 2009 titled "Bias ratio seen to unmask Madoff"! (Wikipedia).
This video defines a ratio and provides several examples on how to write a ratio and shows how to simplify a ratio. http://mathispower4u.wordpress.com/
From playlist Ratios and Rates
Bias Variance Tradeoff Explained!
What is Bias? What is the tradeoff between bias and variance? These questions and more answered today! ABOUT ME ⭕ Subscribe: https://www.youtube.com/c/CodeEmporium?sub_confirmation=1 📚 Medium Blog: https://medium.com/@dataemporium 💻 Github: https://github.com/ajhalthor 👔 LinkedIn: https:/
From playlist The Math You Should Know
What is an angle and it's parts
👉 Learn how to define angle relationships. Knowledge of the relationships between angles can help in determining the value of a given angle. The various angle relationships include: vertical angles, adjacent angles, complementary angles, supplementary angles, linear pairs, etc. Vertical a
From playlist Angle Relationships
Statistics Lesson #4: Sources of Bias
This video is for my College Algebra and Statistics students (and anyone else who may find it helpful). I define bias, and we look at examples of different types of bias, including voluntary response bias, leading question bias, and sampling bias. I hope this is helpful! Timestamps: 0:00
From playlist Statistics
BIAS In Statistics | What Is BIAS? | BIAS Explained | Statistics Tutorial | Simplilearn
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From playlist Data Structures & Algorithms [2022 Updated]
This video introduces the Golden ratio and provides several examples of where the Golden ratio appears. http:mathispower4u.com
From playlist Mathematics General Interest
Solving Percent Problems Using The Percent Proportion
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From playlist The Percent Proportion
CCSS What are supplementary and complementary angles
👉 Learn how to define angle relationships. Knowledge of the relationships between angles can help in determining the value of a given angle. The various angle relationships include: vertical angles, adjacent angles, complementary angles, supplementary angles, linear pairs, etc. Vertical a
From playlist Angle Relationships
Time invariance of total stellar mass-cluster mass relation by Yen-Ting Lin
Program Cosmology - The Next Decade ORGANIZERS : Rishi Khatri, Subha Majumdar and Aseem Paranjape DATE : 03 January 2019 to 25 January 2019 VENUE : Ramanujan Lecture Hall, ICTS Bangalore The great observational progress in cosmology has revealed some very intriguing puzzles, the most i
From playlist Cosmology - The Next Decade
Fellow Short Talks: Dr Ioannis Kosmidis, UCL
Bio Ioannis Kosmidis is a Senior Lecturer at the Department of Statistical Science in University College London. Having obtained a BSc in Statistics at the Athens University of Economics and Business in 2004, he was then awarded his PhD in Statistics in 2007 at University of Warwick with
From playlist Short Talks
👉 Learn how to define angle relationships. Knowledge of the relationships between angles can help in determining the value of a given angle. The various angle relationships include: vertical angles, adjacent angles, complementary angles, supplementary angles, linear pairs, etc. Vertical a
From playlist Angle Relationships
Case Studies with Data: Mitigating Gender Bias on the UCI Adult Dataset
MIT RES.EC-001 Exploring Fairness in Machine Learning, Spring 2020 Instructor: Audace Nakeshimana View the complete course: https://ocw.mit.edu/RES-EC-001S20 YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP63IFQn8FklBOUhYVcmaxpOX This video explores principles involved
From playlist MIT RES.EC-001 Exploring Fairness in Machine Learning, Spring 2020
Public Health Seminar. Structural Considerations in Social Epidemiologic Analysis.
Recorded October 11, 2013. Jay Kaufman, Ph.D.
From playlist Public Health: Graduate Seminars (2013 - 2015)
Voltage Controlled Capacitors - Varactor Diodes
This electronics video tutorial provides a basic introduction into varactor diodes also known as varicaps which can behave as voltage controlled capacitors. The junction capacitance of the diode is inversely related to the reverse voltage applied to it. Varactor diodes are very useful in
From playlist Electronic Circuits
Galaxy Clusters (Lecture 3) by Stefano Borgani
Program Cosmology - The Next Decade ORGANIZERS : Rishi Khatri, Subha Majumdar and Aseem Paranjape DATE : 03 January 2019 to 25 January 2019 VENUE : Ramanujan Lecture Hall, ICTS Bangalore The great observational progress in cosmology has revealed some very intriguing puzzles, the most i
From playlist Cosmology - The Next Decade
Introduction to Population Genetics III: Revisiting Assumptions by Deepa Agashe (NCBS, India)
PROGRAM FIFTH BANGALORE SCHOOL ON POPULATION GENETICS AND EVOLUTION (ONLINE) ORGANIZERS: Deepa Agashe (NCBS, India) and Kavita Jain (JNCASR, India) DATE: 17 January 2022 to 28 January 2022 VENUE: Online No living organism escapes evolutionary change, and evolutionary biology thus conn
From playlist Fifth Bangalore School on Population Genetics and Evolution (ONLINE) 2022
6. Charge Separation, Part II: Diode Under Illumination
MIT 2.627 Fundamentals of Photovoltaics, Fall 2011 View the complete course: http://ocw.mit.edu/2-627F11 Instructor: Tonio Buonassisi This lecture begins with the current-voltage (IV) response of a pn-junction, under varied illumination & bias conditions. IV curves lead to solar conversio
From playlist MIT 2.627 Fundamentals of Photovoltaics, Fall 2011
Naive Bayes Classifier in Python | Naive Bayes Algorithm | Machine Learning Algorithm | Edureka
** Machine Learning Training with Python: https://www.edureka.co/data-science-python-certification-course ** This Edureka video will provide you with a detailed and comprehensive knowledge of Naive Bayes Classifier Algorithm in python. At the end of the video, you will learn from a demo ex
From playlist Machine Learning Algorithms in Python (With Demo) | Edureka
Elisabeth Gassiat: Bayesian multiple testting for dependent data and hidden Markov... - lecture 1
HYBRID EVENT Recorded during the meeting "End-to-end Bayesian Learning Methods " the October 26, 2021 by the Centre International de Rencontres Mathématiques (Marseille, France) Filmmaker: Guillaume Hennenfent Find this video and other talks given by worldwide mathematicians on CIRM's
From playlist Probability and Statistics
This lesson reviews sources of bias when conducting a survey or poll. Site: http://mathispower4u.com
From playlist Introduction to Statistics