Kiplinger"s Personal Finance - August 2016

Kiplinger’s Personal Finance – August 2016
English | 76 pages | True PDF | 31 MB

Coursera - Mathematical Methods for Quantitative Finance by Dr. Kjell Konis (2016)

Coursera – Mathematical Methods for Quantitative Finance
WEBRip | English | MP4 | 960 x 540 | AVC ~63.8 kbps | 25 fps
AAC | 128 Kbps | 48.0 KHz | 2 channels | ~8 hours | 5.98 GB
Genre: eLearning Video / Maths, Economics & Finance

Mathematical Methods for Quantitative Finance covers topics from calculus and linear algebra that are fundamental for the study of mathematical finance. Students successfully completing this course will be mathematically well prepared to study quantitative finance at the graduate level.

The Mathematical Methods for Quantitative Finance course reviews the mathematical methods fundamental for the study of quantitative and computational finance. The areas of focus include calculus and multivariable calculus, constrained and unconstrained optimization, and linear algebra.

Topics covered include the following:

Functions and inverse functions

Limits, derivatives, partial derivatives, and chain rule

Integrals and multiple integrals, changing the order of differentiation and integration

Taylor series approximations

Newton’s method

Lagrange multiplier method

Vector and matrix arithmetic, determinants, eigenvalue-eigenvector decomposition, singular value decomposition

Numerical methods for optimization

Course goal:

Upon completion of the course students will know the fundamental mathematical concepts needed to effectively study quantitative finance areas such as fixed income, options and derivatives, portfolio optimization, and quantitative risk management.

Course Objectives: Upon completion of the course students will:

Understand the concept of a limit, differentiation, and integration;

Be able to compute partial derivatives and multiple integrals;

Understand the utility of matrix decompositions;

Be able to use Lagrange multipliers to solve constrained optimization problems; and

Apply the above methods to problems arising in finance.

also You can watch my other last: Coursera-posts

General
Complete name : Mathematical Methods for Quantitative Finance 8.1 W7.1.1 – Optimal Investment Portfolios (1732).mp4
Format : MPEG-4
Format profile : Base Media
Codec ID : isom
File size : 24.8 MiB
Duration : 17mn 32s
Overall bit rate mode : Variable
Overall bit rate : 198 Kbps
Movie name : MMfQF_W7_P1_Kjell_OptimalInvestmentPortfolios_FINAL
Composer : Jon Keib
Writing application : Lavf52.99.1
desc : This video is about MMfQF_W7_P1_Kjell_OptimalInvestmentPortfolios

Video
ID : 1
Format : AVC
Format/Info : Advanced Video Codec
Format profile : High@L3.0
Format settings, CABAC : Yes
Format settings, ReFrames : 4 frames
Codec ID : avc1
Codec ID/Info : Advanced Video Coding
Duration : 17mn 32s
Bit rate : 63.8 Kbps
Width : 960 pixels
Height : 540 pixels
Display aspect ratio : 16:9
Frame rate mode : Constant
Frame rate : 25.000 fps
Color space : YUV
Chroma subsampling : 4:2:0
Bit depth : 8 bits
Scan type : Progressive
Bits/(Pixel*Frame) : 0.005
Stream size : 8.00 MiB (32%)
Writing library : x264 core 114 r1913 5fd3dce
Encoding settings : cabac=1 / ref=1 / deblock=1:0:0 / analyse=0x3:0x113 / me=hex / subme=2 / psy=1 / psy_rd=0.00:0.00 / mixed_ref=0 / me_range=16 / chroma_me=1 / trellis=0 / 8x8dct=1 / cqm=0 / deadzone=21,11 / fast_pskip=1 / chroma_qp_offset=0 / threads=3 / sliced_threads=0 / nr=0 / decimate=1 / interlaced=0 / constrained_intra=0 / bframes=3 / b_pyramid=2 / b_adapt=1 / b_bias=0 / direct=1 / weightb=1 / open_gop=0 / weightp=0 / keyint=250 / keyint_min=25 / scenecut=40 / intra_refresh=0 / rc_lookahead=10 / rc=crf / mbtree=1 / crf=28.0 / qcomp=0.60 / qpmin=0 / qpmax=69 / qpstep=4 / ip_ratio=1.41 / aq=1:1.00
Language : English

Audio
ID : 2
Format : AAC
Format/Info : Advanced Audio Codec
Format profile : LC
Codec ID : 40
Duration : 17mn 32s
Bit rate mode : Variable
Bit rate : 128 Kbps
Channel(s) : 2 channels
Channel positions : Front: L R
Sampling rate : 48.0 KHz
Compression mode : Lossy
Delay relative to video : -2ms
Stream size : 16.0 MiB (65%)
Language : English

Screenshots

Exclusive eLearning Videos ParRus-blog

←

add to bookmarks

Makers and Takers: The Rise of Finance and the Fall of American Business [Audiobook]

Makers and Takers: The Rise of Finance and the Fall of American Business [Audiobook] by Rana Foroohar
English | May 17, 2016 | ASIN: B01CUKFLII | M4B@64 kbps | 13 hrs 25 mins | 366 MB
Narrator: Rachel Fulginiti | Genre: Nonfiction/Economics

Eight years on from the biggest market meltdown since the Great Depression, the key lessons of the crisis of 2008 still remain unlearned – and our financial system is just as vulnerable as ever. Many of us know that our government failed to fix the banking system after the subprime mortgage crisis. But what few of us realize is how the misguided financial practices and philosophies that nearly toppled the global financial system have come to infiltrate all American businesses, putting us on a collision course with another cataclysmic meltdown.

Drawing on in-depth reporting and exclusive interviews at the highest rungs of Wall Street and Washington, Time assistant managing editor and economic columnist Rana Foroohar shows how the “financialization of America” – the trend by which finance and its way of thinking have come to reign supreme – is perpetuating Wall Street’s reign over Main Street, widening the gap between rich and poor, and threatening the future of the American dream.

Policy makers get caught up in the details of regulating “too big to fail” banks, but the problems in our market system go much broader and deeper than that. Consider that:

Thanks to 40 years of policy changes and bad decisions, only about 15 percent of all the money in our market system actually ends up in the real economy – the rest stays within the closed loop of finance itself.

The financial sector takes a quarter of all corporate profits in this country while creating only 4 percent of American jobs.

The tax code continues to favor debt over equity, making it easier for companies to hoard cash overseas rather than reinvest it on our shores.

Our biggest and most profitable corporations are investing more money in stock buybacks than in research and innovation.

And still the majority of the financial regulations promised after the 2008 meltdown have yet come to pass thanks to cozy relationships between our lawmakers and the country’s wealthiest financiers.

Exploring these forces that have led American businesses to favor balancing-sheet engineering over the actual kind and the pursuit of short-term corporate profits over job creation, Foroohar shows how financialization has so gravely harmed our society and why reversing this trend is of grave importance to us all. Through colorful stories of both “Takers” and “Makers”, she’ll reveal how we change the system for a better and more sustainable shared economic future.

Analyzing Event Statistics in Corporate Finance: Methodologies, Evidences, and Critiques (Repost)

Analyzing Event Statistics in Corporate Finance: Methodologies, Evidences, and Critiques By Jau-Lian Jeng
2015 | 200 Pages | ISBN: 1137397179 | PDF | 1 MB

Analyzing Event Statistics in Corporate Finance provides new alternative methodologies to increase accuracy when performing statistical tests for event studies within corporate finance. In contrast to conventional surveys or literature reviews, Jeng focuses on various methodological defects or deficiencies that lead to inaccurate empirical results, which ultimately produce bad corporate policies. This work discusses the issues of data collection and structure, the recursive smoothing for systematic components in excess returns, the choices of event windows, different time horizons for the events, and the consequences of applications of different methodologies. In providing improvement for event studies in corporate finance, and based on the fact that changes in parameters for financial time series are common knowledge, a new alternative methodology is developed to extend the conventionalanalysis to more robust arguments.

Threat Finance: Disconnecting the Lifeline of Organised Crime and Terrorism

Threat Finance: Disconnecting the Lifeline of Organised Crime and Terrorism by Shima D. Keene
English | 2012 | ISBN: 140945309X | 328 pages | PDF + EPUB | 3 + 2 MB

Criminal and terrorist organisations are increasingly turning to white collar crime such as fraud, e-crime, bribery, data and identity theft, in addition to more violent activities involving kidnap and ransom, narcotics and arms trafficking, to fund their activities and, in some cases pursue their cause. The choice of victims is global and indiscriminate. The modus operandi is continually mutating and increasing in sophistication; taking advantage of weaknesses in the system whether they be technological, legal or political. Countering these sources of threat finance is a shared challenge for governments, the military, NGOs, financial institutions and other businesses that may be targeted. Shima Keene’s Threat Finance offers new thinking to equip any organisation regardless of sector and geographical location, with the knowledge and tools to deploy effective counter measures to tackle the threat. To that end, she brings together a wide variety of perspectives – cultural, legal, economic and technological – to explain the sources, mechanisms and key intervention methodologies. The current environment continues to favour the criminal and the terrorist. Threat Finance is an essential read for fraud and security practitioners, financial regulators, policy-makers, intelligence officials, judges and barristers, law enforcement officers, and researchers in this field. Dr Keene offers an antidote to the lack of good, applied, research; shortcomings in in-house financial and forensic expertise; misdirected financial compliance schemes; legal and judicial idiosyncrasies; unhelpful organisation structures and poor communication. She argues convincingly for a coherent, aggressive, informed and cross-disciplinary approach to an ever changing and rapidly growing threat.