Скачать или смотреть Quantitative Finance - Taught by Incoming Pros at Citadel & Morgan Stanley - Paragon x Elevate

With 200+ live attendees from top firms & universities, watch the full recording of Paragon x Elevate Quantitative Finance for Hedge Fund, Buyside, Asset Management, Investment Banking & Private Equity Careers - by Incoming Pros at Citadel & Morgan Stanley.

Gain a deeper understanding of quantitative applications to asset selection and portfolio management, and differentiate yourself for Quant Finance, Investment Banking or Asset Management Career Paths. Modern Portfolio Theory is what Investment Professionals use in Asset Management & at Hedge Funds!

Elevate is excited to partner with Paragon National Group - a non-profit educational organization founded at UChicago & UPenn, whose focus is value investing fundamentals, computer / data science & quantitative finance - to deliver this training. To learn more about Paragon, visit their website at: https://www.paragonnational.org/. You can subscribe to Paragon National here:
‪@paragonnationalgroup‬

0:00 Elevate Overview
1:30 Paragon Overview
4:00 Why Learn Modern Portfolio Theory
5:00 Practical Examples of Modern Portfolio Theory
7:00 Return Notation
9:20 Portfolio Return Statistics
10:20 Correlation & Covariance
13:15 Imperfect Correlation
17:00 Portfolio Variance Decomposition
19:00 Systematic Risk
20:50 Idiosyncratic Risk
22:00 Portfolio Irrelevance of Individual Security Variance
25:20 Mean Variance & Sharpe Ratio
26:38 Risk and Return Tradeoff
28:22 Diversification across 'n' assets: Mean variance frontier
30:30 Efficient Portfolios
32:10 Tangency Portfolio
38:44 Minimum Variance Portfolio
40:05 Intuition of Asset Allocation
42:00 Application to other Asset Classes
45:30 Notation
48:44 With a Riskless Asset
49:40 Mean Excess Returns
50:50 Calculating Mean-Variance Portfolio Weightings
52:40 Two fund Allocation Adjustment
53:45 Problems with Mean Variance
56:45 Mean-Variance Alteration: Diagonalization
58:45 Quant Finance in Python: Live Example


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