Quantitative Finance

Delve into the world of portfolio optimization with our step-by-step guide on ‘Efficient Frontier Explained in Excel: Plotting a 3-Security Portfolio.’ Learn to calculate expected returns and standard deviation for individual securities, assign random weights, and effectively use the Sharpe Ratio and Covariance Matrix for risk management. We conclude with plotting the Efficient Frontier using Monte Carlo Simulation, helping you identify the optimal portfolio.

💾 Purchase the file created in this video here: https://ryanoconnellfinance.com/product/efficient-frontier-mastery-excel-workbook-for-multiple-security-portfolio/

🎓 Tutor With Me: 1-On-1 Video Call Sessions Available
► Join me for personalized finance tutoring tailored to your goals: https://ryanoconnellfinance.com/finance-tutoring/

👨‍💼 My Freelance Financial Modeling Services:
► Custom financial modeling solutions tailored for your needs: https://ryanoconnellfinance.com/freelance-finance-services/

Chapters:
0:00 – Intro to “Efficient Frontier Explained”
0:41 – Calculate Expected Returns: Individual Securities
3:30 – Calculate Standard Deviation: Individual Securities
4:31 – Assign Random Weights
5:40 – Calculate Total Portfolio Expected Return
6:13 – Create Covariance Matrix
8:31 – Calculate Total Portfolio Standard Deviation
9:29 – Calculate Sharpe Ratio
10:42 – Plot Efficient Frontier Using Monte Carlo Simulation
12:17 – Find the Optimal Portfolio: Portfolio Optimization

*Disclosure: This is not financial advice and should not be taken as such. The information contained in this video is an opinion. Some of the information could be wrong. This channel is owned and operated by Portfolio Constructs LLC

Join Ryan O’Connell, CFA, FRM, in “Value at Risk (VaR) In Python: Historical Method,” as he explores financial risk management. The tutorial covers setting up Python, selecting stock tickers, downloading Adjusted Close Prices from yFinance, and calculating daily log returns for individual stocks. You’ll also create an equally weighted portfolio and compute its total daily returns. Finally, O’Connell guides you through calculating VaR and plotting the results on a bell curve. This tutorial is perfect for financial analysts and Python enthusiasts.

📈 *See Why I Recommend This Broker:* https://ryano.finance/ibkr-overview

💻 *Find the Code Written In this Video Here:* https://ryanoconnellfinance.com/value-at-risk-analysis-using-python/

🎓 *Columbia AI for Business & Finance Certificate Program* 🎓
► *Use code RYAN for up to $500 Off:* https://ryano.finance/columbia-ai

Chapters:
0:00 – Intro to “Value at Risk (VaR) In Python”
0:19 – Installing Necessary Libraries
0:48 – Set Time Range of Historical Returns
1:59 – Choose Your Stock Tickers
2:39 – Download Adjusted Close Prices from yFinance
4:19 – Calculate Individual Stock Daily Log Returns
6:11 – Create an Equally Weighted Portfolio
7:15 – Calculate Total Portfolio Daily Returns
8:10 – Find Portfolio Returns for a Range of Days
9:23 – Calculate Value at Risk (VaR)
11:44 – Plot the Results on a Bell Curve

Disclosure: This is not financial advice and should not be taken as such. The information contained in this video is an opinion. Some of the information could be wrong. This channel is owned and operated by Portfolio Constructs LLC. Some of the links above are affiliate links, meaning, at no additional cost to you, I will earn a commission if you click through and make a purchase.

“Portfolio Optimization in Excel: Step by Step Tutorial” is your ultimate resource for mastering portfolio management techniques using Excel. This tutorial will walk you through step-by-step instructions on how to maximize returns and minimize risk, leveraging data-driven strategies for smarter investment decisions. Whether you’re a novice investor or a seasoned portfolio manager, this video will provide you with the tools and insights needed to optimize your portfolio effectively.

💾 *Purchase the file created in this video here:* https://ryanoconnellfinance.com/product/investment-portfolio-optimizer-excel-workbook/

📈 *Checkout my preferred broker for Portfolio Management:*
https://ryano.finance/ibkr-overview

Chapters:
0:00 – Intro to “Portfolio Optimization in Excel”
0:48 – Inputs Required to Find the Optimal Portfolio
1:18 – Calculating the Expected Return of Individual Securities
5:30 – Calculating the Standard Deviation of Individual Securities
6:57 – Assigning Minimum & Maximum Weights
7:43 – Creating the Covariance Matrix
10:10 – Calculate Portfolio Standard Deviation
11:17 – Calculate Portfolio Expected Return
11:51 – Find the Risk-Free Rate of Return
12:16 – Find the Optimal Portfolio in Excel

*Disclosure: This is not financial advice and should not be taken as such. The information contained in this video is an opinion. Some of the information could be wrong. This channel is owned and operated by Portfolio Constructs LLC

Discover the power of Python for risk analysis in our tutorial ‘Value at Risk (VaR) In Python: Monte Carlo Method.’ We delve deep into the world of financial risk, breaking down the complex Monte Carlo method and its application in calculating VaR. Whether you’re a financial analyst, data scientist, or Python enthusiast, this video will provide you with practical, actionable knowledge. Get ready to master the art of risk prediction using Monte Carlo simulations in Python!

📈 *See Why I Recommend This Broker:* https://ryano.finance/ibkr-overview

💻 *Find the Code Written In this Video Here:* https://ryanoconnellfinance.com/monte-carlo-value-at-risk-python/

🎓 *Columbia AI for Business & Finance Certificate Program* 🎓
► *Use code RYAN for up to $500 Off:* https://ryano.finance/columbia-ai

Chapters:
0:00 – Intro to “Value at Risk (VaR) In Python”
0:15 – Installing Necessary Libraries
0:43 – Set Time Range of Historical Returns
1:54 – Choose You’re Stock Tickers
2:34 – Download Adjusted Close Prices from yFinance
4:14 – Calculate Daily Log Returns
6:06 – Calculate Portfolio Expected Return
7:52 – Calculate Portfolio Standard Deviation
10:11 – Create an Equally Weighted Portfolio
11:35 – Determine Z-Scores Randomly
12:25 – Calculate Scenario Gains & Losses
14:20 – Run 10,000 Simulations (Monte Carlo Method)
15:35 – Specify Confidence Interval Level & Calculate VaR
17:49 – Plot the Results on a Bell Curve

*Disclosure: This is not financial advice and should not be taken as such. The information contained in this video is an opinion. Some of the information could be wrong. This channel is owned and operated by Portfolio Constructs LLC