Portfolio Investing By Ron Bertino

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Description:
Portfolio Investing By Ron Bertino

Portfolio investing
Get steady and consistent returns with low drawdowns, spending just 20 mins per month
Course contents
Introduction

Welcome to the course
Strategic versus tactical asset allocation
Introduction to bonds
Asset classes
Hedge funds
How data can trick you

Returns

Getting historical data
Linear versus log scale
Arithmetic and log price returns
Cumulative arithmetic and log price returns
Converting arithmetic and log returns
Arithmetic and geometric mean
Wealth index
Performance charts

Measuring risk

Variance and standard deviation
The portfolio effect
Sharpe ratio, Sortino ratio, Calmar Ratio, Martin Ratio
Alpha and Beta
Correlation and R Squared
Treynor Ratio and Information Ratio
Value-At-Risk and Expected Shortfall

Factor models

Capital Asset Pricing Model (CAPM)
Fama French 3 factor model

Permanent portfolios

Equal and Value Weighting portfolios
Calculating portfolio returns
Review of 5 different permanent portfolios

Moving average filters

M.A.F. – single asset
M.A.F. – all assets in a portfolio

Modern Portfolio Theory

Introduction to MPT
Correlation and the correlation matrix
Efficient frontier
Minimum variance portfolio and mean-variance efficient portfolios
Rebalancing
Return vs risk graph
Capital Allocation Line, and margin effect on returns
Kelly Criterion – optimal f
Inverse variance portfolio
Risk parity portfolio

Dual Momentum

Review of 6 different dual momentum portfolios

Other portfolios

Review of two Adaptive Allocation portfolios
Review of two Core-Satellite portfolios

Spreadsheets and automation
We will jointly construct spreadsheets that reinforce the concepts presented in the course, using the free Google Sheets technology.
Stock analysis spreadsheet
We will:

import historical data from multiple sources
calculate arithmetic and log returns (standard and cumulative)
create a performance graph in both linear and log scale
calculate and graph drawdowns
calculate various performance and risk stats such as: arithmetic and geometric mean, variance, standard deviation, downside deviation, Sharpe ratio, Sortino ratio,
Value-At-Risk, Skew, Kurtosis
create a pivot table and bar graph showing the historical monthly seasonal performance
display return frequencies and map that to a normal distribution curve in order to be able to visualize skew and kurtosis

(Don’t worry if all of the above terms sound complicated to you right now. By the end of the course, you’re going to be crystal clear on what they mean and how they work)
Conversion spreadsheets
The first spreadsheet will take output from one of the online portfolio backtesting tools we will use, and then convert the output into a clean time series, which we can then analyze in more detail.
The second spreadsheet will do something very similar, but will take calendar style returns as the input and then convert it into a clean time series for further analysis.
Comparison spreadsheet
This spreadsheet will take the log returns of the clean time series data we have now created, and will show the results of two different portfolios side by side, together with stats comparing the two.
Google Apps Script automation code
One of the aims of this course is to present everything without getting into any programming code.
That said, I have created some Google Apps Script automation code which will greatly assist with some of the above steps, in terms of the conversion and comparison spreadsheets I’ve mentioned above.
I do not get into explaining any of the Google Apps Script code within the course, but I do make the source code fully available, for anyone who wishes to use it as a reference for their own spreadsheet automation work.
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