Ron Bertino – Portfolio Investing
Get steady and consistent returns with low drawdowns, spending just 20 mins per month
Do you need steady returns with low drawdowns?
Sure. Doesn’t everybody?
The problem is that we’re led to believe that investing our own money is too risky and we should therefore use hedge funds in order to take care of our long term investments.
Financial concepts tend to sound quite complicated and involve either having to get deep into the weeds with complicated financial formulas, or resorting to having to become a programmer in order to code up even a simple investment strategy.
Could you outperform the average hedge fund?
That may sound like a crazy question to ask, but did you know that the average yearly returns of hedge funds are just 4.5% to 5% over the long term? They may be higher in more recent years, where the stock market has been increasing at an incredible rate, but once you include a few stock market crashes, then the yearly returns drop to an average of around 5%.
That’s a performance statistic which tracks 600 to 800 of the larger hedge funds, where each of these hedge funds need to have at least 100 million dollars of customer funds under management.
While you may be frustrated with that level of lackluster performance, the hedge funds are still perfectly happy to keep charging you their management fee, no matter how they perform.
Ray Dalio claims to have found the Holy Grail
While the average hedge fund performance has been lackluster, there are certain hedge funds that do perform very well. Ray Dalio runs one of the largest hedge funds in the world, called Bridgewater Associates, which as of 2018 manages over 125 billion in customer funds. Ray Dalio himself is a billionaire. So when a person like this makes a statement about having found the Holy Grail, then perhaps we should pay attention.
Here is a short 4 min video, where Ray Dalio explains the concept of the Holy Grail. Note that he’ll reference a bunch of terms that you may be unfamiliar with (standard deviation, correlation, alpha, information ratio, etc). Don’t worry, by the time you complete this course, you’ll know and fully understand all of these financial terms.
The main point he’s making is that the Holy Grail can be achieved by trading a variety of trading strategies or portfolios, where the return of each of these portfolios is unrelated to the others. When one strategy or portfolio is losing money, then hopefully the others aren’t losing money at the same time.
The keys are to:
a) have a variety of different portfolio strategies to choose from
b) be able to measure the degree of correlation between these strategies
You’ll be learning both of the above in this course.
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
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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