Last Updated on July 28, 2021
Table of contents:
- What is the Portfolio Visualizer?
- Is Portfolio Visualizer free?
- Why should I use Portfolio Visualizer?
- Why shouldn’t I use Portfolio Visualizer?
- What are some Portfolio Visualizer alternatives?
- What is Asset Analytics in Portfolio Visualizer?
- How to check for correlation with Portfolio Visualizer?
- What is the Backtest Profolio in Portfolio Visualizer?
- How to Backtest Asset Allocation in Portfolio Visualizer?
- What is Factor Analysis in Portfolio Visualizer?
- How to run a Factor Regression Analysis in Portfolio Visualizer?
- What are Monte Carlo Simulations in Portfolio Visualizer?
- How to run a Monte Carlo Simulation in Portfolio Visualizer?
- What is Portfolio Optimization in Portfolio Visualizer?
- How to perform Mean Variance Optimization with Portfolio Visualizer?
- What are Timing Models in Portfolio Visualizer?
- How to run a Moving Averages model in Portfolio Visualizer?
- How to save your portfolio and simulation models with Portfolio Visualizer?
- How to import Custom Data Series and Benchmarks in Portfolio Visualizer?
- From where does Portfolio Visualizer get their data?
What is the Portfolio Visualizer
Portfolio Visualizer is a no-code platform built for visualizing, analyzing, backtesting and optimizating portfolios and asset relationships.
Is Portfolio Visualizer free?
Portfolio Visualizer comes in several tiers ranging from free to several premium ones. The free version comes available with the following features:
- Portfolio Backtesting
- Monte Carlo Simulation
- Factor Regression
- Asset analytics
- Timing models
- Portfolio visualization
There are two premium plans valued at $19 and $39 per month respectively. Here is what they offer on top of the free plan:
Why should I use Portfolio Visualizer?
- Portfolio visualizer is easy to use
- Is customizable
- Has several optimization strategies
- Offers simulations, factor analysis, and timing models
- Is useful to all sorts of investors and traders
Why shouldn’t I use Portfolio Visualizer?
- Portfolio Visualizer can be a bit confusing for newcomers at times
- Should have more information and tutorials
- Can get too technical at times
What are some Portfolio Visualizer alternatives?
Portfolio Visualizer can be replaced with some alternatives and they are the following:
- Personal Capital
- Investment Account Manager
What is Asset Analytics in Portfolio Visualizer?
Asset Analytics is a set of Portfolio Visualizer tools that are used to find various assets based on their adjusted risk, performance, style, and more. Some of the tools that Asset Analytics offer are these:
- Fund Screener
- Fund Performance
- Asset Correlations
- Asset Autocorrelation
- Asset cointegration and more
How to check for correlation with Portfolio Visualizer?
Let’s check for the correlation between the Box and Dropbox stock daily returns with a rolling correlation of 60 days for the last 3 years.
We can see that the correlation between Box and Dropbox is 0.49 which isn’t bad. Now, let’s switch over to the Rolling Correlation chart to see how it looks like:
What is the Backtest Portfolio in Portfolio Visualizer?
Backtest Portfolio is a feature of the Portfolio Visualizer that allows the user to backtest a portfolio asset allocation and compare its historical and realized returns, as well as risk, to a number of “lazy” portfolios.
There are free tools that Backtest Portfolio offers:
- Backtest Asset Allocation
- Backtest Portfolio
- Backtest Dynamic Allocation
How to Backtest Asset Allocation in Portfolio Visualizer?
To Backtest Asset Allocation in Portfolio Visualizer, you need to specify the main characteristics of your portfolio like the time period, cashflows, rebalancing, asset allocations, and more.
We’ll use a List View with a Year-to-Year time period starting from 2012 with an initial amount of $10k with an annular rebalance. We will compare two portfolios.
The first one will invest 60% in the US Stock Market and 40% in the Total US Bond Market. The second portfolio will invest in the previous two (40% and 30%) and also add 20% to the Global ex-US Stock Market and 10% in REIT.
Let’s see how the two portfolios compare:
These are just some of the things that you can look at, for a more detailed view of the various chart and metrics try it out yourself on the following link.
What is Factor Analysis in Portfolio Visualizer?
Factor Analysis is a statistical procedure that reduces a large amount of data into one or more factors. In the Portfolio Visualizer, you can use advanced Factor Analysis that are specialized for finance.
Here are some of the features that the Factor Analysis tools offers:
- Factor Regression
- Risk Factor Allocation
- Fund Factor Regression
- Factor statistics and more
How to run a Factor Regression Analysis in Portfolio Visualizer?
To run a Factor Regression Analysis in Portfolio Visualizer you will need to specify the regression type, tickers, factor returns, stock market, and more.
This analysis runs on the specified assets using the specified risk factor model. The end result will show how well the returns of the specified assets are explained by the risk factor.
Let’s run the regression on 4 US Stock Market stocks using the Fama-French Research Factors returns for the past 36 months. You can check the other characteristics of our model in the picture below:
If we look at the Factor Analysis Summary we can see that the most Annual Alpha was present in the Tesla stock which isn’t a big surprise:
There are plenty of more statistics and charts that you can look at and I’d advise you to explore them on the following link.
What are Monte Carlo Simulations in Portfolio Visualizer?
In Portfolio Visualizer, the Monte Carlo Simulations are models that predict the probability of various outcomes when random variables are present. It helps us explain the impact of risk and uncertainty on our predictions.
How to run a Monte Carlo Simulation in Portfolio Visualizer?
To run a Monte Carlo Simulation in Portfolio Visualizer, you will need to specify the type of returns you want to simulate, choose a withdrawal model, specify your asset, initial monetary amount, and more.
We will allocate 60% of our initial monetary amount to the US Stock market and 40% to the 10-year Treasury. When it comes to the specifics of our Monte Carlo Simulation, you can check them out in the following picture:
If we look at the Success graph over the years for our Portfolio, we can see that it performed well:
And from the Summary Statistics, we can see the End Balances of our portfolio for specified percentile ranges:
Remember that the Monte Carlo Simulations are hypothetical in their nature and don’t guarantee future results. Moreover, these hypothetical returns don’t take into consideration the trading fees and tax.
On top of that, past performance doesn’t guarantee future results so be sure to advance the analysis with your domain knowledge and hardcore realism.
What is Portfolio Optimization in Portfolio Visualizer?
Portfolio Visualizer comes equipped with several Portfolio Optimization tools that can help you advance your portfolio by taking into consideration things like risk-return ratios, CVaR, risk vs return trade-offs, and more.
The Portfolio Optimization comes equipped with the following tools:
- Historical Efficient Frontier
- Portfolio Optimization
- Black-Litterman Model
- Rolling Optimization and more.
How to perform Mean Variance Optimization with Portfolio Visualizer?
To perform Mean Variance Optimization with Portfolio Visualiser, you need to specify your portfolio type, time period, annual volatility, tickers, and more.
For our Optimization, we will use a Year-to-Year time period starting from 2012 and select 5 portfolio assets to see which ones would be the best to invest in. Those 5 stocks are FB, TSLA, AMZN, GOOGL, and MSFT.
Here are the specifications of our model:
And now, let’s check out some of the results:
As we can see, even tho Microsoft had the best Sharpe ratio, it was a better idea to equally divide our funds into each stock as it yielded bigger returns. To be precise, the equal distribution made 24.48% more.
What are Timing Models in Portfolio Visualizer?
Timing Models in Portfolio Visualizer allow the user to test different timing models that can run on momentum, target volatility, moving averages, Shiller PE ration valuation, and more.
Some of the Timing Models that it offers are the following:
- Market Valuation
- Moving Averages
- Momentum Rotation
- Adaptive Allocation
- Target volatility and more.
How to run a Moving Averages model in Portfolio Visualizer?
To run a Moving Averages model in Portfolio Visualizer, you will need to specify the time period, the timing model, initial amount, the ticker, trading frequency, and more.
For our model, we will select a Moving Averages for Asset timing model that will run from 2012 and use a 10-month simple moving average. A buy signal will be if the Price of the asset crosses the moving average.
The stock that we will use will be the Mastercard stock and the initial amount will be $10k. For more details about the model, check out the picture below:
When we look at the result, we can clearly see that holding on to the stock was much more profitable than using a simple SMA trading strategy:
How to save your portfolio and simulation models with Portfolio Visualizer?
To save your portfolio and various simulation models in Portfolio Visualizer all you need to do is to click the “Save” button that is found either at the beginning of the whole analysis or under every result sub-section.
After clicking the button you will be able to give your analysis a name.
To find your saved work, you can click the “My Models” dropdown menu that is located in the upper right corner of your screen. From there you can access various categories of saved work.
How to import Custom Data Series and Benchmarks in Portfolio Visualizer?
To import Custom Data Series and/or Benchmarks in Portfolio Visualizer you will need to access the “My Models” dropdown menu in the upper right corner and select the thing you want to import under the import section.
From where does Portfolio Visualizer get their data?
Portfolio Visualizer obtains its data from trusted sources like Morningstar, Federal Reserves, CSI, and more. The full list can be viewed in the picture below: