Portfolio Management comes with a lot of different challenges. This article breaks down our functionalities to optimize your work and tells you how we solve these challenges.
First of all it is important to tell you that every user can follow along with this article, create a portfolio and test our manager. Palmy Investing allows everybody to create a portfolio that has a membership.
Another important note is that we do not link brokerage to our portfolios or trade opportunities, that's because our service should solely present data and analytics. Therefore each "buy", "sell" or anything that could be interpreted with a money position is symbolic.
The first step of creating a portfolio is simple: Find a title for your new portfolio. The second step requires you to buy 5 assets. Each buy has the opportunity to set your paid price per share (Asset Price), amount of shares (Quantity) and the date of buying the asset (Evaluation Date).
Afterwards you just became a new portfolio owner who manages the privacy settings and trades. You can e.g. decide to allow read access through the portfolio link (active by default). Therefore you'd be able to share the portfolio's insights without the edit permission of any third party.
When you're portfolio is created the following paths become available:
Our portfolio manager let you interact with an asset in 4 different ways, you can
- Buy
- Sell
- Edit
- Delete
The 'Buy' and the 'Sell' scenario can be described as a Trade, while the 'Edit' and 'Delete' scenarios only affect a buy trade that was already made.
Example:
1 year ago, you decided to buy 3 shares of 'XYZ' for $211 (∑633 USD). Now you've noticed that your trade entry has a wrong price per share (e.g. $205.3). Therefore an edit of the initial trade can be made to adjust.
The possibility to edit and delete bought assets comes with a level of complexity so that we have to adjust the portfolio insights.
Besides the above, our Portfolio Manager let you control the Benchmark and Risk free rate for your Portfolio Insights. That can be overwhelming for beginners and therefore we decided to write a detailed explanation of all formulas.
Entering all your assets manually becomes a pain from at least the fifth. If you have a lot of assets in your portfolio (or not), the CSV import is the most convenient way to add your positions. The feature is free for all members.
Another concept (in Beta) allows you to export the entire portfolio into a single PDF. The PDF will be structured into 4 parts: a cover, a portfolio summary, the Portfolio Metrics and the entire trade history.
It can become difficult to keep track of all your sold & bought assets. Therefore we serve a solution that is easy to understand, scalable and meaningful. We safe all sold assets - Forever. You can come back and analyze your past and current trades at anytime through Summaries, Tables, Scatter Charts or Calendars.
Our Portfolio Insights show you important data about the allocation, performance and risks:
- Assets under Management
- Positions by Weight
- Historical Performance (Absolute & Relative)
- All time High and Close
- Comparison with Benchmarks (e.g. S&P 500)
- Country Allocation
- Sector Allocation
- Intraday Performances
- ... To be continued ...
Instead of describing each part, just take a look at your own portfolio by following this article, or take a look into our demo to understand their impact for analytics.
Besides the fact that we scale up to thousands of trades, we are also a good place for retrieving important portfolio metrics (also KPIs). The following 4 KPIs are supported right now, some may follow in the near future:
- Beta
- Alpha
- Volatility
- Sharpe Ratio
- Sortina Ratio
- Information Ratio
- Portfolio Turnover
I. Beta
Formula- weighted return of the portfolio for the given timeframe
- return of the risk free investment (US Treasury Bill)
- return of the benchmark for the given timeframe
By default, we use the opening date of your portfolio to date as the horizon/timeframe.
So t = Portfolio Timeframe.
To calculate the Weighted Portfolio Returns we sum up all trades performances
together with their realtime weighting.
ROI position t = Return Of Investment from t → calculation time
- position is a stock
it is planned to include ETF positions as well in the future- we now also include ETF positions
- position is sold or still held
Besides the "r( Weighted Portfolio t )" our formula uses "r( Risk Free )" and "r( Benchmark t )". Latter, the benchmark or also known as market return also uses the timeframe to dynamically calculate the performance for the timeframe. Our standard benchmark is the S&P 500.
For the "r( Risk Free )" we use the Return of the 10 Years US Treasury Bill as default. This is a subjective choice and can be changed by you:
II. Jensen's Alpha
Feel free to adjust the benchmark index and the risk-free rate as needed in this context.
Please keep in mind that we use the CAPM (Capital Asset Pricing Model) to calculate the alpha. This has both advantages and disadvantages like almost every model.
III. Volatility & Sharpe Ratio
r( Excess p ) = ROI p - r( Risk Free ) So that we are able to add them together: r( Excess Portfolio ) = Sum( Excess p, Excess p1, Excess p ... ) To finally retrieve the volatility, we compute: Volatility = Standard Deviation( r( Excess Portfolio ) )
These were the current explanations of the four metrics. But that's not all. You can also manipulate the calculated data. If you want to adjust any of these further or need to change the data format, click on the icon next to the date of the calculation:
- Unadjusted (Default)
-
Monthly
- Metric = Metric * Sqrt( 21 )
- Adjusting by 21 trading days per month on average
-
Quarterly
- Metric = Metric * Sqrt( 63 )
- Adjusting by 63 trading days per quarter on average
-
Annualized
- Metric = Metric * Sqrt( 252 )
- Adjusting by 252 trading days per year on average
While some features might need improvement in the current version (feel free to submit feedback as always), some features are already on their way to be announced, e.g. having more portfolio metrics, dividend tracking and ai copilots.