Intro to Portfolio Metrics

Written by

Luke Posey

Published on

July 2, 2020

Note: nothing herein is investment advice. Spawner AI, Inc. does not provide investment, tax, or legal advice of any kind. This is not an offer, solicitation of an offer, or advice to buy or sell securities. Everything herein is for entertainment and educational purposes.

We’ve noticed an overall lack of awareness of basic portfolio metrics throughout the broader trading community. Many of these metrics and basic approaches are based on decades of research and development of best practices, some more practical than others for the common trader or investor.

Quantifying your portfolio’s risk, exposure, and performance is vitally important to continuously monitor the health, balance, and exposure to market forces. The metrics you follow are a personal choice based on your style and strategies. At Spawner, we decided to focus on a fairly broad set of widely used metrics for portfolio managers.

And we want to make sure these metrics are presented in a way that’s interactive and explainable. But we want to create a nice balance. We want the advanced user to quickly view and analyze metrics, while the beginner user can start to learn and understand how the core metrics works. And even the most sophisticated users can use a refresh on the underlying concepts now and then.

Here are some of the key metrics we track on our platform for both the mock (paper) portfolios and live portfolios users may test and trade.

Note that our in-app assistant is built to provide alerts to the user when their metrics exceed or dip below set parameters.

Allocation %

Allocation % gives us the allocation of individual positions in our portfolio. Too high of allocation to an individual stock will expose our overall portfolio to concentration risk. This can creep in over time due to the outperformance of individual holdings.

Allocation preferences will differ asset manager to asset manager. You might decide you only want any individual position to take up 3% of your portfolio. Set, monitor, and rebalance accordingly.


We look at exposure across a few areas. For now we’re measuring sector exposure and various factor exposures like size, yield, value, location, momentum, and volatility. For example, we might not want to be exposed too heavily to utilities and small caps. If we spot a high exposure to our sector of utilities and our size of small caps we can react accordingly Spawner might suggest allocating in other sectors or reducing holdings in utilities. Stocks in a specific sector typically have pretty strong correlation to the performance of that sector.

Sharpe Ratio

Sharpe ratio is very popularly used and for good reason. We use Sharpe to understand our risk adjusted return. We use metrics like Sharpe Ratio so we can get a deeper understanding of our portfolio past pure returns. Using total return on its own isn’t appropriate because to get a high return we may have taken on massive risk. We may have massive drawdowns or volatile swings to get there. Measurements like Sharpe give us insight towards understanding the real performance of our portfolio.

To get to our Sharpe Ratio we subtract the risk-free rate from our total return and divide by the standard deviation of our portfolio’s return. Pretty basic and you’ll see Sharpe Ratio littered all over Spawner.

Sortino Ratio

Sortino ratio is a modification of sharpe that doesn’t penalize volatility to the upside. Instead of dividing by the standard deviation, we only divide by the standard deviation of negative returns. This is seldom seen on the platform but we’re open to upping its visibility if users so choose.


Beta gives us insight to the movement of a security in response to our chosen benchmark.

Lots of folks like to use beta as a way to measure an asset’s exposure to the S&P. We use beta to measure how our portfolio will respond to changes in our benchmark of choice.

We use R² in a similar fashion to beta. R² gives us insight into how much of a portfolio’s return is simply because of their benchmark. R² is measured from 0 to 100 and many alternative approaches try to minimize R². That is to say, we might go for a low R² to try and get returns regardless of where the broader markets are headed. This in mind, imagine we’ve built a portfolio with an R² value close to 100%, but our beta is below 1. The lower our beta goes as the R² value stays the same we’ll be getting a higher risk adjusted return.


Alpha is our measurement of excess returns relative to the benchmark. As active portfolio managers we use alpha to measure whether or not our actions created returns in excess of a passive strategy.


We typical use standard deviation to measure an asset or portfolio’s volatility. We find the standard deviation by taking the square root of the variance. We can build out portfolios that optimize for minimum volatility. Getting a higher return while minimizing volatility is how we work towards a higher sharpe ratio.

Value at Risk (VaR)

We use VaR to measure the probability of loss over a given timeframe. We might say for example that a portfolio on its own has a 3-month 8% VaR o $25,000 — this means there’s an 8% probability the value of our portfolio will drop $25k or more in a 3 month period.

Max Drawdown

Max drawdown is a simple risk measurement. It showcases the maximum loss of an asset’s value in a set time period.

In closing…

There are plenty more metrics to explore. Find the metrics appropriate to track according to the strategies and goals you set in your personal portfolio.