Portfolio123 Alternative: Equities Lab Backtester

With the recent price increase in the services provided by Portfolio123, it has come to light that many users of their service may be looking for alternatives. We've been getting a number of calls these past couple of days from disgruntled users, and we have decided to write out the comparisons between Portfolio123 and Equities Lab here.

Portfolio123 has increased their prices, is it time to change?

With the recent price increase in the services provided by Portfolio123, it has come to light that many users of their service may be looking for alternatives. We’ve been getting a number of calls these past couple of days from disgruntled users, and we have decided to write out the comparisons between Portfolio123 and Equities Lab here.

CostEquities LabPortfolio123 New Price
Barebones version$35/month up to 5 backtests per day$84/month. Backtests allowed, but strategies are limited to just ones they have created.
Medium Version$50/month, unlimited backtests and no limits on using pre-definded screeners. Some advanced fields are only available for Institutional members.$200/month. Pretty much everything needed for the standard investor. If you are an institutional investor, you must use the below version.
Full power – institutional version$100/month no matter what$1,000/month up to $50mm under management. After that add $2,000/month for data.

Portfolio123 is far pricier than the Equities Lab alternative. However, if you receive significant levels of value for your money that extra price tag AND recent 100% price increase might be worth it. Let’s breakdown each aspect of the two services, and you can make an informed decision from there.

The Grading System

The grades in this table and all the ones below are as follows:

A+Amazing. Stands out well beyond its peers, making it the clear leader. May have flaws, but the overall experience is truly exceptional.
A

Very Good. Goes above and beyond the ordinary, giving a better experience.
BGood. It is nice to use, or contributes to the value the package provides. No program can be good everywhere, but it is a goal to aspire to.
CDoes what it is supposed to, give or take. It does the job well enough, without causing annoyance, or requiring too many workarounds.
DWorth avoiding. It mostly does what it is supposed to, after a fashion… with some caveats.
X
Not part of the program. It is simply missing, and the program makes no claim to offer it.
FUnusable. It looks like it works, but doesn’t actually do the job it is supposed to – at all. There are issues that can’t be worked around. F-
F-Deceptive. Using this functionality is dangerous, and may cause users to make bad investments.

Not all grades are created equal – packages getting a low grade on critical functionality will get a lower overall score. Each category that matters is explained below, with a table grading the packages, along with an “overall” grade for the category.

Power

This table is measuring the amount of power available in a “reasonable” amount of effort or time. Easy things should be easy, hard things should be moderate, and the nearly impossible should be doable. The power measured here is also what can be done within the program – rather than by running a bunch of screens, and using Excel to compose the results. Programs with useful functions, and which can compose those useful functions well, will end up with the edge here. Users need to be able to compare quantities (PE > 11), rank quantities (PE in the top 50%), compare quantities across time (PE larger than last year), and compose these operations together. They also need to be able to create and manage moderately complicated formulas (e.g. Piotroski score).

PowerEquities LabPortfolio123
Screen in the pastA
Single Click
A
Single Click
Simple (PE > 11)A
Just type it in, or find it in tools menu
A
Just type it in. Adding a wizard rule didn’t work as it could do PE < 11 only. Change it after the fact
Changes of quantities (PE went down by 20% in the last year)A+
Just type it in. Any field can be lagged any amount, easily
B
Expression must be quoted, preventing nesting. Tricky to do
Ranking stocks (PE in the bottom 30% of the market)A+
Just type it in, any field or equation can be ranked easily

Multiple ranks possible within a screen. Can rank with sector, industry, or custom group, and can filter. Nesting is easy.

B
Use the FRank operator, and set variables to use group/filter. Use of a quoted string for the factor to be ranked makes nesting impractical.
Simple formulas (Piotroski > 7 and Low Price to Book)A+
Piotroski exists as an importable, customizable formula. Piotroski can also be built from scratch, easily, saved and reused.
B
Piotroski score exists, and can be built from scratch, though it will all be one very long freeform rule –all in one line
Complex expressions

(Low Stddev of change PE over one month)

A+
Just nest the expressions. Functions operate on time series, and across sections of the market, and all can be nested. Some can be slow (e.g. a moving average of a rank of PE across the market).
C
Nesting two levels deep is difficult, with one line per nest. Many functions exist to avoid the need to nest, with hardcoded inputs (e.g. AvgVol). This reduces flexibility, as generic versions can’t be found.
Cross market computation

(total earnings of the largest stocks)

A+
Cross sectional expressions are just like other expressions, and are usable everywhere.
C
Can create custom series with cross sectional average on a separate panel, and use them in some functions.
Expected sub-categories

(include only airlines, the S&P 500, etc)

D
Sectors and industries included, but no indexes or exchanges. Usable proxies for S&P, Russell aren’t exact.
B
Sectors, industries, indexes, and International Indices (Primarily Canadian), ETFs
OverallA+
Clearly more powerful than the others, as it is able to handle even very complex terms (e.g. Quality Minus Junk, Olhson’s O score, etc)
B
Powerful enough to get work done, with some work, and some digging.

Data

Investment programs live on their data, and how well it supports backtesting and screening in the past. Investors need data that covers at least one major market cycle, though two is better. They also need fundamental data (earnings, revenue, assets, liabilities, etc.), as well as technical analysis (the ability to play with patterns in the price data). Macroeconomic data (US GDP, inflation, etc.) is very useful, though not critical. Lastly, they may find earnings estimates, ownership information, and foreign data sets useful.

DataEquities LabPortfolio123
Length of historyA
22 years
A
19 years
Fundamental dataA+
Comprehensive set of 600+ fundamental metrics, not including ratios
B
Fundamentals (96 fields) are solid but not deep enough to really dig in
Technical dataA
Moving averages, RSI,MACD, triangles, wedges, a few candlesticks, and the ability to add your own with lagging and sequence operators
B
Reasonably solid set of technical indicators, but adding new ones is very hard
Ownership dataX
No ownership data
A
Earnings EstimatesX
No ownership data
A
Macroeconomic dataA
Seamless integration with quandl allows usage of all quandl data sets including paid ones (if you have subscribed).
B
A few built in Macro factors based on FRED data.
Alternative data setsB
Quandl gives access to large body of data. No foreign stocks. ETFs included, but cannot screen ETF’s.
A
US and Canada stocks
Overall

Data

A
A focus on the core: Amazing fundamentals (600+ fields) and solid technical analysis capabilities make the data solid, useful and powerful.
A+
96 fundamental fields give a usable picture, supplemented by all of earnings estimates, insider trading, institutional trading, and short interest.

Usability

Usability is not the same as simplicity or beauty. It also refers to how easily the user can use the program to get something done, assuming it can be done. Aesthetics, ease of getting started, ease of navigation and speed all matter. However, users need to read and modify what they (or others) have written, so readability and ease of editing matter. Lastly, the pre-built content included enhances learnability and usability.

UsabilityEquities LabPortfolio123
AestheticsB
Good use of colors and shapes. Utilizes the design to help teach the user.
B
Looks good and the looks play into the functionality
DeploymentB
Windows, Mac, or Linux only. Does not require admin rights to install.
B
Web, desktop recommended
Starting a new screenB
Suffers from the blank screen effect, but clicking on the + generates new lines, joined together with ‘and’. Has sensible defaults that are easy to change.
A
Extremely simple – sensible defaults, immediately brought to a drag and drop.
Tooltips, searchability, and autocompleteB
Autocomplete is effective, but does not pop up help while completing. Users need to use the tools pane for that.
A+
Searchable field list works together with autocomplete to make creating expressions easy. Unfortunately, no tooltips on already created rules makes existing expressions obscure. Wizard rules are very limited.
Expression readabilityA+
Tooltips explain functions and fields, so reading unfamiliar expressions is easy. Easy use of variables and formulas help chunking.
A
Expressions created with the wizard tool are incredibly easy to read. Free Form can be obscure, but tooltips help out.
Editing existing contentA+
Drag and drop, extract variable or formula, all easy wrapping of terms all work together to make editing joyful.
A
The fact that terms are text makes editing reasonably easy.
Cut and pasteA+
Any term can be cut and pasted, even into notepad. Multiple cut buffers are a nice touch.
B
Any single rule can be cut and pasted, but the separate dialog boxes impede expression import/export.
Navigation through screensA
Fast navigation, searchable tabs, ctrl-Click to go into an item, and a breadcrumbs trail make navigation easy.
A
Easy to navigate through the existing screen. Select different rules and change settings. See positions, returns, and custom plotted tear sheets fairly easily.
Preloaded content libraryA+
Large, searchable content library. 500+ screens (many of them segments, like “Low P/E”), and 400+ formulas give the user plenty to work with. Piotroski, Beneish, Altman, Montier, etc are all done out, so users can modify them. 500+ formulas to use as building blocks.
B
64 built in screens and 8 formulas get the user started.
Content reuseA+
Both variables and formulas help ensure content reuse. Formulas can have descriptions. These allow users to maintain criteria they use in all their screens (such as no penny stocks)
C
Can create custom series, but not saved sets of conditions for use in screeners.
Handling user errorA+
Much user error is prevented by the editor, with reasonable error messages. Multiple level undo and a restore autosave make it difficult to lose work by mistake.
C
The wizard rules are too limited to help new users for long (cannot screen for PE > 10 via wizard rules, only PE < 10). No undo or autosave.
SpeedA
UI is amazingly fast, and handles massive data well (100,000 trades in a table). Some queries are slow.
A
Queries returning large queries are sluggish, most queries are reasonably fast.
Overall

Usability

A+
An actual joy to use (after the first few minutes of bafflement). The preloaded content inspires the user to new heights. Can be slow sometimes.
B
The system is learnable, and reasonable efficient once learned, but it has a long learning curve. Many tasks remain painful even for those familiar with the system.

Configurability

Configurability lets users bend the software to their will, rather than the other way around. It is essential for people building and tweaking an investment system to be able to find, understand and twiddle the knobs that may drive performance. Being able to control when backtests “rebalance,” or replace all their holdings with new ones, helps ensure the system being used is robust. A strategy that works when rebalanced monthly, but fails weekly or quarterly is probably a disaster. Similarly, while swearing by a stop loss regime is good, being able to test several is better. Being able to get useful data about the results lets users be more confident in the results.

ConfigurabilityEquities LabPortfolio123
Rebalance periodsA+
Fully configurable rebalance, though one must rebalance all stocks, or none.
B
10 Rebalance options based on the day you run the strategy. Will rebalance anywhere from daily to yearly
Buy/Sell without rebalancingC
Can sell without rebalancing, but not buy. Sales go to cash until the next rebalance.
C
Can sell without rebalancing, but not buy.
Stop losses/Stop gainsA
Custom stop losses/gains possible. Stop losses and gains can be adjusted based on conditions. Trailing stops possible.
X
It doesn’t appear that there are any Stops
Minimum/maximum holding periodsA+
Minimum and maximum holding periods can vary per stock and change over time.
X
Beyond a rebalance period there are no time based stops or holding periods.
Data about the backtestA+
Can get a zoo of statistics over time, including holdings, and even use these in the backtest (Stop trading if a threshold is met, etc). Basic plotting is easy, more complicated uses are less obvious.
B
Though there is extensive data for individual companies, their backtest dataset was pretty good, but not the best.
Backtests selling based on other backtests.A+
The results of backtests are just another expression to be used.
C
You can’t do it within their screener tab. Rather you can create a sell “when” in a simulated portfolio.
OverallA+
Virtually everything can be configured – arbitrarily. Options to control leverage and short selling are hard to find and use.
C
No stops, and limited rebalance periods. The backtest report is OK.
AnalyticsEquities LabPortfolio123
TablesA
All results in one page, searchable, sortable by multiple categories, exportable
B
paginated, but can sort columns and export
Backtest performance chartA
Configurable benchmarks, other backtests, and data on chart, which is clickable, zoomable and more
B
A flat chart with an ETF of your choice as a benchmark
Plot a single value or expression

(What is this company’s PE?)

A+
Plots ad-hoc plots and panels, fields and expressions, in screens, backtests and charts.
B
Can plot single value, cannot add plots to backtests
Configurable data displayA+
All data within all pages is completely customizable. Can build tear sheets to supplement those in the system.
B
Can configure data(including custom data) in a separate chart. Can’t easily add data points directly within a screen.
HeatmapsA
Heat maps used in most places throughout the software. All maps allow the adjustment of order, size, and what is considered a good or bad return.
X
No heat maps
Single Stock DisplayA
Interactive charting with custom plotting, customized plotted panels, price history, Trading models, links to news and filings.
A+
Interactive charting with custom plotting, customized plotted panels, news, summary, ranking, filing history, price history.
OverallA+
Backtest by time, positions breakdown, scatter charts, and good reports let users understand the results clearly. The ability to add plots to the backtests is very useful.
B
Solid analytics are usable, if not an absolute joy. The single stock display is very amazing, and a valuable asset by itself to some investors.

Final Assessment

The final assessment pulls all the data from the tables above together into an opinion of how useful the package is for backtesting. Power, usability, configurability and data all matter, but a package that has a clear limitation that makes backtesting impossible or useless will get a low grade regardless of its other capabilities. An article that compared screening, charts, or performance on some other task would give these packages a higher grade.

OverallEquities LabPortfolio123
PowerA+
Equities Lab is able to handle even very complex terms (e.g. Quality Minus Junk, Olhson’s O score, etc)
B
Portfolio123 is powerful enough to get real work done, with some effort, and some digging.
DataA
A focus on the core: Amazing fundamentals (600+ fields) and solid technical analysis capabilities make the data solid, useful and powerful.
A+
96 fundamental fields give a usable picture, supplemented by all of earnings estimates, insider trading, institutional trading, and short interest.
UsabilityA+
An actual joy to use (after the first few minutes of bafflement). The preloaded content inspires the user to new heights. Can be slow sometimes.
B
The system is learnable, and reasonable efficient once learned, but it has a long learning curve. Many tasks remain painful even for those familiar with the system.
ConfigurabilityA+
Virtually everything can be configured – arbitrarily. Options to control leverage and short selling are hard to find and use.
C
No stops, and limited rebalance periods. The backtest report is OK.
AnalyticsA+
Backtest by time, positions breakdown, scatter charts, and good reports let users understand the results clearly. The ability to add plots to the backtests is very useful.
B
Solid analytics are usable, if not an absolute joy. The single stock display is very amazing, and a valuable asset by itself to some investors.
Things to noteMonte Carlo lets you run many similar screens and see how changing parameters changes the results.Uses Compustat data, and has a nice stock comparison tool. Has optimizer to run many similar screens.
OverallA+
Equities Lab validates and creates investable strategies more effectively than any other contender.
B
Portfolio123 has good power, extensive data, and a decent UI make it a solid contender.

At the end of the day, Portfolio123 really is a fantastic tool. If you are a member and you learn the system, you will be able to get things done. The question becomes, is it really worth the high price tag? Equities Lab also isn’t the only alternative; it is just the most comparable in function and the most powerful of all alternatives.

If you’re interested in ditching portfolio123 and becoming an Equities Lab member, you can check out the membership levels here: https://www.equitieslab.com/equities-lab-pricing/

If you’d like to see all potential alternatives in a comprehensive breakdown and are an AAII member, checkout this article on AAII: http://www.aaii.com/computerized-investing/article/a-comparison-of-backtesting-tools

About Tyler McCain

A student of finance at Georgia State University, Tyler has had a passion for the world of finance for as long as he can remember. Joining the Equities Lab team in 2015 he attempts to juggle the perfect mix of school, work, and giving back to the community. When he isn't working at Equities Lab he can often be found helping teach programs at the Rosen Family Foundation - a non-profit that teaches financial literacy to middle and high school students.

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