STRATxAI already offers you the simplest way to take control of your personal investments. 

 full of pre-built strategies you can select one and create an investment portfolio in a few clicks. Watch the performance in a simulated environment or connect to your broker and invest straight away. The choice is yours. 

 you have the pro-tools and framework at your fingertips to go a step further. You can design and build bespoke investment strategies of your choosing.  

 This means we are following a rules based approach, grouping stocks based on one or more criteria from company financial data. 

Leaving emotion and subjectivity at the door, your investing strategies are  based on facts and backed by data.

Your Xplore Stocks portfolio will include a diverse collection of the top ranked stocks selected by the investment strategy you create.

Creating an Xplore investing strategy is quick and easy, however we recommend getting familiar with the terms that are used and the factors and rankings that are available to use.  

If you take a moment to read through the 

 you will be sure to get the most out of the feature. The guides will hopefully spark your  creativity too. 

This is where you get to tap into the extraordinary engine of STRATxAI, built with all the functionality of a quantitative hedge fund. STRATxAI uses powerful computing to run your strategy through proprietary statistical and mathematical models using the world's largest dataset of companies' financial data.

Run your Backtest and wait for a moment while STRATxAI uses these algorithms to assess how your strategy would have performed at any period of time within the past 17 years.

Each strategy you create and backtest will produce a tearsheet pdf which summarises your strategy and analysis. It is personalized with your chosen strategy name and chosen user name (or annonymous) so you can distribute or share the strategy and analysis.

Time to enjoy Xploring, the permutations are endless and your creativity will be unleashed.

We recommend that to get the most out of Xplore, you refer to the Glossary and check out the additional Tutorials on Universe, Factors, Ranking and Backtests. There are also two posts showing the construction of two sample strategies, Value and Quality.

If it's your first time creating a portfolio, or using STRATxAI, you’ll find lots of help in the 

 on investing and portfolio management. Note. Linking a saved Xplore strategy to a portfolio is only available to users with an Xplorer plan. 

Factor investing is for the patient investor who is committed to ride the highs and lows for the long term gain.  

At STRATxAI we are committed to empowering investors with the strategies and skills to have that confidence and commitment.

 Markets are variable and portfolio performances can go up or down. That's why at STRATxAI our goal is to enrich an investors self-belief and enhance their ability to stand firm and achieve their long term investing ambitions.

Introduction to Xplore Stocks. Use hedge fund level pro-tools that are easy enough for anyone to use.

0. Introduction to Xplore Stocks

Welcome to Xplore Stocks! You have just taken the first step to bringing your personal investing ideas to life.

With Xplore Stocks you have the tools and framework to design personal investment strategies and build investment portfolios all of which are based on the 

This means you are following a rules based approach, grouping stocks based on one or more criteria from company financial data. Leaving emotion and subjectivity at the door, your investing strategies will be based on facts and backed by data.

Compare this to the exhaustive work, time and effort you could be spending on researching and tracking individual stocks, reacting to volatility and chasing returns, not to mention the emotional bias you will inherently place on your choices.

Instead your Xplore Stock portfolio will include a diverse collection of the top ranked stocks selected by the investment strategy you create.

You will build your Style Factor strategy in 3 simple steps

Rather than trawling through all US stocks, we’ve made a few simple categorisations to create the STRATxAI Universe. It ranges in size from ~2700 to ~4500 stocks.

Now you can make choices on company value size and sector that will refine that further. This is your Universe.

Set your rules to refine the stocks down to only those that meet your criteria. These are your Factors and will relate to the overall Style Factor strategy you are aiming for eg. factors that relate to Value.

You could have a few hundred stocks in the final group that meet all your criteria and you will want to identify the top stocks for your portfolio. 

Choose from the many sorting options, like liquidity, momentum or gross-margin.

Add a personalised name for your strategy or leave the bespoke automated name.

Either way, each strategy that you create remains your intellectual property.

By now you have discovered that creating an Xplore investing strategy is quick and easy, whether you are a total novice or a seasoned investor. But how do you know if your investment hypothesis and your strategy is any good?

 and wait for a moment while STRATxAI uses these algorithms to assess how your strategy would have performed at any period of time within the past 12 years.

Keep an eye on the notifications on the left side while the number crunching is taking place. It won’t be long before your 

is ready to view on screen. This gives you the headline results of your strategy and compares it to the S&P 500 benchmark. If the topline numbers are looking good and you want more, click for your 

 which provides detailed graphs, charts, and analysis.

This downloadable PDF is your personal strategy paper, with your bespoke strategy name and you as the author. If you just see “Strategy by Anonymous”, go to 

 on the main page to enter a Display Name for yourself.

The tearsheet covers a range of outputs to help you make your decision whether to invest using the strategy or go back and change some parameters and try again.

Linking a saved Xplore strategy to a Portfolio is only available to users with an 

It won’t be long before you are ready to put your strategy into action.

When you click Create Portfolio, you will have a number of options available to you.

A simulated live trading environment with a hypothetical $10k. Track your strategy performance with no real money at risk.

Execute the trades separately with the broker of your choice, keeping a track of them on your STRATxAI portfolio page.

 For users who have augmented their Xplorer plan with Connect. Automate your trading by connecting STRATxAI to your online 

You’ve created an investment strategy and you’ve automated your portfolio with your broker - look at that - you are now Quant Investing with the Style Factor method. Bet you weren't expecting that to be so simple!

This post has given you a top line overview of how Xplore works. We recommend that to get the most out of Xplore, you refer to the Glossary and check out the additional Tutorials on Universe, Factors, Sorting, and Backtests. There are also two posts showing the construction of two sample strategies, Value and Quality.

Factor investing is for the patient investor who is committed to riding the highs and lows for long-term gain.  

 Markets are variable and portfolio performances can go up or down. That's why at STRATxAI our goal is to enrich an investor's self-belief and enhance their ability to stand firm and achieve their long-term investing ambitions.

Welcome to Xplore Stocks. You have just taken the first step to bringing your personal investing ideas to life. 

1. Welcome to Xplore Stocks

The investment 'universe' is the term used to define the set of assets to research and trade.

There are simply too many securities in the world to monitor, so we must narrow our focus to a subset of these. We can filter by asset class by choosing to only invest in stocks and exclude bonds, currencies, and commodities for example. We can also filter by geography, exchange, market capitalisation or liquidity for example. Our choice of universe dictates a lot about the potential risk and return of our investments. Each investor has different preferences on what kind of securities they want to research. This could be based on what country they live in or their particular interests and/or experience. 

Let's take a look at how we construct our top-level universe of equities at STRATxAI. We apply the following filters by default:

Starting with our entire database of equities. After crunching some numbers, we find that there are 112,000 equities traded in the world. These are dispersed across 143 different countries.

We then filter this list down by geography and equity type, selecting ~8500 US common stocks that have traded on public exchanges since 2010. 

Next, we'll add a minimum price and minimum average daily volume (

) filter. We select stocks that have maintained a close price above $2 and an 

 above $500,000. This step helps remove any illiquid stocks that could be delisted as they fall under the exchange price and liquidity requirements.

Finally, we remove Over-the-Counter (OTCs) stocks,  acquisition companies (SPACs) and Chinese ADRs.

Let's take a look at how many stocks this leaves us with. Since we research and backtest strategies on a point-in-time basis, the universe of investable stocks changes over time as we can see.

The STRATxAI universe ranges in size from ~2700 to ~4500 stocks, after applying the filters we described above. Note the large expansion in 2020 when a thousand new companies were listed. There has been a sharp decline since 2021 as many companies have delisted in the current market drawdown in 2022.

With the Xplore Stocks tools, we allow users to filter our preselected universe by 

small, mid and large market capitalisation

 so our users can design strategies that suit their personal needs

The first option is to select the range of market caps that you'd like to invest in. You can choose from Small-Cap, Mid-Cap, and Large-Cap. The 

default is to use the whole universe of stocks

Small-Caps are the stocks that have a market cap lower than the 25th 

Large-Caps are the stocks that have a market cap greater than the 75th percentile. 

Mid-cap stocks are those that fall within the range between the 25th and 75th percentile.

Let's take a look at a chart to make this a little clearer. We'll plot the average market cap of each bucket (small, mid, and large cap) across time.

Since 2010, the average market cap of the Small-Caps is ~$500M, the average market cap of the Mid-Caps is ~$1.5B, and the average market cap of the Large-Caps is ~$5B.

The final step of defining your universe is to choose your sectors. There are 20 sectors in total covering a very broad range of industries. We normally suggest using a broad set of sectors when creating your investment strategies so you limit your exposure to very concentrated sectors. However due to the market dynamics some sectors are just naturally a lot larger than others, as we will see, so some sector risk is unavoidable. Let's look at the data to help explain the sectors a bit more.

As we can see from the above breakdown, the Financial sector accounts for ~26% of our universe. Contrast that to the Communications sector, which comprises only ~1.5% of all entities. The top 3 sectors account for over 50% of the universe. Now, let's look at each sector's market cap.

In the above chart, we have summed the market cap of each sector. We can see a more even spread across the sectors. Technology Services has the largest market cap with ~17% while the Distribution Services sector lags behind at just ~1%.

Be mindful of how you choose your investment universe and use the above data to guide your decision. If you filter too aggressively, in terms of market cap and sectors, you might end up with a very small universe size - which may be riskier and could negatively impact your returns. 

Start exploring and testing your investment ideas with intuitive pro-tools. Have fun constructing your personalized investment strategies and let us know any feedback. 

Choosing an investment universe is the first step in building a data-driven investing strategy.

2. Understanding the Stocks Universe

No investment strategy can be constructed without some set of rules for your strategy to adhere to and follow. As part of our 

 Stock offering, we give our users access to approximately 45 factors that cover a wide spectrum of company financial data and price performance data. These factors allow users to filter their stocks by a strict set of rules and to automate your own investment strategy. 

As standard our core Beginner, Established and Xplorer plan users can apply 3 filters. If you want to unlock more filters augment your core plan with Xpert. 

 which are ways to group stocks together that share common underlying properties. These common underlying properties are found by using individual 

. Factors are single pieces of information that can be used to partly represent a style factor. Each of our 45 factors can therefore naturally be grouped into one of the style factors.   

operation margin, return-on-assets and debt-to-equity

 associated with the overall quality style factor.  

Filters operate very much like a set of criteria that must be obeyed and adhered to and they are an integral part of any investment strategy design. The more filters that are used in the design of your investment strategy, the more complex and constrained the strategy becomes. Using a lot of filters may mean the bar is set too high and as a result not enough stocks may 

All filters chosen by a user must be satisfied - for example, if a stock satisfies 2 out of 3 filters then it still will not be included in your strategy as it still failed to pass the test on 1 filter.

We split our large set of factors into different buckets based on overall 

. By grouping similar factors together this will give users a natural method of choosing their own filters from each style factor.

We provide 12 value factors that cover a broad spectrum of what typically represents a 

. These are split into roughly three segments that focus on 

enterprise and earnings based value metrics

We allow users to choose from 16 different quality factors that all work to formulate a strategy for 

, there is no single universal theme that represents a quality company or stock. It really is more of a 

"the whole is greater than the sum of its parts"

 philosophy. A well-run company with a strong balance sheet, high quality earnings, robust capital structure represents a quality stock. Our range of 16 factors should cover this wide spectrum.   

We provide 3 dividend factors within Xplore, which should provide users with plenty of ways to build dividends into your investment strategy design. 

For our technical grouping, we focus on 3 extremely popular and important concepts when it comes to investing, which are

Momentum: do you like to go with the trend? or are you a natural contrarian? For example, users can use this factor to filter their stock choices to stocks that have recent positive momentum, or if you are more of a bargain-hunter to stocks that have had poor momentum recently. 

Volatility: this will be used by most investors to ensure that they are avoiding the riskiest stocks. One simple way to do this is to use it as a factor and filter out these high-risk stocks. 

Liquidity: we always calculate the total $ volume of each stock through time and then we compare every stock against each other. We then apply a scaling so every stock is given a liquidity score between 0 and 1, with 0 being the least liquid and 1 being the most liquid. 

We have added four extra factors that some users may like to use when comparing financial stocks. These cover such items as interest income to total revenue, debt to market cap, interest income and deposits to assets ratio. 

There are then three natural comparison criteria to apply to each filter:

Users then have two options for using filters on their chosen factors

Enter a fixed specific value and untick the percentile 

. An example of this would be choosing the P/E factor and saying "less than 10", this will return all stocks that have a P/E less than 10. This method will also work for any % based factors such as dividend yield. Choosing "Greater than 2" and unticking the percentile box will return all stocks that have a dividend yield of greater than 2%.  

 and entering a value. An example of this would be choosing the P/E factor and saying "less than 10". This will return all stocks with a P/E that is less than the 10th percentile of all stocks, which is very different from a fixed value of 10 for P/E.  

For advanced users who really have an in-depth knowledge of company fundamental balance sheet items, hardcoded & fixed values like in option 1 above may make sense. For example, an advanced user might suggest they only want to search for companies that are less than a 1.5 P/B, which is a very explicit criteria.

For other users, the second percentile method may be easier to use and requires less knowledge. For example, filtering on the P/E factor using less than the 50th percentile just means that you only want the companies in the bottom 50% (the bottom half of all stocks), based on that P/E factor. 

An Xplore example of numerous difficult filters 

To show the importance of applying just the right amount of filters, here are examples of applying too many or too few.

In this first example we are going to open a new Xplore Stock strategy and choose the defaults of all the market caps and all sectors. Next we are now going to show an example of applying too many filters that are just too strict and no stocks actually satisfy all the filters. 

First, we select stocks in the lowest 5th percentile for the price-to-earnings factor. We choose stocks with a price-to-book ratio of less than 1. For the final filter, we select the stocks with an Altman z-score greater than the 50 percentile (indicating good quality companies). When using percentiles we make sure that the check box is ticked. Finally, we apply a simple 6-month momentum 

 to order by strongest recent performance. 

The results found below clearly indicate that the strategy in question employed filters that were just too strict to meet. Although the average universe size, after applying the filters and sorts, was 19 stocks, the strategy may not be able to form a portfolio of 15 stocks, at some point in time. 

The next example we show is one where choices were made in terms of universe selection that severely impact the algorithm from forming a portfolio. The strategy chooses to only use large cap and only focus on some service sectors. 

The results from this portfolio speak for themselves and this is not really a viable strategy to invest in. Even though two simple factors are chosen, the market cap restriction and the sector choices shrink the universe so much that there are not enough stocks to satisfy the two filters. 

We hope this article helped with your introduction to filters within 

and explained some pitfalls of applying too many of them or with unrealistic parameters. Try it out and let us know how you got on!

Filters allow you to customise your investment strategy to your own specific objectives. We will explain what filters we provide and how to use them.

3. What are the Xplore Stocks filters

 described the factors we expose to users and described some things to be careful of when applying the filters. The method of sorting is a more intuitive concept and is overall, less impactful to a strategy than the filters chosen. 

A sort is only applied after the filtering has occurred. This is the way it has to happen for good reason

Filtering based on factors shrinks the universe of stocks down to only those stocks that pass each and every filter. This means that on a given day your investment strategy will have a list of the stocks that have passed all the filter criteria 

 so you get for example the top 15 stocks 

Any sorting can therefore only be employed after this filtering process - as otherwise if 100 stocks passed all the filters, unless we employ some preference or sort, there would be no way to know how to select your top 15 stocks. This is why one sort, at least, is needed and enforced.

When using more than one sort, we do not incorporate any 

Each factor is used to generate its own individual score for each stock and we calculate the final sort-score for a particular stock by summing up all of the individual rankings for that stock - this is why order is not important. The final top 15 stocks are then chosen by looking at the total sort-score of all the stocks against each other. We can show a small example of this below, where Nike, for instance, has the highest momentum and liquidity. If for this case, we only wanted to return 2 stocks the sort would return NKE and AMZN as they have the two best final sort scores. 

Some of the most popular factors to sort on, and they were the ones we used in our 

These are very popular sort factors since they represent some of the most natural and important concepts in terms of investing. Sorting your final list would be a prudent thing to do, in order to ensure for example that the least volatile stocks or the most liquid stocks are included in your strategy. 

Other users, more familiar with fundamental company financial data, may instead choose to order by specific factors. For example, you could sort by price-to-earnings, operating cash flow ratio or by gross-margin. With our Xplore tool, you can start to build your knowledge and experience and start to experiment.

Example of the impact of sorting on a strategy

 example we had designed and the only thing we are going to change is the sorting method applied to it. This will hopefully illustrate the sensitivity of an investment strategy design to its underlying choices. We can see that the strategy itself produced some decent returns and a good Sharpe ratio and has performed quite well since covid hit. 

 for example was that our factor selection was used to identify the value stocks and then we wanted our sort to incorporate some other information - such as liquidity and volatility. 

Now let's change the sort and remove those three and replace them with one sort. We choose a classic value style metric such as 

 order, thus giving us what appear to be the stocks that exhibit the most value. The evidence is clear, with this choice of sort we lose an estimated 5% annually and our Sharpe ratio is halved from what it was before.

 tool is designed to be very dynamic and robust enough to investigate all sorts of investment strategy design decisions. Please let us know any feedback and enjoy building your own strategies! 

We explain how to use sorts when designing your investment strategy with Xpore Stocks.

4. How to use sorts in Xplore Stocks

 tool, we empower users to create their very own investment strategy and then execute a backtest to see how it would have performed through the last 12 years. We allow users to choose from both fundamental company balance sheet data and as such focus on 

. We also provide technical metrics such as 

 and liquidity. To make it easier to identify what factors you might like to use, we have grouped factors together into overall 

In this post we will go through each metric, inside each of our groups above so users can always know what they are choosing during their investment strategy design. 

The cash a company has at its disposal after accounting for spending on capex and incorporates new debt. It is cash left after accounting for operating expenses and capital expenses. It can then potentially be used to distribute to shareholders, stock buybacks, pay down debt or acquire target companies. It is calculated by 

(cash from operations - capex + net debt issued)

Enterprise value is sometimes used to construct a more accurate value of a company because it takes long and short form debt into account, as well as cash. The EV to sales metric essentially compares the company value to its sales. It is calculated by 

This metric values a company's share price to its free cash flow, which is a strong way to measure a company. Cash is harder to manipulate than earnings and if a company is generating strong cashflow it is in a strong position. It is calculated by 

The ratio of the enterprise value of a company to its earnings after accounting for interest, tax, depreciation and amortization. It can be especially useful comparing companies within industry segments to spot who is a market leader or laggard. It is calculated by 

The ratio of the stock price per share to the earnings per share and really represents what price an investor is willing to pay for a stock per unit of earnings. It is calculated by 

Measures the efficiency or asset turnover. It analyses how effective a company is at using its assets to generate revenue or sales. We use the change in this metric, which is the growth to find companies that are showing improvement in this efficiency metric. It is calculated by 

(the change in (sales/assets) since last reported)

A classic value model by Professor Joseph Piotroski that looks at companies from a value perspective by analysing their balance sheets and calculating 9 metrics. The 9 metrics focus on profitability, leverage and operating efficiency with companies receiving either a 0 or 1 per metric. It ranks companies on a scale of 0 to 9, with 0 being least value and 9 being strong value. It is calculated by using

(Net income, ROA, net operating cash flow, cash flow from operations, long-term debt, current ratio change, share issuance, gross margin change, asset turnover change.)

A nice metric that calculates the efficiency (or return) on how a company is investing its money. A company that has a history of effectively investing capital to generate a profit is a company that will hopefully reward investors with a return. It is calculated by using net operating profit after tax and invested capital

Similar to price-to-earnings but this time the price per share is divided by the sales per share and represents how much an investor will pay per unit of sales. It is calculated by 

This measures the ratio of company operating income to its average capital deployed. It is calculated by 

A ratio that is classic value and it represents the market value of a company compared to its book value, which is its assets minus liabilities. If the ratio is low or less than 1 then the market is valuing the company at less than its book value which may indicate some value. The underlying ratio is calculated on a per share basis by 

(market price per share/book value per share)

This is very similar naturally to EVEBITDA but this metric uses just EBIT. It is calculated by 

If you want to know how much leverage companies use? debt-to-equity is a nice easy way to see this. It is calculated by 

How to know if a company is profitable? The return on equity, which divides the net income of the company by the shareholders equity, is a nice ratio to look at. It is calculated by 

A very effective metric to look at to see how effectively a company can turn a profit per unit of revenue. It is calculated by 

Want to search for high cash generating companies that can easily service their liabilities? This metric is perfect for that and represents how many times a company can pay back its liabilities in a period by its cash generated during that period. It is calculated by 

(cash flow from operations/current liabilities)

This metric analyses how leverage has changed since a company last reported. Has a company increased its use of leverage ? It is calculated by 

(the change in (debt/equity) since company last reported)

The change in liquidity of a company since it last reported. Is a company showing an increase in its liquidity ? It is calculated by 

(the change in (current assets/current liabilities) since company last reported)

Sometimes knowing how stable a ratio is gives useful information. One way to identify stable high quality companies is to look at the volatility of the return-on-equity for example. It is calculated by 

(annualised volatility on quarterly ROE using the last 2 years of company reports)

A nice liquidity ratio that shows if a company can pay short-term obligations. It is calculated by 

Similar to the current ratio but only takes cash into account. It can also be known as the acid test and is calculated by 

(cash + equivalents + receivables + short-term securities/ current liabilities)

Another nice efficiency ratio that measures the ratio of actual cash flows to a company's assets. It is calculated by 

(cash flow from operations/average total assets)

This is the change in the gross margin ratio of a company and clearly a positive change is good. A positive change in a company's margins means they are either utilising their sales more effectively to generate higher profits or they are gaining a competitive advantage compared to their peers in this sector, which is driving higher margins. It is calculated by 

(the change in gross margin since company last reported)

Want to know how much profit a company generates compared to its sales, then this is the ideal candidate and represents just that. It shows the margin a company operates under and clearly a highly efficient company will have a nice high operating margin. It is calculated by 

This can be abbreviated to GPA and represents how efficiently a company can generate gross profits from its underlying assets. A company with a high GPA can be seen as potentially having a sustained competitive advantage over their peers. It is calculated by 

Similar to return-on-equity but this time we scale by assets. It is calculated by 

High gross margin is good for a business naturally. It represents sales minus the cost of goods sold. It is calculated by 

This is a bankruptcy risk metric and is meant to represent the probability of a bankruptcy for a publicly traded company. It uses company information such as profitability, leverage, solvency, liquidity and activity ratios. A score close to 0 indicates a risk of a company going bankrupt and a score 3 or above a company doing good. It is calculated by 

(Zscore = 1.2A + 1.4B + 3.3C + 0.6 + 1.0E)

A = working capital/total assets, B = retained earnings/total assets, C = EBIT/total assets, D = market cap/total liabilities and E = sales/total assets

We describe each of the metrics used within our Xplore Stocks tool so users can start to enjoy creating their own investment strategies. 

5. Xplore Stocks glossary: describing each metric

 post we give brief descriptions of all the metrics we surface to our users so they can build their own investment strategies. We now illustrate the construction of a simple value strategy using Xplore Stocks and show all steps involved in its construction.

 post, over the last decade from 2010-2020 the 

 has had a tough time and struggled to keep pace with the S+P 500, which was driven by a strong quantitative easing tailwind and a tech/growth trend. However, there has been a pullback in the markets with the new inflationary environment in 2022. It has been mentioned by a large cohort of market commentators that 

 and the value factor, in particular, are primed for a strong decade ahead. This has already been evident in 2021 and 2022 where the value factor has performed very well, as referenced by Blackrocks 

Value and min vol strategies are made for these times, with value strategies historically outperforming growth in periods of high inflation, as evidenced by factor returns we analyzed going back to the 1920s.

So with all that said, let's walk through from start to finish an example of how to use 

 to build your very own value investing strategy.

Every user has a choice as to what stocks and sectors to include at the start of their strategy research. These can be personalized to your investing thesis however the results of your strategy, in terms of risk and return and also robustness, will depend on this choice.

 If you narrow down your choices too much and then apply filters that are a bit too strict, you may end up with no strategy as no stocks satisfied all your criteria.

 For initial research, we prefer to choose all market caps and all sectors and Xplore defaults to this for our users.  

 section, users can click "Add Factors" to start accessing all our available factors. Given we are designing a specific 

Use our Xplore Stocks tool to build your  personalised value strategy. Run your own backtest to see how it would have performed. 

Building a value strategy with Xplore Stocks

Value and min vol strategies are made for these times, with value strategies historically outperforming growth in periods of high inflation, as evidenced by factor returns we analyzed going back to the 1920s.

Sign up to unlock

Introduction to Xplore Stocks

Welcome to Xplore Stocks

Understanding the Stocks Universe

What are the Xplore Stocks filters

How to use sorts in Xplore Stocks

Xplore Stocks glossary: describing each metric

Building a value strategy with Xplore Stocks

Building a quality strategy with Xplore Stocks