How it works

MetricAlgo is an advanced SaaS platform that provides distinct statistical analysis services on historical price data.

Comprising two main tool suites:
– Historical Stats Tool
– Metrix SUITE

Both allow you to filter and analyze a historical data archive, processing them through specific metrics. Through these analyses, METRICALGO is able to calculate RESULTS that become statistical advantages and in other cases, actual strategies.

Besides the usual analysis you use for your trading, you can enhance your information with essential historical data to avoid many hidden mistakes.

The statistical analysis of MetricAlgo allows you to add more information to the trader’s decision-making process and will take your awareness of what you are doing to the next level.

The statistical approach is a distinctive feature of MetricAlgo. This type of trading is mostly systematic, algorithmic, continuous, and aims to approach the markets by statistically calculating the probabilities that certain events reflect a statistical trend.

Thanks to this method, you will primarily obtain two indications that turn into two advantages for the trader:
1) knowing the probability that a series of events produce a certain outcome;

2) a mathematical/statistical diagnosis if what is happening now falls within a range of ‘statistical normality’ or ‘statistical exceptionality’, in other words, if the weather is good or bad from the point of view of statistical consistency.

The type of statistics we use is mainly of a fractal and inferential nature. We use concepts like ‘similarity’ to find favorable probability fields, real gold veins for the retail trader in search of ‘advantages’.

In our database, we have stored thousands of historical data series, including stocks, indexes, etc.

A historical data series is nothing more than the candlestick chart you are used to seeing in the world of trading.

Imagine analyzing the sequence of candlesticks after selecting the time frame of interest.

A data series has this structure: Date/Time, Opening Value, Minimum Value, Maximum Value, Closing Value, which as you can see represent the 4 values of a candlestick.

A metric is the rule, or set of rules, that we apply when filtering a series.

Type of opening, Gap, volatility, days, months, etc. are metrics.

For example: filtering a series by emulating the current market situation is a search based on similarity and uses metrics such as current volatility, the current day, the current month, etc.

Metrics are also the results generated from searches, such as Profit/Loss %, Drawdown %, and dozens of other results at your disposal.

The use of one or more of these metrics determines the variety of possible results, just like the number of possible combinations in a game of chess. That’s why MetricAlgo is so powerful.

Historical data series are fascinating to analyze from a statistical standpoint.

Our challenge is to make this analysis accessible to everyone, even without having the necessary expertise to carry out certain types of analysis.

Filtering is an intuitive concept for the human mind and represents exactly what needs to be done when trying to measure a behavior or an event (in our case, price movement) using statistical techniques.

The goal is to find a model that responds to a certain trend with a certain probability.

Imagine wanting to filter a series to understand what happens every Friday in April on a specific stock when the market has a volatility between 10 and 30% and the session opening was negative.

Would you like to know that if you open a BUY position you have a 77% probability of profit?
And with a SELL, 23%? Would you find this information advantageous? Obviously, yes.

You see, filtering means searching for conditions, and every search generates a trading system with its backtest ready to be analyzed.

Historical Stats Tool is a suite of specific and dedicated analyses that you won’t find on other platforms.

The main purpose is to filter the series through metrics to obtain similar samples of events and then analyze the resulting dataset through different types of analysis. such as, the analysis of limits (or deviations), grouped analysis, sequence analysis, gap analysis, etc..

Engaging charts and visualizations aim to make you more informed about the historical nature of the events you are simulating. Here’s the translation: Furthermore, the keywords of these data are probability (%), frequencies, correlation, etc..

Every future type of analysis in its own right, which our team will develop, will find a home within this package.

You can find more details here.

This analysis, made up of various visualizations, aims to shed light on the likelihood that an event will occur within a certain period.

In simple terms: what is the probability that a price will reach a certain value by a certain date?

That’s why we also call them deviations, because we calculate the historical probabilities that within a certain time span the price reaches certain levels, both LONG and SHORT.

The limits are the highs, lows, and closes of the periods analyzed and more.

Use this tool by conducting multiple analyses, narrowing and broadening the filter more and more towards a condition increasingly similar to your idea.

Once finished, you will have a clearer idea of the historical deviation levels and the probabilities that they are reached within the period you defined.

This series of visualizations aim to aggregate the data on limits based on a second variable such as volatility, opening or closing gaps, days, months, years, etc..

For example, deviations grouped by volatility can clearly show you that some deviations are very large, but this only happens in specific volatility ranges, to the extent that you might adjust the filter to eliminate those cases since those levels of volatility are not present today.

Or, in a monthly analysis, you might notice that only on Wednesdays do particular things happen, so you decide to skip that day in the analysis (and maybe even in the strategy you have).

Through this visual tool, you can take a deeper and correlated look at the data obtained from the filter.

This analysis is very interesting as it focuses on calculating the probability of a red or green candle occurring after a series of candles of the same color.

It is mainly used to measure the historical probability of continuing to have the same type of sequence.

For example, imagine having 4 green candles and wanting to know what the historical probability is of another green candle occurring, and perhaps knowing the average historical range of the next opposite candle.

Since we filter a historical series based on metrics we provide directly to the Serie’s filter and based on a specific period like Daily, Weekly, Monthly, etc… it’s important to know the condition of the last ‘active’ period.

For instance, if I do a daily analysis and find some deviations, I will want to know the relationship between the current price behavior on the last day (or the active one) and the history of similar data.

We refer to this concept of ‘current data’ as At Now, denoting the present values indeed.

This concept is important to understand because it is often present in the MetricAlgo charts and interfaces with the purpose of guiding the user based on historical data.

MetricSuite is a SaaS software tool kit made up of two main components: Metrix Analyzer and Metrix Cloud.

The first is used to filter and analyze a historical data archive, processing it through specific metrics to generate a trading system and related results such as Profit/Loss (P/L), Drawdown, Z-score, etc.

The second is an effective tool through which to consult all the generated trading systems, using their respective results as search metrics.

You can find more details here.

Metrix Analyzer is a powerful tool capable of filtering and analyzing a data series from any financial instrument

Effettivamente, è il cuore di Metrix ed è possibile filtrare la serie su molteplici metriche per ottenere risultati più o meno performanti.

The final result of a search on Metrix Analyzer is a trading system, a set of operations collected in a backtest that shows you how well or not that research metric performs.

Our subscribers, our data analysts, and even our artificial intelligence continue to produce results using this tool, constantly creating an expanding pool of trading systems for others to select and evaluate.

Metrix Analyzer helps generate results that in turn become search metrics for Metrix Cloud.

Every time a search is conducted, two trading systems are generated: one for all BUY operations and one for all SELL operations.

These operations yield a final result, a profit/loss, an equity line, and it’s another tool from MetricAlgo.

You’ll be able to calculate the risk you intend to assume in your trading system, or super trading system, by inputting information from your broker and your orders.

A trading system includes the equity line, the maximum drawdown, the profit/loss, the number of trades, and many other details that help you understand whether the system might be suitable for your needs and expectations.

It’s essential to remember that a trading system is based on historical data, and its past performance does not guarantee or predict future returns.

However, statistical analysis can help you understand the probabilities of success and risk associated with a specific system.

Metrix Cloud is the place where you can view all the trading systems generated by Metrix Analyzer.

You can use various search metrics to find the trading systems that best suit your needs.

For example, you might be interested in systems that have had a positive return over the past year, or in systems that have experienced a drawdown of less than 10%. You might also want to view systems that have traded on a specific financial instrument or that have used a particular metric to filter the data.

Metrix Cloud is thus an effective research and analysis tool.

It allows you to examine each trading system in detail, providing a range of useful information, such as profit/loss, drawdown, the number of trades, the profit factor, and much more.

You can also view the details of each individual trade made by the system, to better understand how it works and how it responded in different market situations.

In conclusion, MetricAlgo with its Metrix suite offers a comprehensive platform for creating, analyzing, and managing trading systems based on statistical analysis and algorithms.

This allows you to approach the market with a more scientific and data-driven mindset, potentially improving your trading decisions and helping you manage risks better.

Imagine wanting to create a trading plan that involves one operation a day for the next three months.

Metrix Strategy Builder allows you to search for and select five different trading systems, each of which has proven to be particularly effective on a specific day of the week.

Thus, you might have a system for Monday, one for Tuesday, and so on, up to Friday. Each system might be focused on a different stock, for example, Apple, Microsoft, etc.

Thanks to Metrix Strategy Builder, you can combine these systems to create a “super trading system”. You can set specific criteria for system selection, for example, searching for those with a success probability of 75% or more.

The result will be a combined trading system, based on various probabilities, that offers you a success chance of 75% or more. What results is a multiple and combined system based on a determined probability field.

You’ve created a system that wins 3 out of 4 times.
This is what Metric Strategy Builder is for, to search and analyze trading systems to assess the interest it might have for us and for the trading plan we are designing, combining multiple systems.

Every trading system comes with End of Day (or End of Session) results. This means that no stop loss or take profit orders are applied to simulate the backtest. However, the trading system can be tailored to one’s needs in order to turn ideal data into actual execution action.

So, every trading system also delivers results for operations that involve only the stop loss, only the take profit, or the best historical pairing of stop loss and take profit.

It means that every trading system actually has 4 embedded trading systems.

However, the choice of which stop loss and take profit to use is still arbitrary, and “the best mathematically” is not always the “best for a trader”. For this reason, we have created all the tools to allow you not only to choose your best stop loss and take profit, but also tools capable of calculating how much your broker’s commissions can affect the results of your trading system or super trading system.

This is what we call ‘SIZING YOUR TRADING PLAN’.