Alpha Builder by Limex is an innovative machine-learning toolbox that allows investors to create individualized rules-based stock investment strategies.

Investors can select to invest in stocks included in the S&P500, Nasdaq, or the wider Limex Expanded Universe of the 2,700 largest names incorporated in US exchanges. Subsequently, they can use different risk/reward optimization rules, and filter the investable universe by size, sector, income requirement, growth profile, etc. Finally, the platform will provide a ranking of stocks based on risk-adjusted investment attractiveness, and a suggested portfolio based on the user’s investment policy rules.

The platform will provide back-testing results for each strategy, and users can iterate until finding the one that best fits their investment goal and turn it “live” to receive weekly updates of their selected stock universe’s risk-reward rankings and portfolio suggestions.

Alpha Builder is based on Limex proprietary macro-models developed on Boosted.AI’s SaaS platform. Boosted.AI is a specialized provider of AI-powered investment analytics tools, which are based on Amazon Web Services (AWS) technology.

These macro-models feed off hundreds of fundamental, trading, and policy variables, identifying predictive patterns by analyzing billions of static and dynamic trends over 3 decades of data.

Users of Alpha Builder get to build their own strategies “on top” of Limex’s macro-models. To do that, investors instruct the machine their particular investment criteria, and the platform will adjust its evaluation to give the user a ranked list of stocks and a suggested portfolio.

The most obvious use cases for Alpha Builder are:

1. Stock Selection - investors can use Alpha Builder to rank stocks by their risk-adjusted reward expectation. To do that, the platform will provide a ranking of stocks based on their unique chance of outperforming the market and the expected volatility of that expectation. Investors can look at their ranking and either apply it directly, or cross-reference it with other tools like technical analysis or fundamental research to make their own investment decisions.
2. Idea Generation - users can use the stocks’ ranking to generate a short-list of trading ideas depending on their own needs, whether to create a simple long-only selection, a long/short pair trade, or to hedge a long-term position ahead of an expected turbulent period in the market.
3. Portfolio Construction - the suggested portfolio output is one of the most powerful products of Limex Ai. It allows the user to define the number of positions, the diversification requirements, stop-loss and profit-taking rules, long v short exposures, use of leverage, etc., and creates a suggested portfolio updated on a weekly basis. It back-tests the strategy-based portfolio providing absolute and relative returns, volatility, sharpe ratios, monthly performances, etc. Investors can apply the portfolio suggestion directly to their books, or use it as suggested positions to cross-reference with other tools like trading technicals or fundamental analysis.

Nothing. At Limex we developed a user-friendly, intuitive interface for users to focus entirely on their investment strategy criteria. In other words, investors will walk-through a series of stages in which the only input they need to provide relates to their investment needs with all the complexity of Ai happening behind the screen.

Also, Alpha Builder provides step-by-step tutorials for users to view the process flow prior to using the tool, and on-the-spot information help that explains each command, input bar, and choices available.

The platform guide users through the process, which includes:
1.Strategy Name and Description - the first step is to choose a name and provide a description of the strategy. Given that building the strategy is likely to be a test-and-fail iterative process with a few attempts before finding the optimal solution, it's important that the name and description make quick reference to the test’s version and a short description of the variables used;
2.Target Universe - investors can choose to focus on names included in (a) the S&P500 index, which is a list of the 500 largest, well-known names listed in the US that operate in a wide spectrum of sectors and indices; (b) the Nasdaq100, which are the 100 larger names listed in teh Nasdaq exchange that tilts heavily on tech and media sector; and, (c) the Limex Expanded Universe, which is a list of approximately 2,700 names listed in the US spanning a wider range of market caps and sectors. The choice of universe will affect the learning time required by the machine, as well as the weekly ranking and portfolio updates;
3.Portfolio Preferences - this step is where investors feed their portfolio criteria to the machine.

The first two steps (Long Positions and Short Positions) refer to their long and short exposures:

• Percentage to Long/Percentage to Short - investors tell the machine which portion of the ranking to use when selecting positions. For example, if an investor indicates “use 30% for the long and 20% for the short” the machine will look at the top-30% of the ranking to select stocks to buy long, and the bottom-20% to select stocks to sell short. This step is more relevant when using the S&P500 and Limex Expanded Universe targets as the analysis can be highly time-consuming if the machine needs to characterize each one of the stock’s risk-adjusted reward operating in tandem with the other members in the portfolio;
• Min/Max number of Longs/Shorts - what is the maximum and minimum number of names to be included on either side of the book (long side or short side).
• Min/Max Position per Stock - a complement of the prior step, what is the minimum and maximum size of each position on either side of the book.
• Portfolio Long/Short Percentage - what is the size of each side of the book compared to the value invested. This number can be between 0% and 300% to account for the use of leverage (up to a 2x debt-to-equity ratio). Investors that want to look at a pure long-only strategy will include 0% on the short side, and for using no leverage the size of the long book would be 100%.

Following the general Long/Short requirements, the user will identify macro variables for the portfolio including:

• Investment Horizon - the machine will follow different signals for investors with different expected holding periods. The default is 21 days, which is equivalent to a month in trading days.The machine will re-evaluate the portfolio on a weekly basis which means that a particular stock could have ranked highly on day 1 and poorly on day 8 (for example, if it rallied in the first week) so the machine will suggest to sell the position on the first refreshment.Importantly, signals that are created for 21-days expected holding periods tend to decay very slowly for longer horizons thus a reasonable rule of thumb is to keep the 21-day default if the user is a long-term holder. For momentum traders, shorter periods can have material differences.
• Portfolio Starting Value - this is a yardstick for the machine to put a monetary value on the performance calculations. The default is $100m, which tells the machine to start the back-testing simulation as if it had invested $100m on the first day and never redeemed capital.
• Trading Costs, Smooth Periods, Execution Delays - general execution conditions. The trading costs (default is 0.01%) should reflect all monetary fees (these days mostly at zero) and bid/ask spread inefficiencies. Smooth Periods (default is 1 day) is a dampener for signals that have higher daily volatility; it mostly has “bite” for stocks that are very illiquid and inefficiently traded, which could result in an unnecessarily high trading frequency and jumps in rankings. Execution Delay (default is 1 day) affects mostly the simulation as investors will likely trade on their own schedule - if investors expect to delay the execution of the trades by a day or two since receiving the portfolio and ranking suggestions from the machine, they can ask the platform to use the similar delay in their back-testing.

The next step is for the platform to ask whether to use Stop Loss/Take Profit rules. These are pretty standard:

• activation toggle switch - the first step is to activate (or not) each rule with the toggle switch at the bottom.
• Threshold and Percentage - the Threshold is the level of loss or profit to accept prior to triggering the stop loss/take profit action. The Percentage is the portion of the position to close when that action is taken.
• For example, a stop loss with a 10% Threshold and 50% Percentage to Sell implies that the machine will sell 50% of the position when the loss hits 10%.

Finally, the machine shows a number of toggle switches to activate or de-activate a few more variables ad-hoc to each portfolio description;

4.Optimization Objective - this is where users feed the machine what to prioritize, including:

• Optimization Goal - the user has to pick between maximizing the expected outperformance versus the wider market, minimizing the maximum drawdown (represented by the Value at Risk, VaR), or look for a combined risk/reward optimization maximizing the Sharpe ratio (the Sharpe ratio compares a portfolio’s “units” of additional return over an index - in this case the S&P500 - against the “units” of additional volatility; e.g., a Sharpe above 1 means the the incremental return is relatively higher than the incremental volatility).
• Lower Turnover, Optimize Turnover, Tracking Error Optimizer - these are pure portfolio management and trading rules to avoid excessive churn and aggressive deviations from the benchmark.

Users should be able to iterate a few times until they find a strategy that fits their goals. This implies that the back-testing results are adequate, that the trading frequency matches their dedication expectations, etc.

The platform will produce the stock ranking and suggested portfolio every Sunday-to-Monday night.

Investors can use the ranking and portfolio suggestion as they see fit.

Our support team is available to assist you. Please contact us at alphabuilder@limex.com