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A screener of screeners, Wootrader is creating affordable predictive analytics models for all kinds of investors


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A screener of screeners, Wootrader is creating affordable predictive analytics models for all kinds of investors

Atanas Stoyanov is the CEO of Wootrader.

What is Wootrader?

Atanas Stoyanov, CEO of Wootrader
Atanas Stoyanov, CEO of Wootrader

Wootrader is the only complete system that uses technical analysis, company fundamentals, analysts estimates, options volatility, guru strategies, stock sentiment and more to generate a ranking for each stock.

What makes Wootrader so radically different is that it adapts to the dynamically changing stock markets by using weighted predictive analytics models that have been used for years in other industries, such as military, to predict the trajectories of missiles, business modeling to predict sales of new products, or even in city planning.  The end-user does not have to manually configure screeners into an investing strategy – Wootrader selects and weights every day the screeners that are outperforming the S&P500 Index in the current market conditions. During some periods we have markets driven by fundamentals, other times by technicals, analysts estimates etc. –  this is what Wootrader accounts for.

Do we really need another screener? Don’t most people not understand how to use them effectively? How is it different than other screeners on the market? What’s the use case?

The currently available screeners require a high level of sophistication from end-users. Most screeners focus on technical, fundamentals, or a small combination of the two and the more data points are available, the more complicated those screeners are…to the point of becoming unusable.

By automatically selecting  the best performing screeners, Wootrader allows even beginner investors to use advanced data such as options volatility and analytics, social sentiments, and guru strategies,. on top of technical analysis and company fundamentals.

Additionally, Wootrader daily optimizes the models to use only the screeners that are outperforming the S&P500 depending on the current markets, while the other existing screeners are ’static’ – once the user has configured (and eventually backtested) them – they do not change/evolve and at some point in time, when the markets have changed, the screeners/strategies stop performing.

Enough has been said about the abysmal performance of Mutual Funds, and expert money managers using those same kind of screeners and strategies – over 80% are underperforming the markets exactly for using such ’static’ strategies that work only for short periods of time and need to be constantly maintained.

We see the following as use cases for Wootrader:

  • A complete beginner can log into Wootrader and start investing within 5 minutes using a basic model that has no timeframe constraints
  • More advanced users can use models with specific time/number of stocks constraints. For example, these users would select (using a wizard)  the model that works best for a one-month investing period for a portfolio of 10 stocks.
  • Professional investors can create custom models from scratch by selecting the data points that they believe are the most relevant and Wootrader, under the hood, will use its predictive analytics engine to automatically assign weights based on the current market performance. For example, a user can select some screeners like the P/E Ratio, MACD, 10 Day Options Volatility and Wootrader automatically assigns a weight to each one of them on a daily basis.
  • Financial institutions can integrate the Wootrader models and rankings into their own systems using our REST API

What kind of development went into building a screener of screeners?

Several years went into developing the predictive analytics engine of Wootrader. Currently, our platform is cloud hosted and gets new data every day from Zacks, CSI, Quandl, Orats, PsychSignal, Quantcha and soon, TipRanks (performance weighted analysts ratings and price targets). After the new data is downloaded, Wootrader builds the models and generates the rankings.

My background is in software development and optimization – my previous company (a former Inc 500 firm that I sold in 2007) AutomatedQA/Smartbear.com develops software optimization and test automation tools. Optimizing software and optimizing the stock markets have quite a few surprising similarities.

You’ve integrated your screeners into a few of the online brokers — can you describe how that works from a user’s point of view? Were there technical challenges that you faced?

Actually the brokers are integrated into Wootrader – allowing the user to place trades and retrieve accounts and positions. Wootrader analyzes a user’s existing equity positions and recommends which ones should be sold/bought over the short term. The challenges are mostly due to various implementations of the brokerages APIs, so each integration has to be custom-coded and extensively tested. However there are several new Broker ‘aggregators’  (think of these like portals to other brokers, allowing the use of a unified API to access the different brokers) that we are in the process of integrating – trade.it and tradable.com are two examples.

Another challenge is that not all information is readily available yet through brokerages APIs – for the future, we are working on accessing portfolio transactions such as dividend distributions/reinvestments, interest, splits, and other events like those.

What does 2016 have in store for Wootrader?

The main features coming in 2016 are related to portfolio analysis, as well as tax harvesting and optimizations. We want to make Wootrader a one-stop easy solution for everyday budding investors who desire better-than-market returns while saving on the fees associated with money managers and robo-advisors. We don’t pay our accountants a percentage of our earnings and I have a really hard time accepting fees based on a percentage (small or high) of the assets being managed. We are also constantly adding new great data from various sources.

Photo credit: Dennis Wong / VisualHunt.com / CC BY

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