A Machine Learning Approach to Target Gain & Stop Loss – Learn When to Exit a Position Stop-loss and target gain methods were originated by professional day traders looking to exploit short-term price displacements. In recent years, with a wider adoption of algorithmic trading, rule-based exit conditions expanded in scope for all investment styles, including long-term strategies.  Recent price volatility has caught many investors by surprise, and theory has been quickly replaced by soul searching focusing on one question: “How much pain am I willing to endure?” Many who consider th ..read more

Webinar Seeking Alpha with ESG Data and AI  Portfolio managers and Investment advisors who wish to launch ESG products have several challenges to confront before launch.  Determine the environmental, social and governance target characteristics for their strategy. Examples include Climate Change and Carbon Intensity, Sustainable Resource Management, Board Diversity, and Labor Issues.  Choose from a variety of ESG data sets and scores that enable the creation of portfolios with the desired characteristics and risk/return profiles. Clearly articulate the stock selection drivers ..read more

Quantitative investment portfolios, also known as systematic or algorithmic portfolios, have many advantages, such as the ability to scientifically evaluate dozens of factors in near real-time and execute orders without emotion. While constructing quantitative portfolios involves algorithms, data and technology – the process doesn’t have to be a black box. Algorithmic investing strategies leverage algorithms and data-driven techniques that are initially researched and tested by data scientists and quantitative researchers – people who are trained to identify actionable signals but also traine ..read more

An Algorithmic Approach to Impact Investing Erez Katz, CEO and Co-Founder of Neuravest Research Inc Environmental, social and governance (ESG) investing has been the talk of the town for some time, and the boom is only going to continue. Over $100 trillion of assets under management are today committed to the Principles for Responsible Investment (PRI), while over a fifth of the world’s 2,000 largest public companies have pledged to meet net-zero targets, as sustainability shapes global markets in the 21st century. Naturally, astute asset managers have been quick to adapt and channel market in ..read more

The main challenge when applying technical analysis to intraday strategies is the lookahead bias when attempting to interpret a pattern. When you look back in time, actionable patterns seem easily detectable and compelling. In reality however, these very patterns are mostly undetectable in real-time formation.  Taking an active investment to the next level requires dynamic adaptation of a multitude of factors (not just technical) and combining an ensemble of uncorrelated models into one of the following actions: buy, sell, or do nothing. An Adaptive Long/Short AI approach is designed to ..read more

Wall Street Horizon’s forward-looking corporate event data feeds provide financial services professionals with clear and reliable views of potentially market-moving developments. In response to analysts, portfolio managers, traders and chief investment officers becoming more quant-savvy, Wall Street Horizon leveraged the Neuravest Data Analytics Services (DAS) platform to validate the predictive nature of its corporate events data and enable fund managers to apply actionable signals derived from this data to their investment strategies via model portfolios and smart data feeds. Read along as ..read more

Seth Merrin Executive Chairman, Neuravest It’s no secret that recent years have seen a rapid proliferation of data, especially alternative data. Between 2010 and 2020, the amount of data created, copied, captured and consumed increased by 5,000% (according to Forbes). In the investment management space, this means firms have an unprecedented amount of information to leverage when making critical trading and portfolio management decisions. In theory, this is a good thing, but the reality is that the vanishing scarcity of data has led to stagnation for many asset managers. This trend has coincid ..read more

Erez Katz, CEO and Co-Founder of Lucena Research Traditionally, analysis of corporate earnings reports such as 10K and 10Q has been a task for the fundamental researcher. Hedge fund managers, research analysts and finance experts would normally wait impatiently for corporate filings and eagerly read through such reports in order to answer two fundamental questions: Did the company meet or exceed expectations? What is the new trajectory for the company into its next quarterly or annual earnings? Astute investors know that fundamental research, along with the expertise and time needed to do it ..read more

By Erez Katz, CEO and Co-Founder of Lucena Research  In June of 2020, Lucena partnered with Benzinga to evaluate whether an AI approach to news feed sentiment is predictive for active investment.  It is widely agreed that news media is the most efficient way to convey information to the masses. Naturally, financial news is the most commonly used source of information for high latency investors. In recent years however, with the rapid advancement of NLP (natural language processing) technology, many investors feel left behind. Large and sophisticated hedge funds invested man ..read more

Authored by: Erez Katz For over seven years now, we’ve been on a mission to build a platform that can efficiently validate and deploy big data for successful investment. Our goal was two fold: For Data Providers: Enable data providers with an empirical and defensible validation of their data. Help them target a new set of consumers who are  not looking for the raw data but rather for “fully baked” actionable insights in the form of model portfolios. For Asset Managers: Serve asset managers with a wide array of uncorrelated portfolios powered by machine learning and AI. Each por ..read more