AI for Algorithmic Trading

Use artificial intelligence to improve algorithmic trading speed and accuracy, and increase portfolio returns for your clients

Learn how you can use AI for algorithmic trading to automate the process of keeping up with second-by-second market moves in securities, treasuries, futures, and other investment vehicles. The world of high-frequency trading demands real-time decision-making and split-second transaction capabilities that only artificial intelligence can deliver.


What is algorithmic trading?

Algorithmic trading uses the power of artificial intelligence and machine learning to automatically and accurately extract real-time investment insights from vast quantities of trade and market movement data.

Maximizing returns for institutional investors

Managing pension funds and other institutional portfolios requires close attention to risk while simultaneously optimizing returns that fall within the regulatory scope of each fund. Successfully achieving this delicate balancing act requires fast but confident decision-making strategies on when to enter and exit investment positions.

Balancing risk and return in hedge fund management

These typically aggressive investors have more flexibility to pursue returns than traditional mutual fund managers, who are bound by strict risk management guidelines. But with greater return comes greater risk, which makes investment decision-making critical to the financial success of these higher-risk organizations.

Benefiting from currency fluctuations in international fintech

Making money in international currency trading requires visibility into split-second rate changes, political forces, and central bank decisions. Algorithmic trading solutions keep investment managers ahead of these fast-moving changes and provide a competitive advantage in a landscape where transactions happen in milliseconds or less.

How does AI enable algorithmic trading?

AI-enabled algorithmic trading—whether in securities, commodities/futures, currency, or more arcane derivative investment vehicles—is a critical contributor to successful portfolio management, particularly in an investment landscape characterized by millions of second-by-second transactions and instantly-changing external factors.

Not only can AI-based trading solutions deliver the speed and accuracy your portfolio needs by taking into account all of these factors, AI-driven trading solutions are also fully autonomous, completing transactions without human intervention (or possible errors) as externalities change, positioning you to maximize the returns your clients demand. And, while AI solutions automate the previously manual legwork of trading analysis, the professional trader is nevertheless in charge at all times with fully explainable AI. The accuracy and productivity delivered by AI-based algorithmic trading solutions offer early adopters a significant advantage over their competitors.

Execute faster, more accurate transactions in a millisecond-by-millisecond trading world

Traditional investing has always been a bit subjective, with some pursuing technical investment strategies (momentum, price swings, etc.) while others extol the merits of fundamentals-based investment (attempting to measure a security’s intrinsic value). AI-based trading solutions eliminate the guesswork and subjectivity by analyzing mountains of transaction data in real-time and completing trades faster than possible by humans.

Base investment decisions on real-time transaction data, without the potential for human error

Traditional investment approaches rely on labor-intensive deep dives into historical price data and market factors, followed by endless spreadsheet work and mathematical modeling. AI-powered algorithmic trading, by contrast, incorporates data from millions of transactions, delivering results with no labor-intensive processes at all.  

Automatically extract insights from unstructured financial performance data

A significant percentage of all data related to securities trading is unstructured (e.g., 10K, 10Q, annual reports, and analyst reports). Natural language processing solutions can digest all of this information automatically and use it in conjunction with real-time trading data to maximize the returns generated by your trading desk, whether on the buy or sell side of the market.

AI-powered algorithmic trading across industries

Algorithmic trading in the hedge fund industry

Maximize portfolio returns for your investors by quickly identifying emerging opportunities, particularly in fast-moving areas like arbitrage and news-based security price swings.
  • Identify high-leverage opportunities.
  • Assess and mitigate risk.
  • Maximize portfolio returns.

Algorithmic trading in pensions, annuities, IRAs, and 401ks

Balance risk and return to ensure fund guideline compliance while also consistently delivering the objective return rate for your institutional clients (pensions, annuities, etc.). Enhance your decision-making with automated up-to-the-second insights.

  • Deliver investment return goals.
  • Ensure compliance with fund risk guidelines.
  • Manage client expectations.

Algorithmic trading in international currency trading

Ensure returns in international currency trading with real-time visibility into split-second rate changes, political/economic forces, and central bank decisions. Use the power of AI-based algorithmic trading solutions to keep your investment managers ahead of these fast-moving changes and provide a competitive advantage in a landscape where transactions happen in milliseconds.
  • Stay up to the second on currency exchange swings.
  • Determine and stick to your currency risk profile.
  • Set stop-loss thresholds accurately.

How SparkCognition delivers AI-powered algorithmic trading

SparkCognition’s AI for algorithmic trading applies our patented machine learning and natural language processing algorithms to the vast universe of investment transaction data and analyst/business reporting documents.

Our AI-based algorithmic trading methodology is straightforward and effective, led throughout by SparkCognition AI and domain experts, with minimal time requirements from your staff.


Step 1: Real-time data ingestion

To ingest and analyze historical and real-time security/commodity prices, volumes, and ranges, SparkCognition employs a number of powerful ML-based data validation techniques that enable transaction models to then be used to conduct trades quickly and automatically.

Step 2: Unstructured information analysis

Natural language processing models read and digest vast quantities of written investment-related documents, e.g., 10K/Qs, ARs, and analyst reports. 

Step 3: Transaction model development

Models are constructed to trade quickly and without human subjectivity or emotion, seizing upon opportunities that may last for only milliseconds.

Case studies: Learn more about AI and algorithmic trading

Transform market making with artificial intelligence

Discover ways in which AI for algorithmic trading can help trading desks accomplish more with less. SparkCognition’s market-making platform empowers client traders to radically increase their capacity and ability to manage risk with high-quality, real-time market information, client profiling, and cover predictions that unlock value and efficiency at scale. Read our product sheet

Extracting value from financial documents: NLP processing for the finance industry

The SparkCognition Deep NLP platform is the best way to efficiently analyze and extract actionable insights from the flood of documentation and information available to finance industry professionals. And access to accurate real-time information—regardless of source—is the key competitive advantage in financial trading. Read our solution sheet

How AI builds and sustains a competitive advantage in banking

Learn how SparkCognition’s AI for algorithmic trading solutions can help you assess and hedge against risk while giving your financial professionals the tools they need to identify investment opportunities in a world where margins are more compressed than ever and accurate insights and guidance are critical enablers of successful portfolio management. Read our white paper

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