HIGH-FREQUENCY TRADING: Algorithmic Computerized Stock Trading

Posted on November 6, 2025 by Dr. David Edward Marcinko MBA MEd CMP™

By Dr. David Edward Marcinko MBA MEd

SPONSOR: http://www.MarcinkoAssociates.com

***

***

High-frequency trading (HFT) is a form of algorithmic trading that uses powerful computers and complex programs to execute thousands of trades in fractions of a second. It has transformed modern financial markets by increasing speed, liquidity, and efficiency—but also raised concerns about fairness and stability.

High-frequency trading emerged in the early 2000s as technological advances allowed financial firms to process market data and execute trades faster than ever before. HFT firms use sophisticated algorithms to analyze multiple markets and identify short-term opportunities. These trades are often held for mere seconds or milliseconds, and profits are made by exploiting tiny price discrepancies across assets or exchanges.

One of the defining features of HFT is its reliance on speed. Firms invest heavily in infrastructure—such as co-location services near exchange servers and fiber-optic cables—to gain microsecond advantages over competitors. This race for speed has led to a technological arms race, where milliseconds can mean millions in profit.

HFT contributes significantly to market liquidity, meaning it helps ensure that buyers and sellers can transact quickly at stable prices. By constantly placing and updating orders, HFT firms narrow bid-ask spreads and reduce transaction costs for other market participants. This has made markets more efficient and accessible, especially for retail investors.

However, HFT is not without controversy. Critics argue that it creates an uneven playing field, where firms with access to advanced technology and capital can dominate markets. Concerns about market manipulation—such as quote stuffing (flooding the market with orders to slow competitors) or spoofing (placing fake orders to move prices)—have led to increased regulatory scrutiny.

The 2010 Flash Crash is often cited as a cautionary example of HFT’s potential risks. During this event, the Dow Jones Industrial Average plunged nearly 1,000 points in minutes before rebounding. Investigations revealed that automated trading systems, including HFT algorithms, contributed to the sudden loss of liquidity and extreme volatility.

Regulators have responded by implementing safeguards such as circuit breakers, which pause trading during extreme price movements, and requiring firms to register and disclose their trading strategies. The Securities and Exchange Commission (SEC) and Commodity Futures Trading Commission (CFTC) continue to monitor HFT’s impact on market integrity.

Despite its challenges, HFT remains a dominant force in global finance. It accounts for a significant portion of trading volume in equities, futures, and foreign exchange markets. Many institutional investors rely on HFT strategies to manage large portfolios and hedge risks.

In conclusion, high-frequency trading represents both the promise and peril of technological innovation in finance. While it enhances market efficiency and liquidity, it also introduces new risks and ethical dilemmas.

As markets evolve, balancing innovation with fairness and stability will be essential to ensuring that HFT serves the broader interests of investors and the economy.

COMMENTS APPRECIATED

EDUCATION: Books

SPEAKING: Dr. Marcinko will be speaking and lecturing, signing and opining, teaching and preaching, storming and performing at many locations throughout the USA this year! His tour of witty and serious pontifications may be scheduled on a planned or ad-hoc basis; for public or private meetings and gatherings; formally, informally, or over lunch or dinner. All medical societies, financial advisory firms or Broker-Dealers are encouraged to submit an RFP for speaking engagements: CONTACT: Ann Miller RN MHA at MarcinkoAdvisors@outlook.com 

Like, Refer and Subscribe

***

***

Filed under: "Ask-an-Advisor", finance, Glossary Terms, Marcinko Associates, Portfolio Management | Tagged: , , , , , , , , , , , , , , , | Leave a comment »

INVESTING TRANSFORMATION: Artificial Intelligence

Posted on October 6, 2025 by Dr. David Edward Marcinko MBA MEd CMP™

By Co-Pilot and A. I.

SPONSOR: http://www.CertifiedMedicalPlanner.org

***

***

Artificial Intelligence and Investing: A Transformative Partnership

Artificial Intelligence (AI) is revolutionizing the world of investing, reshaping how decisions are made, risks are assessed, and portfolios are managed. As financial markets grow increasingly complex and data-driven, AI offers powerful tools to navigate this landscape with greater precision, speed, and insight.

At its core, AI refers to systems that can perform tasks typically requiring human intelligence—such as learning, reasoning, and problem-solving. In investing, this translates into algorithms that can analyze vast amounts of financial data, detect patterns, and make predictions with remarkable accuracy. Machine learning, a subset of AI, enables these systems to improve over time by learning from new data, making them especially valuable in dynamic markets.

One of the most significant applications of AI in investing is algorithmic trading. These systems can execute trades at lightning speed, responding to market fluctuations in milliseconds. By analyzing historical data and real-time market conditions, AI-driven trading platforms can identify optimal entry and exit points, often outperforming human traders. High-frequency trading firms have long relied on such technologies to gain competitive advantages.

AI also enhances portfolio management through robo-advisors—digital platforms that use algorithms to provide personalized investment advice. These tools assess an investor’s goals, risk tolerance, and time horizon, then construct and manage a diversified portfolio accordingly. Robo-advisors democratize access to financial planning, offering low-cost, automated solutions to individuals who might not afford traditional advisory services.

Risk assessment is another area where AI shines. By processing alternative data sources—such as social media sentiment, news articles, and satellite imagery—AI can uncover hidden risks and opportunities. For instance, a sudden spike in negative sentiment around a company on Twitter might signal reputational issues, prompting investors to reevaluate their positions. AI models can also forecast macroeconomic trends, helping investors anticipate shifts in interest rates, inflation, or geopolitical events.

Moreover, AI is transforming fundamental analysis. Natural language processing (NLP) allows machines to read and interpret earnings reports, SEC filings, and analyst commentary. This enables investors to extract insights from unstructured data that would be time-consuming to analyze manually. AI can even detect subtle linguistic cues that may indicate a company’s future performance or management’s confidence.

Despite its advantages, AI in investing is not without challenges. Models can be opaque, making it difficult to understand how decisions are made—a phenomenon known as the “black box” problem. There’s also the risk of overfitting, where algorithms perform well on historical data but fail in real-world scenarios. Ethical concerns, such as bias in data and the potential for market manipulation, must also be addressed.

In conclusion, AI is reshaping the investing landscape, offering tools that enhance efficiency, accuracy, and accessibility. While it’s not a panacea, its integration into financial markets marks a profound shift in how capital is allocated and wealth is managed. As technology continues to evolve, investors who embrace AI will be better positioned to thrive in an increasingly data-driven world.

COMMENTS APPRECIATED

EDUCATION: Books

Refer, Like and Subscribe

***

***

Filed under: "Ask-an-Advisor", Accounting, CMP Program, economics, finance, Funding Basics, Glossary Terms, iMBA, Inc., Portfolio Management | Tagged: , , , , , , , , , , , , , , , , , | Leave a comment »