Terms, Phrases, and Abbreviations

0DTE

Options that expire on the same day they are traded. Popular among day traders for quick, high-risk moves.

Algorithm

An algorithm is a step-by-step procedure or set of rules used to solve a problem or perform a task. Algorithms are fundamental in computer science, mathematics, and everyday life—whether it’s sorting data, finding the shortest route on a map, or even following a recipe.

Key Characteristics of Algorithms

• Finite—An algorithm must have a clear beginning and end.
• Well-defined—Each step must be precise and unambiguous.
• Effective—It should solve the problem efficiently.
• Language-independent—Algorithms can be implemented in any programming language.

Types of Algorithms

• Sorting Algorithms—Arrange data in a specific order (e.g., Bubble Sort, Quick Sort).
• Search Algorithms—Find specific data within a dataset (e.g., Binary Search, Linear Search).
• Graph Algorithms—Solve problems related to networks and connections (e.g., Dijkstra’s Algorithm).
• Machine Learning Algorithms—Help computers learn patterns and make predictions.

Bearish divergence

Bearish divergence occurs when an asset’s price reaches higher highs, but a momentum indicator (like RSI or MACD) forms lower highs. This signals weakening momentum despite rising prices, suggesting that the bullish trend may be losing strength and a potential reversal could be ahead.

There are different types of bearish divergence:

• Regular bearish divergence: Happens during an uptrend when price makes higher highs, but the indicator makes lower highs, hinting at a possible trend reversal.
• Hidden bearish divergence: Occurs when price makes lower highs, but the indicator makes higher highs, that the downtrend will continue rather than reverse.

Colocation Services

Colocation services provide businesses with secure, high-performance facilities where they can house their own servers and networking equipment. Instead of maintaining expensive on-premise infrastructure, companies rent space in a data center, benefiting from robust security, cooling systems, and high-speed internet connectivity.

Colocation services are often used by financial firms, cloud providers, and companies needing scalable computing power. They help reduce costs while ensuring high uptime and security.

Data Structures

A data structure is a way of organizing, storing, and managing data efficiently within a computer system. It defines how data elements relate to each other and how they can be manipulated.

Types of Data Structures

• Linear Data Structures – Data is arranged sequentially.
  • Array – A fixed-size collection of elements.
  • Linked List – A dynamic structure where elements are linked.
  • Stack – Follows Last-In-First-Out (LIFO) order.
  • Queue – Follows First-In-First-Out (FIFO) order.
• Non-Linear Data Structures – Data is arranged hierarchically or in complex relationships.
  • Tree – A hierarchical structure with parent-child relationships.
  • Graph – A network of interconnected nodes.
• Dynamic vs. Static Data Structures
  • Static – Fixed memory allocation (e.g., arrays).
  • Dynamic – Memory allocation changes at runtime (e.g., linked lists).

Data structures are essential for efficient algorithm design, database management, and software development.

Digital Asset Staking

Digital asset staking is a process where cryptocurrency holders lock up their tokens to support the operation of a blockchain network and earn rewards in return. It’s commonly used in Proof-of-Stake (PoS) blockchains like Ethereum (ETH) and Solana (SOL), where validators stake their assets to help secure the network and validate transactions.

For traders and investors, staking can provide passive income without selling assets, similar to earning interest in a high-yield savings account. However, it comes with risks, such as lock-up periods and potential losses if the network penalizes validators for improper behavior.

FOMO

FOMO stands for fear of missing out, that anxious feeling that something exciting or rewarding is happening elsewhere and you’re not part of it. It’s often triggered by seeing others’ experiences on social media, like vacations, parties, or even investment opportunities.

The term gained traction in the early 2000s and has since become a cultural shorthand for that nagging sense of being left behind. It’s not just social, it can show up in trading too, like jumping into a stock just because everyone else is.

Heap Property

The heap property is a fundamental rule that governs heap data structures, ensuring that the parent node maintains a specific relationship with its child nodes. There are two types:

• Max Heap Property: The value of each parent node is greater than or equal to the values of its children.
• Min Heap Property: The value of each parent node is less than or equal to the values of its children.

This property ensures that the root node always holds the maximum (in max heap) or minimum (in min heap) value, making heaps useful for priority queues and efficient sorting algorithms like Heap Sort.

High-performance computing (HPC)

High-performance computing (HPC) refers to the use of powerful computer systems, often supercomputers or clusters, to process massive amounts of data and solve complex problems at extremely high speeds. These systems rely on parallel computing, where multiple processors work simultaneously to handle intensive workloads.

HPC is widely used in fields like AI, machine learning, financial modeling, climate simulations, and drug discovery.

LEAPS

LEAPS (Long-Term Equity Anticipation Securities)—Options with expiration dates longer than one year, used for long-term positioning.

Long Position

A long position refers to the purchase of an asset with the expectation that its value will increase over time. Investors take long positions in stocks, bonds, commodities, or options when they believe the price will rise.

A long position is the opposite of a short position, where traders bet on price declines.

Market psychology

Market psychology refers to the collective emotions and behaviors of investors that drive price movements, often influenced by fear, greed, optimism, and panic rather than pure fundamentals. Understanding these psychological forces can help traders anticipate market shifts before they fully materialize.

Here are some key aspects of market psychology:

• Herd Mentality: Investors tend to follow the crowd, leading to exaggerated market trends. This can result in bubbles during euphoric buying or crashes when panic selling takes over.
• Fear & Greed Cycles: Markets often swing between fear (leading to sell-offs) and greed (driving rallies). Recognizing these emotional extremes can help traders position themselves strategically.
• Overconfidence & Euphoria: When prices rise rapidly, investors may become overconfident, ignoring risks. This often precedes sharp corrections.
• Capitulation & Despair: At market bottoms, investors give up and sell at a loss, creating opportunities for contrarian traders who recognize undervaluation
• Confirmation Bias: Traders seek information that supports their existing views, sometimes ignoring warning signs of reversals.

Integrating market psychology into your approach could enhance your ability to spot trend shifts before they happen.

Monthlies

Standard options that expire on the third Friday of each month, providing more liquidity and stability.

Quadruple witching, or quad witching

“Quadruple witching,” or “quad witching,” refers to the expiration dates of four types of derivatives: stock options, stock index options, stock futures, and stock index futures, all occurring on the same day. These days, which fall on the third Friday of March, June, September, and December, often see increased trading volume and volatility as investors adjust or close out their positions. The last hour of trading on these days is sometimes called the “quadruple witching hour”.

In options trading, quadruple witching is like a volatility catalyst on steroids.

• Options Expiration Frenzy – Stock options and index options both expire during quad witching. As expiration nears, traders rush to close, roll, or adjust positions, especially if they’re ITM (in the money) or close to key strike prices. This leads to:
  • Sudden surges in volume
  • Unusual price behavior near major strike levels
  • Pinning effects, where prices gravitate toward popular strike prices due to dealer hedging
• Hedging and Gamma Exposure – Market makers and institutional players dynamically hedge their options exposure. As expiration hits, gamma ramps up, meaning delta changes rapidly, requiring fast adjustments in hedged stock positions. This creates bursts of buying or selling pressure—a dream (or nightmare) for nimble traders.
• Volatility Patterns – Historically, quad witching sees:
  • Higher intraday volatility
  • A tendency for false breakouts or intraday reversals
  • Spikes in implied volatility (IV), especially in the days leading up
• Trading Opportunity and Risk – For active traders, it’s fertile ground for:
  • Short-dated options plays like 0DTE strategies
  • Spread adjustments
  • Scalping volatility But it also raises the need for tight risk control—you don’t want to get whipsawed by a gamma-induced market swing.

Quarterlies

Expire at the end of financial quarters, often aligning with earnings cycles and macroeconomic events.

Recursive Algorithms

Recursive algorithms are algorithms that solve problems by breaking them down into smaller instances of the same problem. This approach involves a function calling itself repeatedly until it reaches a base case, where the problem is simple enough to be solved directly.

Key Features of Recursive Algorithms

• Base Case: The stopping condition where recursion ends.
• Recursive Case: The part of the function that calls itself to solve a smaller instance of the problem.
• Stack Memory Usage: Each recursive call adds a new layer to the call stack, which can lead to stack overflow if the recursion is too deep.

Examples of Recursive Algorithms

• Factorial Calculation: $$ n! = n \times (n-1)! $$
• Fibonacci Sequence: $$ F(n) = F(n-1) + F(n-2) $$
  • def fibonacci(n):
  • if n <= 1: # Base case
  • return n
  • else:
  • return fibonacci(n – 1) + fibonacci(n – 2) # Recursive case
• Binary Search: Efficiently searches a sorted list by repeatedly dividing it in half.
  • def binary_search(arr, target, left, right):
    if left > right:
    return -1 # Base case (not found)
    mid = (left + right) // 2 if arr[mid] == target: return mid # Base case (found) elif arr[mid] < target: return binary_search(arr, target, mid + 1, right) # Recursive case else: return binary_search(arr, target, left, mid - 1) # Recursive case

Recursive algorithms are powerful but can sometimes be inefficient if they lead to excessive function calls. Optimization techniques, like memoization and tail recursion, help improve performance.

Selling Borrowed Shares

Selling borrowed shares refers to the process of short selling, a strategy where traders seek to profit from a declining stock price. In this approach, a trader borrows shares from a broker and sells them at the current market price, hoping to buy them back later at a lower price. Once the stock price drops, the trader repurchases the shares at a reduced rate, returns them to the broker, and keeps the difference as profit.

This method allows investors to capitalize on bearish trends but comes with significant risk, as an unexpected price increase could lead to unlimited losses. Short sellers must carefully manage their positions to avoid being caught in a short squeeze, where rapidly rising prices force them to buy back shares at elevated levels.

Short Position

A short position is a trading strategy where an investor sells a security first with the intention of buying it back later at a lower price. This is done when a trader believes the asset’s price will decline, allowing them to profit from the difference.

Short selling is commonly used for hedging, speculation, or market corrections.

Short Squeeze

A short squeeze occurs when a stock’s price rises sharply, forcing short sellers to buy back shares to cover their positions, which further drives the price up. This creates a self-reinforcing cycle where increasing demand pushes the stock even higher, often leading to significant losses for short sellers and substantial gains for long investors

How a Short Squeeze Happens

• High Short Interest – Many traders have shorted the stock, expecting it to decline.
• Sudden Price Increase – Positive news or strong buying pressure causes the stock to rise unexpectedly.
• Forced Buybacks – Short sellers scramble to buy shares to limit losses, accelerating the price surge.
• Market Volatility – The squeeze can lead to extreme price swings, benefiting long investors while punishing short sellers.

GameStop Short Squeeze (2021)

• What happened: Hedge funds like Melvin Capital shorted large amounts of $GME, expecting its price to drop.
• Action: Retail traders on Reddit’s r/WallStreetBets noticed the high short interest and initiated a buying frenzy.
• Result: The stock skyrocketed, triggering a short squeeze — forcing short sellers to buy back at higher prices to cover losses.

Short squeezes are often triggered by unexpected news, earnings surprises, or coordinated buying activity.

Support Levels

In trading and technical analysis, support levels refer to price points where an asset tends to stop falling and may reverse direction due to increased buying interest. These levels are formed when demand for the asset strengthens, preventing further decline.

Key Aspects of Support Levels

• Psychological Barrier: Traders often recognize support levels as areas where buying pressure outweighs selling pressure.
• Historical Price Action: Support levels are identified based on past price movements where the asset has previously bounced back.
• Technical Indicators: Moving averages, trendlines, and Fibonacci retracement levels can help confirm support zones.
• Breakouts & Reversals: If a price breaks below a support level, it may signal further decline. Conversely, a strong bounce from support can indicate a potential uptrend.

Weeklies

Contracts that expire every Friday, offering short-term trading opportunities with rapid time decay.