The following represent a small sample of financial terms, phrases, and abbreviations that I have encountered and think the novice investor and/or trader should be familiar with.
5% Rule
5 Percent Rule
The 5% rule for investors is a guideline that suggests no single investment should make up more than 5% of a portfolio. This principle helps investors maintain diversification, reducing risk by preventing overexposure to any one asset or security.
Algorithms
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.
Data Structures
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.
Earnings Cycle
Earnings Cycle
The time frame between one earnings report and the next is often referred to as the earnings cycle or earnings period. This cycle typically aligns with a company’s fiscal quarter, which is a three-month period used for financial reporting.
Some investors also refer to this window as the earnings season, which is the period when most publicly traded companies release their quarterly earnings reports
Earnings Period
Earnings Period
The time frame between one earnings report and the next is often referred to as the earnings cycle or earnings period. This cycle typically aligns with a company’s fiscal quarter, which is a three-month period used for financial reporting.
Some investors also refer to this window as the earnings season, which is the period when most publicly traded companies release their quarterly earnings reports
Long Position
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.
Short Position
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.
RSI (Relative Strength Index)
RSI
The Relative Strength Index (RSI) is a momentum oscillator used in technical analysis to measure the speed and magnitude of recent price changes. Developed by J. Welles Wilder Jr., RSI helps traders identify whether an asset is overbought or oversold
Key Aspects
- Calculation: RSI is computed using the ratio of average gains to average losses over a set period, typically 14 days
- Interpretation
- Overbought: RSI above 70 suggests the asset may be overvalued and due for a price decline
- Oversold: RSI below 30 indicates the asset may be undervalued, signaling a potential buying opportunity
- Divergence: When RSI moves in the opposite direction of price, it can signal a trend reversal
- Usage: Traders use RSI to identify entry and exit points, confirm trends, and analyze market sentiment
- Limitations: RSI signals are not always accurate and should be used alongside other technical indicators