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Game Theory Equilibrium

In game theory, an equilibrium refers to a state in which all participants in a strategic interaction choose their optimal strategy, given the strategies chosen by others. The most common type of equilibrium is the Nash Equilibrium, named after mathematician John Nash. In a Nash Equilibrium, no player can benefit by unilaterally changing their strategy if the strategies of the others remain unchanged. This concept can be formalized mathematically: if SiS_iSi​ represents the strategy of player iii and ui(S)u_i(S)ui​(S) denotes the utility of player iii given a strategy profile SSS, then a Nash Equilibrium occurs when:

ui(Si,S−i)≥ui(Si′,S−i)for all Si′u_i(S_i, S_{-i}) \geq u_i(S_i', S_{-i}) \quad \text{for all } S_i'ui​(Si​,S−i​)≥ui​(Si′​,S−i​)for all Si′​

where S−iS_{-i}S−i​ signifies the strategies of all other players. This equilibrium concept is foundational in understanding competitive behavior in economics, political science, and social sciences, as it helps predict how rational individuals will act in strategic situations.

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Efficient Markets Hypothesis

The Efficient Markets Hypothesis (EMH) asserts that financial markets are "informationally efficient," meaning that asset prices reflect all available information at any given time. According to EMH, it is impossible to consistently achieve higher returns than the overall market average through stock picking or market timing, as any new information is quickly incorporated into asset prices. EMH is divided into three forms:

  1. Weak Form: All past prices are reflected in current stock prices, making technical analysis ineffective.
  2. Semi-Strong Form: All publicly available information is incorporated into stock prices, rendering fundamental analysis futile.
  3. Strong Form: All information, both public and private, is reflected in stock prices, suggesting even insider information cannot yield excess returns.

Critics argue that markets can be influenced by irrational behaviors and anomalies, challenging the validity of EMH. Nonetheless, the hypothesis remains a foundational concept in financial economics, influencing investment strategies and market regulation.

Control Systems

Control systems are essential frameworks that manage, command, direct, or regulate the behavior of other devices or systems. They can be classified into two main types: open-loop and closed-loop systems. An open-loop system acts without feedback, meaning it executes commands without considering the output, while a closed-loop system incorporates feedback to adjust its operation based on the output performance.

Key components of control systems include sensors, controllers, and actuators, which work together to achieve desired performance. For example, in a temperature control system, a sensor measures the current temperature, a controller compares it to the desired temperature setpoint, and an actuator adjusts the heating or cooling to minimize the difference. The stability and performance of these systems can often be analyzed using mathematical models represented by differential equations or transfer functions.

Dirichlet Kernel

The Dirichlet Kernel is a fundamental concept in the field of Fourier analysis, primarily used to express the partial sums of Fourier series. It is defined as follows:

Dn(x)=∑k=−nneikx=sin⁡((n+12)x)sin⁡(x2)D_n(x) = \sum_{k=-n}^{n} e^{ikx} = \frac{\sin((n + \frac{1}{2})x)}{\sin(\frac{x}{2})}Dn​(x)=k=−n∑n​eikx=sin(2x​)sin((n+21​)x)​

where nnn is a non-negative integer, and xxx is a real number. The kernel plays a crucial role in the convergence properties of Fourier series, particularly in determining how well a Fourier series approximates a function. The Dirichlet Kernel exhibits properties such as periodicity and symmetry, making it valuable in various applications, including signal processing and solving differential equations. Notably, it is associated with the phenomenon of Gibbs phenomenon, which describes the overshoot in the convergence of Fourier series near discontinuities.

Panel Regression

Panel Regression is a statistical method used to analyze data that involves multiple entities (such as individuals, companies, or countries) over multiple time periods. This approach combines cross-sectional and time-series data, allowing researchers to control for unobserved heterogeneity among entities, which might bias the results if ignored. One of the key advantages of panel regression is its ability to account for both fixed effects and random effects, offering insights into how variables influence outcomes while considering the unique characteristics of each entity. The basic model can be represented as:

Yit=α+βXit+ϵitY_{it} = \alpha + \beta X_{it} + \epsilon_{it}Yit​=α+βXit​+ϵit​

where YitY_{it}Yit​ is the dependent variable for entity iii at time ttt, XitX_{it}Xit​ represents the independent variables, and ϵit\epsilon_{it}ϵit​ denotes the error term. By leveraging panel data, researchers can improve the efficiency of their estimates and provide more robust conclusions about temporal and cross-sectional dynamics.

J-Curve Trade Balance

The J-Curve Trade Balance is a concept that illustrates the relationship between a country's trade balance and the effects of a currency depreciation or devaluation over time. Initially, when a currency is devalued, the trade balance often worsens due to the immediate increase in the price of imports and the lag in the response of exports. This creates a short-term dip in the trade balance, represented as the downward slope of the "J". However, as time progresses, exports begin to rise due to increased competitiveness abroad, while imports may decrease as they become more expensive domestically. Eventually, this leads to an improvement in the trade balance, forming the upward curve of the "J". The overall shape of this curve emphasizes the importance of time in economic adjustments following changes in currency value.

Szemerédi’S Theorem

Szemerédi’s Theorem is a fundamental result in combinatorial number theory, which states that any subset of the natural numbers with positive upper density contains arbitrarily long arithmetic progressions. In more formal terms, if a set A⊆NA \subseteq \mathbb{N}A⊆N has a positive upper density, defined as

lim sup⁡n→∞∣A∩{1,2,…,n}∣n>0,\limsup_{n \to \infty} \frac{|A \cap \{1, 2, \ldots, n\}|}{n} > 0,n→∞limsup​n∣A∩{1,2,…,n}∣​>0,

then AAA contains an arithmetic progression of length kkk for any positive integer kkk. This theorem has profound implications in various fields, including additive combinatorics and theoretical computer science. Notably, it highlights the richness of structure in sets of integers, demonstrating that even seemingly random sets can exhibit regular patterns. Szemerédi's Theorem was proven in 1975 by Endre Szemerédi and has inspired a wealth of research into the properties of integers and sequences.