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• Non-Stationary
  ...der, like daily closing prices of Bitcoin futures – stationarity refers to statistical properties that remain constant over time. More specifically, a stationary ...wever, understanding the concept of stationarity is important because many statistical forecasting methods, including those used in [[Algorithmic Trading]], *requ
  11 KB (1,559 words) - 04:01, 20 March 2025
• Augmented Dickey-Fuller test
  ...its [[stationarity]]. Understanding stationarity is paramount because most statistical models, including those used for forecasting in trading, *require* stationa *Stationarity* means that the statistical properties of a time series – its mean, variance, and autocorrelation –
  12 KB (1,744 words) - 16:21, 16 March 2025
• Cointegration
  ...We will focus on practical application, assuming a basic understanding of statistical concepts. ...ore [[Time Series]] that, while individually non-stationary (meaning their statistical properties change over time – more on that later), have a stable, long-te
  12 KB (1,668 words) - 14:48, 18 March 2025
• Augmented Dickey-Fuller (ADF) test
  ...ADF test, let’s define stationarity. A stationary time series is one whose statistical properties, such as mean, variance, and autocorrelation, are constant over ...by periods of calm. This non-stationarity poses a significant problem for statistical modeling.
  12 KB (1,825 words) - 04:13, 16 March 2025
• Heteroskedasticity
  ...Analysis]], and fundamental news, a deeper understanding of the underlying statistical properties of market data can provide a significant edge. One such property ...ich the variability of a random variable (in our case, the error term in a statistical model predicting crypto futures prices) is not constant across all values o
  12 KB (1,651 words) - 02:42, 19 March 2025
• Cointegration analysis
  ...or more time series that individually may be non-stationary (meaning their statistical properties, like mean and variance, change over time) but together exhibit ...'''Stationary Time Series:''' A stationary time series possesses constant statistical properties over time. Its mean, variance, and autocorrelation remain relati
  12 KB (1,639 words) - 14:49, 18 March 2025
• CUSUM test
  The Cumulative Sum (CUSUM) test is a powerful statistical tool used to detect small, persistent changes in the mean of a process over ...shifted. Think of it as a sensitive alarm system. Traditional statistical tests like a [[t-test]] require a pre-defined hypothesis and compare two distinct
  11 KB (1,670 words) - 13:31, 18 March 2025
• CI/CD
  ...s from multiple developers into a central repository. Automated builds and tests are run on these merges to detect integration issues as early as possible. * **Build Automation:** This step compiles the code, runs unit tests, and packages the application for deployment. Tools like Maven, Gradle, and
  13 KB (1,895 words) - 14:05, 25 March 2025
• Curve Fitting
  ...values predicted by the curve. This difference is quantified using various statistical measures, like the [[Mean Squared Error]] (MSE). * **Statistical Tests:** Statistical tests can help determine which function best fits the data based on criteria like
  11 KB (1,602 words) - 18:53, 16 March 2025
• Models
  ...crypto futures, ranging from simple technical indicators to sophisticated statistical and machine learning approaches. We will aim to equip you with a foundation * '''Quantitative Models:''' These employ mathematical and statistical techniques to identify trading opportunities.
  11 KB (1,528 words) - 23:37, 19 March 2025
• Differencing
  ...oin over time – *stationary*. This stationarity is vital for applying many statistical and machine learning models used in trading. This article will break down d ...derstand why we need it. A [[Time Series]] is considered stationary if its statistical properties, such as mean and variance, are constant over time. In simpler
  12 KB (1,672 words) - 21:02, 16 March 2025
• Pair trading strategy
  ...ds diligent research, robust risk management, and a solid understanding of statistical analysis. This article will provide a comprehensive introduction to pair tr ...nfirms that there's a long-term equilibrium relationship. [[Cointegration tests]] are crucial for validating potential pairs.
  12 KB (1,650 words) - 08:22, 20 March 2025
• Correlation coefficient
  At its core, correlation describes the statistical relationship between two variables. In trading, these variables are typical ...*Dedicated Statistical Software:** Packages like R and SPSS offer advanced statistical analysis capabilities.
  12 KB (1,593 words) - 15:33, 18 March 2025
• Quantitative Strategien
  ...tion of market conditions, quantitative strategies employ mathematical and statistical models to identify and execute trading opportunities. This article will pro ...ven Decision Making:''' All decisions are grounded in data analysis, using statistical techniques to identify edges.
  11 KB (1,512 words) - 17:02, 20 March 2025
• Backtesting bias
  * **Robustness Testing:** Subject your strategy to various stress tests. Vary the parameters slightly and observe how the performance changes. A * **Statistical Significance Testing:** Use statistical tests (e.g., [[Monte Carlo simulation]]) to determine whether the observed perfor
  12 KB (1,646 words) - 04:40, 16 March 2025
• Risk of Curve Fitting
  ...ures]] trading, represents a significant and often overlooked risk. It’s a statistical pitfall that can lead to the development of trading strategies that *appear ...Furthermore, crypto markets are notoriously non-stationary, meaning their statistical properties change over time. A strategy that worked well in a bull market
  12 KB (1,731 words) - 00:06, 21 March 2025
• Backtesting Bias
  * **Statistical Significance Testing:** Use statistical tests to determine whether the observed performance is statistically significant * **Robustness Testing:** Subject your strategy to a variety of stress tests and scenarios to assess its resilience to different market conditions. Con
  11 KB (1,539 words) - 08:26, 25 March 2025
• Pairs trading
  ...nship between the two assets. This is often done using historical data and statistical measures like [[correlation coefficient]] and [[cointegration]]. ...s a more sophisticated statistical measure than correlation. Cointegration tests whether a linear combination of two or more time series is stationary (mean
  12 KB (1,667 words) - 08:25, 20 March 2025
• Pair trading
  ...stable pattern. This pattern can be expressed as a ratio, a spread, or a statistical measure like co-integration. ...tion, cointegration considers the time series properties of the assets and tests if a linear combination of them is stationary. This means the spread betwee
  12 KB (1,641 words) - 08:21, 20 March 2025
• Augmented Dickey-Fuller (ADF) Test
  ...able predictions. The [[Augmented Dickey-Fuller (ADF) test]] is a powerful statistical tool used to determine whether a time series is stationary. This article wi ...rading]], require stationary data for accurate forecasting. If the data’s statistical properties change over time, the model’s predictions will become increasi
  12 KB (1,766 words) - 09:59, 18 March 2025

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