What this category covers
Models for serial dependence, stationarity, forecasting, structural breaks and evolving market states. Each concept page explains the quantitative meaning, how the idea is used in portfolio or market analysis, the relevant formula or analytical framework, variables, a compact example and the main limitations to keep in view.
Core concepts
Quick entry pointsAll Time Series Analysis & Forecasting concepts
32 entriesAR(1) Process
AR(1) Process is a stochastic-process concept used to describe how a financial variable evolves through time under uncertainty. Its assumptions about drift, volatility, jumps or mean reversion determine the paths the model can generate and therefore the risks it can represent.
Quantitative FinanceAR(p) Model
AR(p) Model is a quantitative model or framework used in time series analysis & forecasting to convert assumptions and observed market information into a structured estimate, state or decision rule. Its value comes from making the relationships explicit enough to calibrate, test and compare rather than relying on intuition alone.
Quantitative FinanceARIMA Model
ARIMA Model is a quantitative model or framework used in time series analysis & forecasting to convert assumptions and observed market information into a structured estimate, state or decision rule. Its value comes from making the relationships explicit enough to calibrate, test and compare rather than relying on intuition alone.
Quantitative FinanceARIMAX Model
ARIMAX Model is a quantitative model or framework used in time series analysis & forecasting to convert assumptions and observed market information into a structured estimate, state or decision rule. Its value comes from making the relationships explicit enough to calibrate, test and compare rather than relying on intuition alone.
Quantitative FinanceARMA Model
ARMA Model is a quantitative model or framework used in time series analysis & forecasting to convert assumptions and observed market information into a structured estimate, state or decision rule. Its value comes from making the relationships explicit enough to calibrate, test and compare rather than relying on intuition alone.
Quantitative FinanceAugmented Dickey-Fuller Test
Augmented Dickey-Fuller Test is a statistical diagnostic used in time series analysis & forecasting to test a specific property of data, residuals, forecasts or model behavior. The result is evidence about an assumption or hypothesis, not a standalone trading signal.
Quantitative FinanceAutoregressive Distributed Lag Model
Autoregressive Distributed Lag Model is a quantitative model or framework used in time series analysis & forecasting to convert assumptions and observed market information into a structured estimate, state or decision rule. Its value comes from making the relationships explicit enough to calibrate, test and compare rather than relying on intuition alone.
Quantitative FinanceAutoregressive Process
Autoregressive Process is a stochastic-process concept used to describe how a financial variable evolves through time under uncertainty. Its assumptions about drift, volatility, jumps or mean reversion determine the paths the model can generate and therefore the risks it can represent.
Quantitative FinanceBai-Perron Test
Bai-Perron Test is a statistical diagnostic used in time series analysis & forecasting to test a specific property of data, residuals, forecasts or model behavior. The result is evidence about an assumption or hypothesis, not a standalone trading signal.
Quantitative FinanceChow Test
Chow Test is a statistical diagnostic used in time series analysis & forecasting to test a specific property of data, residuals, forecasts or model behavior. The result is evidence about an assumption or hypothesis, not a standalone trading signal.
Quantitative FinanceCointegration Test
Cointegration Test is a statistical diagnostic used in time series analysis & forecasting to test a specific property of data, residuals, forecasts or model behavior. The result is evidence about an assumption or hypothesis, not a standalone trading signal.
Quantitative FinanceCUSUM of Squares Test
CUSUM of Squares Test is a statistical diagnostic used in time series analysis & forecasting to test a specific property of data, residuals, forecasts or model behavior. The result is evidence about an assumption or hypothesis, not a standalone trading signal.
Quantitative FinanceCUSUM Test
CUSUM Test is a statistical diagnostic used in time series analysis & forecasting to test a specific property of data, residuals, forecasts or model behavior. The result is evidence about an assumption or hypothesis, not a standalone trading signal.
Quantitative FinanceDickey-Fuller GLS Test
Dickey-Fuller GLS Test is a statistical diagnostic used in time series analysis & forecasting to test a specific property of data, residuals, forecasts or model behavior. The result is evidence about an assumption or hypothesis, not a standalone trading signal.
Quantitative FinanceDiebold-Mariano Test
Diebold-Mariano Test is a statistical diagnostic used in time series analysis & forecasting to test a specific property of data, residuals, forecasts or model behavior. The result is evidence about an assumption or hypothesis, not a standalone trading signal.
Quantitative FinanceDistributed Lag Model
Distributed Lag Model is a quantitative model or framework used in time series analysis & forecasting to convert assumptions and observed market information into a structured estimate, state or decision rule. Its value comes from making the relationships explicit enough to calibrate, test and compare rather than relying on intuition alone.
Quantitative FinanceDynamic Linear Model
Dynamic Linear Model is a quantitative model or framework used in time series analysis & forecasting to convert assumptions and observed market information into a structured estimate, state or decision rule. Its value comes from making the relationships explicit enough to calibrate, test and compare rather than relying on intuition alone.
Quantitative FinanceDynamic Regression
Dynamic Regression is a regression-based technique used in quantitative finance to estimate how a target variable changes with one or more explanatory variables. In practice, the usefulness of the estimate depends on specification, stability and the treatment of time dependence and heteroskedasticity.
Quantitative FinanceEngle-Granger Test
Engle-Granger Test is a statistical diagnostic used in time series analysis & forecasting to test a specific property of data, residuals, forecasts or model behavior. The result is evidence about an assumption or hypothesis, not a standalone trading signal.
Quantitative FinanceError Correction Model
Error Correction Model is a quantitative model or framework used in time series analysis & forecasting to convert assumptions and observed market information into a structured estimate, state or decision rule. Its value comes from making the relationships explicit enough to calibrate, test and compare rather than relying on intuition alone.
Quantitative FinanceETS Model
ETS Model is a quantitative model or framework used in time series analysis & forecasting to convert assumptions and observed market information into a structured estimate, state or decision rule. Its value comes from making the relationships explicit enough to calibrate, test and compare rather than relying on intuition alone.
Quantitative FinanceExponential Weighted Moving Average Model
Exponential Weighted Moving Average Model is a quantitative model or framework used in time series analysis & forecasting to convert assumptions and observed market information into a structured estimate, state or decision rule. Its value comes from making the relationships explicit enough to calibrate, test and compare rather than relying on intuition alone.
Quantitative FinanceForecast Encompassing Test
Forecast Encompassing Test is a statistical diagnostic used in time series analysis & forecasting to test a specific property of data, residuals, forecasts or model behavior. The result is evidence about an assumption or hypothesis, not a standalone trading signal.
Quantitative FinanceHidden Markov Model
Hidden Markov Model is a quantitative model or framework used in time series analysis & forecasting to convert assumptions and observed market information into a structured estimate, state or decision rule. Its value comes from making the relationships explicit enough to calibrate, test and compare rather than relying on intuition alone.
Quantitative FinanceJohansen Test
Johansen Test is a statistical diagnostic used in time series analysis & forecasting to test a specific property of data, residuals, forecasts or model behavior. The result is evidence about an assumption or hypothesis, not a standalone trading signal.
Quantitative FinanceKPSS Test
KPSS Test is a statistical diagnostic used in time series analysis & forecasting to test a specific property of data, residuals, forecasts or model behavior. The result is evidence about an assumption or hypothesis, not a standalone trading signal.
Quantitative FinanceLinear State-Space Model
Linear State-Space Model is a quantitative model or framework used in time series analysis & forecasting to convert assumptions and observed market information into a structured estimate, state or decision rule. Its value comes from making the relationships explicit enough to calibrate, test and compare rather than relying on intuition alone.
Quantitative FinanceLocal Level Model
Local Level Model is a quantitative model or framework used in time series analysis & forecasting to convert assumptions and observed market information into a structured estimate, state or decision rule. Its value comes from making the relationships explicit enough to calibrate, test and compare rather than relying on intuition alone.
Quantitative FinanceLocal Linear Trend Model
Local Linear Trend Model is a quantitative model or framework used in time series analysis & forecasting to convert assumptions and observed market information into a structured estimate, state or decision rule. Its value comes from making the relationships explicit enough to calibrate, test and compare rather than relying on intuition alone.
Quantitative FinanceMA(q) Model
MA(q) Model is a quantitative model or framework used in time series analysis & forecasting to convert assumptions and observed market information into a structured estimate, state or decision rule. Its value comes from making the relationships explicit enough to calibrate, test and compare rather than relying on intuition alone.
Quantitative FinanceMarkov Switching Model
Markov Switching Model is a quantitative model or framework used in time series analysis & forecasting to convert assumptions and observed market information into a structured estimate, state or decision rule. Its value comes from making the relationships explicit enough to calibrate, test and compare rather than relying on intuition alone.
Quantitative FinanceMoving Average Process
Moving Average Process is a stochastic-process concept used to describe how a financial variable evolves through time under uncertainty. Its assumptions about drift, volatility, jumps or mean reversion determine the paths the model can generate and therefore the risks it can represent.