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Volatility Models & Stochastic Processes

Models for evolving volatility, diffusion, jumps and the stochastic processes underlying financial prices and rates. This category groups related methods so readers can move from the underlying idea to implementation, interpretation and model risk without searching across an undifferentiated master list.

32 conceptsDefinitions + formulasWorked mini-examples

What this category covers

Models for evolving volatility, diffusion, jumps and the stochastic processes underlying financial prices and rates. 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 points

All Volatility Models & Stochastic Processes concepts

32 entries
Quantitative Finance

APARCH Model

APARCH Model is a quantitative model or framework used in volatility models & stochastic processes 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 Finance

ARCH Model

ARCH Model is a quantitative model or framework used in volatility models & stochastic processes 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 Finance

Close-to-Close Volatility

Close-to-Close Volatility is a quantitative-finance concept used within volatility models & stochastic processes. It provides a precise language for describing how market data, uncertainty, models or portfolio decisions are measured and tested.

Quantitative Finance

Compound Poisson Process

Compound Poisson 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 Finance

Conditional Volatility

Conditional Volatility is a quantitative-finance concept used within volatility models & stochastic processes. It provides a precise language for describing how market data, uncertainty, models or portfolio decisions are measured and tested.

Quantitative Finance

Cox-Ingersoll-Ross Process

Cox-Ingersoll-Ross 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 Finance

Diffusion Process

Diffusion 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 Finance

Dupire Local Volatility

Dupire Local Volatility is a quantitative-finance concept used within volatility models & stochastic processes. It provides a precise language for describing how market data, uncertainty, models or portfolio decisions are measured and tested.

Quantitative Finance

EGARCH Model

EGARCH Model is a quantitative model or framework used in volatility models & stochastic processes 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 Finance

EWMA Volatility

EWMA Volatility is a quantitative-finance concept used within volatility models & stochastic processes. It provides a precise language for describing how market data, uncertainty, models or portfolio decisions are measured and tested.

Quantitative Finance

FIGARCH Model

FIGARCH Model is a quantitative model or framework used in volatility models & stochastic processes 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 Finance

Forward Volatility

Forward Volatility is a quantitative-finance concept used within volatility models & stochastic processes. It provides a precise language for describing how market data, uncertainty, models or portfolio decisions are measured and tested.

Quantitative Finance

GARCH Model

GARCH Model is a quantitative model or framework used in volatility models & stochastic processes 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 Finance

Garman-Klass Volatility

Garman-Klass Volatility is a quantitative-finance concept used within volatility models & stochastic processes. It provides a precise language for describing how market data, uncertainty, models or portfolio decisions are measured and tested.

Quantitative Finance

GJR-GARCH Model

GJR-GARCH Model is a quantitative model or framework used in volatility models & stochastic processes 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 Finance

HARCH Model

HARCH Model is a quantitative model or framework used in volatility models & stochastic processes 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 Finance

Hawkes Process

Hawkes 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 Finance

Heston Stochastic Volatility Model

Heston Stochastic Volatility Model is a quantitative model or framework used in volatility models & stochastic processes 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 Finance

Instantaneous Volatility

Instantaneous Volatility is a quantitative-finance concept used within volatility models & stochastic processes. It provides a precise language for describing how market data, uncertainty, models or portfolio decisions are measured and tested.

Quantitative Finance

Ito Process

Ito 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 Finance

Jump Diffusion Process

Jump Diffusion 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 Finance

Levy Process

Levy 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 Finance

Local Volatility Model

Local Volatility Model is a quantitative model or framework used in volatility models & stochastic processes 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 Finance

Local-Stochastic Volatility Model

Local-Stochastic Volatility Model is a quantitative model or framework used in volatility models & stochastic processes 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 Finance

Long-Run Volatility

Long-Run Volatility is a quantitative-finance concept used within volatility models & stochastic processes. It provides a precise language for describing how market data, uncertainty, models or portfolio decisions are measured and tested.

Quantitative Finance

Markov Process

Markov 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 Finance

Mean-Reverting Process

Mean-Reverting 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 Finance

Ornstein-Uhlenbeck Process

Ornstein-Uhlenbeck 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 Finance

Parkinson Volatility

Parkinson Volatility is a quantitative-finance concept used within volatility models & stochastic processes. It provides a precise language for describing how market data, uncertainty, models or portfolio decisions are measured and tested.

Quantitative Finance

Poisson Jump Process

Poisson Jump 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 Finance

Range-Based Volatility

Range-Based Volatility is a quantitative-finance concept used within volatility models & stochastic processes. It provides a precise language for describing how market data, uncertainty, models or portfolio decisions are measured and tested.

Quantitative Finance

Risk-Neutral Measure

Risk-Neutral Measure is a quantitative measure used to summarize a specific property of returns, risk, dependence or model performance. Its interpretation depends on the sampling window, benchmark, frequency and assumptions used to construct it.

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