Predict-then-optimise fits a forecast by a statistical loss (mean squared error, a likelihood) and passes it to an optimiser that chooses the portfolio; the two steps are fitted separately.
Quantitative Finance · Glossary
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Primary & Middle School MathematicsGrades 1–9 Online
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High School MathematicsGrades 10–12 Online
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University Mathematics — Year 1Bachelor Year 1 Online
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University Mathematics — Year 2Bachelor Year 2 Online
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University Mathematics — Year 3Bachelor Year 3 Online
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Primary & Middle School PhysicsGrades 1–9 Online
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High School PhysicsGrades 10–12 Online
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University Physics — Year 1Bachelor Year 1 Online
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University Physics — Year 2Bachelor Year 2 Online
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University Physics — Year 3Bachelor Year 3 Online
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Primary & Middle School BiologyGrades 1–9 Online
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High School BiologyGrades 10–12 Online
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University Biology — Year 1Bachelor Year 1 Online
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University Biology — Year 2Bachelor Year 2 Online
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University Biology — Year 3Bachelor Year 3 Online
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Markets I: The Ecosystem and Exchange-Traded MarketsMarkets Online
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Markets II: Rates, FX and CreditMarkets Online
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Markets III: Commodities, Energy and CryptoMarkets Online
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Quantitative MethodsMethods Online
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Derivatives and VolatilityDerivatives Online
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Rates, Credit, XVA and RiskRates, credit & risk Online
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Research Craft: Predictors, Backtests, Measurement, PortfoliosResearch Online
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Strategies I: Equities and FuturesStrategies Online
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Strategies II: Volatility, Relative Value, Macro and the Bank DesksStrategies Online
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Microstructure and ExecutionExecution Online
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Market Making and High-Frequency TradingMarket making Online
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Machine Learning for MarketsMachine learning Online
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Low-Latency SoftwareTechnology Online
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Networks, Hardware and Trading InfrastructureTechnology Online
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Research, Data and Risk PlatformsTechnology Online
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The Desk and the FirmThe firm Online
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The Industry: Firms, Roles and CareersCareers Online
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The Interview BookCareers Online
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