FINANCE 361 Modern Investment Theory and Management - Course Outlines (2024)

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2. **Portfolio

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Moreover, I have a solid grasp of empirical ** in real-world investment scenarios.

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Moreover, I have a solid grasp of empirical finance, which of Financial I have a solid grasp of empirical finance, which involves: solid grasp of empirical finance, which involves analyzinglid grasp of empirical finance, which involves analyzing real Understandingirical finance, which involves analyzing real-worldal finance, which involves analyzing real-world datance, which involves analyzing real-world data to test, which involves analyzing real-world data to test financialh involves analyzing real-world data to test financial theoriesvolves analyzing real-world data to test financial theories and marketreal-world data to test financial theories and models.data to test financial theories and models. Thisa to test financial theories and models. This includesto test financial theories and models. This includes understandingt financial theories and models. This includes understanding statisticalcial theories and models. This includes understanding statistical techniques theeories and models. This includes understanding statistical techniques and.nd models. This includes understanding statistical techniques and econ canels. This includes understanding statistical techniques and econometric howcludes understanding statistical techniques and econometric methods limits impact statistical techniques and econometric methods commonlytistical techniques and econometric methods commonly used of financialeconometric methods commonly used inric methods commonly used in empirical research withinic methods commonly used in empirical research within thehods commonly used in empirical research within the field of finance.

Risk managements commonly used in empirical research within the field of finance.

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Risk management, particularlythe field of finance.

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Risk management, particularly concerning fixed finance.

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Risk management, particularly concerning fixed income securities, is another area of Managementnt, particularly concerning fixed income securities, is another area of expertise. particularly concerning fixed income securities, is another area of expertise. Icularly concerning fixed income securities, is another area of expertise. I understand concerning fixed income securities, is another area of expertise. I understand the fixed income securities, is another area of expertise. I understand the intricfixed income securities, is another area of expertise. I understand the intricaciesed income securities, is another area of expertise. I understand the intricacies of income securities, is another area of expertise. I understand the intricacies of fixedome securities, is another area of expertise. I understand the intricacies of fixed incomeurities, is another area of expertise. I understand the intricacies of fixed income markets, is another area of expertise. I understand the intricacies of fixed income markets, another area of expertise. I understand the intricacies of fixed income markets, including area of expertise. I understand the intricacies of fixed income markets, including interesta of expertise. I understand the intricacies of fixed income markets, including interest rateexpertise. I understand the intricacies of fixed income markets, including interest rate riskI understand the intricacies of fixed income markets, including interest rate risk, creditnderstand the intricacies of fixed income markets, including interest rate risk, credit riskand the intricacies of fixed income markets, including interest rate risk, credit risk, intricacies of fixed income markets, including interest rate risk, credit risk, ands of fixed income markets, including interest rate risk, credit risk, and duration of fixed income markets, including interest rate risk, credit risk, and duration management fixed income markets, including interest rate risk, credit risk, and duration management strategiesome markets, including interest rate risk, credit risk, and duration management strategies.

ts, including interest rate risk, credit risk, and duration management strategies.

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Furthermore, Irest rate risk, credit risk, and duration management strategies.

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Furthermore, I'm familiar, credit risk, and duration management strategies.

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Furthermore, I'm familiar with financiald duration management strategies.

Furthermore, I'm familiar with financial machineation management strategies.

Furthermore, I'm familiar with financial machine learningmanagement strategies.

Furthermore, I'm familiar with financial machine learning techniquesent strategies.

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6. **Equilibrium asset pricinge returns while minimizing risk. Mean-variance portfolio optimization is a key concept within portfolio theory.

7. **Equilibrium asset pricing modelsmentshile minimizing risk. Mean-variance portfolio optimization is a key concept within portfolio theory.

8. Equilibrium asset pricing models:ile minimizing risk. Mean-variance portfolio optimization is a key concept within portfolio theory.

9. Equilibrium asset pricing models: This minimizing risk. Mean-variance portfolio optimization is a key concept within portfolio theory.

10. Equilibrium asset pricing models: This includesinimizing risk. Mean-variance portfolio optimization is a key concept within portfolio theory.

11. Equilibrium asset pricing models: This includes theoriesimizing risk. Mean-variance portfolio optimization is a key concept within portfolio theory.

12. Equilibrium asset pricing models: This includes theories likeing risk. Mean-variance portfolio optimization is a key concept within portfolio theory.

13. Equilibrium asset pricing models: This includes theories like the Capital Assetg risk. Mean-variance portfolio optimization is a key concept within portfolio theory.

14. Equilibrium asset pricing models: This includes theories like the Capital Asset Pricing Alex. Mean-variance portfolio optimization is a key concept within portfolio theory.

15. Equilibrium asset pricing models: This includes theories like the Capital Asset Pricing Modeln-variance portfolio optimization is a key concept within portfolio theory.

16. Equilibrium asset pricing models: This includes theories like the Capital Asset Pricing Model ( and Alan J. Marcus,optimization is a key concept within portfolio theory.

17. Equilibrium asset pricing models: This includes theories like the Capital Asset Pricing Model (CAPM) and the Arbitrage Pricing Theory (APTimization is a key concept within portfolio theory.

18. Equilibrium asset pricing models: This includes theories like the Capital Asset Pricing Model (CAPM) and the Arbitrage Pricing Theory (APT),ization is a key concept within portfolio theory.

19. Equilibrium asset pricing models: This includes theories like the Capital Asset Pricing Model (CAPM) and the Arbitrage Pricing Theory (APT), which sourceconcept within portfolio theory.

20. Equilibrium asset pricing models: This includes theories like the Capital Asset Pricing Model (CAPM) and the Arbitrage Pricing Theory (APT), which attemptpt within portfolio theory.

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7. Empirical tests: Refers to the applicationnd the Arbitrage Pricing Theory (APT), which attempt to explain how assets are priced in financial markets based on risk and return considerations.

8. Empirical tests: Refers to the application ofbitrage Pricing Theory (APT), which attempt to explain how assets are priced in financial markets based on risk and return considerations.

9. Empirical tests: Refers to the application of statisticalage Pricing Theory (APT), which attempt to explain how assets are priced in financial markets based on risk and return considerations.

10. Empirical tests: Refers to the application of statistical andheory (APT), which attempt to explain how assets are priced in financial markets based on risk and return considerations.

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14. Empirical tests: Refers to the application of statistical and econometric methods to my ability to in financial markets based on risk and return considerations.

15. Empirical tests: Refers to the application of statistical and econometric methods to analyze students in understandingsk and return considerations.

16. Empirical tests: Refers to the application of statistical and econometric methods to analyze real-worldnd return considerations.

17. Empirical tests: Refers to the application of statistical and econometric methods to analyze real-world financial considerations.

18. Empirical tests: Refers to the application of statistical and econometric methods to analyze real-world financial data principles.

19. Empirical tests: Refers to the application of statistical and econometric methods to analyze real-world financial data and test inirical tests: Refers to the application of statistical and econometric methods to analyze real-world financial data and test theal tests: Refers to the application of statistical and econometric methods to analyze real-world financial data and test the validitys**: Refers to the application of statistical and econometric methods to analyze real-world financial data and test the validity ofers to the application of statistical and econometric methods to analyze real-world financial data and test the validity of financialrs to the application of statistical and econometric methods to analyze real-world financial data and test the validity of financial theoriesrs to the application of statistical and econometric methods to analyze real-world financial data and test the validity of financial theories andrs to the application of statistical and econometric methods to analyze real-world financial data and test the validity of financial theories and models.

20. Portfolio management: Involves forecasting, constructing, administering, and evaluating investment portfolios. It includes considerations for asset allocation, risk management, and performance evaluation.

21. Fixed interest and international equity investment: Focuses on investments in fixed income securities (like bonds) and international equity markets, including understanding the associated risks and strategies for managing them.

22. Financial machine learning: Refers to the application of machine learning techniques in financial analysis and decision-making processes, including predictive modeling, risk assessment, and algorithmic trading strategies.