Interest Rate Simulation Crash Course – Detailed Course Description
|Course Content|||||Introduction|||||Buy this Course|||||Read Course Online|
a. Equilibrium vs. No-Arbitrage models
2. BASIC CONCEPTS
3. DERIVATION OF THE ZERO AND FORWARD CURVES
b. Deriving the Zero Curve
c. Deriving the Forward Curve
4. BUILDING EQUITIES, COMMODITIES, CURRENCIES & INTEREST RATE MONTE CARLO SIMULATORS IN EXCEL
f. Linking Monte Carlo Simulation with Binomial Trees and the Black Scholes model
5. ONE-FACTOR MODELS
b. Black Derman Toy (BDT) Model
6. MULTIPLE FACTOR MODELS
7. MONTE CARLO SIMULATION APPLICATION: FORECASTING MONETARY POLICY RATE DECISION FOR PAKISTAN
Yes – Available for sale
Construction of BDT
How to utilize the results of the BDT model
Interest rates tend to fluctuate on a day to day basis as well as occasionally when there is a regime shift. These changes can signify a significant risk to those portfolios/ instruments whose values are derived from movements in the interest rate. Over the years many tools and products have been created that seek to hedge against or reduce and /or control such risk.
Models are usually employed in order to value instruments which are dependent on interest rates as well as to value the new hedge instruments.
Models are defined by state variables and their processes. The values taken by the state variables that constitute a model give the position or state of the item being model. The processes determine how the state variables change over time. Interest rate processes or changes in state variables are usually stochastic processes, i.e. they incorporate an element of randomness. These processes can usually be divided into a non-random deterministic component, called drift and a random, noise term called volatility.
The purpose of interest rate models therefore is firstly to understand interest rate behaviour. By being able to study the distributional and statistically properties of interest rate movements such as the width of the distribution, its shape, the likelihood of reaching certain levels, etc, the risk manager is better able to discern interest rate movements, determine the likely range of future values and estimate the probabilities of losing more that a given amount. Understanding the movements helps in setting acceptable limits; helps in setting economic policy; helps in valuing financial instruments more reliably or hedging them more effectively.
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