Economic Variables And Asset Returns Using Monte Carlo Technique

1428 Words Mar 31st, 2015 6 Pages
1. Introduction
Economic trends vary from time to time. No one ensures today’s gain will lead to the consequence that I will still profit tomorrow. Therefore, it is truly crucial to generate scenarios for various economic variables and asset returns using Monte Carlo technique across multiple time periods. Moreover, many economic variables such as equity returns, credit transitions and exchange rates are stochastic processes. As a simple illustration for equity scenarios, we can use the basic Geometric Brownian Motion, which is given by: , which is unpredictable ‘random shocks’. In order to deal with the randomness, Economic Scenario Generators produce the forward-looking situations for a specified set of risk factors.
Generally, ESG widely uses in two main directions: real-world projections for risk management and market-consistent valuation for pricing. The market-consistent valuation, also known as risk-neutral valuation will be discussed in the following sections.
2. Liability Valuation
2.1 Cash Flows
A UK based insurance company has recently sold retirement products that offer policyholders a lump sum of £500,000 at retirement. All policyholders will retire in exactly 15 years. Ignoring fees, commissions, margins for profits, etc., how much should the company charge for such a product? From the above graph, we know no inflows and outflows during the first 14 years while in the fifteenth years, a lump sum cash flow of £500,000 will be paid…
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