Interest Rates and Insurance Company Investment Behavior

2019 ◽  
Author(s):  
Ali K. Ozdagli ◽  
Zixuan (Kevin) Wang
Keyword(s):  
Interest Rates ◽  
Investment Behavior ◽  
Insurance Company

scholarly journals PERHITUNGAN PREMI ASURANSI JOINT LIFE DENGAN MODEL VASICEK DAN CIR

2019 ◽  
Vol 8 (3) ◽  
pp. 246
Author(s):  
I MADE WAHYU WIGUNA ◽  
KETUT JAYANEGARA ◽  
I NYOMAN WIDANA
Keyword(s):  
Stochastic Process ◽  
Interest Rates ◽  
Life Insurance ◽  
Insurance Premium ◽  
Insurance Contract ◽  
Insurance Company ◽  
Vasicek Model ◽  
Cir Model ◽  
Premium Payment ◽  
Premium Price

Premium is a sum of money that must be paid by insurance participants to insurance company, based on  insurance contract. Premium payment are affected by interest rates. The interest rates change according to stochastic process. The purpose of this work is to calculate the price of joint life insurance premiums with Vasicek and CIR models. The price of a joint life insurance premium with Vasicek and CIR models, at the age of the insured 35 and 30 years has increased until the last year of the contract. The price of a joint life insurance premium with Vasicek model is more expensive than the premium price using CIR model.

scholarly journals The Optimal Strategy of Reinsurance-Investment Problem for an Insurer with Dynamic Income Under Stochastic Interest Rate

2016 ◽  
Vol 4 (3) ◽  
pp. 244-257
Author(s):  
Delei Sheng
Keyword(s):  
Interest Rate ◽  
Interest Rates ◽  
Control Technique ◽  
Stochastic Interest Rate ◽  
Insurance Company ◽  
Power Utility ◽  
Investment Problem ◽  
Stochastic Interest ◽  
Hamilton Jacobi Bellman ◽  
Constant Interest Rate

AbstractThis paper considers the reinsurance-investment problem for an insurer with dynamic income to balance the profit of insurance company and policy-holders. The insurer’s dynamic income is given by a net premium minus a dynamic reward budget item and the net premium is obtained according to the expected premium principle. Applying the stochastic control technique, a Hamilton-Jacobi-Bellman equation is established under stochastic interest rate model and the explicit solution is obtained by maximizing the insurer’s power utility of terminal wealth. In addition, the comparison with corresponding results under constant interest rate helps us to understand the role and influence of stochastic interest rates more in-depth.

Optimal stopping of a risk process: model with interest rates

2002 ◽  
Vol 39 (2) ◽  
pp. 261-270 ◽  
Author(s):  
Bogdan Krzysztof Muciek
Keyword(s):  
Interest Rates ◽  
Optimal Stopping ◽  
Process Model ◽  
Stopping Time ◽  
Risk Process ◽  
Risk Theory ◽  
Dynamic Programming Method ◽  
Insurance Company ◽  
Initial Capital ◽  
The Times

The following problem in risk theory is considered. An insurance company, endowed with an initial capital a ≥ 0, receives premiums and pays out claims that occur according to a renewal process {N(t), t ≥ 0}. The times between consecutive claims are i.i.d. The sequence of successive claims is a sequence of i.i.d. random variables. The capital of the company is invested at interest rate α ∊ [0,1], claims increase at rate β ∊ [0,1]. The aim is to find the stopping time that maximizes the capital of the company. A dynamic programming method is used to find the optimal stopping time and to specify the expected capital at that time.

Optimal stopping of a risk process: model with interest rates

2002 ◽  
Vol 39 (02) ◽  
pp. 261-270 ◽  
Author(s):  
Bogdan Krzysztof Muciek
Keyword(s):  
Interest Rates ◽  
Optimal Stopping ◽  
Process Model ◽  
Stopping Time ◽  
Risk Process ◽  
Risk Theory ◽  
Dynamic Programming Method ◽  
Insurance Company ◽  
Initial Capital ◽  
The Times

The following problem in risk theory is considered. An insurance company, endowed with an initial capital a ≥ 0, receives premiums and pays out claims that occur according to a renewal process {N(t), t ≥ 0}. The times between consecutive claims are i.i.d. The sequence of successive claims is a sequence of i.i.d. random variables. The capital of the company is invested at interest rate α ∊ [0,1], claims increase at rate β ∊ [0,1]. The aim is to find the stopping time that maximizes the capital of the company. A dynamic programming method is used to find the optimal stopping time and to specify the expected capital at that time.

scholarly journals The Effects on Investment Behavior of Zero Interest Rate Policy—Evidence From a Roulette Experiment

2019 ◽  
Vol 6 (4) ◽  
pp. 18 ◽  
Author(s):  
Christian A. Conrad
Keyword(s):  
Interest Rate ◽  
Interest Rates ◽  
Risk Taking ◽  
Investment Decision ◽  
Investment Behavior ◽  
Real Economy ◽  
Interest Rate Policy ◽  
Capital Costs ◽  
Investment Decision Making ◽  
Negative Interest Rates

This paper examines the effects of interest rate cuts on investment behavior. The methodology is to simulate investment decision making under different capital costs. The experiment showed that decreasing interest rates encourage risk-taking. With the decreased interest rate as borrowing costs the risk taking increased weakly but continuously. The risk taking increased strongly when the interest rate reached zero. Thus the experiment showed excessive risk-taking when there were no capital costs. This finding supports the hypothesis that extreme expansive monetary policy with low, zero or negative interest rates encourage financial bubbles and overinvestments or wrong investments in the real economy.

Lumpy Investment, Business Cycles, and Stimulus Policy

2021 ◽  
Vol 111 (1) ◽  
pp. 364-396 ◽  
Author(s):  
Thomas Winberry
Keyword(s):  
Interest Rate ◽  
Business Cycles ◽  
Interest Rates ◽  
Real Interest Rate ◽  
Extensive Margin ◽  
Investment Behavior ◽  
The Real ◽  
Lumpy Investment ◽  
Aggregate Investment ◽  
Micro Level

I study the aggregate implications of micro-level lumpy investment in a model consistent with the empirical dynamics of the real interest rate. The elasticity of aggregate investment with respect to shocks is procyclical because more firms are likely to make an extensive margin investment in expansions than in recessions. Matching the dynamics of the real interest rate is key to generating this result because it disciplines the interest-elasticity of investment and avoids counterfactual behavior of the model that would otherwise eliminate most of the procyclical responsiveness. Therefore, data on interest rates place important discipline in aggregating micro-level investment behavior. (JEL D25, E13, E22, E23, E43, G31, H25)

EFFICIENT DYNAMIC HEDGING FOR LARGE VARIABLE ANNUITY PORTFOLIOS WITH MULTIPLE UNDERLYING ASSETS

2020 ◽  
Vol 50 (3) ◽  
pp. 913-957
Author(s):  
X. Sheldon Lin ◽  
Shuai Yang
Keyword(s):  
Interest Rates ◽  
Computing Time ◽  
Insurance Companies ◽  
Insurance Company ◽  
Simulation Approach ◽  
Stochastic Interest Rates ◽  
Dynamic Hedging ◽  
Market Risks ◽  
Stochastic Interest ◽  
Hedging Portfolio

AbstractA variable annuity (VA) is an equity-linked annuity that provides investment guarantees to its policyholder and its contributions are normally invested in multiple underlying assets (e.g., mutual funds), which exposes VA liability to significant market risks. Hedging the market risks is therefore crucial in risk managing a VA portfolio as the VA guarantees are long-dated liabilities that may span decades. In order to hedge the VA liability, the issuing insurance company would need to construct a hedging portfolio consisting of the underlying assets whose positions are often determined by the liability Greeks such as partial dollar Deltas. Usually, these quantities are calculated via nested simulation approach. For insurance companies that manage large VA portfolios (e.g., 100k+ policies), calculating those quantities is extremely time-consuming or even prohibitive due to the complexity of the guarantee payoffs and the stochastic-on-stochastic nature of the nested simulation algorithm. In this paper, we extend the surrogate model-assisted nest simulation approach in Lin and Yang [(2020) Insurance: Mathematics and Economics, 91, 85–103] to efficiently calculate the total VA liability and the partial dollar Deltas for large VA portfolios with multiple underlying assets. In our proposed algorithm, the nested simulation is run using small sets of selected representative policies and representative outer loops. As a result, the computing time is substantially reduced. The computational advantage of the proposed algorithm and the importance of dynamic hedging are further illustrated through a profit and loss (P&L) analysis for a large synthetic VA portfolio. Moreover, the robustness of the performance of the proposed algorithm is tested with multiple simulation runs. Numerical results show that the proposed algorithm is able to accurately approximate different quantities of interest and the performance is robust with respect to different sets of parameter inputs. Finally, we show how our approach could be extended to potentially incorporate stochastic interest rates and estimate other Greeks such as Rho.

scholarly journals PENENTUAN CADANGAN PREMI UNTUK ASURANSI JOINT LIFE

2016 ◽  
Vol 5 (1) ◽  
pp. 32
Author(s):  
NI LUH PUTU RATNA DEWI ◽  
I NYOMAN WIDANA ◽  
DESAK PUTU EKA NILAKUSMAWATI
Keyword(s):  
Interest Rates ◽  
Life Insurance ◽  
Calculation Method ◽  
First Year ◽  
Insurance Company ◽  
Premium Payment ◽  
Mortality Table ◽  
Constant Interest ◽  
Annual Premium

Premium reserve is a number of fund that need to be raised by insurance company in preparation for the payment of claims. This study aims to get the formula of premium reserve as well as the value of the premium reserve for joint life insurance by using retrospective calculation method. Joint life insurance participants in this study are limited to 2 people. Calculations in this study is using Indonesian Mortality Table (TMI) 2011, joint life mortality tables, commutation tables, value of annuities, value of single premiums and constant annual premium and using constant interest rates of 5%. The results showed that by using age of the participant insurance joint life of x = 50 and y = 45 years and the premium payment period of t = 10 years, we obtained that the value of premium reserve from the end of the first year until the  end of the 11th year has increased every year, while the value of premium reserves from the end of the 12th year and so on until a lifetime has decreased every year.

scholarly journals Explicit Solution of the Optimal Reinsurance-Investment Problem with Promotion Budget

2016 ◽  
Vol 4 (2) ◽  
pp. 131-148
Author(s):  
Delei Sheng
Keyword(s):  
Interest Rates ◽  
Closed Form Solution ◽  
Hjb Equation ◽  
Form Solution ◽  
Control Technique ◽  
Insurance Company ◽  
Risk Management Process ◽  
Stochastic Interest ◽  
Hamilton Jacobi Bellman ◽  
Policy Holder

AbstractThe lack of surrendering profits to policy holder leads to the development of this paper. For an insurer with promotion budget, both the interests of the insurance company and policy-holder are given a balance. In addition, promotion budget is introduced into the risk management process, which makes cheap reinsurance more fair. This article aims at obtaining the explicit strategy and value function for an investment-reinsurance problem under stochastic interest rates. Applying stochastic control technique, a Hamilton-Jacobi-Bellman (HJB) equation is established. The closed-form solution for the HJB equation and a verification theorem are obtained. At last, some numerical analysises illustrate the impacts of different parameters.

scholarly journals GEOGRAPHICAL DIVERSIFICATION AND LONGEVITY RISK MITIGATION IN ANNUITY PORTFOLIOS

2021 ◽  
pp. 1-36
Author(s):  
Clemente De Rosa ◽  
Elisa Luciano ◽  
Luca Regis
Keyword(s):  
Interest Rates ◽  
Risk Mitigation ◽  
Longevity Risk ◽  
Insurance Company ◽  
International Expansion ◽  
Life Insurance Company ◽  
Continuous Time Model ◽  
Time Model ◽  
Risk Margin ◽  
Geographical Diversification

ABSTRACT This paper provides a method to assess the risk relief deriving from a foreign expansion by a life insurance company. We build a parsimonious continuous-time model for longevity risk that captures the dependence across different ages in domestic versus foreign populations. We calibrate the model to portray the case of a UK annuity portfolio expanding internationally toward Italian policyholders. The longevity risk diversification benefits of an international expansion are sizable, in particular when interest rates are low. The benefits are judged based on traditional measures, such as the Risk Margin or volatility reduction, and on a novel measure, the Diversification Index.

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