Stochastic investment model
Appearance
![]() | This article has multiple issues. Please help improve it or discuss these issues on the talk page. (Learn how and when to remove these template messages)
|
A stochastic investment model tries to forecast how returns and prices on different assets or asset classes, (e. g. equities or bonds) vary over time. Stochastic models are not applied for making point estimation rather interval estimation and they use different stochastic processes.[clarification needed] Investment models can be classified into single-asset and multi-asset models. They are often used for actuarial work and financial planning to allow optimization in asset allocation or asset-liability-management (ALM).
Single-asset models
[edit]Interest rate models
[edit]Interest rate models can be used to price fixed income products. They are usually divided into one-factor models and multi-factor assets.
One-factor models
[edit]- Black–Derman–Toy model
- Black–Karasinski model
- Cox–Ingersoll–Ross model
- Ho–Lee model
- Hull–White model
- Kalotay–Williams–Fabozzi model
- Merton model
- Rendleman–Bartter model
- Vasicek model
Multi-factor models
[edit]Term structure models
[edit]Stock price models
[edit]Inflation models
[edit]Multi-asset models
[edit]- ALM.IT (GenRe) model
- Cairns model
- FIM-Group model
- Global CAP:Link model
- Ibbotson and Sinquefield model
- Morgan Stanley model
- Russel–Yasuda Kasai model
- Smith's jump diffusion model
- TSM (B & W Deloitte) model
- Watson Wyatt model
- Whitten & Thomas model
- Wilkie investment model
- Yakoubov, Teeger & Duval model
Further reading
[edit]- Wilkie, A. D. (1984) "A stochastic investment model for actuarial use", Transactions of the Faculty of Actuaries, 39: 341-403
- Østergaard, Søren Duus (1971) "Stochastic Investment Models and Decision Criteria", The Swedish Journal of Economics, 73 (2), 157-183 JSTOR 3439055
- Sreedharan, V. P.; Wein, H. H. (1967) "A Stochastic, Multistage, Multiproduct Investment Model", SIAM Journal on Applied Mathematics, 15 (2), 347-358 JSTOR 2946287