White Papers & Research
  • White Paper: Optimal Allocation to Deferred Income Annuities (November 2018)

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    In this paper we employ a lifecycle model that uses utility of consumption and bequest to determine an optimal Deferred Income Annuity (DIA) purchase policy. We lay out a mathematical framework to formalize the optimization process. The method and implementation of the optimization is explained, and the results are then analyzed. We extend our model to control for asset allocation and show how the purchase policy changes when one is allowed to vary asset allocation. Our results indicate that (i.) refundable DIAs are less appealing than non-refundable DIAs because of the loss of mortality credits; (ii.) the DIA allocation region is larger under the fixed asset allocation strategy due to it becoming a proxy for fixed-income allocation; and (iii.) when the investor is allowed to change asset-allocation, DIA allocation becomes less appealing. However, a case for higher DIA allocation can be made for those individuals who perceive their longevity to be higher than the population.

  • Research: Evaluating Guaranteed Income Across Different Types of Annuities (October 2018)

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    Data from the CANNEX annuity pricing and analysis service shows that different types of annuities with equivalent benefits provide higher income guarantees depending upon gender, how long income is delayed, and whether it is for a single person or a couple.

  • Research: Accumulation Value of Fixed Annuities (MYGA & FIA): Understanding Yields by Product Design (April 2018)

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    Data from the CANNEX annuity comparison system shows how the two types of fixed annuities behave very differently based on strategy and crediting method.

  • Research: Buffer Strategies Outside of Structured Notes (December 2017)

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  • White Paper: Approximate Solutions to Retirement Spending Problems and The Optimality of Ruin (March 2017)

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    This paper summarizes an enhancement to a patented methodology that optimizes a withdrawal strategy from an investment account to support sustainable income in retirement. Originally developed in 2011 by Moshe Milevsky and Huaxiong Huang, this retirement spending policy uses stochastic control theory and dynamic programming to adjust withdrawal rates based on market performance as well as an investor’s risk preference and mortality.

  • White Paper: Determining the Economic Suitability of a VA Transaction (August 2016/Revised March 2017)

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    In this paper we propose a scoring methodology for VA transactions that is intended to improve current evaluation practices – and empower financial institutions, their advisors and clients to make more informed decisions about annuity transactions.

  • Research: U.S. Income Annuity Buyer Study (2016)

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    This report provides a comprehensive review of Income Annuity sales from 2012 through third quarter 2015 and representing contract-level data from 22 manufacturers (83 percent of the industry). The 2016 Income Annuity Buyers Study was conducted by the LIMRA Secure Retirement Institute in partnership with CANNEX. Details around product features and buyer demographics are provided along with insights on purchasing behavior and trends.

  • White Paper: Product Allocation for Retirement Income - PrARI (May 2015)

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    With a myriad of investment and insurance products available in the market to address retirement income concerns, the new challenge is answering the question: Which of these products are suitable and in what proportions? This document examines the risks in retirement, explains the concept of product allocation, and shows how to apply this new approach to retirement income planning.

  • Research: Features in Income Annuities (May 2013)

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    Carriers continue to add many features to the income annuity to help broaden their appeal. This joint report by CANNEX & LIMRA provides details on which features are currently available on both immediate and deferred income annuities.

  • White Paper: Optimal Initiation of a GLWB in a Variable Annuity: No Arbitrage Approach (February 2013)

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    This paper by H. Huang, M.A. Milevsky and T.S. Salisbury offers a financial economic perspective on the optimal time (and age) at which the owner of a Variable Annuity (VA) policy with a Guaranteed Living Withdrawal Benefit (GLWB) rider should initiate guaranteed lifetime income payments.

    Huang is a Professor of Mathematics and Statistics at York University, Milevsky is Associate Professor of Finance, York University, and Executive Director of the IFID Centre. Salisbury is Professor of Mathematics and Statistics at York University, all in Toronto, Canada.

  • Research: Liquidity Features in Income Annuities (October 2011)

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    This joint report by CANNEX & LIMRA report examines the various forms of liquidity currently available in the market for clients who are living and actively managing their retirement portfolios. Seven of the top 10 participating companies offered a liquidity feature for their 2010 income annuity sales.

  • Research: Features in Income Annuities (June 2007)

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    This original report by CANNEX provides details on which features were available on Single Premium Immediate Annuities (SPIA).

  • White Paper: The Implied Longevity Yield: A Note on Developing an Index for Life Annuities (September 2004)

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    In this paper by M.A. Milevsky an index is developed for tracking the dynamic behavior of life (pension) annuity payouts over time, based on the concept of self-annuitization. The implied longevity yield (ILY) value is defined equal to the internal rate of return (IRR) over a fixed deferral period that an individual would have to earn on their investable wealth if they decided to self-annuitize using a systematic withdrawal plan. A larger ILY number indicates a greater relative benefit from immediate annuitization.

  • White Paper: Exchanging Variable Annuities: An Optimal Test for Suitability (September 2004)

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    In this paper we offer a novel method of assessing whether exchanging one variable annuity (VA) policy for another, destroys or adds value from a purely economic perspective. We do this by decomposing the policy into a portfolio of financial options and then use an option pricing model to compute the difference in aggregate value between the embedded options in the new and old VA.