SSRN Author: Moshe A. MilevskyMoshe A. Milevsky SSRN Content
http://www.ssrn.com/author=1080
http://www.ssrn.com/rss/en-usFri, 11 Aug 2017 04:24:16 GMTeditor@ssrn.com (Editor)Fri, 11 Aug 2017 04:24:16 GMTwebmaster@ssrn.com (WebMaster)SSRN RSS Generator 1.0New: Tax Effects in Canadian Equity Option MarketsThe Canadian Income Tax Act induces individual investors to close their short equity option positions at the end of the year and, if necessary, reopen them at the beginning of next year. This article analyzes the conditions under which it is optimal to close or leave open a short option position over the tax year boundary. The analysis shows that the latter decision depends on transaction costs, the investor’s marginal tax rate, the interest rates, the initial and end-of-the-year option prices, as well as whether the option position is naked or covered. The article also examines the impact of tax regulations in Canada on the pricing of naked vs. covered call options and American vs. European options.
http://www.ssrn.com/abstract=2631564
http://www.ssrn.com/1616114.htmlThu, 10 Aug 2017 06:58:08 GMTREVISION: Approximate Solutions to Retirement Spending Problems and the Optimality of RuinMilevsky and Huang (2011) investigated the optimal retirement spending policy for a utility-maximizing retiree facing a stochastic lifetime but assuming deterministic investment returns. They solved the problem using techniques from the calculus of variations and derived analytic expressions for the optimal spending rate and wealth depletion time under the Gompertz law of mortality. Of course, in the real world financial returns are stochastic as well as lifetimes, raising the question of whether their qualitative insights and approximations are generalizable or practical.
We solve the retirement income problem when investment returns are indeed stochastic using numerical PDE methods, assuming the principles of stochastic control theory and dynamic programming. But then -- and this is key -- we compare the proper optimal spending rates to the analytic approach presented in Milevsky and Huang (2011) by updating the portfolio wealth inputs to current market values. Our main practical ...
http://www.ssrn.com/abstract=2944125
http://www.ssrn.com/1579273.htmlSun, 02 Apr 2017 14:30:08 GMTREVISION: Approximate Solutions to Retirement Spending Problems and the Optimality of RuinMilevsky and Huang (2011) investigated the optimal retirement spending policy for a utility-maximizing retiree facing a stochastic lifetime but assuming deterministic investment returns. They solved the problem using techniques from the calculus of variations and derived analytic expressions for the optimal spending rate and wealth depletion time under the Gompertz law of mortality. Of course, in the real world financial returns are stochastic as well as lifetimes, raising the question of whether their qualitative insights and approximations are generalizable or practical.
We solve the retirement income problem when investment returns are indeed stochastic using numerical PDE methods, assuming the principles of stochastic control theory and dynamic programming. But then -- and this is key -- we compare the proper optimal spending rates to the analytic approach presented in Milevsky and Huang (2011) by updating the portfolio wealth inputs to current market values. Our main practical ...
http://www.ssrn.com/abstract=2944125
http://www.ssrn.com/1579008.htmlFri, 31 Mar 2017 14:42:58 GMTNew: Retirement Spending and Biological AgeWe solve a retirement lifecycle model in which the consumer's age does not move in lockstep with calendar time. Instead, biological age increases at a stochastic non-linear rate in chronological age, which one can think of as working with a clock that occasionally moves backwards in time. Our paper is inspired by the growing body of medical literature that has identified biomarkers of aging which -- practically speaking -- offer better estimates of expected remaining lifetime and future mortality rates. It isn't farfetched to argue that in the not-too-distant future of wearable technology, personal age will be more closely associated with biological time vs. calendar age or time. Thus, after introducing our stochastic mortality model we derive optimal consumption rates in a classic Yaari (1965) framework adjusted to our proper clock and time. In addition to the normative implications of having access to biological age, our positive objective is to partially explain the ...
http://www.ssrn.com/abstract=2918055
http://www.ssrn.com/1567048.htmlThu, 16 Feb 2017 08:48:19 GMTNew: The Implied Longevity Curve: How Long Does the Market Think You Are Going to Live?We use market quotes of life annuity prices to extract information about the market’s view of survival probabilities using a framework that links the term structure of mortality and interest rates. Our main computational result is that in the year 2004 prices implied a 40.1-percent probability of survival to age ninety for a seventy-five-year old male (51.2 percent for a female). But, by early 2014 the implied survival probability had increased to 46.1 percent (and 53.1 percent). The corresponding implied life expectancy has increased (at the age of seventy-five) from 13.09 years for males (15.08 years for females) to 14.28 years (and 15.61 years). In other words, over the past decade markets implied an improvement in longevity of between six and seven weeks per year for males and between one and three weeks for females. Although these values are implied from quotes, they are consistent with forward-looking demographic projections. Similar to implied volatility in option pricing, we ...
http://www.ssrn.com/abstract=2792276
http://www.ssrn.com/1538060.htmlMon, 24 Oct 2016 05:46:26 GMT