Apr 14, 2018

RH Links - 4/14/18

QUOTE OF THE DAY

The primary determinant of retirement cost is longevity. Dirk Cotton

GRAPHIC OF THE DAY





RETIREMENT FINANCE AND PLANNING

What asset classes – if any – are useful in hedging against inflation? Simple question, not an easy answer. It all depends on the horizon! … In fact, the only asset class that had any chance at all to not just keep up with inflation but also supports a withdrawal rate in the neighborhood of 3.5-4% would be equities.  … With bonds, you trade lower short-term volatility for a higher probability of running out of money in the long-term!  What would I do personally?... I am probably going to increase our real estate investments going forward. 


All else equal, individuals retiring a few years apart can have vastly different retirement income outcomes (making retirement outcome a function of one’s conception date). A new bond has been proposed to improve retirement security – with a forward-start (tied to date of retirement), income-only (as individuals need steady income), real cash flow stream (linked to appropriate indices), for a fixed period (tied to average life expectancy). This paper examines standard portfolio choices (60/40, target date funds), along with holding this new bond in isolation, from a retirement income perspective to demonstrate how this new bond, either individually or when used in standard portfolio choices could greatly improve retirement outcomes. The paper concludes with a Monte-Carlo simulation that further validates the value of this new bond given the potential risks to all investment choices given future equity, interest rate and inflation scenarios. [Comment: and after the fixed period?] 


The primary determinant of retirement cost is longevity. … We develop retirement plans using models of the future but some models are much better than others. Nor is the model a plan…. Though it is true that we can't foresee our future path, it is also irrelevant — the purpose of the Monte Carlo model isn’t to predict an individual retiree’s path through the future (that’s impossible) but to explore a broad range of possible scenarios and develop some estimate of the probability of each actually being realized. Simulation is essentially a gigantic "what-if" analysis. 

[wait for it….] "What else can be done? There is one option. Instead of the fixed amount, if they target the withdrawal as the % of the portfolio" 

We demonstrate in this work that the existence of long memory in mortality data improves the understanding of mortality and the model incorporating a long memory structure provides a new approach to enhance the mortality forecasts…On comparing different life expectancy estimates, results show the Lee Carter model without the long memory component may provide underestimates of life expectancy. This underestimation has great impact on the old-age support programs in social security and pension and may eventually lead to insufficient funds in a pension scheme. In summary, it is crucial to investigate how the long memory feature in mortality influences life expectancies in the construction of life tables.  

On Stochastic vs. Deterministic Models, me
a well informed skeptic with a seasoned sensibility and at least some knowledge of how the underlying processes work can look at any tool's output and use it to their advantage while seeing and then discounting the weaknesses. [question: "doesn't seem weird to quote yourself?" "yes"]

MARKETS AND INVESTING

Question: Assume you are advising a pension fund, endowment or foundation. What is a reasonable long-term expectation for real returns for a well-diversified portfolio? Support as you see fit. 

The plausible consequences of the passive investment boom include [i] less information efficiency of markets, [ii] greater incentive for low-quality issuance and corporate leverage, [iii] greater price correlation across securities, and [iv] stronger transmission of financial shocks into emerging economies. 

[link from reader David C.  I thought this was interesting and worthy.  I skipped over the risk parity sections, though. A reader would be at least as well served by going to Markowitz's own comments on Markowitz and Kelly in his 2016 book vs. indirectly via a PIMCO analyst but this is a good, robust interpretation and cover.  Regarding the authors reverence for utility: academics and advanced practitioners take a fair amount of risk in disagreeing with this reverence.  Amateurs can (even though I just did some utility work myself) say: "uh....yeah...whatever." Worth a look, though.]   

For most investors, failure means not meeting one’s financial objectives.  In the portfolio management context, failure comes in two flavors: slow failure results from taking too little risk and fast failure results from taking too much risk. 


ALTERNATIVE RISK

The solution to inflation protection is to think outside the immediate inflation securities box. Three alternatives come to mind, real estate, systematic trading, and commodity risk premium portfolios. Each offers a slightly different approach to providing inflation protection… A relatively new strategy would be to invest in a commodity portfolio that is based on commodity risk premiums. Instead of investing in a long-only basket with fixed commodity weights, investors would build a commodity portfolio based on well-defined risk premiums such as carry (backwardation/contango), momentum (trend), value, and volatility. This portfolio will be uncorrelated with core traditional assets and should be positioned to take advantage of inflation increases.  [I have a slice of commodity futures vol]  

Systematic strategies, by design, have a natural order flow, leading to coordinated portfolio trade lists.  The execution of these trade lists increases covariances and correlations of intraday returns and volume, both contributing to variability of observed execution costs… Academic evidence suggests that reducing tracking error (active risk) during times of high volatility in the market is an effective strategy for avoiding “bad” times in factor investing…  The issue of whether or not “machine learning” is actually a new paradigm for systematic strategies has not been determined.  It is undeniable that quants have always used “big data” and statistical methods which are the commonly accepted hallmarks of machine learning.  Can other machine learning approaches such as pattern recognition, outperform the traditional application of linear regression to factor investing and trading?  The empirical evidence with respect to the application of machine learning to all aspects of investing: alpha, beta, risk management, trading and execution is yet to be explored.  


So, when things are brought to the same common denominator – risk-wise – we estimate the Yale endowment underperforms (after fees) both a leveraged version of the 60/40 portfolio and an auto-pilot Risk Parity portfolio.  Though we believe there is a role for alternatives and active management in a portfolio, when we factor in risk to the Yale endowment performance puzzle, we’re on the side of Buffett in this duel.


SOCIETY AND CAPITAL

This research seeks to determine the financial price of being both Sharī‘ahcompliant and socially responsible. We examine the financial performance of self-composed Islamic portfolios with varying ESG scoring. The results indicate no adverse effect on returns due to the application of Islamic and ESG screens, with a substantially higher performance for positive screening on governance during post subprime crisis’ period. Significant outperformance still arises for portfolios with bad records in community and human rights though. Performances are controlled for market sensitivity, investment style, momentum factor and sector exposure.  

A Generation of Interest Rate Illiterates, Brian Wesbury, Robert Stein of First Trust Advisors,
An entire generation of investors has been misled about interest rates: where they come from, what they mean, how they're determined. 

The ground under the cities of South Florida is largely porous limestone, which means water will eventually rise up through it. [my home sweet home] 


The more sophisticated science becomes, the harder it is to communicate results. Papers today are longer than ever and full of jargon and symbols. They depend on chains of computer programs that generate data, and clean up data, and plot data, and run statistical models on data. These programs tend to be both so sloppily written and so central to the results that it’s contributed to a replication crisis, or put another way, a failure of the paper to perform its most basic task: to report what you’ve actually discovered, clearly enough that someone else can discover it for themselves. 



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