Which Portfolio Rebalancing Software is Right for You? (2/2)

This is part 2 of 2 of a summary from a panel discussion at the Tools and Technology Today (T3) Conference, which took place February 11-13, 2013 in Miami, FL.  You can read part 1 here.

Moderator: Tess Downing, Financial Advisor, Fox, Joss & Yankee, LLC


Does your product update portfolios using real time prices before rebalancing?

iRebal retrieves the latest pricing as soon as a rebalance is run, Fava stated.  All of the recommended trades are created using dollar amounts instead of number of shares, since they believe this provides a better picture of how the trades will impact cash levels.  They convert this to the number of shares when trades are approved and also refresh the pricing, she noted.

Tamarac also offers real-time pricing as part of their rebalance and also real-time execution reports for equities and ETFs, Rembe said.  Also, when you tell the system to update the cash positions, it evaluates T1 and T3 settlement to ensure that the accounts won’t be short cash.  If they are, then it provides an option to put those trades on hold and execute them on a later date, he said.

TradeWarrior receives real-time pricing from an external feed that can be used to update positions before running a rebalance, Evans said.

Rowling pointed out that TRX was designed to focus on trading of Dimensional Fund Advisors (DFA) funds, so they haven’t previously had a need for real-time pricing.  However, in response to recent requests from clients, they plan to support real-time pricing in a release sometime in the second quarter of 2013, she said.

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RIAs Take Advantage of Discretion to Launch UMAs and Improve Efficiency

This is a summary from a session of the MMI Tech and Ops Conference with a panel made up of Registered Investment Advisors (RIAs).  The discussions centered around the use of Unified Managed Accounts (UMAs) and the advantages of discretionary versus non-discretionary accounts.


Roger Paradiso, Director/CIO, Managing Director, Morgan Stanley Smith Barney


Dan Sherman, SVP, Family Wealth Director, Morgan Stanley Smith Barney.  Dec 1990, Sherman Group.  They manage over $1 bil in house and advise $2 bil out of house with a seven person team, using a top down method and proprietary financial planning process.

Mark Rogozinski, President, Rockit Solutions, LLC.  They are a back office solution for single and multi-family offices and trust companies.  They are a wholly-owned subsidiary of Rockefeller Financial with around $30 bil in AUM.  Mark has been at RockIt for two years.

Tim Flynn, RIA, President, Tim Flynn LLC.  Currently transitioning from traditional, corporate RIA to a hybrid RIA.  Boutique shop in NYC.  5 people, 3 registered reps and 2 support.  Currently managing $425 mm AUM internally, and $350 mm away, consulting primarily to retirement plans.

Are you using UMA programs and if so, what features do you think are the most useful to your clients?

Rogozinski theorized that all the advantages of UMAs evaporated during the financial crisis, specifically around overlay management and tax efficiency.  Their clients started getting out of UMAs and back into SMAs since there were no longer any embedded gains, which would prohibit them from moving.  Another factor was new technology that Rockit introduced that allows their clients to become their own overlay managers.

In the RIA space, Rockit implemented a new UMA strategy, which is very cost effective and tax efficient, Rogozinski reported.  The new system allows them to service smaller clients at lower thresholds and offer more separate account managers on their platform.  Many firms sold all their UMA assets and switched to mutual funds, since there were no embedded gains after the market crisis.  It’s a very cyclical business and five years from now will probably return to UMAs when the market goes back up and creates new embedded gains, he projected.

Flynn built his practice with open architecture and non-discretionary accounts.   Then he realized that it was expensive and didn’t scale very well.  About 18 months ago, he began to shift his focus to UMAs through two platforms available from his broker-dealer.  UMAs allow him to deploy assets differently, he can run more assets with a smaller staff footprint.  These products have enabled him to become more competitive.

Dan Sherman has seven people on his team at Morgan Stanley, four of whom are partners.   They use a top down financial planning perspective that eventually ends up with an asset management end product.  According to Sherman, they have shifted the bulk of their capital appreciation assets onto their UMA platform.  These assets include more than just equity, but not traditional fixed income.  On the fixed income side, they run a traditional transaction-based business, he said.

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Defining Tax Management

In the most recent edition of my Managed Accounts Newsletter (MA Monitor, Feb 2009), I compared different recommendations of the minimum value for a managed account that is required in order for tax management to be effective. The values ranged from $0 (no minimum) up to $1,000,000:

I have since received a few updates, including one from Joe Mrak who wanted to amend his comments:

I actually agree with Dale from M3 that an account should be at least $1 MM for “tax optimization” vs what I was think for the $200K account “tax treatment”.

This raises a semantic issue since there is no standard definit0n of tax management as well as a lot of overlap between the many terms currently in use.  Here are a few tax management terms that I have found:

  • tax optimization
  • tax treatment
  • tax aware
  • tax sensitive
  • tax efficient
  • tax managed
  • tax centric

Joe’s update includes a good definition of tax optimization in his clarification of a minimum account value:

Just to clarify that point…my thought has always been that most accounts can benefit from some tax rules (don\’t allow a ST gain etc.), but the more involved tax optimization of an account where you are doing much more algorithmic logic to determine the trade-offs of alpha, risk and tax only makes sense on accounts with $1 MM or more. No sense in working that hard on a $200K account that will see little to no benefit to that extra effort.

He also added:

I want to be more tax aware than tax optimized. I believe that only a handful of advisors can understand the value proposition of all-out tax optimization.

As a follow-up, I asked Joe if he could also provide his definitions for tax aware versus tax treatment:

Tax Aware – The system is constantly seeking to offset gains and losses at any time of the year and all investment decision takes into account tax.

Tactical Tax Treatment – Tactical gain/loss management based on a request or done on an annual basis.  So tax is considered, but only ad-hoc by request or specific action.

IMO, this definition of tax treatment sounds a lot like tax harvesting, which is a feature of some Separately Managed Account (SMA) programs.  Although, there is also a difference between manual and automated tax harvesting.

Now that I’ve opened a can of worms related to the many definitions of tax management, I’ll be continuing to delve into more detail on the many different terms in future posts.

A Conversation with Randy Bullard

Last week I had the opportunity to speak with Randy Bullard, Founder and EVP of Business Development at Placemark Investments.  I planned to ask him a series of detailed questions about his company’s tax management and optimization services.

Here is the list of topics I wanted to cover:

  • Tax Aware Transition of Pre-Existing Securities
  • Tax Aware Withdrawals
  • Tax Efficient Rebalancing
  • Short Term Gain Deferral
  • Systematic Tax Loss Harvesting
  • Tax Lot Management Between Managers

Well, we didn’t get to all of these issues, but we managed to knock off a few.  We went into such a deep dive that I lost track of time and before I knew it we had spent 90 minutes on the phone and both had to run to other meetings.

Randy’s Rules:

There are two things that all tax management systems should do: Absolutely eliminate wash sales & keep all capital gains as long-term.

Tax management is not tax avoidance.  You should always realize gains smartly and as tax efficiently as possible.

Tax-Aware Transition of Pre-Existing Securities

When I was designing the rules for the rebalancing engine at Standard & Poor’s, I spent untold hours contemplating the myriad of issues surrounding transition of pre-existing securities (also referred to as “legacy assets”) into customer accounts.  This includes brand new accounts that are funded with a mix of cash and securities and existing accounts that are being transitioned from one product to another.

According to Randy, Placemark takes the legacy assets and evaluates the risk characteristics using multi-factor risk data (provided by Northfield) in order to measure the correlation and affiliated risk of the securities versus other securities or an index.

There are many questions that need to be addressed before the transition can be properly evaluated.  What is the tax impact to the client if we sell the stock(s)?  What risk reduction do they see?  Cost vs Risk?  What is the risk of not selling?  What is the appropriate measure of risk?  What is the appropriate risk target?

What is the risk position going to be after the initial set of trades to begin the transition process?  A client may have a bunch of managers he likes, so Placemark compares the correlation of the customer’s holdings versus the manager portfolios.  They then choose the one with highest correlation.  Even if they’re highly correlated, there is always a stock-specific risk.  Multi-factor risk only explains 80-90% of a stock’s performance.  The remaining 10% are due to factors beyond your control.

Randy then walked me through a widely seen scenario: A customer wants to open a new account by transferring his existing assets; 30 stocks, many with big long-term capital gains, with a total market value of $1 mil plus another $1 mil in cash equivalents.

One approach is to transition the customer’s assets into a Benchmark-Constructed Portfolio.  Let’s assume that the customer has to keep 20 securities out of 30 and the target benchmark is the S&P500.  Take the liquid portion of customers portfolio and buy securities that move the portfolio towards the S&P500.  You can buy other securities in the S&P500 that have directly opposite offsetting risk factors versus the 20 stocks the customer owns.  This creates a “completion portfolio,” which is something that institution wealth managers have been doing for a long time.

Any risk-model-based optimizer does this well, Randy added.  What basket of securities should I buy with the $1 mil that combined with the 20 legacy stocks has the highest correlation and lowest tracking error to the target benchmark?  If the 20 legacy securities are all in financial services, then you should use the $1 mil to buy a basket of securities that are negatively correlated to financial services.  The basket is mathematically constructed to offset the risk factors of the portfolio.  You can then create a new portfolio that has a tracking error within 5 bps of target benchmark.   Of course, this is only one approach.

A different approach would have to be used if the client didn’t want an index as the target benchmark.  Let’s say he wants to go for alpha and wants some actively-managed benchmark instead.

If the manager has 70 stocks in her portfolio and the client has 20 legacy stocks and over time wants to move into a portfolio that matches the manager.  Now, you have a much more constrained portfolio and have to stick to the universe and relative weights of manager.  This approach is more constrained, less flexible and incurs more risk to client.

Using the same basic optimizer, the 70 stocks in the manager’s model have correlations that are compared to the 20 legacy stocks that the client holds.  A decision must be made on a liquidation schedule based on the correlation to the manager’s model.  Perhaps the client wants a three year selldown, with no more than $50K in long-term gains realized per year, but still wants to minimize the tracking error vs the active benchmark.

So, which positions should be sold first?  Some stocks have lots of risk associated depending on the target benchmark.  This becomes one of the variables to optimize with, balancing risk versus tax.

For example, selling stock X might generate a $10K tax event and selling stock Y might generate a $20K tax event.  But this decision is not as black and white as it seems.  How much gains have already been realized?  How much budget is left?   You should usually hold highly-correlated stocks longer unless they have minimal tax impact.

Tax Loss Harvesting

Some overlay managers follow the strategy of generating losses even if the client has no offsetting capital gains.  This is called “banking” the losses.  However, they’re only worth $3,000 in the absence of offsetting gains, so you have to carry them forward to future tax years.

This strategy is bullshit, Randy claimed.  This strategy involves banking losses that may or may not be of any value in the future.  Randy’s opinion is that since the loss will still be there in the future, why bank it now?

This strategy bears some amount of tracking error and incurs transaction costs.  Even parking the cash in an ETF will result in stock-specific risk (what if the stock you sold goes up during the 30-day wash sale period?).  There is no actual value to do this today if there are no offsetting gains, Randy concluded.

Tax Alpha Claims

One thing in particular that I wanted to take a deeper dive into was Randy’s claim that Placemark’s discretionary overlay managent service can deliver between 70 -80 basis points in tax alpha. (from a meeting we had on 02/09/09)

We agreed that there is no GIPS-compliant way to measure tax alpha, but you can compare the taxable gains of your tax managed accounts versus the non-tax managed at the end of the year.

You could run a monte carlo simulation on any set of drivers, such as portfolio turnover.

Short term gain avoidance is by far the biggest way to generate tax alpha (80-90%), but requires an accurate method of tax code modeling.

In over 95% of client accounts, Placemark completely eliminates short term capital gain realization.  In their non-tax optimized accounts, 50% of capital gains are short-term.  They have to make some assumptions based on the projected amount of gains, such as what is the most appropriate ST/LT mix for each client?

For example, look at a SMA program over a 10-15 year period (before 2008!), Randy offered.  Assume a market return = 8%, with 50% long-term and 50% short-term gains. The average SMA manager has 70-80% turnover, which means that short-term gains must exist!

If client X has a long-term capital gains rate of 20% and a short-term capital gains rate of 40% and the return was 8%, break out the 8% at these two rates.  What if you only have gains at the long-term rate?  What is value added for this client?

There aren’t good tools for doing tax optimization, Randy asserted.  There are two classes of optimizers; mathematical vs rules-based.  You can get 75% of value by using rules-based, so using an optimizer is often warranted.

Some product notes:

  • Placemark built their tax management process 10 years ago.  There was only one piece of software on the market at the time that did it right.  They were an institutional financial optimizer engine.  Would create an optimal blend of trades to solve problem.
  • Placemark’s engine solves complex tax problems in seconds vs hours for other tools.  They use Northfield’s multi-factor risk-base data, but not their optimizer.

Seeking Tax Alpha

The term “tax alpha,” which was coined by Rob Arnott of investment manager Research Affiliates, represents the improvement in net returns gained from effective tax management. (from Seeking Tax Alpha By David E. Adler at AdvisorMax.com)

During my research and discussions with industry professionals, I’ve discovered (not surprisingly) that there are many definitions of tax alpha.

For example, according to an article that is also titled, Seeking Tax Alpha by John Phoenix, CEO of Metamorphosis Money Management (M3):

Tax alpha is the improvement of portfolio returns created by sound tax management: strategically harvesting stock losses for tax deductions by selling depreciated stocks at opportunities as they occur.

This definition seems limiting since tax harvesting is far from the only tax management method available to an investment manager.  Of course, one M3’s main sales tools is their focus on year-round tax harvesting.  So, this emphasis in John’s article is not surprising.