L O S S H A R V E S T I N G

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1 L O S S H A R V E S T I N G Examining Tax Efficient Investing Strategies for Maximizing After-Tax Wealth November 2012 Chris Fronk, CFA, CPA Senior Portfolio Manager and Product Strategist caf5@ntrs.com Michelle Markus, CFA, CFP Portfolio Manager mm98@ntrs.com Anne Hickman, CFA Portfolio Manager awh1@ntrs.com Tax efficient investing has evolved significantly over the years. Increasing awareness that taxes are likely the single largest cost in a portfolio has led many taxable investors to run dedicated tax-loss harvesting programs. In such a strategy, it is important to determine the main drivers of loss harvesting in order to maximize after-tax wealth. The following analysis examines the effects of varying the different parameters, including trade frequency, estimated tracking error, and transaction costs, that a tax advantaged portfolio manager must consider when constructing an effective tax-loss harvesting strategy. In order to analyze this, we ran multiple scenarios through simulated loss harvesting trading for a full calendar year. All of the scenarios began with an initial cash contribution of $10 million, which was used to fund a S&P 500 portfolio with approximately 10 basis points of estimated tracking error. In subsequent periods, each scenario tested a different combination of trading frequency and estimated tracking error in order to compare the effects of these inputs on the amount of losses realized during the year. The Effects of Trading Frequency on Losses The first parameter we examined was the frequency with which portfolios were traded in order to realize losses and maintain a target level of estimated tracking error. The two scenarios compared were Monthly, which was traded every month, and High Risk Quarterly, which was traded every three months. All other parameters were held constant. Both strategies maintained estimated tracking error at a level of basis points. Each scenario captured almost all available losses at the time of the trade. At the end of the year, Monthly had realized $1.37 million in losses, or 13.7% of the initial portfolio value. Quarterly had realized $1.04 million in losses, or 10.4% of the initial portfolio value. The results show that monthly trading increased the amount of losses the portfolio manager was able to harvest. Since the unrealized losses within a portfolio fluctuate over time, trading the portfolio more regularly allows the manager to opportunistically capture more losses. The additional $330,000 in realized losses produced by trading monthly created $115,500 in additional after-tax wealth 1, or 1.2% of additional after-tax alpha, as compared to trading quarterly. In addition to the increased after-tax benefit, trading more frequently allows the portfolio manager to better control intra-period fluctuations in risk factors, which should reduce pre-tax tracking error over the long run. Measuring the Tradeoff between Estimated Tracking Error and Losses It is important to realize that the level of estimated tracking error in a portfolio affects the likelihood that pre-tax performance will deviate from the benchmark. If a portfolio has an 1 Based on a short-term capital gains tax rate of 35%. northerntrust.com 1 of 5

2 estimated tracking error level of 1.25%, then the risk model would predict a 33% probability that the annual returns will deviate from the benchmark return by more than 1.25%. In a portfolio with lower estimated tracking error, the expected volatility of returns relative to the benchmark is reduced and the likelihood of large pre-tax performance deviations from the benchmark decreases. The question then is how is the level of loss realization impacted by changes in the level of expected tracking error in the portfolio. To answer this question, we measured the tradeoff between lower risk and loss harvesting opportunities by creating a Medium Risk Monthly and a Low Risk Monthly scenario. Both portfolios were funded with the same initial cash and risk level as the Monthly scenario, but in the first loss harvesting trade in January, risk was limited to 65 basis points for the Medium Risk Monthly scenario and 25 basis points for the Low Risk Monthly scenario. The subsequent trades for both scenarios maintained the same risk level. Medium Risk Monthly captured on average 75% of the available losses at the time of each trade and at the end of the year it harvested $1.31 million in total realized losses. Low Risk Monthly captured on average 45% of the available losses at the time of each trade and at the end of the year it harvested $1.15 million in total realized losses. In the Medium Risk Monthly scenario, we were able to harvest approximately 96% of the total losses realized in the Monthly scenario and more losses than the Quarterly scenario. Similarly, the Low Risk Monthly scenario harvested more losses than the Quarterly scenario and around 84% of the losses of the Monthly scenario. Thus, the results show that there is a positive but diminishing relationship between increased risk and increased loss harvesting opportunities. Interestingly, our simulated trading scenarios also suggest that the amount of losses realized is more sensitive to changes in the trade frequency than to the changes in estimated tracking error. Regardless of the trade frequency, however, an investor must weigh the benefit of additional losses against the increased risk of pre-tax performance tracking error relative to the benchmark. Average Portfolio Estimated Tracking Error 12-month Net % of Unrealized Losses Harvested Per Trade Monthly 1.15% ($1,368,000) 95% Quarterly 1.15% ($1,038,000) 95% Medium Risk Monthly 0.65% ($1,313,000) 75% Low Risk Monthly 0.25% ($1,148,000) 45% Transaction Costs and Other Considerations The results above suggest that no matter what the risk level, a monthly trading strategy provides superior loss harvesting opportunities. In light of this, why might some firms trade less frequently than monthly? A central consideration of the trade frequency decision is transaction costs. It is important for a portfolio manager to consider commissions, implicit northerntrust.com 2 of 5

3 trading costs associated with thinly traded markets, and other trading costs when designing a tax loss harvesting strategy. Though the Monthly and Medium Risk Monthly scenarios traded more often than the Quarterly scenario, assuming a commission rate of $0.01 per share, the value of the additional losses harvested was worth the higher commission costs. 12-month Net After Tax Wealth Created (Assumes 35% Tax Rate) Shares Traded ($0.01/share) (% Market Value) After Tax Wealth Created, Net of Monthly ($1,368,000) $478,800 1,656,000 $17, % $461,800 Quarterly ($1,038,000) $363, ,000 $7, % $356,300 Medium Risk Monthly ($1,313,000) $459,550 1,157,000 $12, % $447,550 Low Risk Monthly ($1,148,000) $401, ,000 $7, % $394,800 Per-transaction ticket charges, however, are a different type of cost that can add up more quickly. Whether or not a portfolio is subject to these charges depends on each investor s fee agreement with the bank where the assets are custodied. It is important for the portfolio manager to be aware of these and other costs in order to adjust the investment strategy to balance the value of loss harvesting opportunities against the trading costs incurred. If these costs aren t a factor the portfolio manager has much greater freedom to trade more frequently and maximize realized losses in an account. For example, if the Quarterly scenario had a $10 per ticket custody transaction charge and traded 1,185 securities, it would have $11,850 in additional cost, thus reducing the after tax benefit by approximately 12 basis points. Temporarily Increasing Risk In September, Kathleen decides to terminate her large-cap manager, which will result in significant gains. In need of losses to offset these gains, Kathleen contacts her TAE portfolio manager. They decide to temporarily raise the estimated tracking error in the portfolio from 25 basis points to 75 basis points in order to realize more losses before the end of the tax year. In the following year, Kathleen is concerned about risk and would like to reduce the portfolio s tracking error back to its previous level. The TAE portfolio manager runs an analysis of the required rebalancing trade and finds that reducing estimated tracking error in a single trade would produce a large-short term gain, eliminating the after-tax value created in the previous year. Instead of this single trade, the portfolio manager creates a strategy to bring estimated tracking error down over time, taking long-term gains to minimize the tax impact of the rebalance. northerntrust.com 3 of 5

4 It is also important to consider the amount of time during the year that the portfolio had an increased level of risk. For example, an investor who only allowed risk to increase during the last quarter of the year will not get the same level of realized losses as the scenarios, due to the shortened time period and they would not be able to take advantage of any market volatility earlier in the year. Additionally, if an investor wanted to raise risk temporarily and then rebalance back to a low level of estimated tracking error, they would need to consider the potential realized gain needed to reduce the estimated tracking error back to a lower level. To demonstrate this impact, we included a final trade one month after the year of testing was complete, which rebalanced each scenario to 25 basis points of estimated tracking error. In our Monthly scenario, this trade resulted in a gain of approximately $348,000, reducing the total net loss over the 13-month period to $1.02 million. At the other end of the spectrum, a January trade in our Low Risk Monthly scenario to maintain risk at 25 bps resulted in a net loss of approximately $9,000, increasing the total net loss over the same period to $1.16 million. For the purposes of this analysis, we rebalanced risk in a single trade, one month after the testing was complete. The tax impact suggests that for investors that are more sensitive to gains, it may make sense to bring risk down over time, opportunistically taking long-term gains as they become available instead of short-term gains. Average Portfolio Estimated Tracking Error 12-month Net Rebalancing Trade Post Trade Risk 13-month Net Monthly 1.15% ($1,368,000) $348, % ($1,020,000) Quarterly 1.15% ($1,038,000) $275, % ($763,000) Medium Risk Monthly 0.65% ($1,313,000) $135, % ($1,178,000) Low Risk Monthly 0.25% ($1,148,000) ($9,000) 0.25% ($1,157,000) Conclusion Many factors must be taken into consideration when constructing a tax-loss harvesting program. Our trading simulation shows that more frequent trading significantly increases the amount of realized losses in a portfolio, assuming transaction costs are properly managed. Our research also shows that while there is a trade-off between minimizing estimated tracking error and maximizing realized losses, each strategy provides substantial after-tax value added and can be appropriate for different situations. Model Assumptions All scenarios used the HICO methodology for tax lot accounting. All scenarios were funded with an initial cash contribution of $10 million and purchased the same initial portfolio in December 2010, which had approximately 10 bps of estimated tracking error relative to the S&P 500 Index. northerntrust.com 4 of 5

5 scenarios maintained estimated tracking error at a level of basis points, Medium Risk scenarios maintained estimated tracking error at 65 basis points, while Low Risk scenarios maintained estimated tracking error at 25 basis points. Past performance is no guarantee of future results. Index performance returns do not reflect any management fees, transaction costs or expenses. It is not possible to invest directly in any index. There are risks involved in investing including possible loss of principal. There is no guarantee that the investment objectives of any fund or strategy will be met. Risk controls and models do not promise any level of performance or guarantee against loss of principal. This material is directed to eligible counterparties and professional clients only and should not be relied upon by retail investors. The information in this report has been obtained from sources believed to be reliable, but its accuracy and completeness are not guaranteed. Opinions expressed are current as of the date appearing in this material only and are subject to change without notice. This report is provided for informational purposes only and does not constitute investment advice or a recommendation of any security or product described herein. Indices and trademarks are the property of their respective owners. All rights reserved. northerntrust.com 5 of 5