BKLN White Papers

A Motor for Your Sailboat: Getting There Faster with Enhanced Tax-Loss Harvesting

Tax-loss harvesting has become an important part of many financial advisors’ toolkits. When implemented systematically in direct index portfolios, it can add significant value to clients through reduction of overall capital gains taxes – whether the overall objective of the client is to improve after-tax returns or to diversify away from a large appreciated stock position. In this paper, we discuss how traditional tax-loss harvesting strategies can be further enhanced through long/short extensions.

BKLN White Paper Series | Q2 2024
BKLN White Papers

Nasdaq-Brooklyn ADR™ Index

American depositary receipts (ADRs) offer a convenient way for investors in separately managed accounts to gain exposure to international equities. However, existing ADR indices can be expensive to trade because liquidity in an ADR can be much lower than expected based on the firm’s market capitalization. The Nasdaq-Brooklyn ADR Index presents an innovative solution that creates a liquidity-adjustment factor to optimally utilize liquidity across ADRs while maintaining broadly diversified international exposures. This significantly reduces trading costs for investors.

White Paper In Partnership with Nasdaq | Q4 2023
BKLN White Papers

Losing Concentration: Exiting Large Stock Positions in a Tax-Efficient Way

Since wealth tends to be created by entrepreneurs who embrace concentrated risks, prospective clients of financial advisors often hold appreciated stock positions that they wish to sell down in a tax efficient way. In this white paper for investment advisory professionals, we will discuss our approach to managing the tax-efficient diversification of such outsized positions toward a desired target portfolio.

BKLN White Paper Series | Q4 2023
Finance & Portfolio Management

Underperformance of Concentrated Stock Positions

The case for diversifying out of concentrated positions is even stronger than most investors realize. Outsized positions in individual stocks not only increase portfolio volatility, but usually they also reduce portfolio return. Over the past century, the median ten-year return on individual U.S. stocks relative to the broad equity market is –7.9%, underperforming by 0.82% per year. Stocks with strong prior performance have underperformed even more, by 1.94% per year.

Working Paper
BKLN White Papers

Custom Direct Indexing: Benefits of Separately Managed Accounts with Tax Loss Harvesting

We review opportunities for taxable investors to improve the outcomes of their overall portfolio.

BKLN White Paper Series | Q3 2022
BKLN White Papers

How Tax Loss Harvesting and Custom Direct Indexing Can Enhance Portfolios

How Can Tax Loss Harvesting and Custom Direct Indexing Enhance Portfolios? A Conversation with Brooklyn’s Chief Investment Officer Erkko Etula and Head of Equities Antti Petajisto, Q1 2023.

BKLN White Paper Series | Q1 2023
Finance & Portfolio Management

Inefficiencies in the Pricing of Exchange-Traded Funds

We document that the prices of exchange-traded funds can deviate significantly from their net asset values, especially in funds holding international or illiquid securities. We introduce a novel approach to control for stale pricing of the underlying assets and confirm that the mispricings are real. Cost-conscious ETF investors should be aware of these potential hidden costs.

Financial Analysts Journal (lead article)
Finance & Portfolio Management

The Index Premium and Its Hidden Cost for Index Funds

We find that the index premium for the S&P 500 and Russell 2000 has historically averaged +8.8% and +4.7% for additions, respectively, and -15.1% and -4.6% for deletions. We introduce a new concept that we label the index turnover cost, which represents a hidden cost borne by index funds (and the indexes themselves) due to the index premium. We estimate its lower bound as 21-28bp annually for the S&P 500 and 38-77bp annually for the Russell 2000, which is much larger than the management fees of many index funds.

Journal of Empirical Finance
Finance & Portfolio Management

Active Share and Mutual Fund Performance

We use Active Share and tracking error to sort active mutual funds into style groups. We find that the most active stock pickers have outperformed their benchmark indices even after fees and transaction costs, while closet indexers have been reliable underperformers after expenses. Closet indexing increases in volatile and bear markets and has become more popular over time.

Financial Analysts Journal, Winner of the Graham and Dodd Scroll Award (top 3 FAJ paper)
Finance & Portfolio Management

Should Benchmark Indices Have Alpha? Revisiting Performance Evaluation

Standard academic factor models produce economically and statistically significant nonzero alphas even for passive benchmark indices such as the S&P 500 and Russell 2000. We track down the issues behind this, propose alternative models and show that they outperform the standard models in common applications such as performance evaluation of mutual fund managers.

Critical Finance Review (lead article), Winner of the Commonfund Best Paper Prize at the EFA Annual Meeting
Finance & Portfolio Management

Global Return Premiums on Earnings Quality, Value, and Size

We find that a simple global long-short strategy betting on high earnings quality produces a higher Sharpe ratio than the overall market or similar strategies betting on value or small stocks. Because the earnings quality portfolio has a negative correlation with a value portfolio, an investor wishing to invest in both exposures can achieve significant diversification benefits.

Working Paper
Finance & Portfolio Management

Dash for Cash: Monthly Market Impact of Institutional Liquidity Needs

We present broad-based evidence that the monthly payment cycle induces systematic patterns in liquid markets around the globe. We document temporary increases in the costs of debt and equity capital.

The Review of Financial Studies
Finance & Portfolio Management

Financial Intermediaries and the Cross-Section of Asset Returns

Financial intermediaries trade frequently in many markets using sophisticated models. Their marginal value of wealth should therefore provide a more informative stochastic discount factor than that of a representative consumer.

Journal of Finance, Winner of Amundi Smith Breeden Distinguished Paper Prize
Finance & Portfolio Management

Advancing Strategic Asset Allocation in a Multi-Factor World

Strategic asset allocation is arguably one of the most important, yet least advanced, aspects of investing. We present a new approach to strategic asset allocation that leverages the idea that long-term investment returns derive from multiple distinct sources.

Journal of Portfolio Management
Finance & Portfolio Management

Broker-Dealer Risk Appetite and Commodity Returns

We show that the risk-bearing capacity of U.S. securities brokers and dealers is a strong determinant of risk premia in commodity derivatives markets.

Journal of Financial Econometrics, Winner of Engle Prize in Financial Econometrics
Finance & Portfolio Management

Financial Amplification of Foreign Exchange Risk Premia

We decompose the U.S. dollar risk premium into components associated with macroeconomic fundamentals and a component associated with financial intermediary balance sheets.

European Economic Review
Finance & Portfolio Management

Blockchain Policy and Fintech

We describe use cases of blockchain technology in finance.

Global Fintech: Financial Innovation in the Connected World
Artificial Intelligence

Data-Driven Dynamic Decision Models

We develop a machine learning method for automatically generating models of dynamic decision-making that both have strong predictive power and are interpretable in human terms.

IEEE Press
Artificial Intelligence

Contract as Automaton: Representing a Simple Financial Agreement in Computational Form

We show that the fundamental legal structure of a well-written financial contract follows a state-transition logic that can be formalized mathematically as a finite-state machine. By conceptualizing and representing the structure of a financial contract in this way, we expose it to a range of powerful tools and results from the theory of computation.

Artificial Intelligence & Law
Artificial Intelligence

Computable Contracts and Insurance: An Introduction

We explain how computable contracts, coupled with automation, can drive innovation in the insurance business.

MIT Computational Law Report
Artificial Intelligence

Predicting Human Cooperation

We present the first computational model of human behavior in repeated Prisoner’s Dilemma games that unifies the diversity of experimental observations in a systematic and quantitatively reliable manner.

Plos One
Impact Investing & Climate Change

Climate-Contingent Finance

Climate-contingent finance is a fresh approach to addressing catastrophic risk, building a bridge between long-term funding needs and financial risk management. It can be generalized to any situation where multiple entities share exposure to a risk where they lack direct control over whether it occurs (e.g., climate change, or a natural pandemic), and one type of entity can take proactive actions to benefit from addressing the effects of the risk if it occurs (e.g., through innovating on crops that would do well under extreme climate change or vaccination technology that could address particular viruses) with funding from another type of entity that seeks a targeted financial return to ameliorate the downside if the risk unfolds.

Berkeley Business Law Journal
Impact Investing & Climate Change

Environmental Impact Bonds: A Common Framework and Looking Ahead

We define Environmental Impact Bond mechanics, elucidate the difference between EIBs and Green Bonds, and propose a common vocabulary for the field.

Environmental Research: Infrastructure and Sustainability
Impact Investing & Climate Change

Betting and Belief: Prediction Markets and Attribution of Climate Change

We present a simulation model as a computational test-bed for climate prediction markets. Traders adapt their beliefs about future temperatures based on the profits of other traders in their social network.

IEEE Press
Impact Investing & Climate Change

A Machine Learning Approach to Forecasting Remotely Sensed Vegetation Health

We built an open-source AI tool to produce short-term forecasts of vegetation health at high spatial resolution, using data that are global in coverage.

International Journal of Remote Sensing
Impact Investing & Climate Change

Impact of Seasonal Forecast Use on Agricultural Income: An Empirically-Grounded Simulation

Our simulation models show that a farmer using seasonal forecasts has more diversified crop selections, which drive increases in average agricultural income.

Environmental Research Letters
Impact Investing & Climate Change

A Review of Decision-Support Models for Adaptation to Climate Change in the Context of Development

We review models and literature regarding climate change adaptation, and present an argument in favor of using various computational modeling tools.

Climate & Development

Advisory services, including planning and portfolio management, are provided for a fee by Brooklyn Investment Group, LLC, a registered internet-only investment adviser and a wholly-owned subsidiary of Skopos Labs, Inc. For more information about Brooklyn Investment Group’s advisory services, see our Form ADV Parts 2A & 2B, Form CRS and other Disclosures.

Investing involves risks. The value of your investment will fluctuate over time. It could increase or you could lose some or all of your investment. Before investing, consider your financial circumstances, investment objectives, Brooklyn Investment Group’s fee, and other expenses.

Brooklyn Investment Group, LLC does not provide legal or tax advice, and the information provided should not be considered legal or tax advice. Consult an attorney, tax professional, or other advisor regarding your specific legal or tax situation.

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