Brokerage Commissions Research Articles

Mutual Funds’ Soft Dollar Arrangements: Determinants, Impact on Shareholder Wealth, and Relation to Governance

Mutual fund advisers either expense the cost of research and other services or pay for them with soft dollars. This study is the first to use actual soft dollar and total brokerage commission figures for a large number of funds and to examine how soft dollars are linked to mutual fund governance. Employing a survivorship bias-free sample of actively managed US mutual funds, we find that higher soft dollar and total brokerage commissions are associated with higher advisory fees but not with higher risk-adjusted fund returns. These findings suggest that mutual fund shareholders, on average, do not benefit from the research and the information supplied by third parties such as brokers. We also find that larger and more highly compensated boards are associated with lower advisory fees. Larger boards are also associated with slightly lower turnover. The median tenure of board directors is negatively correlated with soft dollar commissions and turnover, but not correlated with total brokerage commissions or the cost of turning over a portfolio. Higher proportions of directors with a finance background are associated with higher advisory fees, brokerage commissions, and turnover costs. These associations might indicate greater agency costs.

Institutional Trading, Brokerage Commissions, and Information Production Around Stock Splits

We make use of a large sample of transaction-level institutional trading data to test an extended version of Brennan and Hughes’ (1991) information production theory of stock splits. We compare brokerage commissions paid by institutional investors before and after a split, assess the private information held by them, and relate the informativeness of their trading to brokerage commissions paid. We show that institutions make abnormal profits net of brokerage commissions by trading in splitting stocks. We also show that the information asymmetry faced by firms goes down after stock splits. Overall, our empirical results support the information production theory.

New insights into mutual fund brokerage commissions

Using data collected from equity mutual fund reports filed by single-fund registrants to the Securities and Exchange Commission, I study the determinants of brokerage commissions paid by fund managers when they buy or sell securities and investigate the role these commissions play in fund performance. Consistent with related studies, my results from cross-sectional analyses reveal that higher portfolio turnover funds are associated with higher commissions and larger funds incur lower commissions, as well as the positive relation between expense ratios and commissions. This positive relation is puzzling as most commissions include “soft dollars” for payments of products and services that should be already covered by the costs reported under expense ratios. However, once I take into account unobservable fund heterogeneity, I find that higher expense ratio funds do not necessarily pay higher commissions. Further, controlling for whether a fund increased commission payments as the result of flow-induced trading, I show that the underperformance related to brokerage commissions documented in the literature is attributable (at least partly) to higher level of fund flows.

SVM을 이용한 시스템트레이딩전략의 선택모형

KOSPI200 선물 트레이딩을 위해 업계에서는 여러 전략으로 포트폴리오를 구성해서 운용한다. 동일한 전략 모음을 갖고 있더라도 포트폴리오를 어떻게 구성하느냐에 따라 수익은 크게 차이가 난다. 시장 상황에 맞는 전략들로 포트폴리오를 구성하는 것은 오랜 경험과 탁월한 노하우가 있어야하는 어려운 작업이다. 본 논문에서는 SVM을 활용하여 쉽고 빠르게 적절한 전략 포트폴리오를 구성하는 방법을 제시하였다. 본 논문에서 제안한 시스템의 성과는 벤치마킹의 성과와 비교하여 2배 이상의 수익을 내는 것을 확인하였다. 1990.01.03~2011.11.04 동안의 KOSPI200 데이터 중 이전 80%의 데이터로 학습을 하고 최근 20%의 데이터로 성능을 시험하였다. 각 전략별로 선택여부를 판별하는 SVM모델을 만들고 그 결과를 바탕으로 포트폴리오를 구성하였다. 벤치마킹을 위해 KOSPI200 선물을 2계약 매수한 경우의 수익, 시험 시작 직전 30일간 최고 수익을 낸 2개 전략의 수익, 실제 최고 수익을 낸 전략 2개를 보유했을 때의 수익과 비교하였다. 매매 비용을 반영하지 않을 때는 벤치마킹은 132.2~510.37pt의 수익을 냈고, 본 시스템은 1072.36~1140.91pt의 수익을 보여주었다. 그리고 거래비용을 감안하면 벤치마킹은 130.44~502.41pt의 수익을 냈고, 본 시스템은 706.22pt~768.95pt의 수익을 나타내었다. 본 논문은 기계학습을 통한 전략 포트폴리오를 구성하는 방안이 유의미하며 실전에 활용할 수 있음을 보여주었다. 이를 바탕으로 여러 전략과 다양한 시장에 적용해서 안정성을 검증하면 견고한 상용 솔루션으로 발전시킬 수 있을 것이다. 그리고 자금관리 기법을 더 반영한다면 수익을 더욱 크게 향상시킬 수 있을 것이다. System trading is becoming more popular among Korean traders recently. System traders use automatic order systems based on the system generated buy and sell signals. These signals are generated from the predetermined entry and exit rules that were coded by system traders. Most researches on system trading have focused on designing profitable entry and exit rules using technical indicators. However, market conditions, strategy characteristics, and money management also have influences on the profitability of the system trading. Unexpected price deviations from the predetermined trading rules can incur large losses to system traders. Therefore, most professional traders use strategy portfolios rather than only one strategy. Building a good strategy portfolio is important because trading performance depends on strategy portfolios. Despite of the importance of designing strategy portfolio, rule of thumb methods have been used to select trading strategies. In this study, we propose a SVM-based strategy portfolio management system. SVM were introduced by Vapnik and is known to be effective for data mining area. It can build good portfolios within a very short period of time. Since SVM minimizes structural risks, it is best suitable for the futures trading market in which prices do not move exactly the same as the past. Our system trading strategies include moving-average cross system, MACD cross system, trend-following system, buy dips and sell rallies system, DMI system, Keltner channel system, Bollinger Bands system, and Fibonacci system. These strategies are well known and frequently being used by many professional traders. We program these strategies for generating automated system signals for entry and exit. We propose SVM-based strategies selection system and portfolio construction and order routing system. Strategies selection system is a portfolio training system. It generates training data and makes SVM model using optimal portfolio. We make <TEX>$m{\times}n$</TEX> data matrix by dividing KOSPI 200 index futures data with a same period. Optimal strategy portfolio is derived from analyzing each strategy performance. SVM model is generated based on this data and optimal strategy portfolio. We use 80% of the data for training and the remaining 20% is used for testing the strategy. For training, we select two strategies which show the highest profit in the next day. Selection method 1 selects two strategies and method 2 selects maximum two strategies which show profit more than 0.1 point. We use one-against-all method which has fast processing time. We analyse the daily data of KOSPI 200 index futures contracts from January 1990 to November 2011. Price change rates for 50 days are used as SVM input data. The training period is from January 1990 to March 2007 and the test period is from March 2007 to November 2011. We suggest three benchmark strategies portfolio. BM1 holds two contracts of KOSPI 200 index futures for testing period. BM2 is constructed as two strategies which show the largest cumulative profit during 30 days before testing starts. BM3 has two strategies which show best profits during testing period. Trading cost include brokerage commission cost and slippage cost. The proposed strategy portfolio management system shows profit more than double of the benchmark portfolios. BM1 shows 103.44 point profit, BM2 shows 488.61 point profit, and BM3 shows 502.41 point profit after deducting trading cost. The best benchmark is the portfolio of the two best profit strategies during the test period. The proposed system 1 shows 706.22 point profit and proposed system 2 shows 768.95 point profit after deducting trading cost. The equity curves for the entire period show stable pattern. With higher profit, this suggests a good trading direction for system traders. We can make more stable and more profitable portfolios if we add money management module to the system.

Trading team composition for the intraday multistock market

Automated traders operate market shares without human intervention. We propose a Trading Team based on atomic traders with opportunity detectors and simple effectors. The detectors signalize trading opportunities. For each trading signal, the effectors follow deterministic rules on when and what to trade in the market. The detectors are based on Partial Least Squares. We perform some trading experiments with twelve BM&FBovespa stocks. The empirical findings indicate that the proposed trading strategy reaches a 77.26% annualized profit, outperforming by 380.07% the chosen baseline strategy with a 16.07% profit. We also investigate Multistock Resolution Strategy (MSR) performance subject to brokerage commissions and income tax. Whenever the initial investment is at least US$ 50,000, the MSR strategy provides a profit of at least 38.63%.

Cyclical Determinants of Brokerage Commission Rates

This study evaluates the determinants of percentage commission rates in the residential brokerage industry. The model developed here predicts that market share of the brokerage firm, property selling difficulty, and prevailing market conditions influence commission rates. Empirical analysis using a sample of 14,891 condominium transactions from the Fort Lauderdale, Florida area provides support for the model’s predictions.

Disclosure and agency conflict: Evidence from mutual fund commission bundling

This study provides empirical evidence on the role of disclosure in resolving agency conflicts in delegated investment management. For certain expenditures, fund managers have alternative means of payment which differ greatly in their opacity: payments can be expensed (relatively transparent); or bundled with brokerage commissions (relatively opaque). We find that the return impact of opaque payments is significantly more negative than that of transparent payments. Moreover, we find a differential flow reaction that confirms the opacity of commission bundling. Collectively, our results demonstrate the importance of transparency in addressing agency costs of delegated investment management.

Liquidity on the Budapest Stock Exchange 2007-2010

The Budapest Liquidity Measure (BLM) was created by the Budapest Stock Exchange (BSE) in 2005 to provide the market with a simple index which assists market participants in making investment decisions by showing how liquid the single securities and the entire market is at the moment. Liquidity is calculated as the sum of the adverse price movement created by the transaction of the investors and the liquidity premium to be paid for the transaction. These two factors together are also referred to as the implicit cost or indirect cost of trading. The extent of this cost depends on the current state of the order book. Trading also incurs explicit or direct costs, e.g. brokerage fees and commissions, stock exchange fees and taxes (Kutas-Vegh [2005]). These costs are not included in the BLM as these can easily be identified and quantified, and the aim of the BLM is to measure the effect of implicit costs not measured earlier. Our study presents the methodology of the BLM and compares it to the other liquidity proxies used in the market.

Hedge Funds and Analyst Optimism

This study explores the relationship between hedge fund equity holdings and sell-side analyst recommendations. In line with anecdotal evidence which suggests that sell-side analysts are now under tremendous pressure to generate brokerage commissions from their lucrative hedge fund clients, we show that sell-side analysts tend to issue buy and strong buy recommendations on stocks predominantly held by hedge funds. These stocks do not deserve the flattering reports lavished by analysts. Relative to other buy and strong buy recommendations, these favorable recommendations parlay into poorer three-month and six-month stock returns going forward. Hedge funds take advantage of the flattering reports by concurrently offloading their stock holdings. We obtain similar conclusions with analyst upgrades and downgrades, relative recommendations, and 12-month price targets. The findings are robust to adjustments for analyst stock coverage, and are stronger for seasoned analysts, indicating that analysts are not simply incorporating information embedded in hedge fund holdings. Consistent with the notion that analysts are driven by brokerage commissions, analysts are more likely to craft optimistic reports for stocks held by high dollar turnover hedge funds than for stocks held by other less important hedge fund clients. Finally, hedge funds ameliorate the reputation cost of a buoyant recommendation by voting biased analysts as all-stars. Our results suggest that in a post Spitzer-era, Wall Street research departments, having been forcibly weaned off investment banking revenues, now contend with new hedge fund-induced conflicts of interests.

Optimal Brokerage Commissions for Fair Insurance: A First Order Approach

This paper studies a principal-agent insurance brokerage problem with a risk-averse principal (an insured) and a risk-neutral agent (a broker). The concept of “mean-preserving, spread-reducing” (MPSR) effort is introduced to model the broker's activities. Using the first-order approach, it is shown that under some common conditions, the insured may “concavify” the reward function to induce the risk-neutral agent to exert MPSR brokering effort. These conditions, together with an additional condition, guarantee the validity of the first-order approach even when the monotone likelihood ratio condition (used exclusively to justify the first-order approach) is violated.

Brokerage Commissions: The Hidden Costs of Owning Mutual Funds

Brokerage Commissions: The Hidden Costs of Owning Mutual Funds

Brokerage Commissions and Soft Dollars: The Hidden Costs of Owning Mutual Funds

Brokerage Commissions and Soft Dollars: The Hidden Costs of Owning Mutual Funds

Transaction costs and market efficiency: Evidence from commission deregulation

Abstract This study analyzes the impacts of explicit transaction costs on weak-form market efficiency within the context of the brokerage commission deregulation in Japan in October 1999, which led to lower commission rates across the market. Applying two alternative statistical tests to both daily and weekly data, we find that return randomness (unpredictability) increases significantly for stocks listed in Japan, but not for the Japanese stocks dually listed in the United States, which are immune to the deregulation. These results suggest an inefficiency loss or an efficiency gain in the Japanese equity market following the deregulation, insofar as randomness proxies for efficiency.

Transaction Costs and Market Efficiency: Evidence from Commission Deregulation

This study analyzes the impacts of explicit transaction costs on weak-form market efficiency within the context of the brokerage commission deregulation in Japan in October 1999, which led to lower commission rates across the market. Applying two alternative statistical tests to both daily and weekly data, we find that return randomness (unpredictability) increases significantly for stocks listed in Japan, but not for the Japanese stocks dually listed in the United States, which are immune to the deregulation. These results suggest an inefficiency loss or an efficiency gain in the Japanese equity market following the deregulation, insofar as randomness proxies for efficiency.

Does Brokerage Commission Determine Market Share of an Online Brokerage?: An Empirical Investigation of Online Brokerage Services

Does Brokerage Commission Determine Market Share of an Online Brokerage?: An Empirical Investigation of Online Brokerage Services

Brokerage Commissions and Institutional Trading Patterns

The institutional brokerage industry faces an ever-increasing pressure to lower trading costs, which has already driven down average commissions and shifted volume toward low-cost execution venues. However, traditional full-service brokers that bundle execution with services remain a force and their commissions are still considerably higher than the marginal cost of trade execution. We hypothesize that commissions constitute a convenient way of charging a prearranged fixed fee for long-term access to a broker's premium services. We derive testable predictions based on this hypothesis and test them on a large sample of institutional trades from 1999 to 2003. We find that institutions negotiate commissions infrequently, and thus commissions vary little with trade characteristics. Institutions also concentrate their order flow with a relatively small set of brokers, with smaller institutions concentrating their trading more than large institutions and paying higher per-share commissions. These results are stable over time, are consistent with our predictions, and cannot be explained by cost-minimization alone. Finally, we discuss the evolution of the institutional brokerage market within the proposed framework and make informal predictions about future developments in the industry. The Author 2009. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org, Oxford University Press.

The End of “Soft Dollars”?

Over the past few decades, mutual fund shareholders have paid to brokerage and investment banking firms billions of dollars in so-called soft-dollar commissions that have far exceeded the costs of executing the transactions. Over the years, the U.S. SEC’s inconsistent interpretations of pertinent sections of the Securities Exchange Act of 1934 have generally allowed the continued use of soft dollars for the payment of not only brokerage commissions but also research products and services. This article discusses the history of the practice and suggests two approaches that may hasten the end of the era of soft dollars: client commission-sharing arrangements and paying for research directly in cash. See comments on this article.

International market structure: global problems and micro solutions

PurposeThe purpose of this paper is to present new empirical evidence on global trends in equity‐related transaction costs and trading volume, as well as to highlight recent research in international market microstructure.Design/methodology/approachEstimates of brokerage commissions, indirect trading costs, and trading volume are obtained from a comprehensive institutional investor database. Quarterly data are used to compute trends in transaction costs and trading volume, as well as shifts in trading between mature and emerging markets.FindingsThe results indicate a steady decline in brokerage commissions around the world but indirect trading costs appear to have reached a plateau. The fastest growth in trading volume can be found in the emerging markets of South America but the USA leads the way in terms of the steepest reductions in transaction costs.Research limitations/implicationsThe paper relies on one source of transaction cost estimates over a relatively short period (March 2005‐December 2007).Originality/valueThe paper provides comprehensive and current empirical evidence on important trends in international market microstructure.

Which Factors Influence Trading Costs in Global Equity Markets?

This article examines global trends in equity-related transaction costs and trading volume by identifying recent patterns in institutional brokerage commissions, indirect trading costs, and trading activity. The results indicate a steady decline in brokerage commissions around the world, but indirect trading costs appear to have reached a plateau. The fastest growth in trading volume can be found in the emerging markets of South America, but the United States leads the way in terms of the steepest reductions in transaction costs. The empirical evidence also shows there is a simultaneous relationship between global equity trading volume and transaction costs that is driven by trends in both U.S. and local equity markets. This suggests that global investors are likely becoming more cost-sensitive and increasingly open to directing orders to those international markets where transaction costs are lower.

Directed Brokerage no More: The Effects of New Regulation in the Mutual Fund Industry

There is an extensive literature documenting a mutual fund performance deficit, whereby a large number of mutual funds underperform the market index. One possible cause is conflicts of interest between mutual funds and investors. I explore the consequences of a new regulation prohibiting funds from rewarding brokers' promotion efforts via trade execution. While this new rule targeted the elimination of excessive trading commissions, I document that it indirectly affected portfolio management style, fees, performance, and the competitive dynamics of the industry. The new rule led to a decrease in portfolio turnover and an increase in returns for affected funds. However, evidence also indicates that brokers have begun compensating for lost revenues from directed brokerage commissions by implementing revenue sharing agreements. Although affected funds have lower inflows after the regulation, suggesting that brokers' bias is partly eliminated, revenue sharing agreements appear to be the new means of increasing fund inflows.