Transaction cost analysis

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Transaction cost analysis (TCA), as used by institutional investors, is defined by the Financial Times as "the study of trade prices to determine whether the trades were arranged at favourable prices – low prices for purchases and high prices for sales". [1] It is often split into two parts – pre-trade and post-trade. Recent regulations, such as the European Markets in Financial Instruments Directive, have required institutions to achieve best execution.

Contents

Pre-trade

Pre-trade analysis is the process of taking known parameters of a planned trade and determining an execution strategy that will minimize the cost of transacting for a given level of acceptable risk. It is not possible to reduce both projected risk and cost past a certain efficient frontier, since reducing risk tolerance requires limiting market exposure and thus trading faster. In this situation, market impact cost is much greater than for trades that accept greater risk and are executed more slowly. [2]

Effect on Financial Markets

Robert Almgren and Neil Chriss wrote their seminal paper on "Optimal execution of portfolio transactions", modelling the effect of transaction costs on the liquidation of an optimal portfolio. [3] Robert Almgren and Tianhui Li subsequently expanded this to a paper on "Option Hedging with Smooth Market Impact", [4] extending the original analysis to derivative markets.

Post-trade

The post-trade process involves first recording the data from previous trading periods, including trade timing, arrival price, average execution price, and relevant details about market movement. These data are then measured and compared to several benchmarks, such as the volume-weighted average price (VWAP), time-weighted average price (TWAP), participation-weighted average price (PWP), or a variety of other measures. Implementation shortfall is a commonly targeted benchmark, which is the sum of all explicit and implicit costs. Sometimes, an opportunity cost of not transacting is factored in. [5] After measurement, costs must be attributed to their underlying causes. Finally, this analysis is used to evaluate performance and monitor future transactions.

Record

Transaction cost analysis aims to improve trading at the level of individual decisions. This requires accurately recording the timing and content for every event in an order's life cycle. Financial Information eXchange (FIX) messages usually provide a consistent and highly accurate source of information for interactions between traders and brokers.

Data drawn from an order management system (OMS) or execution management system (EMS), however, are not as granular or as uniform as data from FIX, potentially leading to flawed conclusions unless significant effort is made to address this concern. All gaps must be filled in by supplementing FIX or OMS/EMS messages by communicating with brokers, traders, and portfolio managers.

Measure

A variety of measures and benchmarks are used in transaction cost analysis. The multitude of definitions for best execution and the dangers inherent in placing too much emphasis on a single statistic necessitate the ability to compare agents to a diverse set of benchmarks. These comparisons allow costs to be split into several categories, including explicit cost, implicit cost, delay cost, and opportunity cost. The accurate measurement of each of these costs is necessary to facilitate decision management. For example, if the combination of explicit and implicit costs, which represent the realized cost of transacting, is greater than the opportunity cost of not transacting, it suggests that trades may have been executed too quickly. If the reverse is true, it suggests the need to execute more quickly. [6]

Attribute

Reliable measurements allow decisions to be matched with observed outcomes. In the attribution phase, the four cost categories are broken down further, turning previously confusing statistics into intuitive measures representing specific aspects of a trade. For example, application of a transaction cost model helps split Implementation Shortfall into the parts resulting from the size of the order, volatility, or paying to cover the spread. Proper attribution must also distinguish the influence of market factors (i.e. Sector, Region, Market capitalization, and Momentum) from that of human skill.

It is at this stage that problems that can arise if data is not supplemented with communication become clearly evident. For example, an incorrect determination of the time a trader gained control of an order could result in an unfair impact on the performance reported for that trader, when in reality the problem may have resulted from a delay between the portfolio manager and the desk.

Evaluate and monitor

The final stage of transaction cost analysis involves combining the results of the measurement and attribution to evaluate each agent. This is often done through periodic reports detailing important statistics as well as graphics to help visualize trends in the data. Transaction cost analysis providers will often include regular consulting to help draw conclusions from the data, establish goals to improve performance, and monitor future trading to determine the impact of any changes.

Related Research Articles

In economics and finance, arbitrage is the practice of taking advantage of a difference in prices in two or more markets; striking a combination of matching deals to capitalise on the difference, the profit being the difference between the market prices at which the unit is traded. When used by academics, an arbitrage is a transaction that involves no negative cash flow at any probabilistic or temporal state and a positive cash flow in at least one state; in simple terms, it is the possibility of a risk-free profit after transaction costs. For example, an arbitrage opportunity is present when there is the possibility to instantaneously buy something for a low price and sell it for a higher price.

In economics and related disciplines, a transaction cost is a cost in making any economic trade when participating in a market. The idea that transactions form the basis of economic thinking was introduced by the institutional economist John R. Commons in 1931, and Oliver E. Williamson's Transaction Cost Economics article, published in 2008, popularized the concept of transaction costs. Douglass C. North argues that institutions, understood as the set of rules in a society, are key in the determination of transaction costs. In this sense, institutions that facilitate low transaction costs, boost economic growth.

In financial markets, market impact is the effect that a market participant has when it buys or sells an asset. It is the extent to which the buying or selling moves the price against the buyer or seller, i.e., upward when buying and downward when selling. It is closely related to market liquidity; in many cases "liquidity" and "market impact" are synonymous.

<span class="mw-page-title-main">Bid–ask spread</span> Financial markets concept

The bid–ask spread is the difference between the prices quoted for an immediate sale (ask) and an immediate purchase (bid) for stocks, futures contracts, options, or currency pairs in some auction scenario. The size of the bid–ask spread in a security is one measure of the liquidity of the market and of the size of the transaction cost. If the spread is 0 then it is a frictionless asset.

In finance, a portfolio is a collection of investments.

Financial risk management is the practice of protecting economic value in a firm by managing exposure to financial risk - principally operational risk, credit risk and market risk, with more specific variants as listed aside. As for risk management more generally, financial risk management requires identifying the sources of risk, measuring these, and crafting plans to address them. See Finance § Risk management for an overview.

Investment management is the professional asset management of various securities, including shareholdings, bonds, and other assets, such as real estate, to meet specified investment goals for the benefit of investors. Investors may be institutions, such as insurance companies, pension funds, corporations, charities, educational establishments, or private investors, either directly via investment contracts/mandates or via collective investment schemes like mutual funds, exchange-traded funds, or REITs.

Triangular arbitrage is the act of exploiting an arbitrage opportunity resulting from a pricing discrepancy among three different currencies in the foreign exchange market. A triangular arbitrage strategy involves three trades, exchanging the initial currency for a second, the second currency for a third, and the third currency for the initial. During the second trade, the arbitrageur locks in a zero-risk profit from the discrepancy that exists when the market cross exchange rate is not aligned with the implicit cross exchange rate. A profitable trade is only possible if there exist market imperfections. Profitable triangular arbitrage is very rarely possible because when such opportunities arise, traders execute trades that take advantage of the imperfections and prices adjust up or down until the opportunity disappears.

In finance, volume-weighted average price (VWAP) is the ratio of the value of a security or financial asset traded to the total volume of transactions during a trading session. It is a measure of the average trading price for the period.

Algorithmic trading is a method of executing orders using automated pre-programmed trading instructions accounting for variables such as time, price, and volume. This type of trading attempts to leverage the speed and computational resources of computers relative to human traders. In the twenty-first century, algorithmic trading has been gaining traction with both retail and institutional traders. A study in 2019 showed that around 92% of trading in the Forex market was performed by trading algorithms rather than humans.

Best execution refers to the duty of an investment services firm executing orders on behalf of customers to ensure the best execution possible for their customers' orders. Some of the factors the broker must consider when seeking best execution of their customers' orders include: the opportunity to get a better price than what Is currently quoted, and the likelihood and speed of execution.

In financial markets, implementation shortfall is the difference between the decision price and the final execution price for a trade. This is also known as the "slippage". Agency trading is largely concerned with minimizing implementation shortfall and finding liquidity.

The following outline is provided as an overview of and topical guide to finance:

Market microstructure is a branch of finance concerned with the details of how exchange occurs in markets. While the theory of market microstructure applies to the exchange of real or financial assets, more evidence is available on the microstructure of financial markets due to the availability of transactions data from them. The major thrust of market microstructure research examines the ways in which the working processes of a market affect determinants of transaction costs, prices, quotes, volume, and trading behavior. In the twenty-first century, innovations have allowed an expansion into the study of the impact of market microstructure on the incidence of market abuse, such as insider trading, market manipulation and broker-client conflict.

Neil A. Chriss is a mathematician, academic, hedge fund manager, philanthropist and a founding board member of the charity organization "Math for America" which seeks to improve math education in the United States. Chriss also serves on the board of trustees of the Institute for Advanced Study.

In economics and finance, the price discovery process is the process of determining the price of an asset in the marketplace through the interactions of buyers and sellers.

In trading strategy, news analysis refers to the measurement of the various qualitative and quantitative attributes of textual news stories. Some of these attributes are: sentiment, relevance, and novelty. Expressing news stories as numbers and metadata permits the manipulation of everyday information in a mathematical and statistical way. This data is often used in financial markets as part of a trading strategy or by businesses to judge market sentiment and make better business decisions.

Smart order routing (SOR) is an automated process of handling orders, aimed at taking the best available opportunity throughout a range of different trading venues.

Robert F. Almgren is an applied mathematician, academic, and businessman focused on market microstructure and order execution. He is the son of Princeton mathematician Frederick J. Almgren, Jr. With Neil Chriss, he wrote the seminal paper "Optimal execution of portfolio transactions," which Institutional Investor said "helped lay the groundwork for arrival-price algorithms being developed on Wall Street." In 2008 with Christian Hauff, he cofounded Quantitative Brokers, a financial technology company providing agency algorithmic execution in futures and interest rate markets. He is currently Chief Scientist at QB and a visiting professor in Operations Research and Financial Engineering at Princeton University.

Alpha profiling is an application of machine learning to optimize the execution of large orders in financial markets by means of algorithmic trading. The purpose is to select an execution schedule that minimizes the expected implementation shortfall, or more generally, ensures compliance with a best execution mandate. Alpha profiling models learn statistically-significant patterns in the execution of orders from a particular trading strategy or portfolio manager and leverages these patterns to associate an optimal execution schedule to new orders. In this sense, it is an application of statistical arbitrage to best execution. For example, a portfolio manager specialized in value investing may have a behavioral bias to place orders to buy while an asset is still declining in value. In this case, a slow or back-loaded execution schedule would provide better execution results than an urgent one. But this same portfolio manager will occasionally place an order after the asset price has already begun to rise in which case it should best be handled with urgency; this example illustrates the fact that Alpha Profiling must combine public information such as market data with private information including as the identity of the portfolio manager and the size and origin of the order, to identify the optimal execution schedule.

References

  1. ↑ "Transaction Cost Analysis Definition from Financial Times Lexicon". lexicon.ft.com. Retrieved 2016-07-16.
  2. ↑ Almgren, R. and N. Chriss (2000). Optimal execution of portfolio transactions. J. Risk 3 (2), 5–39.
  3. ↑ Robert Almgren, Neil Chriss, "Optimal execution of portfolio transactions" J. Risk, 3 (Winter 2000/2001) pp.5–39
  4. ↑ Robert Almgren; Tianhui Li (2016). "Option Hedging with Smooth Market Impact". Market Microstructure and Liquidity. 2: 1650002. doi:10.1142/S2382626616500027.
  5. ↑ root (2010-06-27). "Implementation Shortfall Definition | Investopedia" . Retrieved 2016-07-16.
  6. ↑ Perold, André. "The Implementation Shortfall: Paper vs. Reality." Journal of Portfolio Management 14, no. 3 (spring 1988): 4–9.
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