The Expanded Implementation Shortfall

The views and opinions expressed in this article are solely those of the author and not necessarily the view and opinion of JPMorgan Chase & Co or any of its divisions or affiliates. This article is for informational purposes only and is not intended as an offer or solicitation for the purchase or sale of any financial instrument. Forthcoming: Robert Kissell, Journal of Trading, Summer 2006

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The Expanded Implementation Shortfall:

“Understanding Transaction Cost Components”

Robert Kissell

May 2006

Abstract:

Transaction costs and transaction cost analysis (TCA) has captured renewed attention in the

financial industry due to the recent increase in electronic orderflow and algorithmic trading.

To assist investors understand these costs and how they affect trading performance we have

unbundled transaction costs into nine components. We provide a categorization scheme to

understand how these costs can be managed during the implementation and a classification

system to understand where and when these costs arise during the investment cycle. This

classification system, the expanded implementation shortfall, is based on the work of Perold

(1988) and Wagner & Edwards (1993), and subsequently serves as foundation for

understanding transaction costs and devising an execution strategy that is consistent with the

overall investment objective.


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I. Introduction

There has been a recent renewed interest in transaction costs and transaction cost analysis

(TCA). This is primarily due to the increase in electronic orderflow and algorithmic trading.

Investors (both buy-side and sell-side alike) are eager to better understand transaction costs

in order to properly assess trader, broker, and algorithmic performance. But, unfortunately,

costs are rarely evaluated from the underlying objective of the fund. And improper evaluation

metrics will likely lead to biased analyses and erroneous conclusions. There is also often a

disconnect between the trader’s implementation goals and the portfolio manager’s investment

goals which can lead to an inefficient portfolio mix and further reduced utility (Kissell &

Malamut, 2006b). In order to properly measure implementation performance it is necessary

to have an understanding of all transaction cost components and how they influence trading.

What are transaction costs? Transaction costs are those costs that arise during the

implementation of any business decision. In economic terms they are the costs paid by

buyers but not received by sellers, and/or the costs paid by sellers but not received by buyers.

In the equity markets, financial transaction costs represent the costs incremental to the

decision prices without regards to who receives the incremental payment. For example, a

buyer of stock wishing to transact at $30.00 but ultimately pays $30.25 per share in total

(including commissions, fees, market impact, etc.) incurs total transaction cost of $0.25/share

regardless of who receives this incremental payment (e.g., broker, seller, exchange, etc.).

Similarly, a seller wishing to transact at $25.00 but ultimately receives only $24.90 per share

incurs total transaction cost of $0.10. This definition follows directly from the


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Implementation Shortfall (IS) metric proposed by Perold (1988) and is a good place to begin

our investigation of transaction cost components.

II. Implementation Shortfall

Implementation shortfall is measured as the difference between the dollar return of a paper

portfolio (paper return) where all shares are assumed to transact at the prevailing market

prices at the time of the investment decision and the actual dollar return of the portfolio (real

portfolio return). Mathematically, this is written as:

Return Portfolio Real -Return Paper IS= (1)

To gain a thorough understanding of how these transactions costs effect portfolio returns we

consider three cases of Implementation Shortfall: i) complete execution where all shares are

transacted, ii) incomplete execution where the fund incurs opportunity cost, and iii)

incomplete execution where we differentiate between trading related, investment related, and

opportunity cost (expanded implementation shortfall). This last case of implementation

shortfall classifies costs based on where they occur during the investment cycle. The

technique is attributable to Wagner & Edwards (1993) and is of fundamental importance for

understanding TCA and devising proper performance metrics.

Case I: Complete Execution

A fund wishes to purchase S shares of a stock that is current trading at dP dollars per share.

If at some future period in time such (e.g., the end of trading) the stock price is NP , the total


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dollar paper return is calculated as follows:

dN PSPS ⋅−⋅=Return Paper (2)

Here, dPS ⋅ represents the starting value of the portfolio (e.g., the amount of money to

invest), NPS ⋅ represents the ending value of the portfolio (e.g., the portfolio value at the end

of trading)1.

If the manager transacted all S shares, e.g., Ss j =∑ , the actual portfolio return is

computed as follows:

fixedpsPS jjN −−⋅= ∑Return Portfolio (3)

where, js is the number of shares executed in the jth transaction, ∑ js is the total number of

shares executed, jp is the price of the jth transaction, and jj ps∑ is the total transaction

value (e.g., cash invested). The fixed fees represent the commission, taxes, clearing and

settlement charges, ticket charges, etc., and results in a reduction in portfolio return. Also,

0, >jsS indicates a buy order (cash investment) and 0, <jsS indicates a sell order (cash

redemption).


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Then, implementation shortfall is then computed as follows:

( ) ( )

fixedSPps

fixedpsPSPSPS

djj

jjNdN

−−=

−−⋅−⋅−⋅=

∑

∑ 4444 34444 2144 344 21Return PortfolioReturnPaper

IS

(4)

Notice that when all shares are executed the implementation shortfall measure is simply the

total transaction value minus the value at the time of the investment decision minus fixed

costs. The measure does not depend on the future stock price NP at all.

Case II: Incomplete Execution (Opportunity Cost)

In a situation where the entire order is not executed, e.g., Ss j <∑ , the paper return is still

computed according to equation (2), but actual portfolio return is computed in a slightly

different manner. This is explained as follows:

The total cash on hand to invest at time dt is dPS ⋅ . If the actual transacted value is∑ jj ps ,

the dollar amount that is not invested in the portfolio is simply the difference of these

amounts, e.g., jjd psSP ∑− . Then, the ending value of the portfolio is equal to the total

number of shares transacted evaluated at the stock price at the end of the trading horizon,

1 In these examples we assume all decisions are buys orders (cash investment), e.g., S>0 and sj>0. In situations

where the decision is a sell order (cash redemption) we simply take the sign of S and sj to be negative, e.g., S<0

and sj<0. This way, the side of the transaction does not change any of the formulations.


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e.g., ( ) Nj Ps∑ , plus the amount of cash not invested in the portfolio, e.g., jjd psSP ∑− .

These values are as follows:

{AvailableCash

Value Portfolio Beginning dSP= (5)

( )44 344 2143421

Dollars UninvestedValueStock

Value Portfolio Ending ∑∑ −+= jjdNj psSPPs (6)

Actual portfolio return is then calculated as follows:

( ){ }( ) fixedpsPs

fixedpsSPPsfixed

jjNj

jjdNj

−−=

−−−+=

=

∑∑∑∑ dSP

-ValueBeginning-ValueEnding Return Portfolio

(7)

Implementation shortfall in a situation with unexecuted orders is:

{ } ( ){ }44444 344444 214434421

Return Portfolio

NReturnPaper

PIS fixedpssSPSP jjjdN −−−−= ∑∑ (8)

Expanding on equation (8) we have:

( ) fixedpsSPPsS jjdNj −+−−= ∑∑IS (9)

where ∑− jsS is the number of unexecuted shares.

The number of initial shares S to transact can be written as ( ) ∑∑ +−= jj ssSS .

Therefore, equation (9) can be rewritten as follows:


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( ) ( )( )( ) ( ) ( )

( ) ( )( ) fixedPPsSPsps

fixedpsPsPsSPsS

fixedpsPssSPsS

dNjdjjj

jjdjdjNj

jjdjjNj

−−−+−=

−+−−−−=

−++−−−=

∑∑∑∑∑∑∑

∑∑∑∑IS

(10)

Finally, we have the implementation shortfall measure defined by Perold (1988) that

distinguishes between execution cost and opportunity cost of the order.

( ) ( )( ) fixedPPsSPsps dNjdjjj −−−+−= ∑∑∑ 444 3444 21444 3444 21Costy OpportunitCostExecution

IS (11)

Case III: Incomplete Execution (Investment Related and Trading Related Costs)

Inspection of equation (11) shows that the execution cost component of the implementation

shortfall formula actually spans two time horizons: investment and trading. The investment

horizon is the time period from the investment decision td to the time that trading begins t0.

The trading horizon is the time period from the commencement of trading t0 to the end of

trading tn.

If 0P represents the midpoint of the bid-ask spread at the time the order was entered to the

market (e.g., the arrival price), the price change over the period td to tn can be written in terms

of 0P as follows:

( ) ( ) ( )dNdN PPPPPP −+−=− 00 (12)

Then, equation (11) can be rewritten as:


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( ) ( )( ) ( )( )

( ) ( ) ( )( ) fixedPPsSPspsPPS

fixedPPsSPPsSPsps

NjdjjjN

djNjdjjj

−−−+−+−=

−−−+−−+−=

∑∑∑∑∑∑∑

00

00IS (13)

That is,

( ) ( ) ( )( ) fixedPPsSPspsPPS NjdjjjN −−−+−+−= ∑∑∑ 444 3444 21444 3444 2143421Costy Opportunit

0

Related TradingRelated Investment

0IS Expanded (14)

This is the expanded implementation shortfall metric proposed by Wagner & Edwards (1993)

that makes a distinction between the investment and trading horizons and provides important

insight into specifying appropriate execution strategy. For example, see Almgren & Chriss

(2000), Kissell & Glantz (2003), or Rakhlin & Sofianos (2006).

III. Transaction Cost Classification

As depicted in equation (14) transaction costs can be classified into investment related,

trading related, and opportunity cost. This classification system is described below:

Investment-Related Costs. Investment related transaction costs are those costs that arise

during the investment decision phase of the investment cycle. This constitutes the period of

time from the investment decision to the time the order is released to the market. Investment-

related transaction costs often arise due to lack of communication between the portfolio

manager and trader in deciding upon the proper implementation objective (strategy) or due to

a delay in selecting the appropriate broker, algorithm, or algorithmic parameter. The longer it


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takes for the manager and trader to resolve these issues the more potential there is for adverse

price movement (ultimately making the investment more costly). Traders often spend

valuable time investigating how lists should be implemented and what broker or trading

venue to use. The easiest way to reduce investment related transaction cost is for the manager

and traders to work closely together to determine the strategy most consistent with the

investment objective of the fund. This, however, requires proper pre-trade analysis and

decision-making tools to be able to rapidly evaluate costs, assess strategies, and select

algorithms.

Trading-Related Costs. Trading-related transactions costs comprise the largest subset of

transaction costs and include those costs that arise during the implementation of the

investment decision (the time period from the start of trading to the end of trading). While

these costs cannot be eliminated completely they can be managed via an appropriate

execution strategy. The largest trading related transaction costs are market impact and timing

risk. But these components are conflicting terms. Market impact is highest utilizing an

aggressive trading strategy and lowest utilizing a passive strategy. Timing risk, on the other

hand, is highest with a passive strategy and lowest with an aggressive strategy. Traders,

therefore, need to balance the tradeoff between market impact and timing risk based on the

funds overall risk appetite. Furthermore, they need to ensure that the execution strategy or

algorithm is consistent with the overall investment objectives of the fund. This requires a

thorough cost analysis of the order or trade list and a complete understanding of transaction

cost components.


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Opportunity Cost. Opportunity cost represents the foregone profit or loss resulting from not

being able to fully execute the order within the allotted time period. It is measured as the

number of unexecuted shares multiplied by the price change over the period the order was in

the market. That is:

( )( )0O PPsSC Nj −−= ∑ (15)

Opportunity cost will arise either because the trader was unwilling to transact shares at the

existing market prices, because of insufficient market liquidity, or both. The best way to

reduce opportunity cost is for managers and traders to work together to determine if the

market can readily absorb the specified number of shares within the manager’s specified

price range. If the trader determines that the market can not readily absorb the entire order

the manager can modify the order to a size that can be easily transacted in the marketplace

prior to trading and then invest the surplus cash into the next most attractive investment

instrument.

Opportunity cost can be viewed as an investment related and trading related cost. This can be

shown by tracing the price trajectory ( )dN PP − over the entire time horizon ( )dN tt − . It is

shown mathematically as follows:


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( )( )( ) ( ) ( )[ ]( )( ) ( )( )

444 3444 21444 3444 21Horizon Trading

0

Horizon Investment

0

00

O

∑∑∑∑

−−+−−=

−+−−=

−−=

jNdj

dNj

dNj

sSPPPPsS

PPPPsS

PPsSC

(16)

IV. Transaction Cost Categorization

Financial transaction costs are comprised of fixed and variable components and consist of

both visible and hidden (non-transparent) fees. The fixed-variable categorization of costs

follows the more traditional economics breakdown of costs and the visible-hidden

categorization follows the more traditional financial description of transaction costs.

Fixed cost components are those costs that are not dependent upon the implementation

strategy. They cannot be managed or reduced during implementation. Variable cost

components, on the other hand, do vary during implementation of the investment decision

and are a function of the underlying implementation strategy. Variable cost components

make up the majority of total transaction costs. Money managers, traders, and brokers can

add considerable value to the implementation process simply by controlling these variable

components in a manner consistent with the overall investment objective of the fund.

Financial transaction costs are also categorized as visible or hidden cost components. Visible

or transparent costs are those costs whose fee structure is known in advance. For example,

visible costs may be stated as a percentage of traded value, as a $/share cost applied to total

volume traded, or even as some percentage of realized trading profit. Visible cost


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components are primarily attributable to commissions, fees, spreads, and taxes. Hidden or

non-transparent transaction costs are those costs whose fee structure is not known in advance

with any degree of exactness. For example, the exact cost for a block order will not be known

until after the transaction has been completed (if executed via agency) or until after the bid

has been requested (if principal bid). The cost structures for these hidden components are

typically estimated using statistical models. For example, market impact costs are often

estimated via non-linear regression estimation.

Non-transparent transaction costs comprise the greatest portion of total transaction cost and

provide the greatest potential for performance enhancement. Traders and/or algorithms need

to be especially conscious of these components in order to add value to the implementation

process. If they are not properly quantified and controlled, they can cause a superior

investment opportunity to become only marginally profitable and/or a profitable opportunity

to turn bad.

V. Unbundled Transaction Cost Components

Investors can gain significant insight into how transaction costs influence trading by

unbundling these costs into their basic components. In total, there are nine distinct cost

components: commissions, taxes, fees, spreads, delay cost, price appreciation, market impact,

timing risk, and opportunity cost. Each of these is described below.

1. Commission


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Commission is payment made to broker-dealers for executing trades. It is generally

expressed on a per share basis (e.g., cents per share) or based on total transaction value (e.g.,

some basis point of transaction value). While commission charges are known in advance,

they do vary from broker to broker. At times, they may vary based on trading difficulty

where easier trades receive a lower rate and the more difficult trades are charged a higher

rate. Commissions are categorized as a fixed and visible transaction cost component.

2. Fees

Fees charged during execution of the order include ticket charges assessed by floor brokers,

exchange fees, clearing and settlement costs, SEC transaction fees. Very often brokers

bundle these fees into the total commissions charge. Fees are a fixed and visible transaction

cost component.

3. Taxes

Taxes are a levy assessed to funds based on realized earnings. Tax rates vary by investment

and type of return. For example, capital gains, long-term earnings, dividends, and short-term

profits can all be taxed at different rates. Taxes are a visible and variable cost component.

They are visible because tax rates are known in advance and variable because the exact

transaction price dictates the total tax quantity.


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4. Spreads

Spread cost is the difference between best offer (ask) and best bid price. It is intended to

compensate broker-dealers for matching buyers with sellers, for risks associated with

acquiring and holding an inventory of stocks (long or short) while waiting to unwind the

position, and for the potential of adverse selection resulting from transacting with informed

investors. Spreads represent the round-trip cost of transacting for small orders (e.g., 100

share lots) but do not accurately represent the round-trip cost of transacting blocks (e.g.,

10,000+ shares). Spread cost is a visible and variable transaction cost component. They are

visible because they are easily observed from the market at any point in time. They are

variable because they do at times vary across the day. For example, spreads for some stocks

tend to be larger at the open and close than during midday.

5. Delay Cost

Delay cost represents the loss in investment value between the time the managers makes the

investment decision dt and the time the order is released to the market 0t . Managers who buy

rising stocks and sell falling stocks will incur a delay cost. Any delay in order submission in

these situations will result in less favorable execution prices and higher costs. Delay costs

can arise for many reasons. First, delay cost may arise because traders hesitate in releasing

the orders to the market. Second, delay cost may arise due to trader uncertainty regarding

who are the “capable” brokers for the particular order or trade list. Some brokers are more

capable at transacting certain names or more capable in certain market conditions. Third,

traders may incorrectly anticipate market direction and wait for better prices. But if the


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adverse trend persists the delay cost can be quite large. Fourth, traders may unintentionally

convey information to the market that they need to transact shares causing adverse price

movement prior to order submission. Fifth, overnight price change is another reason for

delay cost. For example, stock price often changes from the close to the open. Investor can

not participate in this price change so the difference results in a sunk cost in times of adverse

change or a savings in times of a favorable change. Delay cost is a non-transparent and

variable transaction cost component.

Example: Delay Cost

A fund manager instructs the trader to buy 250,000 shares of a stock that is currently trading

at $30. The trader then investigates who is most capable broker to handle the order. However,

by the time the trader chooses a broker and submits the order to the market the price has risen

to $30.25 per share. In this case, the trader’s hesitation cost the fund $0.25 per share or 83

basis points. This 83bp is an avoidable delay cost. In another situation, after the market close

a manager uncovers an undervalued stock with closing price of $50 and instructs the trader to

purchase 50,000 shares. The trader submits a buy order prior to the market open the next day

but because the stock opens at a higher price the execution occurs at $50.50 resulting in a

delay cost of $0.50 or 100bp. In this case the delay cost may be due to the market drawing

the same conclusion as the manager about the stock being undervalued and adjusting its

price. Here the delay cost is an unavoidable cost.


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6. Price Appreciation

Price appreciation represents the natural price movement of stock. For example, how the

stock price would evolve in a market without any uncertainty. Price appreciation is also often

referred to as price trend, drift, momentum, or alpha. It represents the cost (savings)

associated with buying stock in a rising (falling) market or selling (buying) stock in a falling

(rising) market. Price appreciation is dependent upon the stock trend and implementation

strategy. Price appreciation is a non-transparent variable transaction cost component.

Example: Price Appreciation

A manager decides to buy 250,000 shares of XYZ currently trading at $30 and expected to

increase 20% annually. Assuming a linear trend the stock will increase $0.04/day. If the

trader were to buy 50,000 shares a day over next five days they can expect to realize an

average price of $50.08 per share. Total price appreciation cost in this example is $.08/share

or 16bp.

7. Market Impact

Market impact cost represents the movement in the price of the stock caused by a particular

trade or order. Market impact is one of more costly transaction cost components and always

causes adverse price movement and results in a drag on performance. Market impact is often

incorrectly referred to as slippage or erosion. While it does constitute a part of these terms it

certainty does not comprise the entire portion. Market impact costs will occur for two

reasons: i) the liquidity demands of the investor, and ii) the information content of the order.


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The liquidity demand of the order requires a payment (premium for buys or a discount for

sells) to attract additional buyer or sellers into the market. The information content of the

trade typically signals to the market that the stock is under- or over-valued. Market impact

cost is dependent on size, volatility, side of transaction, prevailing market conditions over the

trading horizon such as liquidity and intraday trading patterns, and specified implementation

strategy. Market impact is a non-transparent variable transaction cost component.

Mathematically, the market impact cost of an order is the difference between the price

trajectory of the stock with the order and the price trajectory that would have occurred had

the order had not been released to the market. Unfortunately, we can not simultaneously

observe both price trajectories - it is only possible to observe the evolution of price with the

order or the evolution of price without the order. It is not possible to construct a controlled

experiment to simultaneously observe both circumstances of price evolution. As a result,

market impact has often been described as the Heisenberg uncertainty principal of finance.

Madhavan (2000) provides a nice description of market impact cost for a sell order. This is

illustrated in Figure 1. In this example, the stock is trading at around $10.00. An investor

enters a sell order into the market which exerts downward pressure on the price and the order

is subsequently traded at $9.80. Shortly thereafter, the transaction the price rebounds to

$9.95. It does not revert all the way back to $10 because the market infers the sell order to be

a signal that the stock was likely overvalued and adjusts it price to a lower level. In this

example the total market impact cost of the trade is $0.20 computed as the original price


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minus the transaction price. Permanent market impact cost is $0.05 (since the price was

originally $10 and reverted to $9.95), and temporary market impact cost is $0.15 (computed

as the difference between total and permanent impact).

A second description of market impact cost can be illustrated through traditional economic

supply-demand curves (Figure 2). Suppose the stock is currently in equilibrium with q*

shares transacting at price of p*. A buyer enters the market with an incremental ∆q shares

which results in a shift in the market demand curve from D to D’ (to reflect increased

demand). The information content associated with this buy order signals to the market that

the stock is undervalued and causes an upward shift in the market supply curve from S to S’

(to reflect the higher price). Therefore, the transaction price for the incremental ∆q shares

will be p1.

After those shares are transacted in the market there is then uncertainty as to what will occur

next. We know that demand will decrease since those ∆q shares have been transacted. But

what will be the new post trade level of demand?

In one scenario, demand is expected to revert back to its original level q*, e.g., there will be a

shift in the market demand curve from D’ to D”. Then the new equilibrium point will be q*

shares (the same as the original) but a new equilibrium price of p2. This is determined from

the intersection of D’’ and S’. Hence, total market impact cost is p1 – p*, temporary market

impact cost is p1 – p2 and permanent market impact cost is p2 – p*. In this scenario, the


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assumption is that the buyers will still be willing to transact shares at the higher prices. For

example, index managers often need to transact shares that are in the benchmark index

regardless of the prices.

A second possible scenario states that since the price increased after the trade (due to the

information content of the buy order) there will be fewer participants willing to transact at

higher prices. Therefore, there will be a post trade decrease in demand. For example, many

value managers will only transact in stocks that are incorrectly priced in the market, so once

the market adjusts the prices to the true intrinsic value the opportunity for superior returns is

reduced and decreased demand for transaction.

This scenario is explained through the market demand curve shifting from D’ back to D.

Then the new equilibrium price will be p3 (still higher than the original level of p* but lower

than in the first scenario of p2) but a lower equilibrium demand of q’. This equilibrium point

is determined by the intersection of D and S’. In this example, the market impact cost is

exactly the same as the first scenario, e.g., p1 – p*. But temporary market impact cost is

higher p1 – p3 and permanent market impact cost is lower p3-p*.

The uncertainty in the new equilibrium level of demand and price is a major reason behind

the difficulty in distinguishing between temporary and permanent market impact cost.

Unfortunately, it is rarely addressed in the financial literature.


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Figure 1 Market Impact Illustration – Sell Order

Market Impact Illustration - Sell Order

Time

Price

Total Impact Temporary

Permanent10.00

9.80

9.95

Trade

Figure 1: Market Impact Illustration – Sell Order. The diagram shows the stock price fluctuating at around

$10.00 until an investor sells shares and pushes the price down to $9.80. Immediate after the transaction the

price rebounds back to $9.95. The total market impact of this transaction is $0.20 per share ($10.00-

$9.80=$0.20). Temporary market impact is $0.15 ($9.95 – $9.90 = $0.15), and permanent market impact is

$0.05 ($10.00-$9.95=$0.05).


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Figure 2 Supply Demand Illustration

Supply-Demand Equilibrium - Buy Order

Quantity

Price

D′

S

D

S′

D′′

q*+?qq*

p

p*

q'

pp

Figure 2: Supply-Demand Equilibrium – Buy Order. The stock price is initially in equilibrium at q* shares

and a price of p*. A buyer enters the market causing an imbalance of ∆q shares which shifts the market

demand curve from D to D’. This action signals to sellers that the price is undervalued so sellers increase

their market price (e.g., resulting in a shift of the market supply curve from S to S’). Therefore, the

execution price of the incremental ∆q shares is p1. But after the ∆q shares have been transacted there is

uncertainty regarding what might occur. One scenario expects that buying demand will returns to its normal

level of q* thus the market demand curve shifts back from D’ to D’’. This results in a new equilibrium

price of p2 and q* shares. Another scenario expects that since market prices have increased due to the

information content of the order there will be fewer buyers willing to transact. This results in a decrease in

demand from the original levels (e.g., the market demand curve shifting from D’ back to D) and a new

equilibrium point with price p2 and quantity q’.


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Example 1: Temporary Market Impact

A trader receives a buy order for 50,000 shares of RLK. Market quotes, however only have

1,000 shares at the best ask of $50. There is another 2,000 shares at $50.25, 3,000 shares at

$50.50, and 4,000 shares at $50.75. The trader can only execute 1,000 shares at the best

available price and another 9000 shares at the higher prices for an average price of $50.50,

but only executes 10,000 shares of the original 50,000 share order. To attract the additional

liquidity into market the trader needs to offer a premium, hence, incurring market impact

cost. This cost stems from the liquidity demand that causes an imbalance in supply-demand

equilibrium (see Figure 2). Liquidity demand is an example of temporary market impact cost.

Example 2: Permanent Market Impact

A trader receives a buy order for 250,000 shares of RLK. But inadvertently, this information

is released to the market which signals to participants that the stock is likely undervalued.

Thus, investors who currently own stock will be unwilling to sell shares at the undervalued

price and will adjust their price upwards to reflect the new intrinsic value. Information

content is an example of permanent market impact.

8. Timing Risk

Timing risk refers to the uncertainty surrounding the estimated transaction cost. It is due to

price volatility and liquidity risk. Price volatility will cause the stock price to be either higher

or lower than estimated due to forces independent of the order. Liquidity risk will cause the

market impact cost to be either higher or lower than estimated. The liquidity portion of


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timing risk is dependent upon volumes, intraday trading patterns, and cumulative market

impact cost caused by other market participants. Timing risk is a hidden variable transparent

cost component.

Example: Timing Risk

If a stock is currently trading at $50 we can be reasonable sure that it will be trading between

$49.90 and $50.10 over near term (say next few minutes or hours) but we do not have the

same level of confidence that the stock will still be trading between $49.90 and $50.10 after a

couple of days. A more realistic price range for this time period is likely to be between

$48.50 and $51.50. When investors execute orders over time, prices will likely become

higher or lower due to factors not related to the order. Assume a trader receives a buy order

for 100,000 shares of ABC and decides to trade the list passively by slicing the order over

several days. If the price moves favorably they will receive better prices but if the price

moves adversely they will receive worse prices. During times of higher market volume

traders will incur less market impact costs and during times of lower market volume traders

will incur higher market impact cost. Timing risk is intended to provide a reasonable range

surrounding the estimated transaction cost of the order. It is not intended to provide a range

surrounding the stock price at the end of trading.

9. Opportunity Cost

Opportunity cost represents the forgone profit of not being able to completely execute the

investment decision. The reason is usually due to insufficient liquidity, adverse price


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movement, or both. In situations where managers are buying stocks that are rising and selling

stocks that are falling, the inability to fully execute an investment decision results in a missed

profiting opportunity. It represents a cost to the fund and results diminished portfolio returns.

Opportunity cost is a hidden variable transaction cost component.

Example: Opportunity Cost

A manger discovers an undervalued stock currently trading at $50 per share and instructs a

trader to buy 250,000 shares. The trader executes the order using a slicing strategy in order to

minimize market impact but is only able to 200,000 shares by the end of day. At that time,

the price increased to $51 and is no longer undervalued so the manager cancels the remaining

shares. The opportunity cost of not being able to execute this entire order is $50,000. This is

computed as 50,000 multiplied by the $1/share price movement.

VI. Unbundled Transaction Costs Categorization

The categorization of the nine unbundled transaction cost components is shown in Table 2.1.

As shown in the table, each of these costs is categorized as fixed or variable and as visible or

non-transparent. Notice that the majority of these costs are non-transparent and variable. This

represents both good and bad news for investors. It is good news because the costs are

primarily variable and can be controlled during implementation via an appropriate trading

strategy or algorithm, so traders who practice fiduciary transaction cost management during

implementation can add significant value to the process. But unfortunately, the bad news is


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that the cost structure is unknown so investors need to estimate these cost structures and

develop proper and accurate transaction cost models. And this is no easy task.

To the extent that the cost structure estimation model and parameters is estimated accurately

investors will be able to reduce overall costs. But incorrect specification of these parameters

ould result in improper strategy selection, higher cost, and reduced performance.

Table 2.1 Unbundled Transaction Costs

Fixed Variable

Visible: Commission SpreadsFees Taxes

Non-Transparent: n/a Delay CostPrice AppreciationMarket ImpactTiming RiskOpportunity


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Table 2.2 Transaction Cost Classification

Transaction Costs

Investment Costs Trading Costs Opportunity Cost

- Taxes - Commission - Opportunity Cost- Delay Cost - Fees

- Spreads- Price Appreciation- Market Impact- Timing Risk

VII. Conclusion

The recent increase in electronic orderflow and algorithmic trading has caused a renewed

interest in transaction costs and transaction cost analysis (TCA). But a complete

understanding of these costs is required in order to be positioned to specify appropriate

execution strategies and algorithms. For example, some of the more sophisticated trading

algorithms have been designed to manage transactions costs (most notably market impact and

timing risk) over the specified trading horizon while adapting to changing market conditions

and prices (Malamut & Kissell, 2006a). So if these cost components are not fully understood

it is unlikely that the investor specified algorithmic trading rules will be able to provide

implementation that is consistent with the underlying investment objectives of the fund.


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To assist investors better understand costs we provided a system that unbundled transaction

costs into nine components and then categorized these costs as fixed or variable and as

hidden or transparent in order to understand which costs can be managed via an effective

trading strategy. Furthermore, we provided a transaction cost classification system based on

where and when these costs occur during the investment cycle (e.g., investment related,

trading related, and opportunity cost) in order to gain insight into whose role it is to manage

what costs (e.g., portfolio manager, trader, or broker). This classification scheme, denoted in

this paper as the expanded implementation shortfall, combines the seminal work of Perold

(1988) and Wagner & Edwards (1993). As shown above, the expanded implementation

shortfall metric is of fundamental importance for understanding transaction costs. It also

serves as the basis for managing transaction costs and ensuring that the underlying execution

strategy is consistent with the overall investment objective of the fund.

VIII. References

Almgren, R., and N. Chriss, (2000) "Optimal execution of portfolio transactions," Journal of

Risk (3) 2, pg. 5-39.

Kissell, R., M. Glantz (2003). Optimal Trading Strategies, AMACOM, Inc., New York.

Kissell, R., and R. Malamut (2006a),"Algorithmic Decision Making Framework," Journal of

Trading, Winter 2006, Vol. 1, No. 1, pg, 12 – 21.

Kissell, R., and R. Malamut (2006b),"Unifying the Investment and Trading Theories,”

unpublished manuscript.


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Madhavan, A. (2000). “Market Microstructure – A Survey,” Journal of Financial Markets 3,

pg. 205-258.

Perold, A. F. (1988), “The implementation shortfall: Paper versus reality,” Journal of

Portfolio Management Vol. 14, No. 3 (Spring), pg. 4-9.

Rakhlin, D., and G. Sofianos (2006), “The Impact of an Increase in Volatility on Trading

Costs,” Journal of Trading, Spring 2006, Vol. 1, No. 2, pg. 43- 50.

Wagner, W., and H. Edwards (1993). “Best Execution,” Financial Analyst Journal, Vol. 49,

No. 1, Jan/Feb 1993, pg 65-71.

Documents

The Expanded Implementation Shortfall