1. JOURNAL OF FINANCIAL AND QUANTITATIVE ANALYSIS VOL. 18, NO. 3. SEPTEMBER 1983
Negotiated Brokerage Commissions
and the Individual Investor
Gerald A. Blum and Wilbur G. Lewellen*
The elimination in 1975 of fixed minimum brokerage commission rates for
agency transactions in equity securities was one of the more highly publicized
events in the still-ongoing process of the deregulation of American financial mar-
kets. While, prior to that time, commission rates on large stock transactions—
that were executed primarily for institutions—had become increasingly subject
to negotiation, individual investors effectively faced an industry-wide fixed price
schedule for the vast majority of their transactions. At the insistence of the Secu-
rities and Exchange Commission, the privilege of negotiation on commission
rates was extended to securities trades of all sizes as of May 1, 1975, a date the
brokerage industry only half-humorously dubbed ' 'Mayday'',
Since then, some of the anticipated shake-out in the industry has occurred as
weaker firms have been absorbed by their stronger competitors, and a new class
of "discount" brokerage houses offering little more than order execution ser-
vices at commission rates well below those posted by the full-service retail firms
has grown up (see [5], [6], and [13]). The latter have not, however, disappeared.
Presumably, this is because individual investors either continue to value the re-
search and other services they acquire with their higher commission rates, or
because those rates indeed are often negotiated downward in practice at full-ser-
vice houses. Our focus here is on the second of these two phenomena.
Specifically, we shall examine the frequency, magnitude, and correlates of
the discounts from scheduled commission rates obtained by a large sample of
individual investors during the 1970s, We find that such discounts from posted
rates did become fairly common, that they increased in size over time, and that
they were related to certain distinctive characteristics of both the investors and
the securities transactions involved in a manner that seems plausible. Nonethe-
• Babson College and Purdue University, respectively. This study comprises a portion of the
National Bureau of Economic Research program of research in Financial Markets and Monetary Eco-
^Q^Tc^on ' " P P " " ^°' ""^ " " ' ' y f'""" "'^ National Science Foundation under Grant No SOC-
7825789 IS gratefully acknowledged. Any opinions, findings, and conclusions or recommendations
expressed are those of the authors, and do not necessarily reflect the views either of the National
Science Foundation or of the National Bureau of Economic Research. The authors acknowledge-
without imputing culpability—the advice and suggestions of K. Rao Kadiyala, Gary G. Schlarbaum
Keith V. Smith, and Gordon P. Wright.
331

2. less, they were not sufficient to offset fully the appearance of a general trend
since Mayday for small investors' commission costs to rise, at least at full-ser-
vice brokers [12].
I. The Data
The transactions studied are those that were executed by one of the nation's
largest retail brokerage firms on behalf of its customers between May 1, 1975
and the end of September 1979. The accounts involved are those of mdividual
investors- corporate, institutional, and investment club accounts were excluded
from consideration. The sample selected has three components. The first compo-
nent was chosen randomly from a list of the firm's customers who had aecounts
open eontinuously over the period January 1, 1964 through December 31, 1970.
This group comprised the sample that was developed for an earlier study of mdi-
vidual investor behavior [2], [3], and data for transactions on the aecounts that
remained open were compiled through 1979 for the current investigation.
The seeond component consists of a similar, new random sample drawn
from the list of accounts that were in eontinuous existence from January 1, 1971
through September 30, 1979. This sample was obtained to be the focus of an
update and expansion of the analyses performed on its predecessor. In both in-
stances, a requirement of account longevity was imposed to permit longitudinal
studies of investment performance and behavior to be undertaken [4], [11]. No
restrictions or minimum conditions on either trading frequency or portfolio size
were applied as seleetion criteria, however; both samples are quite diverse along
these dimensions. In total, the two groups include approximately 6,000 mdividu-
als
The third component, chosen as a control, was drawn at random from all the
accounts that were open with the firm at some time between January 1971 and
September 1979, regardless of duration. The control group contains just over
2 000 individuals. For all three groups, a complete record for 1971-1979 of the
trading activity in the account was furnished by the cooperating brokerage house.
Those transactions that occurred beginning on May 1, 1975 are our present con-
Trades executed by the firm on a principal basis, and ones not involving
common stocks, were culled from the file. The resulting data base eneompasses
93 528 agency transactions in equity securities, the salient features of which are
portrayed in Table 1. As is evident, transactions over a wide range of sizes are
included, with ample representation at all levels. While trades on the New York
Stock Exchange comprise the majority, some 40 percent involved securities
listed on the American or one of the regional exchanges, or traded in the UlC
market The transactions are divided approximately evenly between purchases
and sales with round-lot orders predominant. Just 50 percent were executed for
eustomers who maintained a margin account.' For all transactions, the brokerage
commissions actually paid by the customer were recorded. These were compared
1 This does not necessarily imply that every trade in such an account was margined, however.
The transactions file does not contain that information on a trade-by-trade basis.
332

3. with the charges in the firm's posted rate schedules to determine whether com-
mission discounts were obtained.
TABLE 1
Characteristics of the Transactions Data Base: 1975-1979
(N = 93,528)
Type of Trade Trading Locale
Purchase 49% NYSE 61%
Sale 51 AMEX 13
Quantity OTC 5
Round Lot 85% Regionai 21
Odd Lot 15 Transaction Size*
Account Type Under$2000 36%
Margin 45% $2000-84999 32
Cash 55 $5000-39999 18
$10,000-$24,999 10
$25,000-$49,999 3
$50,000 and over 1
*Per-share price times number of shares traded. Exoludes commission charges
An issue of concern with regard to the generalizability of our findings is the
extent to which the observed experience of the customers of the particular firm
that supplied the data analyzed here can be considered representative. We believe
so, for several reasons—among them, the mandates of competition. The firm has
long been, and still continues to be, among the nation's ten largest full-service
brokerage houses. It has primarily a retail orientation, and has managed success-
fully to grow and remain profitable in the rapidly changing environment of the
last decade. Our assumption is that this would not have occurred had the firm not
sustained a competitive array of investment products and prices. If there were
pressures in the post-Mayday market to provide commission discounts, the firm
inevitably would have felt them in the same way as other full-service brokerage
houses.
Second, in earlier studies, the firm's customer base was found to exhibit
demographic characteristics that in all major dimensions were a virtual duplicate
of those of the total U.S. shareholder population (see [2], [8], and [9]). One
might, therefore, expect that the degree of interest in, and insistence upon, ob-
taining commission discounts from the firm also would be decently characteristic
of that broader shareholder population. Finally, the posted commission rate
schedules of the firm, over the time period investigated, were quite consistent
with those of other major full-service brokerage houses [12]. Hence, the bench-
marks from which any discounts we observe would have been offered were stan-
dard for the industry. For three reasons, then, we have confidence that the rela-
tionship between the firm and its customers captured by our data is likely to be a
respectably representative one.
The nature of the rate schedules in question merits some brief attention.
333

4. Underlying the charge quoted for any given transaction was a set of formulas that
specified the percentage commission rates to be imposed on trades of succes-
sively larger volumes; different such percentages applied to securities in different
per-share price ranges. In addition, distinctions were made between round- and
odd-lot trades, and various mandated minimum and maximum charges as over-
rides to the formulas.
The net result was commission schedules that had the general (and logieal,
assuming that order execution costs have an inherent fixed component [7]) char-
acter that the percentage rates quoted diminished with increasing dollar order
size. Three other points are worth noting: (1) the same posted rates applied to
both purchase and sale transactions; (2) the rates were the same for listed and
OTC stocks; but (3) the rates were raised sequentially over time after Mayday in
three steps. Each such change increased the quoted commission rates for virtu-
ally all transactions (there were no reductions), and the secular increase was no-
ticeably greater for small trades.
II. Methodology and Hypotheses
Using standard linear regression, cross-classification, and discriminant
analysis techniques, we tested the data for the presence of statistically significant
relationships between the percentage discounts (if any) from concurrent posted
commission rates offered by the firm on each of the 93,528 common stock trades
in our data base, and a set of independent variables that characterized the transac-
tion and the customer involved. Thus, the dependent variable was defined as (Cj
- Cf,)ICs, where Cj is the dollar amount of the scheduled commission for the
trade and C^ is the actual commission paid, as recorded in the transaction file.
The independent variables encompass both categorical and cardinal attributes of
the trade and the customer account.
Included among the former are: (1) whether the transaction was for a round-
or an odd-lot number of shares; (2) whether it was a purchase or a sale; (3) the
commission schedule in force at the time; (4) whether the transaction occurred in
a cash or margin account; and (5) whether it was undertaken at the suggestion of
the firm's account executive ("solicited") or initiated by the customer ("unsoli-
cited"); each trade in the file carried such a tag.
The cardinal attributes examined include the dollar size of the transaction
(price per share times number of shares) and two indices of the level of trading
activity in the account in question: the dollar volume of eommon stock transac-
tions executed in the account during the year immediately preceding the observed
trade, and the aggregate commission revenue to the firm generated by the ae-
count over the same period. For a transaction that occurred on Oetober 1, 1978,
therefore, both trading volume and commission revenues in the associated ac-
count for the interval October 1, 1977 through September 30,^ 1978 were
summed and attached to the transaction as customer "attributes." Since press
reports [ 1 ] suggest that it is the pace of annual trading activity by a customer that
is the primary determinant of full-service houses' willingness to contemplate of-
fering a commission discount, the two measures indicated seem reasonable ones
for our purposes here. Because they inevitably will be highly correlated across
334

5. accounts, they were, of course, employed as alternative rather than coincident
independent variables in the statistical tests.^
Our hypothesis was that the size and frequency of observed commission
discounts would turn out to be directly related to the level of activity in the sam-
pled accounts. We also expected to find that discounts became larger and more
frequent over time, both because of growing competitive pressures from discount
brokers and because the secular increase in posted commission rates imbedded in
the succession of such schedules provided a steadily larger "umbrella" under
which to offer discounts. We further anticipated a positive relationship between
the size of the individual transaction observed and the frequency of discounting,
on the suspicion that the formal quoted rate schedules, even after Mayday, were
not in fact "tilted" sufficiently to reflect fully brokerage firms' internal econo-
mies of scale in order execution. A coincident pattern of more frequent discounts
on round-lot orders was expected as well, for similar reasons. Finally, we pre-
dicted that customers having margin accounts would obtain discounts more often
than those with cash accounts by the logic that they may be characterized as more
"sophisticated" and, therefore, more apt to attempt to negotiate on charges. The
likely influence of the other identifiable attributes of the sampled transactions,
however (whether the trade involved was a purchase or a sale and whether the
order was solicited or unsolicited), was less clear to us on an a priori basis.
III. The Discount Profile
Some insight into these phenomena, and into the overall commission dis-
count policy of a full-service brokerage house, can be gained from the frequency
distributions arrayed in Table 2. Evidently, discounting did occur more than oc-
casionally: fully one-fourth of the post-Mayday trades observed were charged
commissions at below-posted-schedule rates. The incidence rose from 20 percent
in the immediate post-Mayday period (when commission Schedule #1 was in
force) to 34 percent by 1979 (Schedule #3). The frequency of large discounts
(30 percent or more) roughly doubled over that same time span.^
Conditioned by press reports suggesting that most full-service brokers are
not very forthcoming in either advertising the availability of or actually offering
discounts (see [1], [6], and [10]), we were surprised to find them occurring so
often in our data. A word of caution, however, is in order. Our sample of ac-
counts contains a relatively high proportion of longtime customers of the firm. It
may be the case that such individuals were able to obtain commission reductions
at above-normal success rates, merely by virtue of the longevity of their relation-
2 The independent variable we would really like to have, obviously, is one that indicates
whether the customer actually asked for a discount on a particular trade. Regrettably, those data are
unavailable in the transaction file.
^ Because the firm did some rounding of its commission charges to even dollar amounts for
many trades—and because some data entry errors inevitably would have occurred in recording the
commission figures on the file—any observed discount of less than 5 percent was assumed to reflect
one of these phenomena, and was treated as belonging in the "no discount" category. It is difficult to
believe, for example, that a recorded commission of $185 for a transaction that should carry a $186
charge according to the posted rate schedule really represents the results of negotiation. Approxi-
mately 2 percent of the trades in the data file were reclassified in this manner.
335

6. TABLE 2
The Commission Discount Profile: 1975-1979
Commission Discount as a Percent
of Scheduled Commission Rate:
Transaction
Category None < 15% 15%-30% 30%-50% > 50%
A. All Post-Mayday Trades 75% 8% 7% 6% 4%
B. Applicable Commission Schedule:
#1 (Early) 80% 8% 5% 4% 3%
#2 (Middle) 77 7 6 6 4
#3 (Late) 66 9 11 8 5
C. Order Size;
Under $2000 84% 5% 5% 4% 2%
$2000-$4999 78 9 6 5 2
$5000-$9999 71 10 9 6 4
$10,00Q-$24,999 60 11 11 10 8
$25,000-$49,999 36 11 16 18 19
$50,000 and over 14 8 23 30 25
D. Annual Account Trading Volume (Preceding Year):
Under $25,000 85% 6% 5% 3% 1%
$25,000-399,999 53 15 14 11 7
$100,000-$249,999 47 12 14 15 12
$250,000 and over 29 19 22 14 16
E. Order Quantity:
Round Lot 74% 8% 8% 6% 4%
Odd Lot 78 5 7 6 4
F. Order Type:
Purchase 78% 8% 7% 4% 3%
Sale 72 8 8 8 4
G. Account Type:
Cash 74% 7% 8% 7% 4%
Margin 76 9 6 6 3
H. Order Origin:
Solicited 75% 8% 8% 6% 3%
Unsolicited 75 8 6 7 4
336

7. ships. Hence, there may be something of an upward bias in the count within the
sample. On the other iiand, this should not affect the cross-sectional discount
profile as it is influenced by other attributes of the customer or the transaction.
From Table 2, it is apparent that influences of this sort were present, prominent
among them the indicated secular growth in discount size and frequency.
Consistent with expectations, both the dollar amount of the trade executed
and the level of trading activity in the account of the customer who placed the
order display a strong positive relationship to the magnitude of the commission
discount obtained. Whereas discounts were provided on only 16 percent of small
(under $2,000) orders, they occurred in 86 percent of the cases involving trades
of more than $50,000, and the majority of the latter were in excess of 30 percent
off scheduled rates. Similarly, individuals whose annual trading volume was less
than $25,000 realized discounts on approximately one-seventh of their trades,
these being generally small reductions. Customers who traded more than a quar-
ter million dollars' worth of common stock annually, however, paid below-
schedule commission rates on nearly three of every four transactions, and less
than half the scheduled rate about one time in six. Crude as our volume measure
is, the findings are striking.'' A formal cross-classification analysis of the data,
arrayed by the discount percentage categories shown in Table 2, and then by
applicable commission schedule, by transaction size, and by account activity
level, yielded chi-square statistics in all three instances that implied departures
from the total sample discount distribution at well beyond the 99 percent confi-
dence level.
In fact, because of the very large sample size with which we are dealing,
commensurate levels of statistical significance were indicated by cross-classifica-
tion analyses of the discount percentage groupings against the other four categor-
ical attribute variables listed in Table 2 as well—although, clearly, the opera-
tional significance of those relationships is much more modest. We observe a
tendency for discounts to be only slightly more prevalent on round-lot than on
odd-lot orders. Presumably, this is a reflection of the fact that the predominant
influence on the availability of a commission discount is account activity (see
below) and it so happens, as a separate cross-tabulation reveals, that even high-
volume customers engaged in odd-lot transactions during the time period studied
with a frequency not much different from the sample as a whole.
There is a stronger suggestion that discounts were obtained more often and
in larger amounts on sale transactions than on purchases. While we had no de-
veloped hypothesis in this regard, we can propose some possible explanations.
On occasion, there may have been an understanding between the customer and
the account executive, at the time a security purchase order was entered, that a
discount would be made available when and if the other end of the investment
"round trip" was also executed through the firm. In another instance, a discount
on a sell order might be offered as an inducement and encouragement to the
customer to place his or her next purchase order with the firm. These are only
speculations, however.
"• A similar profile also emerged when trades were categorized by the level of the preceding
year's commission revenues generated by the account.
337

8. The discount differentials are similarly undramatic when the sampled trans-
actions are divided according to whether they occurred in a cash or a margin
account, and whether the order in question was solicited or unsolicited. To the
extent that a pattern can be discerned, it is in a direction counter to what we
expected to observe. In particular, cash-account customers seem to have done
better at obtaining discounts than individuals with margin accounts, despite our
perception of the latter group as more negotiation-prone. Conceivably, such cus-
tomers may instead see themselves as consuming the full range of the firm's ser-
vices and, therefore, more willing to pay full price; the firm may have a commen-
surate attitude on the other side of the bargain. By similar reasoning, the slightly
smaller incidence of large discounts on solicited orders than on unsolicited ones
may reflect the larger service component of the former, i.e., the account execu-
tive's time and effort in calling the investment opportunity to the customer's at-
tention.
IV. Multivariate Analyses
The most substantial influences on commission discount availability and
size appear to be account activity, the magnitude of the trade, and the posted
commission schedule in force—the last of these effectively being a time proxy.
This inference is supported by a stepwise multiple regression analysis of the data,
wherein the percentage commission discount obtained is the dependent variable
and the various transaction attributes listed in Table 2 are the independent vari-
ables. The results are as follows:
Variable Coefficient
Step Entered Sign
Past Year's TracJing Volume {$)
Transaction Size ($)
Commission Schedule #3 (= 1)
Margin Account ( = 1)
Purchase Order ( = 1)
Solicited Order ( = 1)
Commission Schedule #2 (= 1)
Round-Lot Order ( = 1)
All coefficients were significant at the 99 percent confidence level or better
(again, a virtually inevitable consequence of a very large sample size). All had a
sign consistent with the messages of Table 2, and the entry order of the variables
accords well with those same messages,^
While the overall explanatory power of the regression equation was rela-
tively modest yielding an R^ of 18 percent, this could be anticipated given that
approximately 75 percent of the observations on the dependent variable had a
value of zero. More importantly, 60 percent of that explained variance was ac-
5 Commission Schedule # I was omitted as an independent variable, to avoid overspecifying the
relationship.
338

9. eounted for by the first independent variable entered (annual customer trading
volume), and fully 91 percent by the first three. Clearly, the remaining attributes
were of minor consequenee.*
Comparable results were obtained when the alternative measure of account
activity noted above—commission revenues generated by the customer during
the year preceding a trade—was substituted for trading volume as a eandidate
independent variable. The stepwise entry and coefficient profile are as follows:
Variable Coefficient
Step Entered Sign
1 Transaction Size ($) -t-
2 Past Year's Commissions ($) +
3 Commission Schedule #3 ( = 1) -i-
4 Margin Account ( = 1) -
5 Purchase Order ( = 1) -
6 Commission Schedule #2 ( = 1) +
7 Round-Lot Order (=1) +
8 Soiicited Order ( = 1)
Again, all coefficients were statistically significant at the 99 percent level, with
the first three variables entered contributing 88 percent of the total explained
variance. In this formulation, however, the R^ declines by one-third and the re-
vised aetivity measure falls to second place in the entry sequence. It appears,
therefore, that a customer's annual trading volume is a better indicator of the
commission discount than is the level of past commissions paid. This seems logi-
cal since the diseounts that were obtained on previous trades by high-volume
customers would effeetively introduce some noise into the past-commission fig-
ures recorded for them.^
Finally, the transactions were divided into two groups—trades on which a
discount was received and those on which the full scheduled eommission rate
was paid—and a stepwise multiple discriminant analysis was performed to iden-
tify the correlates of group membership. The findings shown in Table 3 reinforce
the regression results. Account activity, trade size, and the dummy variable for
commission Schedule # 3 are entered in the first three steps. They display F
values and standardized discriminant function coefficients well in excess of those
of the other candidate variables, and they are the only variables for which the
differences in group means are at all substantial. Table 3 indicates that the typical
customer who obtained a eommission discount (which averaged 30 percent) had
annual trading volume of over $230,000 and a mean individual trade of some
* Collinearity among the independent variables did not pose a problem. The highest simple cor-
>
relation coefficient between any two independent variables was 0.233, and most were in the range of
- O . l t o -1-0.1.
' As supplementary analyses, the transactions data were also stratified by stock-price categories
(e.g., trades in stocks selling within a quarter point of $10, $20, $30, etc.) and regression equation
estimates obtained for each such category. The results were consistent throughout: account activity,
trade size, and the commission schedule regime were the dominant explanatory variables; and the
equation fits were better when past trading volume rather than past commission revenue was used as
the activity measure.
339

10. $11,000; the corresponding figures for the full-rate payers were approximately
$70,000 and $4,000, respectively.
V. The De Facto Commission Profile
On that basis and as a device to summarize our findings, the relationships
between the actual per-share commission charges paid hy high-volume and low-
volume customers, and the scheduled rates posted hy the cooperating brokerage
firm during the period studied, are recorded in Table 4 for certain benchmark
transactions. For the analysis here, the commission charges recorded in the trans-
actions file for all trades in stocks selling within one-quarter point of $10 and $50
at the time of the trades were averaged and converted to percentage figures. This
was done separately for each of the three commission-schedule regimes and,
within each, for trades of 100, 300, and 500 shares. The results for other stock-
price categories were consistent with those portrayed. Transactions involving
low-volume customers were defined (pursuant to the message of Table 3) as
those occurring in accounts in which trades totaling less than $100,000 had been
executed during the prceding year; if the total exceeded $100,000, the transac-
tion was assigned to the high-volume group.
The pattern is clear. For trades in low-price stocks, both scheduled and ac-
tual percentage brokerage commission charges increased for customers with low
levels of trading activity, despite a certain degree of discounting after Mayday.
For transactions in higher-priced securities, the same individuals experienced ei-
ther only modest increases or held their own. High-volume traders, on the other
hand, appear to have enjoyed commission rate reductions across the board, in
amounts that by the end of the period under investigation were quite sizeable.^
Thus, there was a noticeable change over that period in the tilt of the de facto
commission profile. The evidence is strong enough to suggest that the trend will
continue.
8 As one of the paper's referees pointed out, however, if the indicated commission rates are
indexed by the roughly 8 percent per annum inflation rate experienced during the same years, the real
rate charged actually declined for all transactions.
340

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341

12. TABLE 4
Selected Comparisons of Scheduled and Actual
Brokerage Commission Rates: 1975-1979
(Expressed as a Percentage of Order Size)
A. For Stocks Selling at $10 Per Share
Commission (%)
Order Pre- Schedule Schedule Schedule
Size M ay day #1 #2 #3
Scheduled Rates
100 Shares 2.8% 3.0% 3.2% 3.3%
300 Shares 2.5 2.7 2.8 3.0
500 Shares 2.1 2.3 2.5 2.6
Paid by Low-Volume Customers
100 Shares 2.8% 3.0% 3.2% 3.3%
300 Shares 2.5 2.6 2.6 2.8
500 Shares 2.1 2.2 2.3 2.4
Paid by High-Volume Customers
100 Shares. 2.8% 2.4% 2.4% 2.0%
300 Shares 2.5 2.0 2.0 1.8
500 Shares 2.1 1.7 1.7 1.5
B. Eor Stocks Selling at $50 Per Share
Commission (%)
Order Pre- Scheduie Schedule Schedule
Size Mayday #1 #2 #3
Scheduled Rates
100 Shares 1.4% 1.6% 1.7% 1.7%
300 Shares 1.4 1.4 1.5 1.5
500 Shares 1.3 1.3 1.4 1.4
Paid by Low-Volume Customers
100 Shares 1.4% 1.6% 1.7% 1.7%
300 Shares 1.4 1.4 1.4 1.4
500 Shares 1.3 1.3 1.3 1.3
Paid by High-Volume Customers
100 Shares 1.4% 1.3% 1.2% 1.0%
300 Shares 1.4 1.1 1.0 •0.9
500 Shares 1.3 1.0 0.9 0.8
342

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66.
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20.
343