Net Settlement and Counterparty Risk: Evidence from the Formation of the NYSE Clearing House in 1892

Net Settlement and Counterparty Risk: Evidence From the Formation of the NYSE Clearing House in 1892

Abstract

Several theoretical papers have evaluated settlement systems, yet no empirical work has examined the systemic effects of an actual shift from a bilaterally-cleared gross system to one employing multilateral net settlement. This paper evaluates the broker insolvency rates that accompanied the NYSE’s adoption of a multilateral net system when it instituted its clearinghouse 1892. This study is the first empirical analysis of a securities settlement system using archival data; it is also the first empirical study of an equity settlement system and a ringing system. Our analyses provides compelling evidence that net settlement reduced broker insolvencies, thus enhancing systemic stability

1 In the wake of the severe liquidity freeze that seized financial markets in the fall of 2008, risk has been under increased regulatory scrutiny, especially with the counterparty and systemic risk from decentralized bilateral clearing arrangements often found in over-the-counter swaps and derivatives markets. As a result, the Commodity Exchange Act, as amended by Title VII of the

Dodd-Frank Wall Street Reform and Consumer Protection Act (“Dodd-Frank Act”) of 2010, provided a comprehensive regulatory reform of swaps trading. The regulation required swap settlement to occur through a central clearing counterparty (CCP) and be subject to netting by novation. Netting by novation involves a counterparty exchanging its legal obligation to settle individual trades on a gross basis for an obligation to settle trades on a net basis vis-à-vis the

CCP.

As part of the bill, Congress authorized the Secretary of Treasury to make a determination whether foreign exchange (FX) swaps and FX forwards should be exempted from the Dodd-Frank requirements. The exemption was granted by the Secretary of Treasury on

November 20, 2012. An important issue behind the exemption was that FX swaps and forwards were largely settled on the Continuous Linked Settlement Bank (CLS) platform, which allowed multilateral payment-versus-payment settlement, which is distinct from netting by novation. Under multilateral payment-versus-payment settlement a counterparty is released from its obligation if, and only if, its counterparty also manages to settle.

The issue of how to organize settlement of financial transactions was just as relevant to the establishment of the NYSE’s first clearinghouse in 1892. A related contemporary issue is whether full multilateral netting by novation would provide benefits beyond the alternative

2 multilateral payment-versus-payment (a.k.a. delivery-versus-payment or DVP) system, which may alone be sufficiently robust to manage the risks involved. In 1892 the NYSE adopted a form of multilateral DVP for their clearinghouse. The advantage was that counterparties could be assured of settlement, without the more difficult step of creating an institution which would internalize settlement obligations. A key question regarding this “intermediate” step is whether it would be sufficient to reduce settlement risk for NYSE participants.1 In this study, we examine the frequency of broker failure rates before and after the formation of the New York Stock

Exchange Clearing House (NYSECH) in 1892. We find, much like studies of CLS bank and FX settlement risk (e.g., Committee on Payment and Settlement Systems, 2008) that the multilateral

DVP method adopted by the NYSE clearing house was effective in significantly reducing settlement risk.

The establishment of the NYSECH provided enormous benefits: improved timeliness of

settlement, less reliance on bank overdrafts, and less risk of delivering money to a counterparty

who might fail later in the day. The offsetting of counterparty claims greatly reduced the

cumbersome and difficult physical delivery of stock and funds that occurred each day, and

reduced reliance on daylight overdraft credit from Wall Street banks and reliance on funding

from the call loan market.

An examination of the broker failure rates preceding and following the opening of the

Clearing House offers a unique opportunity to measure the contribution of net settlement to the

1 Intermediate since the NYSE clearinghouse later adopted the netting by novation step when it moved to establish the Stock Clearing Corporation in 1920.

3 systemic stability of the New York stock market. The NYSECH incorporated many important features of risk management that are common in modern securities settlement systems, including the use of simultaneous clearing, offsetting of multilateral positions, and surviving counterparties sharing in losses in the event of default. Our examination of archival data regarding broker insolvencies shows that broker failures were much less likely both in normal times and during times of market turbulence once the NYSECH commenced operations.

Many of the recent regulatory reform efforts have been intended to reduce settlement risk—the risk that the contract will not be settled in accordance with the original terms, including when one party delivers one leg of the transaction, but does not receive the other leg. Generally speaking, settlement risk is highest when gross bilateral settlement (that is, a fully decentralized method of settlement) is used (Kahn, McAndrews, and Roberds 2003). In such a system, parties exchange gross amounts asynchronously to complete settlement. Risk is high because a trader can be exposed to the risk of the full principal amount of the trade after the trader delivers, but has failed to receive, the contractually agreed upon amount. This risk, sometimes called

“Herstatt” or “time-gap” risk (Committee on Payment and Settlement Systems, 1990), was prevalent in the FX market prior to the creation of the Continuous Linked Settlement Bank in

2002. Much like the NYSECH, CLS is not a CCP, but clears and settles trades simultaneously, and establishes conditions under which a significant offsetting of net obligations occurs.

In recent years theoretical research has examined the relative merits of gross settlement

systems versus those that offset net claims. While this debate continues, virtually no empirical

research has evaluated the impact on counterparty risk and systemic stability of an actual shift

4 from bilaterally-cleared gross settlement to multilateral net settlement.2 Resistance to proposals to alter derivatives market settlement may reflect the paucity of applied research in which a financial market has made such a switch. Relevant data regarding the effects of such a change does not appear to exist.

Kroszner (1999) states, “The historical development of futures clearing-houses and how they address issues of risk has been largely overlooked in both the academic literature and the current policy debates”. The same can be said for the historical development of equity clearinghouses. This paper addresses a gap in the literature by measuring the changes in broker insolvency rates caused by the NYSE’s shift from bilateral gross settlement to multilateral net settlement when it instituted its first-ever clearinghouse in May 1892. This is the first empirical paper to utilize archival data to examine this transition and only the second paper to evaluate the benefits of a multilateral net settlement system operating without a CCP.

Contrary to the practices of most modern CCP settlement systems, NYSECH did not engage in novation. Instead it operated at the nexus of a multilateral net settlement system known as “ring settlement”. Ringing was a common form of settlement among late 19th century U.S. exchanges. A ring system typically employs a central agent to direct settlement according to a set of rules agreed to by ring members. Ring settlement has largely been ignored by modern

2 Most of these papers fail to make a clear distinction between netting with novation, in which the clearing house becomes a central clearing counterparty (becoming the counterparty to each trader) and netting without novation, in which traders are still exposed to the risk of default by their trading counterparty. In these latter types of systems, the way traders are exposed to the risk of counterparty failure can vary. For example, in some systems all trades are unwound in the event of a default, while in others only a subset of trades are removed from settlement. We discuss the specific rules of the NYSECH beginning on page 15, but for the purposes of this paper we describe its settlement procedure as a net settlement system, but not as a CCP.

5 settlement system architects, and it is the authors’ hope that this study will encourage a reconsideration of the relative merits of such a system.

This paper is organized as follows: Section I examines the settlement literature, while

Section II provides background on the historical settlement practices of the New York stock market in the late 19th century. Section III offers a brief description of the archival data that has been utilized while Section IV presents a series of hypotheses related to the operation of the

NYSE Clearing House and its impact upon stock market dynamics. Analysis of the data garnered from handwritten logs and minutes of NYSE committee meetings follows in Section V, testing the hypotheses proposed in Section IV. A discussion of the findings concludes the article in

Section VI.

I. Settlement Literature

The literature regarding securities settlement activity is limited, and generally confined to studies that utilize modeling techniques to examine optimal settlement cycles and intra-day borrowing policies (Lester 2009). Even fewer historical examinations of securities clearinghouse activity have been conducted; nearly all recent scholarship has focused upon the dynamics of systems for settling commodity trades and interbank payments utilizing novation through a CCP.

Despite the relative paucity of research concerning equity settlement systems, an examination of the often parallel research concerning large value payments systems may be useful since both

6 systems for settling financial claims share many similarities3. It can be argued that since interbank payment systems utilize time horizons more closely approximate to those employed by the NYSECH, they are more appropriate for comparison purposes than are futures clearinghouses engaged in the settlement of long term obligations. The review that follows draws from several strands of the payments system literature4.

Several papers contrast gross and net settlement systems, with a particular emphasis on participant default rates, transactional efficiencies and the use of collateral and regulation to incent fulfillment of contractual obligations. Net settlement systems typically operate on a deferred basis, aggregating settlement commitments entered into during a trading session, then permitting participants to discharge their net obligations during a settlement cycle. While such systems often generate operational efficiencies and have lower capital requirements, gross settlement systems normally require participants to either hold funds sufficient to settle all transactions, or to obtain some form of intraday credit from a third party. Such “daylight overdrafts” permit participants to settle transactions whose aggregate value far exceeds their actual funds on deposit, with the proviso that all outstanding obligations must be extinguished at the end of each settlement cycle (Mengle 1985, 17). Settlement systems may be an important

3 Kahn and Roberds (2009, 12) in a survey of payments economics write, “There is also an important practical symbiosis between securities settlement and large value payment systems. Securities settlement systems depend on large-value payment systems for the final settlement of ‘funds positions’- positions left over after any netting of securities trades has occurred”.

4 In payment systems, the flows of delivery are one way—the delivery of some good, service, or extension of credit occurred prior to the payment obligation. Once the payer is obliged to make payment, there is no offsetting obligation from the payee. In securities settlement systems, by contrast, such as the NYSE Clearing House, one party is obliged to deliver stocks and the other is obliged to deliver money. These types of systems have been moving toward more centralized settlement systems for decades, involving either multilateral payment-versus- delivery or full multilateral netting by novation.

7 factor in generating systemic risk since their design and operation may affect the probability of participant default. A primary distinction between net and gross settlement derives from the way each system’s idiosyncratic vulnerability contributes to systemic risk.

By design, net settlement gives priority to offsetting claims and discharges them as a matter of routine, however, in order to deal with the impact of defaults net settlement systems typically provide for one of two basic forms of loss sharing arrangements. Under one version, transactions are unwound by the removal of the trades from the day’s activity, after which the remaining net positions are recalculated and settled, whereas under the second form, known as the “Lamfalussy Rule” (Committee on Payment and Settlement Systems 1990), participating members are allocated losses on some form of a pro rata basis

Net settlement systems have a long history, having been widely employed by European banks for centuries (DeRoover 1948). In the United States, as informal multilateral netting systems were adapted by futures exchanges for use within organized clearinghouses in the late

19th century (Moser 2000), net systems became the primary method used for settlement during the National Banking Era (Cannon 1910). Net systems have proved to be suitable for a variety of securities transactions (Baer, France, and Moser 1995), and they have been employed within modern large-value payment systems as late as the 1990s (Folkerts-Landau, Garber, and

Schoenmaker1996).

During financial crises liquidity can be withdrawn from settlement systems; under severe circumstances gross settlement systems may incent participants to engage in strategic default (a

8 concept developed in Kahn and Roberds, 1999) as a means of increasing welfare, thus creating a

“payments gridlock” in which agents seek to protect themselves from defaulting counterparties by withdrawing intraday credit. The resulting “speculative gridlock equilibrium” (Freixas, Parigi, and Rochet 2000) occurs not because banks fear losses due to a decline in specific investment collateral, but rather to distrust of the creditworthiness of counterparties (Kahn, McAndrews, and

Roberds, 2003). Gridlock equilibriums may be manifestations of systemic risk indicative of the increasing possibility of financial contagion, an area of particular contemporary interest in the wake of the subprime crisis. This appears to have been the case in New York during the Panic of

1873, for which 57 broker failures were blamed (Eames, 1894).

A. Netting Benefits

One way of reducing the dangers created by liquidity withdrawal may be by reducing the levels of funds necessary to operate a given settlement system. Netting has the potential to minimize the need for liquidity since each participant only has to remit a reduced net payment at the end of each settlement cycle rather than a series of gross payments; as a result they can maintain lower clearing balance (Zhou 2000, and Johnson, McAndrews, and Soramaki 2004). In addition to reducing interest-related costs, lower liquidity needs potentially enhance the ability of participants to discharge their contractual obligations, enhancing counterparty confidence and lowering systemic risk in the process5.

5 In Kahn, McAndrews, and Roberds’ (2003) study, “Settlement Risk under Gross and Net Settlement”, the authors present a model in which they show that systems of net settlement may offer advantages over gross settlement,

9 One of the primary shortcomings of the literature is the assumption that multilateral settlement systems must necessarily utilize a CCP, ignoring the fact that historically, the use of multilateral netting systems without novation (“ring settlement”) was widespread in the late 19th and early 20th centuries. Ringing was the predominant method of settlement employed by U.S. exchanges in the late 19th century, typically utilizing either a clearinghouse or bank as facilitator and employing rules that compelled exchange members to abide by settlements reached by the ring (Moser 2000). To the best of the authors’ knowledge, the only paper that quantitatively examines and contrasts bilateral, CCP and ring clearing arrangements is Jackson and Manning

(2007). In fact, its treatment of ring clearing arrangements appears to be unique among contemporary modeling papers.

The formation of the NYSECH provides a demarcation line that facilitates an examination of the circumstances before and after a shift from bilateral gross settlement to a multilateral net settlement system. The literature detailed in this section offers a number of theories regarding settlement systems, although few utilize hard data. The next section will detail the formation of the New York Stock Exchange Clearing House and the available archival data. particularly in the way they reduce collateral requirements and avoid the gridlock equilibriums associated with gross settlement that may lead to autarky. Importantly, they attribute the ability of netting to reduce settlement risk as a key contributor to the “historical predominance” of net settlement systems. The model that the authors employ is one in which agents (banks) engage in one or more rounds of trade settlement, under net and gross settlement with variations in the payoffs associated with bankruptcy rules. Interestingly, unlike prior studies, which typically assume that gross settlement systems utilize a delivery-versus-payment (DVP) system in which trading and settlement occur simultaneously, the authors contrast net settlement systems with gross settlement systems in which payment is not made at the same time as the trade. In other words, they consider non- real time gross settlement systems in which counterparty risk exists for the period between trading and settlement. Such a system was generally utilized in the New York stock market through most of the 19th century.

II. Historical NYSE settlement

Prior to the establishment of the NYSE’s first clearinghouse (NYSECH) in 1892, trade clearing and settlement occurred bilaterally between NYSE brokers. Settlement activities were required to conclude by 2:15 pm T+1. John Grosvenor Wilson (1905, 423) vividly described the tumult that swept the thronged streets surrounding Wall Street as the 2:15 deadline approached.

Prior to the Clearing House all securities sold in the regular way were compelled to be actually (physically) delivered at sometime the succeeding day before 2:15 p.m. Immense values in stocks, bonds and checks were thus entrusted to an army of messenger boys scurrying through the streets from office to office. It is little less than miraculous that so few losses occurred, but the liability to great loss was the ever present cause of anxiety…. The old system was responsible for much wasteful expense and unnecessary labor. Many more clerks and book-keepers were required. There was constant difficulty as to delivery on time, that is, before 2:15 P.M. Sometimes fifty or more boys would be collected by a single large house before 10 A.M. on occasions when big deliveries had to be made of the previous day’s sales. As 2 o’clock approached, the streets of the financial district presented a curious spectacle. By common consent the delivery boys were given the right of way. Running at top speed, their hands full of securities and checks, the boys were everywhere in evidence. Between 2 and 2:15 P.M. the large offices became blocked with long queues standing at cashiers’ windows with sales ticket and deliveries. Every day in busy times “past delivery hours—too late!” was heard in almost every office, and many brokers were forced to carry undelivered stocks overnight and borrow money upon them.

Strains within this gross settlement system increased as trading activity increased and new securities were listed.

11 A. Overcertification and the NYSE’s Gross Settlement System

Under gross settlement NYSE brokers required access to particularly large

amounts of overnight funds to finance T+1 settlement. Required settlement funds typically far

exceeded a broker’s own funds. Therefore, brokers relied upon the New York City clearing

banks to facilitate overnight settlement through “overcertification.”6 With this process clearing

banks certified a broker’s checks for far in excess of the broker’s cash balance, with the

understanding that the broker would deposit funds before the unsecured loan had cleared through

the clearing banks, either from the security settlement itself or from using certificates to secure a

collateralized loan.7

Overcertification created significant counterparty risks for the banking community, and

thus created opportunities for strategic default. During periods of financial stress the banks might

6 Sereno Pratt (1903, 181) describes how overcertification was integrated into the clearing process.For instance, a broker buys 5,000 shares of New York Central at 162, amounting to $810,000. But he executes the order for his customer on a margin of $81,000, so that he must pay the difference of $729,000, either out of his own capital or else borrow of the banks. Necessity compels him to go to the banks. He takes the 5,000 shares of the New York Central to the banks and offers them as collateral for a loan. … The broker has bought stock for which, on delivery, he must pay $810,000. Now, before he can get any loans from the banks on this stock he must have the stock in his possession, so as to be able to use it as collateral for the loans. Before he can get it in his possession he must pay for it. His balance in the bank may not be more than $50,000. … The broker, in the case instanced, draws a check for $810,000 in payment for the stock. The check is sent to the bank where the broker keeps his account for certification. The cashier or paying teller indorses the check across its face, thus certifying not only that the signature is correct, but that the bank will pay the amount of the check on presentation and identification, or when it comes to it through the operations of the Clearing-House. But it has been said that the broker has a balance of only $50,000, and here the bank is certifying to his check for $810,000. That is what is called ‘overcertification’ 7 Broker failures during the Panic of 1857 led to curtailment of the use of time contracts for settlement. The concurrent emergence of a broker “call loan” market permitted overnight settlement to become the norm until the 1930s. As well, Myers (1931, 282) suggested that overcertification developed at least a quarter-century before the National Banking era and was permitted by most state banking statutes.

12 restrict or suspend brokers’ access to overcertified checks, and the resulting money market

stringency often exacerbated financial-sector crises, as illustrated next.8

B. Panic of 1873 and Pressure for a Securities Clearinghouse

During the Panic of 1873, conditions supporting strategic default developed, and the New

York City banks suspended the overcertification privilege extended to NYSE brokers9. As a

result, the NYSE was forced to suspend trading for an unprecedented nine days (The Nation,

1873, 23). Financial panics followed in 1884 and 1890 without the closure of the NYSE.10

During this period the NYSE and the New York City clearing banks continued to negotiate over

the settlement system the NYSE would use and access to the liquidity needed to finance

settlement.

8 It appears, ironically, that overnight settlement practices may have aggravated the problem of failing brokers. Writing in 1903, Sprague blamed the immediacy of the liquidity requirements inherent in the NYSE system of daily settlement for broker failures; which tended to spike during periods of financial tumult (Sprague, 1903, 45). The practice of overcertification, while providing critical intra-day liquidity to the NYSE’s settlement process, also posed the systemic risk of broker defaults and credit losses. During periods of panic buyers could walk away from buy orders, leaving brokers with losses and potential defaults on overcertified checks. Anticipating this outcome Wall Street banks and trust companies normally participating in overcertification might withdraw the privilege extended to brokers. 9 1873 was the only panic where the NYCHA banks suspended both convertibility and the overcertification privilege. 10 Some researchers have laid blame for the financial crises of the period on the settlement system itself. Michie (1986, 182) writes: “The daily settlement system tended to exaggerate crises. The short time before payment was due meant that it was difficult for either bankers or brokers to take measures to avoid crisis. Any tightening of the money available on the call-loan market had an immediate and all-embracing impact, since almost all borrowings were for day-to-day money. If stocks could not be immediately liquidated, or if prices dropped to the extent that loans were no longer covered, the brokers would be unable to repay the banks. For example, in 1890, when Decker, Howell & Co. failed, the Bank of North America had to suspend operations, leading to a general restriction of credit.”

13 C. The NYSE's First Clearinghouse

The NYSE finally yielded to threats from the New York City banks to cease their funding after the Barings Panic of 1890.11 The NYSE adopted its first clearinghouse on May 17, 1892, the one-hundredth anniversary of the founding “Buttonwood Agreement.”

The NYSE’s clearinghouse adopted a net settlement method. Brokers submitted their trades to the clearinghouse for overnight processing. Table I (taken from Noyes, 1893, 261) illustrates the netting process. According to the sheet, 1,000 shares of St. Paul were purchased and 500 shares sold, netting to 500 shares to be delivered. Similarly, No. West. nets to zero, Mo.

Pac. requires 200 shares for delivery, and New Eng. requires 1,000 shares to be delivered.

Netting across all brokers reduces deliveries from 5100 shares to 1700 shares. Without netting, checks for $258,675 would have been issued, and checks for $181,850 received, totaling

$440,525.12 With netting, checks for only $89,000 need to be issued by this broker, and checks for only $12,175 received, totaling $101,175. Thus netting reduced required financing by more than seventy-five percent, and reduced the number of security deliveries required.13

Insert Table 1 about here.

11 For details of the negotiations between the New York Clearing House Association and the NYSE, see McSherry and Wilson (2013). 12 Note that the clearinghouse’s convention was to set a “clearing price” for a particular security to the even price nearest to the quotation of the day’s last sale in the stock. 13 The clearinghouse performed the netting of trades without acquiring any settlement obligations itself. Thus the NYSE’s first clearinghouse was not a central counterparty.

14 D. Organization of the New York Brokerage Industry

The NYSE membership levels and brokerage industry credit conditions remained relatively constant during the period under study. NYSE memberships expanded from 1060 to 1100 seats on November 12, 1879, and that number remained stable throughout the period under study. Margin requirements were not subject to stock exchange regulation, varying instead as a matter of brokerage firm policy. While margin requirements were certainly influenced by money market conditions and stock market volatility, there were no uniform margin requirements for members of the NYSE during this period. Margin varied among brokers and by type of security, with lower volatility stocks generally requiring less margin. In 1875, 10 percent of the par value was a common margin requirement (although some firms required a 15 or 20 % deposit of cash). It appears that a 7 percent decline in value was enough to set off a margin call (Hickling, 1875, 17) after which investors were required to put up additional capital or be “sold out” by their broker. Margin calls for maintenance were often made after a decline of merely 2 or 3 percent (Fowler, 1870, 64, 65, 82) . In 1887, Ten percent was reported as a typical margin requirement for speculators trading through a “banker-broker” (Smith, 1887, 3).

III. Data

A time series of NYSE broker failures is collected for the period: 1873-1910 from the archives of the NYSE. The NYSE’s Committee on Admissions, List of Suspended Members records every member suspension over the period: (1/23/1871- 10/1/1940). A broker insolvency occurred when an NYSE member failed to comply with contractual obligations or became insolvent. The broker was suspended until settlement was made with counterparties among the

15 Exchange membership.14 The NYSE utilized a version of the Lamfalussy Rule, allocating liability for member defaults only to those parties with whom the defaulting broker had made contracts prior to his default (New York Stock Exchange Clearing House Rules, 1892).

In 1876 the Committee on Insolvencies was formed with the responsibility of determining if an insolvent broker had behaved in a “reckless and unbusinesslike manner” before a broker could be re-admitted to trading privileges.15 As well, Reports of the Committee for Re- admission, Minutes of the New York Stock Exchange, Minutes of the Governing Committee, and

Minutes of the NYSE’s Finance Committee were used to collect and check data on broker failures. Table II gives a detailed list of the archival sources.

Insert table II about here

IV. Hypotheses

The time series of broker insolvencies covering the period: 1873-1910 is used to test hypotheses related to how the clearinghouse formation impacted NYSE broker defaults. In particular, the study hypothesizes that the 1892 formation of the NYSE clearinghouse should

14 Under NYSE rules, brokers were required to declare their own insolvency to the Governing Committee when they were “unable to meet their engagements.” Broker failures were then made public, typically by ringing the trading floor bell to halt trading so that the Exchange’s presiding officer could publicly announce the broker’s suspension from the podium. Exchange members would subsequently file claims related to the cost of “buying in” unsettled transactions with the insolvent member. In all cases, membership rights of the failed broker were held in abeyance until all internal NYSE claims had been paid. After a period of time (typically 1-3 years) the Governing Committee would order seats to be sold to pay off unresolved member claims. 15 An examination of Committee records reveals concerns with brokers who behaved in an unacceptable manner. Suspended brokers found “guilty” of inappropriate behavior were barred from reinstatement and their Exchange seats were sold. Kahn, McAndrews and Roberds (2003, 598-9) argue that attaching an asset such as an exchange seat creates disincentives for strategic default.

16 result in a decrease in NYSE member insolvencies. Pre clearinghouse, gross settlement had created bottlenecks, particularly during periods of high trading volumes and falling security prices, as during market panics. With buyer’s remorse, brokers might see customers walk away from losing trades. As discussed above, the clearing banks suspended financing trades during the

Panic of 1873. The formation of the clearinghouse would greatly reduce the financing needed to affect settlement, and would thus decrease the related operational bottlenecks.

We hypothesize that the impact of clearinghouse formation would be particularly apparent during periods of peak trading volumes and during market downturns. Periods of peak trading volumes would require high levels of financing and large numbers of physical security deliveries. Buyer’s remorse during market downturns would potentially require brokers to suffer losses on securities unclaimed by buyers.

The analysis incorporates a number of control variables to capture market movements.

The control variables are: (1) monthly NYSE trading volume (Volume), (2) an NYSE equity market index (Index, taken from Goetzmann, Ibbotson and Peng (2001)), (3) the maximum monthly call loan rate (Call_Max), (4) monthly series of NYSE seat prices (Seat), (5) an NBER recession variable (NBER) taking value 1 with NBER contractions and 0 with expansions, and

(6) the interaction between variables (1) and (2), both stated as percentage change in value.

Trading volume data was compiled from NYSE Total Sales 1879-1934 (NYSE Archives). Data on the remaining variables were taken from various volumes of the Commercial and Financial

Chronicle.

17 V. Study Results

Figure 1 gives the distribution of our principal study variable: the number of broker insolvencies per month. The distribution is shown separately for the pre- and post-clearinghouse

(CH) periods: that is, pre-May 1892 versus post-May 1892 inclusive. As discussed above, monthly data on this variable is taken from the List of Suspended Members and other sources listed in Table II. As well, Table III gives descriptive statistics for the broker insolvency and other study variables.

Insert Figure 1 and Table III about here.

The mean number of broker insolvencies in the pre_CH (pre clearinghouse) period is

1.957 per month, while post_CH the mean is 0.580. The maximum number of insolvencies is 36 per month pre_CH, while post_CH the maximum drops to 7. Figure 1 also suggests that the founding of NYSE’s first clearinghouse greatly shifted the distribution of broker insolvencies to the left. Thus, founding the clearinghouse appears to have greatly reduced the occurrence of broker failures.16

Insert Figure 2 about here.

16 We propose that the mechanism at work was simply the transition from gross settlement to net settlement, which greatly reduced the number of transactions that went to settlement. Pratt estimated that more than $17 billion of certified checks were obviated in 1901 alone (“these sums are so great as to be beyond human comprehension” he wrote), saving the New York banks certifications averaging $50,000,000 per day (Pratt, 1912, 167).

18 Figure 2 shows the historical sequence of monthly insolvencies. The figure also indicates several episodes of stock market panic. Broker insolvencies peaked with the Panic of 1873, with

36 broker insolvencies. This panic was unique in that all NYSE trading was suspended for nine days, when the New York City banks refused to extend financing for trade settlement, as discussed previously. Clearly, the loss of financing contributed to the large number of broker insolvencies. After the Panic of 1873, insolvencies tended to decline, particularly with the founding of the NYSE’s clearinghouse. Figure 2 suggests that there were fewer broker insolvencies associated with financial panics post clearinghouse formation, despite the significant panics in 1893 and 1907.

Insert Figure 3 about here.

Figure 3 presents monthly aggregate trading volume for years: 1879-1908. The figure shows that trading volume increased enormously in the years following the founding of the clearinghouse.17 Figure 3 suggests that the removal of operational bottlenecks due to the use of

17 At this time, minimum broker commissions were fixed by NYSE rules. A minimum charge of 1/8 of par value (12.5 percent) was required for all transactions with non-NYSE members. Among members, charges were fixed as 1/50 of par value, which was typically 100. Thus, independent brokers transacting overflow business for other members became known as “$2 brokers”.

19 net settlement at least facilitated the enormous increase in trading volume that began in the late

1890s.18

A. Control Variables

NYSE trading volume tends to peak during market panics, while stock market prices tend to decline, call loan rates increase, and NYSE seat prices decline. However, specific control variables take on additional significance. We would expect that high NYSE trading volumes reflect the “bottlenecks” that brokers faced in trying to settle trades on a gross basis. As well, falling stock market prices might influence buyers to walk away from outstanding buy orders, i.e., “buyer’s remorse,” which would then result in losses and insolvencies of buying brokers through the replacement cost of covering unsettled trades.19 Note that the interaction between these two variables would imply that high transactional volumes would have greater significance in the presence of “buyer’s remorse”. As well, seat prices reflect the collateral value available to cover losses to NYSE members from broker failures. We would expect that higher seat prices would result in fewer broker insolvencies. Finally, high call loan rates would indicate financing bottlenecks and imply high trade settlement cost.

Table III presents descriptive statistics for the study’s control variables, divided between the pre- and post-clearinghouse (CH) periods (that is, May 1892). NYSE trading volume growth

18 The delay in the increase in trading volume may have been due to (1) the lingering effects of the depression of 1893, (2) the rapid monetary reflation of the late 1890s with new gold discoveries (see Wilson and McSherry, 2014), and (3) the industrial consolidation over 1895-1904, dubbed the “Morganization of America” (Sobel, 1965). 19 Testimony to the Committee on Insolvencies indicates that buyer default was a frequent source of broker insolvency. Buyers were most likely to default during declining markets, when their losses would become apparent at settlement.

20 tended to escalate post_CH, from an average rate of 4.61 percent per month pre_CH, versus

12.94 percent post_CH. As well, periods of peak trading volume were more frequent in the post- clearinghouse period, with financial panics occurring in 1893, 1895-6, 1899, 1901 and 1907.

Mean maximum call loan rates were substantially higher post_CH (13.16%) than pre-CH

(10.92%). Peak call loan rates of 186% occurred during the Panic of 1899, and 125% during the

Panic of 1907. Note that NYSE seat prices also increased substantially in the post_CH period, in part driven by the large increase in trading volume.

B. Correlations

Table IV lists correlations among all study variables. Broker insolvencies and losses per insolvency are listed first. During the pre-clearinghouse period, the broker insolvency variable is positively correlated with the NYSE monthly trade volume (%ΔVolume), positively correlated with monthly maximum call loan rates (Call_Max), and negatively correlated with the stock market index variable (%ΔIndex). The results suggest that broker insolvencies peaked when trading volumes were increasing, call loan rates were high, and when stock market prices were falling.

Post-clearinghouse formation the same basic correlations occurred, except that the positive correlation between broker insolvencies and NYSE monthly trade volume was no longer significant. The implication would be that the bottlenecks that occurred due to high trading volume were reduced by the net clearing introduced by the NYSE’s clearinghouse.

21 Place Table IV about here.

C. Regression analysis results

Our analysis focuses on the occurrence of broker failure as a key indicator of the counterparty risk between NYSE brokers and the New York City banks that provided their trade settlement funding. As discussed above, the banks provided settlement financing through overcertification of broker’s settlement checks.

Table V presents regression results. The regression model explains 27.7% of the total variance. The overall regression F statistic is 16.475, indicating an overall significance of p<.001. The control variables have their expected signs: that is, higher insolvencies occurred with (1) higher NYSE trade volume, (2) lower market prices, (3) higher call loan rates, (4) lower seat prices, and (5) during NBER contractions. Call Max and %ΔVolume are the most significant variables. The %ΔVolume results again point to the operational bottlenecks from large increases in NYSE trading volumes that contributed to broker insolvencies.

Place table V about here

22 CH is a dummy variable with value 1.0 for the post-clearinghouse period: 5/1892-

12/1908 inclusive, and value 0.0 over the pre-period: 2/1879-4/1892 inclusive. The significant and negative coefficient on CH indicates that broker insolvencies were lower post formation of the NYSE clearinghouse. In addition, the interaction effect between CH and %ΔVolume is highly significant, suggesting that formation of the clearinghouse ameliorated the negative effects of volume spikes by reducing the number of operational bottlenecks. These two results suggest that the NYSE clearinghouse’s system of net settlement contributed to an improvement in overall NYSE systemic stability.

To control for other unmodeled effects, Table VI presents regression results before and after the establishment of the NYSE clearinghouse. The results indicate that the varable:

%ΔVolume loses significance in the post-CH period, suggesting that the volume-related operational bottlenecks that resulted in higher broker insolvencies pre-CH were reduced through the net settlement instituted by the clearinghouse.

Place table VI about here

D. Robustness analysis: Poisson regression of Broker Insolvencies

As a robustness check for the ordinary least squares results, a weighted least squares

(WLS) regression analysis is performed on the dependent variable: Broker Insolvencies. A WLS

23 approach provides maximum likelihood estimates if Broker Insolvencies follow a Poisson distribution.20 Results are presented in Table VI. Comparing back to Table V, all coefficients have their expected signs, and roughly same significance level. Finally, for completeness Table

VIII presents WLS results for the pre-CH and post-CH periods. As before, the results are comparable to those presented in Table V.

E. Anecdotal Evidence of the Impact of the Clearinghouse

“It may be safely said that there could not have been such an expansion of share business and of market for securities in New York as has taken place, without the (New York Stock Exchange) clearing system.” (American Bankers Association, 1910, 55)

Further evidence of the impact of introducing NYSE’s first clearinghouse can be developed by comparing the Panic of 1890 with the Panic of 1893. Knox (1903, 201) states that the Panic of 1893 was the more severe: “The year will always be unfortunately celebrated for one of the worst financial crises that has occurred in the business history of the United States”. In

1890 a mere 0.15% of all U.S. state and national banks were suspended, while in 1893 an astonishing 4.2% were forced to suspend (Wicker, 2000, 6). As well, in 1890 the New York City banks issued $16,645,000 worth of clearinghouse certificates in an effort to maintain liquidity, while in 1893 $41,490,000 worth of certificates were issued (Eames, 1894, 66-67). Finally,

NYSE archives indicate that there were 19 NYSE broker failures in 1890, while there were only

20 The WLS weights are taken as the reciprocal of the predicted values from the previous iteration of the WLS. To account for a small number of near-zero and negative predicted values (predicted values<0.01), their predicted values were set to 0.01 in value. Five iterations of WLS were performed.

24 7 broker failures in 1893. This reduced failure rate reflects the efficiencies introduced by the clearinghouse resulting from the reduction in transactions to be settled after netting.

This observation was also made by Emery (1896, 86):

“It was the borrowing panic of 1890 and 1891 that brought forcibly home to the Stock Exchange the impossibility of further continuing the cumbersome method of cash payments. This method necessitated a vast amount of borrowing and a cash settlement of all loans. When the stringency came at that time, many failures resulted from the impossibility of procuring the necessary loans. On the other hand, on the Consolidated Stock Exchange of New York, a young and less important exchange, the failures were comparatively few. This difference was ascribed by Bradstreet’s solely to the fact that one institution attempted to carry on its business by old- fashioned methods, while the other was equipped with a modern clearing system.The explanation is easily accepted in view of the comparative ease with which the Stock Exchange has weathered similar troubles since the clearinghouse was adopted. The demoralization that prevailed in industrial shares in the spring of 1893, for example, put the new system to a severe, but successful test. It was stated that the adjustment of losses due to the important failures incident to the heavy decline in ‘Cordage’, ‘Sugar’ and other stocks was effected by stock deliveries involving only $200,000; while it was thought by some that, without the clearing system, the panic of that summer would have necessitated the closing of the Exchange.”

Historical observers also commented on how the clearinghouse handled the rapid increase in trading volumes in the early 1900s. “It is conceded that it would have been impossible to have transacted the stock business of 1901 ex-Clearing House. The machinery of the street would have broken down” (Pratt, 1912, 165). Pratt estimated that more than $17 billion of certified checks were obviated in 1901 alone (“these sums are so great as to be beyond human comprehension” he wrote), saving the New York banks certifications averaging $50,000,000 per day (Pratt, 1912, 167). When the shares traded on the panic day of May 9, 1901 settled on the following day, 452 Clearing House members settled $961,300,000 worth of stock, obviating the

25 need for $221,050,000 worth of certified checks (Pratt, 1912, 166). The Clearing House almost certainly was responsible for a reduction of the strain on the banking system, Pratt estimated that more than $17 billion of certified checks were obviated in 1901 alone (“these sums are so great as to be beyond human comprehension” he wrote), saving the New York banks certifications averaging $50,000,000 per day (Pratt, 1912, 167).

VI. Conclusions

The study has examined the effects of the NYSE’s introduction of a net settlement system when it inaugurated its first securities clearinghouse in 1892. The study is the first empirical analysis of a securities settlement system using archival data. In addition, it is the first empirical study of both an equity settlement system and a ring settlement system.

This study reports that the mean number of broker insolvencies in the pre_CH (pre clearinghouse) period is 1.957 per month, while post_CH the mean is 0.580., a reduction in broker failure by 70%. The regression results suggest that the volume-related operational bottlenecks that resulted in higher broker insolvencies pre-CH were reduced through the net settlement instituted by the clearinghouse. These two results suggest that the NYSE clearinghouse’s system of net settlement contributed to an improvement in overall NYSE systemic stability.

26 The results are in line with predictions of the theoretical settlement literature, as with

Kahn, McAndrews, and Roberd (2003), which predicts a lower settlement failure rate under net settlement versus gross settlement.. Gross settlement can result in a higher settlement failure rate because a trader can be exposed to the risk of the full principal amount of the trade after the trader delivers, but has failed to receive the contractually agreed upon amount. This risk, has been called “Herstatt” or “time-gap” risk.

The NYSECH was not a CCP, and therefore was able to avoid concentrating risk within itself, while leaving brokers liable for lower net exposure21. Contrary to the practices of most modern CCP settlement systems, the NYSE Clearing House did not engage in novation. Instead it operated at the nexus of a multilateral net settlement system known as “ring settlement”.

Ringing was a common form of settlement for late 19th century U.S exchanges, typically employing a central agent to direct settlement activities according to a set of rules agreed to by members of the ring. Ring settlement has largely been ignored by modern settlement system architects, and it is the authors’ hope that this study will encourage a reconsideration of the relative merits of such a system because it preserves monitoring incentives among participants without centralizing settlement risk within a CCP. As discussed in the introduction, this study has important implications for contemporary regulatory efforts to improve settlement practices in over-the-counter markets.

21 It is important to note that brokers were still exposed to counterparty risk, thus incentivizing them to monitor counterparty performance.

27 Table I: Settlement Obligations of a Broker With Non-Offsetting Trades

Source: Noyes, Stock Exchange Clearing Houses (1893, 261)

28 Table II: NYSE Archival Data Sources

1 Minutes of the NYSE Committee on Admissions (1868-1972). The committee had oversight of Exchange memberships, which first became saleable in 1868. As well as qualitative details on exchange memberships, the minutes contain data on the frequency and severity of broker failures. 2 Committee on Admissions, List of Suspended Members (1/23/1871- 10/1/1940). The list records every member suspension during the dates indicated. In addition, it records extensions of the period for reinstatement granted by the Committee for Admissions, as well as dates of the dispositions of memberships. The data gives a precise determination of broker-failure dates. 3 Committee on Admissions, Claims Against Membership (1870-1940). The volume details claims of injured members against insolvent counterparty members, and details regarding the disbursement of funds with sales of insolvent-member memberships. In addition to the claims data, the volume contains data on seat sales. 4 Minutes of the NYSE Committee on Insolvencies (1876-1925). The committee was formed to determine the nature of broker failures, and specifically whether “reckless and unbusiness-like” practices were involved in a broker insolvency. 5 Report of Committees for Re-admission (1837-1869). The committee’s reports provide a rich source of qualitative data regarding the circumstances of broker failures and re-admission of suspended brokers after claims on their membership were resolved. 6 Minutes of the New York Stock Exchange (1869-1929), Minutes of the Governing Committee (1869-1938), Minutes of Finance Committee. These records contain additional qualitative and quantitative data that has been useful in illuminating the details of settlement operations at the NYSE. 7 NYSE Total Sales (Stock and Bond volume) 1879-1934: The series contains the daily trading volume for stocks, government, state and railroad bonds, listed as well as unlisted securities.

29 Table III: Descriptive Statistics for Study Variables

______Pre-Clearinghouse Period______N Min Max Mean Median S.D. (1) Broker Insolvencies 256 0 36 1.957 1.000 3.163 (2) Volume 000’s 160 2,907 14,404 7,478 7,121 2,434 (3) %ΔVolume 159 -.5251 1.1690 .0461 .0178 .320 (4) Index 268 0.900 2.510 1.671 1.710 0.357 (5) %ΔIndex 268 -.2017 .2262 .0019 -.0007 .0473 (6) Call_Max 172 0.0200 1.8900 .1092 .0600 .2435 (7) Seat 186 4264 33667 19511 21000 8270 (8) NBER 268 0.00 1.00 0.53 1.00 0.500 (9) (2)*(4) 159 -.06 .15 .0038 .0007 .0209

______Post-Clearinghouse______N Min Max Mean Med S.D. (1) Broker Insolvencies 200 0 7 0.580 0.000 1.067 (2) Volume 000’s 200 1,272 42,138 12,612 11,172 7,991 (3) %ΔVolume 200 -0.8970 13.6965 0.1294 -0.0415 1.0419 (4) Index 200 1.4800 3.7500 2.5412 2.3200 0.7301 (5) %ΔIndex 200 -.1340 .0845 .0032 .0061 .0334 (6) Call_Max 200 0.0100 1.8600 0.1316 0.0500 0.2460 (7) Seat 200 15000 93000 46866 40018 26361 (8) NBER 200 0.00 1.00 0.47 0.00 0.50 (9) (2)*(4) 200 -.0900 .4000 .0047 .0003 .0321

The Table gives the number of observations (N), the minimum (Min), the maximum (Max), the mean (Mean), the median (Median), and the standard deviation (Std) of monthly values.

Descriptive statistics are for: (1) Broker Insolvencies, the number of broker insolvencies reported per month, (2) monthly NYSE trading volume (Volume), (3) monthly NYSE trading volume restated in monthly percentage change (%ΔVolume), (4) an NYSE equity market index (Index, taken from Goetzmann, Ibbotson and Peng (2001)), (5) Index, restated in monthly percentage change (%ΔIndex), (6) the maximum monthly call loan rate (Call_Max), (7) monthly series of NYSE seat prices (Seat), (8) an NBER recession variable (NBER) taking value 1 with NBER contractions, and 0 with expansions, and (9) the interaction between variables (3) and (5).

The NYSE’s first security clearinghouse was founded in May 1892. The pre-clearinghouse period extends from 1/1871 to 5/1892. The post-clearinghouse period extends from 5/1892 to 12/1908, to include the Panic of 1907, the last major financial crisis before the founding of the Federal Reserve System.

30 Table IV: Correlations among Study Variables

______Pre-Clearinghouse Period______

(1) (2) (3) (4) (5) (6) (1) Insolvencies 1 (2) %ΔVolume .243** 1 (3) %ΔIndex -.147** .238** 1 (4) Call_Max .429** .030 -.115 1 (5) Seat -.066 -.067 -.173** -.024 1 (6) NBER .178 -.045 -.210** .160** .143** 1

______Post-Clearinghouse Period______

(1) (2) (3) (4) (5) (6) (1) Insolvencies 1 (2) %ΔVolume -.013 1 (3) %ΔIndex -.231** .122 1 (4) Call_Max .323** -.012 -.225** 1 (5) Seat -.096 .049 -.025 .049 1 (6) NBER .193 -.081 -.164** .153** -.158** 1

Note that data on the variable %DVolume was not available until February 1879. To create a uniform data sample, the data used here and with the analyses below all used this same start date. Specifically, the pre-clearinghouse period covers monthly dates February 1879 to April 1892, and the post-clearinghouse period covers May 1892 through December 1908.

* indicates significance at the 0.05 level, ** indicates significance at the 0.01 level, *** indicates significance at the 0.001 level

31 Table V: Regression Analysis of Broker Insolvencies

Regression R2 equals 27.7%. Overall regression F-test equals 16.475 (with significance = 0.000)

B Std. Error t Sig. (Constant) .715 .146 4.913 .000*** (1) %ΔVolume 1.748 .323 5.418 .000*** (2) %ΔIndex -4.140 1.893 -2.186 .029* (3) Call_Max 2.260 .295 7.670 .000*** (4) SeatPrice -4.495E-6 .000 -1.344 .180 (5) NBER .307 .138 2.222 .027* (6) (1)*(2) -6.723 4.253 -1.581 .118 (7) CH -.351 .158 -2.218 .027* (8) (1)*(7) -1.536 .334 -4.604 .000***

Regression analysis of dependent variable: Broker Insolvencies. The independent effects include: (1) monthly NYSE trading volume restated as percent monthly change (%ΔVolume), (2) An NYSE equity market index (Index, taken from Goetzmann, Ibbotson and Peng (2001)) restated as percent monthly change (%ΔIndex), (3) the maximum monthly call loan rate (Call_Max), (4) monthly series of NYSE seat prices (Seat), (5) an NBER recession variable (NBER) taking value 1 with NBER contractions, and 0 with expansions, (6) the interaction effect between (1) and (2), (7) a dummy variable (CH) equal to 1.0 post-May 1892 inclusive, and 0.0 in the period before formation of the NYSE’s first security clearinghouse, and (8) the interaction between variables (1) and (7).

* indicates significance at the 0.05 level, ** indicates significance at the 0.01 level, *** indicates significance at the 0.001 level

32 Table VI: Regression Analysis of Broker Insolvencies By Sample Periods

A. Pre-Clearinghouse Regression Results

Regression R2 equals ?%. Overall regression F-test equals 16.392 (with significance = 0.000)

B Std. Error t Sig. (Constant) .773 .488 1.583 .115 (1) %ΔVolume 1.823 .375 4.862 .000*** (2) %ΔIndex -3.284 2.837 -1.157 .249 (3) Call_Max 4.269 .551 7.751 .000*** (4) SeatPrice -1.684E-5 .000 -.807 .421 (5) NBER .368 .243 1.515 .132 (6) (1)*(2) -11.350 6.457 -1.758 .081

B. Post-Clearinghouse Regression Results

Regression R2 equals 16.4%. Overall regression F-test equals 6.238 (with significance = 0.000)

B Std. Error t Sig. (Constant) .496 .174 2.855 .005** (1) %ΔVolume 0.160 0.157 1.014 0.312 (2) %ΔIndex -4.683 2.375 -1.971 .050* (3) Call_Max 1.119 .305 3.665 .000*** (4) SeatPrice -3.577E-6 .000 -1.305 .194 (5) NBER .259 .147 1.761 .080 (6) (1)*(2) -4.978 5.296 -.904 .348

* indicates significance at the 0.05 level, ** indicates significance at the 0.01 level, *** indicates significance at the 0.001 level

33 Table VII: Poisson Regression of Broker Insolvencies

Regression R2 equals 18.8%. Overall regression F-test equals 9.946 (with significance = 0.000)

B Std. Error t Sig. (Constant) .676 .111 6.076 .000*** (1) %ΔVolume .867 .233 3.728 .000*** (2) %ΔIndex -2.484 1.315 -1.889 .060 (3) Call_Max 2.142 .426 5.035 .000*** (4) SeatPrice -2.33E-006 .000 -1.050 .295 (5) NBER .199 .109 1.833 .068 (6) (1)*(2) -2.581 3.179 -.366 .418 (7) CH -.300 .124 -2.426 .016* (8) (1)*(7) -.805 .246 -3.936 .001***

Regression results for weighted least squares (WLS) analysis of dependent variable: Broker Failures. Five iterations of WLS were performed. Weights were set equal to the reciprocal of the predicted value from the previous iteration. To account for a small number of near-zero and negative predicted values (predicted values<0.01), their predicted values were set to 0.01 in value. Note that WLS is a common approach used to obtain maximum likelihood estimates for Poisson regression.

* indicates significance at the 0.05 level, ** indicates significance at the 0.01 level, *** indicates significance at the 0.001 level

34 Table VIII: Poisson Regression of Broker Insolvencies By Sample Periods

A. Pre-Clearinghouse Regression Results

Regression R2 equals 28.2%. Overall regression F-test equals 9.689 (with significance = 0.000)

B Std. Error t Sig. (Constant) .466 .299 1.559 .121 (1) %ΔVolume 1.334 .272 4.912 .000*** (2) %ΔIndex -1.524 1.675 -.910 .364 (3) Call_Max 3.506 .988 3.549 .001** (4) SeatPrice 3.10E-006 .000 .242 .809 (5) NBER .227 .172 1.315 .191 (6) (1)*(2) -7.872 4.159 -1.893 .060

B. Post-Clearinghouse Regression Results

Regression R2 equals 13.1%. Overall regression F-test equals 4.791 (with significance = 0.000)

B Std. Error t Sig. (Constant) .442 .147 3.012 .003** (1) %ΔVolume 0.093 0.144 0.643 0.521 (2) %ΔIndex -2.505 2.011 -1.246 .214 (3) Call_Max .963 .437 2.202 .029* (4) SeatPrice -1.96E-006 .000 -.862 .390 (5) NBER .248 .134 1.851 .066 (6) (1)*(2) -3.782 5.015 -.754 .452

* indicates significance at the 0.05 level, ** indicates significance at the 0.01 level, *** indicates significance at the 0.001 level

35 Figure 1: Histograms of Monthly Number of Broker Insolvencies, Pre- and Post-Establishment of the NYSE’s First Clearinghouse

Frequency Histogram of Monthly Broker Insolvencies: Jan. 1871 – April 1892 140

120

100

0 0 1-2 3-4 5-6 7-8 9-10 10+

Frequency Histogram of Monthly Broker Insolvencies: May 1892 – Dec. 1908 140

120

100

0 0 1-2 3-4 5-6 7-8 9-10 10+

The data sources used to compile data on broker insolvencies include the List of Suspended Members, Claims Against Membership, and Minutes, all documents of the NYSE’s Committee on Membership. These documents were accessed from the NYSE’s Archives.

36 Figure 2: Monthly NYSE Broker Insolvencies: 1871-1908 40 Black Friday Panic of Panics of Panic of 1893 1895-6 & 35 1873 1873 1899 Barings Panics of 30 Grant & Panic 1901 & 1907 Ward of 1890 25 Panic of 1884 20

0 1870 1875 1880 1885 1890 CH 1895 1900 1905

Figure 2 depicts the monthly number of broker insolvencies over the period: 1871-1908;the present study’s regression analysis examines the period February 1879 to December 1908. Overall, the frequency of broker failures prior to the May 17, 1892 founding of the NYSE Clearing House (CH) is substantially higher than it was during the period after the clearinghouse commenced net settlement operations. Also, peak numbers of broker failure often accompanied major financial panics. However, this relationship seems to diminish in the post clearinghouse period. Data compiled from documents located at the New York Stock Exchange Archives, including the Minutes Of The Committee on Insolvencies, Minutes of the Admissions Committee, Minutes of the Governing Committee, Minutes of the New York Stock Exchange and Admissions Committee Suspended Broker List. The commencement of Clearing House operations is denoted by an arrow marked with “CH”. During the pre-Clearing House panics of 1873, 1884 and 1890, there were markedly more severe episodes of broker insolvencies than during the post-Clearing House panics of 1893, 1895, 1899, 1903 and 1907.

37 Figure 3: Monthly NYSE Equity Trading Volume 1879-1908

45000000 Panic of 1903 40000000 Panic of 1907

35000000 Barings Panic of Grant & Ward 30000000 Panic 1893 Panic of 1884 of 1890 25000000

20000000

15000000

10000000

5000000

0 1875 1880 1885 1890 CH 1895 1900 1905 1910 1915

Figure 3 depicts monthly aggregate trading volume for the years 1879 through 1908. Declining trading activity in the years immediately following the formation of the NYSE Clearing House (CH) placed downward pressure on broker commission income. The removal of operational bottlenecks through the institution of net settlement appears to have contributed to operational efficiencies that contributed to the enormous increase in trading volume that began in the late 1890s. Krozner (1999, 601) theorizes that the introduction of clearinghouses results in transactional efficiencies that provide significant incentives to centralize trading. Data compiled from NYSE Total Sales 1879- 1934. NYSE Archives.

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