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The Effects of Margin Changes on the Composition of Traders

and Market Liquidity: Evidence from the Taiwan Futures

Exchange

By

Robin K. Chou, George H. K. Wang and Yun-Yi Wang

Keywords: Margins; Trading activity; Trader types; Liquidity; Volatility.

JEL Classification: G10.

________________ *Robin K. Chou, Professor of Finance and Risk and Insurance Research Center, College of Commerce, National Chengchi University, Taipei, Taiwan, e-mail: [email protected]; George H. K. Wang, Research Professor of Finance, School of Management, George Mason University, Fairfax, VA, e-mail: [email protected]; Yun-Yi Wang, Associate Professor of Finance, Feng Chia University, Taichung, Taiwan, e-mail: [email protected]. The authors thank John Howe and Xuemin Yan, as well as seminar participants at the University of Missouri for their helpful comments and suggestions. Robin K. Chou gratefully acknowledges financial support from the National Science Council of Taiwan (No. 102-2628-H-004-001) and from the National Natural Science Foundation of China (Nos. 71232004, 71373296, 71372137 and 70902030). Yun-Yi Wang gratefully acknowledges financial support from the National Science Council of Taiwan (No. 102-2918-I-035-002).

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The Effects of Margin Changes on the Composition of Traders

and Market Liquidity: Evidence from the Taiwan Futures

Exchange

Abstract

We examine the effects of margin changes on futures trading activity, the composition

of traders, and market liquidity using an account-level data set from the Taiwan

Futures Exchange. We find that margin increases reduce trading activity for all trader

types, which indicates that higher margins increase trading costs. Institutional trading

is more sensitive to changes in margin requirements than individual traders. This, in

turn, leads to increases in market price volatility and decreases in market liquidity.

These results imply that margin requirements are not an effective policy tool for

limiting the trading activity of noise speculators to reduce market volatility.

Keywords: Margins; Trading activity; Trader types; Liquidity; Volatility.

JEL Classification: G10.

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1. INTRODUCTION

Margin requirements are used to protect the financial integrity of the futures

markets. They are often viewed by regulators and researchers as an important policy

tool to reduce excessive volatility and maintain market stability.1 The notion that the

regulation of margins can be an effective policy tool to reduce price volatility rests on

the assumption that excess speculator participation will induce market-destabilizing

price fluctuations. Increases in margins are often viewed as effective means to drive

speculators out of the markets.

Previous empirical results regarding the impact of margin changes on price

volatility are mixed. For example, Hardouvelis and Kim (1995, 1996), Chatrath,

Adrangi, and Allender (2001), and Daskalaki and Skiadopoulos (2012) report a

significantly positive relationship between margin changes and price volatility, while

Ma, Kao, and Frohlich (1993) report the opposite. Hartzmark (1986), Kupiec (1987),

and Fishe, Goldberg, Gosnell, and Sinha (1990), however, do not find consistent

relationships between margin changes and price volatility.

Different traders may incur different trading costs due to margin requirements.

Hartzmark (1986) suggests that to evaluate whether margin requirements are an

1 The Dodd-Frank Wall Street Reform and Consumer Protection Act (enacted in 2010) transfers the authority of margin setting from the exchanges to the clearing houses, due to the potential conflicts of interests.

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appropriate and effective policy tool for reducing speculative trading, it is necessary

to know the differences in trading costs for different traders that are associated with

margin requirements. He argues that small traders are generally cash deficient and are

more likely to find themselves constrained when faced with a margin increase.

Similarly, Hardouvelis (1990) argues that because speculators hold more risky assets

and less cash in their portfolios, they may be more sensitive to margin changes.

In other words, after margin increases, traders that experience higher changes in

trading costs are more likely to exit the market. Thus, it is possible to observe the

effects of margin changes on the relative trading costs of different traders through the

changes in their trading activities. Furthermore, changes in the composition of traders,

price volatility, and market liquidity surrounding margin changes have important

implications for the effectiveness of the margin policy.

We examine an account-level data set from the Taiwan Futures Exchange

(TAIFEX) with complete intraday trading records for four trader types: foreign

institutions, proprietary firms, domestic institutions, and individual traders. We further

classify individual traders into two groups: individual day traders and individual

non–day traders. Day trading is prevalent on the equity and futures markets in Taiwan

(Barber, Lee, Liu, and Odean, 2009, 2014; Chou, Wang, Wang, and Bjursell, 2011),

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and due to the extremely short holding periods, day traders are likely trading mainly on

the basis of speculative motives (Barber et al., 2014).

This paper examines the effects of margin changes on trading activity of different

types of traders, as well as the impact of margin changes on the futures market volatility

and liquidity (trading volume and bid-ask spreads). We also test the impact of futures

margin changes on futures pricing errors, a measure of the pricing relationship between

the stock and the futures markets. The margin requirements will likely change the

trading strategies of traders having positions in both markets and thus influence their

dynamic pricing relationships.

This research differs from the extant literature in the following ways. First, our

account-level data enable us to trace the trading records of each account and clearly

identify trader types. We can explore the effects of margin changes on their trading

activities and link them to price volatility and market liquidity. Prior studies often

argue that individual traders are more sensitive to the changes in margins than

institutional traders (i.e., Hartzmark, 1986; Chatrath et al., 2001). To the best of our

knowledge, however, few empirical studies, if any, directly verify this popular belief.

Second, our data allow us to define day traders and thus test the hypothesis that

Fishe et al. (1990) suggest. Specifically, they argue that because margins are paid on

positions held, not positions traded, margin increases will result in more day trading,

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given that day traders do not carry positions at the end of a trading day and thus are not

required to post margins overnight.

Third, most previous studies (Hardouvelis and Peristiani, 1992; Chatrath et al.,

2001) use weekly or bimonthly trading activity data of speculators and hedgers from

the Commodity Futures Trading Commission (CFTC) large trader report to examine

the impact of the margin changes on different traders, but changes in margin

requirements can occur on any day, which creates a data misalignment problem. Our

daily trader and market data are better matched with the changes in margins.

Finally, Adrangi and Chatrath (1999) and Chatrath et al. (2001) suggest that the

impact of margins on trading activity across different contract maturities reveals the

type of costs imposed by margins. If margins impose significant opportunity costs,

traders will be more sensitive to margin changes when they are farther from maturity.

If the transaction costs of margins are more important, traders will be more sensitive

to margin changes as the contracts approach expiration.2 However, in the U.S. futures

markets, margin requirements can be satisfied by holding interest-earning treasury

bills in the margin account, so the opportunity costs of posting margins are almost

zero and may be difficult to detect.

2 Transaction costs arise from posting margins and recomposing portfolios.

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During most of our sample period, the TAIFEX did not allow initial margins to

be posted by holding interest-earning treasury bills, and futures traders had to bear

sizable opportunity costs by posting margins with cash.3 Thus, by examining futures

contracts of different maturities on the TAIFEX, we can better delineate the impacts

of transaction and opportunity costs due to margin changes on the trading behavior of

different trader types.

We obtain several noteworthy empirical results. Increases in margins negatively

affect the trading activities of the market and those of all trader types, which is

consistent with the hypothesis that higher margins induce higher costs of trading.

However, we find that contrary to the common belief in the literature, institutional

traders are actually more sensitive to changes in margin requirements than individual

traders. Furthermore, the changes in margins are positively related to subsequent price

volatility and bid-ask spreads, while they are negatively related to liquidity. Overall,

margin increases leave the market with relatively more individuals (small speculators),

which in turn leads to higher price volatility and lower market liquidity.

We organize the rest of the paper as follows: In Section 2, we review the

literature and propose our hypotheses. In Section 3, we describe the institutional

3 After November 10, 2008, the TAIFEX began to allow initial margins to be satisfied by holding interest-earning treasury bills in the margins account. However, our sample period ends in December 2008, so our data overlap with this change for less than two months. The empirical results remain similar if we remove these two months of data.

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features of the TAIFEX and the data. In Section 4, we propose our empirical

methodology, and in Section 5, we present the empirical results on the impact of

margin charges. In Section 6, we offer a discussion of our findings and conclude.

2. LITERATURE REVIEW AND HYPOTHESIS DEVELOPMENT

Black (1976) argues that there are no opportunity costs associated with futures

margins. The daily marking-to-market feature of these markets forces the value of

contracts to zero because the contract is effectively rewritten each day. However, this

view does not take into account the costs associated with the initial margin when

traders first enter the futures market. Black (1976) and Anderson (1981) note that the

initial margin requirements can be satisfied by posting interest-earning treasury bills.

Therefore, the opportunity costs of posting margin are also zero because the market

participants receive interest payments from the margin account. Thus, according to

this view, margin changes will not affect the behavior of traders and will have no

effects on market activity. This makes margin requirements an ineffective policy tool

for reducing excessive speculation because the margin level is not likely to be an

important factor in determining traders’ demands for futures.

In contrast, Telser (1981), Hartzmark (1986), and Hardouvelis (1990), among

others, propose that margins and margin changes do impose considerable costs on

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traders. Telser (1981) argues that even though margin accounts may earn interest,

investors need to react to changes in the levels of margin requirements by reallocating

their financial resources. Once treasury bills are used as deposits for margins, they are

unavailable for other purposes. They are no longer part of the trader’s precautionary

balances, and the trader may lose the ability to take advantage of profitable

opportunities that may suddenly present themselves. Therefore, margin requirements

and margin changes are significant determining factors of traders’ futures demands.

Hartzmark (1986) develops a model of trader behaviors that incorporates the

transaction and opportunity costs associated with margins. Because margin

requirements are relevant to trader decisions, changing them would affect trader

behaviors and the likelihood of trader participation in the market. Drawing on these

arguments, we form our first hypothesis:

Hypothesis 1: If increases in margins induce higher trading costs, margin changes will

have a negative impact on the trading activities of all traders.

Numerous studies have found that individual traders in Taiwan tend to incur

trading losses and are thus assumed to be uninformed (Barber et al., 2009; Chou and

Wang, 2009; Chang, Hsieh, and Lai, 2013; Barber et al., 2014). On the TAIFEX,

institutional traders may have stronger incentives to trade futures for hedging

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purposes than individual traders. Individual traders appear to trade mainly for

speculative purposes.

Furthermore, day trading is prevalent on the Taiwan markets, which accounts for

more than one-third of all trading volume (Barber et al., 2009; Chou et al., 2011;

Barber et al., 2014). As Barber et al. (2014) point out, day traders, given their short

holding period, are most likely speculators. Individual futures day traders are

responsible for 96.98% of all day-trading value on the TAIFEX, and their average

trading profits are significantly negative (Chou, Wang, and Wang, 2014). The vast

majority of day traders (over 80%) in Taiwan lose money, which indicates that they

are likely to be uninformed speculators (Barber et al., 2014).

It is often asserted in the literature that small and uninformed speculators will be

the first to exit the market when margin requirements are raised (Hartzmark, 1986;

Chatrath et al., 2001). Implicit in this assertion is that this group of traders bears the

highest costs and risks of transacting. Alternatively, if transaction costs are important

for informed traders, higher margins may also result in informed traders leaving the

market. Kalavathi and Shanker (1991) build a model to address the demand for

futures contracts by hedgers and the consequences of increasing initial margin

requirements on this demand. They show that the impact of an increase in margin

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requirements lowers the demand for futures contracts by hedgers. Accordingly, we

propose our second hypothesis:

Hypothesis 2: If increases in margins affect the trading costs of small speculators (i.e.,

individual and individual day traders) more than those of institutions,

then small speculators are more likely to leave the market and/or trade

less than other trader types.

Many theoretical papers show that noise traders are responsible for exacerbating

market price volatility.4 If small and uninformed speculators are first to exit the

market when margin requirements are raised, margin requirements can be used to

reduce market price volatility due to excessive speculation by uninformed speculators

(Hartzmark, 1986). Accordingly, we form the third hypothesis as follows:

Hypothesis 3: There is a negative relationship between changes in margins and changes

in price volatility because small speculators (i.e., individual and

individual day traders) are more likely to leave the market after margin

increases.

4 See, for example, Black (1986), DeLong, Shleifer, Summers, and Waldmann (1990), Campbell and Kyle (1993), Campbell, Lettau, Malkiel, and Xu (2001), and Scheinkman and Xiong (2003).

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3. MARKET DESCRIPTION AND DATA

The TAIFEX is an order-driven electronic futures market without designated

market makers. Liquidity is generated endogenously by market participants. Before

placing orders, traders must meet the initial margin requirements set by the TAIFEX.

The initial margin of a futures contract is in absolute dollar terms and is set to cover at

least 1.5 times its 99% Value at Risk (VaR). At the close of each trading day, the

TAIFEX calculates the market total required margins, which are the initial margin

times the market total open interest.

At the close of each trading day, the TAIFEX also calculates estimated market

total required margins with an updated 99% VaR.5 These are calculated as the

updated 99% VaR times the market total open interest. If the estimated market total

required margins are 10% higher than yesterday’s market total required margins, the

TAIFEX will consider adjusting the margin requirements. When a margin adjustment

is decided, it is announced on the day before the adjustment.

Our samples include the two most actively traded futures contracts on the

TAIFEX: the Taiwan Stock Exchange Index futures (FITX) and the Taiwan Stock

Exchange Mini Index futures (MTX).6,7 The sample period is from January 2002 to

5 The VaR is revaluated on the basis of the highest price volatility of the past 30, 60, 90, or 180 days. 6 Both the FITX and MTX futures are based on the Taiwan Stock Exchange Capitalization Weighted Stock Index. The MTX futures has a contract value that is one-fourth that of the FITX.

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December 2008. We obtained our data set directly from the TAIFEX. The data set

contains detailed transaction records for all investors, including date and time of a

transaction, its direction (buy or sell), quantity, transaction price, and, most important,

account and trader type identifications. The trader type identification enables us to

categorize four trader types: foreign institutions, proprietary firms, domestic

institutions, and individual traders.

This data set enables us to trace the detailed trading activity of each account by

trader type. Therefore, we can also distinguish between individual day traders and

individual non–day traders. Day traders are defined as those who buy and sell the exact

same amount of a particular futures contract on the same day (i.e., traders that do not

carry inventory overnight).

Figure 1 presents the time-series behaviors of margin changes and futures price

volatility. The TAIFEX margin changes seem to be positively related to the current

and subsequent price volatility.8 This result supports the general belief asserted in

prior literature (Hardouvelis, 1990; Hardouvelis and Kim, 1996) that exchanges

systematically raise (lower) margin requirements in anticipation of higher (lower)

future volatility to control for traders’ risk exposures. 7 We repeat all tests on the Taiwan Stock Exchange Electronic Sector Index futures and the Taiwan Stock Exchange Financial Sector Index futures and find similar results. We also perform all tests on the nearby, the first deferred and the second deferred contracts for all index futures and again find similar results. To save space, we present only the results of two maturity contracts (the nearby and the first deferred) for FITX and MTX. Other results are available upon request. 8 To control for the endogeneity between margin changes and volatility, in the subsequent analyses, we follow Wang and Yau’s (2000) approach and use a four-equation structure model.

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<Figure 1 is inserted about here>

The descriptions of margin requirements for the two futures contracts during our

sample period appear in Table 1. Panel A shows the summary statistics for margin

requirements and the ratio of margins to contract value. Panel B presents the

frequency of initial margin changes over our sample period.

<Table 1 is inserted about here>

Following Chatrath et al. (2001), for our primary analyses, we consider a

“relative cost” approach to measure margin requirements as the ratio of margins to

contract values for our major tests. As a robustness check, in ancillary analyses, we

also use the dummy variable approach to capture the effect of margin changes. As

Panel A of Table 1 shows, the mean margin ratios for FITX and MTX are 8.23% and

8.35%, respectively. As Panel B of Table 1 shows, there was a relatively high

frequency of initial margin changes in 2007 and 2008, which suggests that the

TAIFEX was likely using margins as a tool to limit traders’ risk exposure during the

financial crisis (i.e., a high volatility period).

The dates and percentages of initial margin changes appear in Table 2. There was

a total of 22 margin changes, with 8 increases and 14 decreases. The absolute

percentage changes in initial margins range from 7.88% to 33.33%. The sizable

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changes in margins provide an ideal setting for examining the effects of margin

changes on trading activity, the composition of traders, and price volatility.


4. EMPIRICAL METHODOLOGY

4.1 Event Study Method

We first use the event study method to examine the impact of margin changes on

trading activities, price volatility, and market liquidity. The event study method is

often used in studies of margin changes (i.e., Hartzmark, 1986; Hardouvelis and

Peristiani, 1992). We define the event window as 15 days before and after the

announcement day of margin changes.9 We first split the whole sample into margin

increase and margin decrease events. This enables us to test whether there is an

asymmetric effect between margin increases and decreases. We test the differences in

means surrounding a margin change with both the parametric and the nonparametric

methods.10

9 We also define event windows of 1, 5, 10, and 30 trading days surrounding margin changes and find similar results. To save space, we do not report these results, but they are available upon request. 10 We only report the results of the t-test. The results of the nonparametric Kruskal-Wallis tests are similar.

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4.2 Regression Analysis

We next perform regression analyses to examine the impact of margin changes

on our variables of interest, using control variables. As Figure 1 shows, because

exchanges may systematically raise (lower) margin requirements in anticipation of

higher (lower) future volatility, we use a four-equation structural model framework in

reduced form to estimate the relationships among margin changes, trading activities,

price volatility, and bid-ask spreads.11

We follow the literature and control for other important factors that are likely to

influence trading activity, price volatility, and liquidity (Wang and Yau, 2000;

Chatrath et al., 2001). For trading activity, we specify the regression model as

follows:

, 0 1 1 2 1 3 1 4 1 5 1

6 1 ,i t t t t t t

t t

TA Margin PV TTM RF BAS

OI e

(1)

where trading activity (TAi,t) is a function of lagged margin (Margint-1), lagged price

volatility (PVt-1), time to maturity (TTM), lagged risk-free rate (RFt-1), lagged effective

bid-ask spread (BASt-1), and lagged open interest (OIt-1).

We measure trading activity, TAi,t, as either open interest or trading volume of

each type of trader. We measure Margint-1 as the ratio of initial margins to futures

11 To avoid the simultaneous equation biases, trading volume, price volatility, and bid-ask spreads are lagged by one period in Equations (1), (2), (3), and (4). For further discussion of this issue, see Wang and Yau (2000).

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contract value. PVt-1 denotes the Parkinson (1980) high-low volatility. We expect

volatility to be positively related to trading volume, in accordance with the mixture

distributions’ hypothesis. TTM controls for the maturity effect. RFt-1 is the risk-free

interest rate. We expect RFt-1 to be inversely related to trading volume because it

reflects the opportunity costs of holding inventory. BASt-1 is the bid-ask spread and

represents a major component of the transaction costs; we expect this to be inversely

related to trading volume. We expect OIt-1 to a have a positive impact on trading

volume because higher open interest is likely to generate more trading volume.

To compare the effects of margin changes on trading activities among different

types of traders, we transform all variables in Equation (1) into log forms.

Coefficients can be readily interpreted as the elasticity of trading volume with respect

to the explanatory variables.

The price volatility equation is as follows:

0 1 1 2 1 3 2 4 5 1 6 1

7 1 1 8 1 9

10 , 1 ,

t t t t Monday t t Ret

t t t

Total t t

PV Margin PV PV D R R D

R Margin BAS TTM

Vol

(2)

where price volatility (PVt) is a function of lagged margin (Margint-1) and the

one-period and two-period lagged price volatilities (PVt-1 and PVt-2), which capture

the persistence in price volatility. The Monday dummy (DMonday) controls for the

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Monday effect. DRet is a dummy variable equal to one if the return on day t-1 is

negative and zero otherwise, and it captures the asymmetric relationship between

return and volatility. The interaction term of lagged return (Rt-1) and DRet controls for

the asymmetry effects of return on volatility. Following Hardouvelis and Theodossiou

(2002), we include the interaction term Rt-1Margint-1 to capture the asymmetric

relationship between margin requirements and volatility. Other control variables

include lagged effective bid-ask spreads (BASt-1), time to maturity (TTM), and lagged

total trading volume (VolTotal,t-1).

We expect to find a positive relationship between price volatility and bid-ask

spreads because part of the intraday volatility is due to the bid-ask spread bounces.

Market makers demand wider bid-ask spreads when they adopt a position against a

large trade because they demand a liquidity premium.

The bid-ask equation is as follows:

0 1 1 2 3 1 4 1 5

6 , 1 ,

t t Monday t t

Total t t

BAS Margin D PV BAS TTM

Vol

(3)

where bid-ask spreads (BASt) are a function of lagged margin (Margint-1). The control

variables include lagged price volatility, (PVt–1), controlling for price risk, the Monday

dummy (DMonday), lagged bid-ask spreads (BASt–1), lagged total trading volume

(VolTotal,t-1), and time to maturity (TTM).

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Finally, the margin equation is as follows:

1 11 10 1 2 3 4,

t tt t ttMargin PV BASRF TA

(4)

where margin is a function of lagged price volatility (PVt-1), lagged risk-free rate

(RFt-1), lagged effective bid-ask spread (BASt-1), and lagged market trading activity

(TAt-1), measured by trading volume.

To avoid the simultaneous equation bias, we include only lagged variables in

Equations (1), (2), (3), and (4). We estimate the parameters using the ordinary least

squares (OLS) method and use the Newey and West heteroskedasticity and

autocorrelation consistent covariance matrix to obtain the consistent standard errors of

parameters.

5. EMPIRICAL RESULTS

Although how margin requirements are affected by factors such as volatility and

trading volume is an important topic, in this paper, we are primarily concerned with

the effects of margin changes on futures markets. Thus, we focus on the impact of

margin changes on the futures market liquidity in the following analysis.12

12 Consistent with the prior literature, we also find that market volatility has a significant impact on margin changes. We omit the results of how other variables affect margins, but these are available upon request.

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5.1 Effect of Margin Changes on Trading Activity

Following Hartzmark (1986), we calculate the average trading activity for 15 trading

days before and after margin changes. Table 3 presents the average open interest and

trading volume surrounding margin changes, with Panel A (B) showing the results for

margin increases (decreases).


Panel A of Table 3 shows that, in general, trading activity exhibits a significant

decrease after margin increases, which is fairly consistent across different contracts

(FITX and MTX), maturity (the nearby and the first deferred contracts), and trader

types (foreign institutions, proprietary firms, domestic institutions, individual traders,

individual day traders, and individual non–day traders). In Panel B, however, trading

activity tends to increase significantly after margin decreases. These results are

consistent with Hypothesis 1 and with the work of Telser (1981) and Hartzmark

(1986), who show that margins impose significant trading costs on futures traders, and

therefore trading activity significantly declines (increases) following an increase

(decrease) in margin requirements.

We observe several other noteworthy results in Table 3. First, with regard to

trading activity, both open interest and volume are significantly negatively related to

margin increases. These results do not support Black (1976), who argues that because

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intraday trading is not constrained by initial margin requirements, margins will have

no effect on volume.

Second, Hartzmark (1986) and Chatrath et al. (2001) suggest that speculators or

smaller traders are particularly sensitive to margin changes, while the effect of margin

changes on informed or institutional traders is unclear. However, the empirical results

reported in Table 3 show that margin increases have significantly negative impacts not

only on trading volume and open interest of individual traders but also on those of

institutional traders. Indeed, in subsequent analyses, we show that institutional traders

are actually more sensitive to the changes in margins.

Third, we generally find negative relationships between trading activity and

margin changes for the nearby contracts as well as for the first deferred contracts. As

we pointed out previously, if margins impose relatively more significant transaction

(opportunity) costs, traders will be sensitive to margin changes as the contracts

approach (move farther away from) maturity. Our results thus show that margins

impose both significant transaction and opportunity costs on futures traders, findings

that are inconsistent with those of Adrangi and Chatrath (1999) and Chatrath et al.

(2001). Although they do not find opportunity costs to be significant, their samples of

U.S. futures traders, a priori, do not seem to bear substantial opportunity costs.

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Finally, Fishe et al. (1990) predict that margin increases will result in more

day-trading activity. Because day traders do not carry overnight positions, they

experience less of a cost hike due to margin increases than non–day traders. However,

Table 3 shows that the trading volume of individual day traders actually declines

when margins increase, which does not support Fishe et al.’s argument. We find that

the trading costs raised by margin increases outweigh the potential benefits of not

posting margins overnight by switching to day trading, so the day-trading activity is

still reduced.

We next perform regression analyses to control for other factors that may affect

trading activity. We report the empirical results on the trading activity of FITX and

MTX in Panels A and B of Table 4, respectively. In Table 4, Model (1) shows the

results for open interest; Model (2) shows the results for total volume; and Models

(3)–(8) show the volume results for foreign institutions, proprietary firms, domestic

institutions, individual traders, individual day traders, and individual non–day traders,

respectively.


As Models (1) and (2) in Table 4 show, most of the coefficients of Volatilityt-1 are

significantly positive, and those of RFt-1 and Spreadt-1 are significantly negative.

These results are consistent with the findings in prior literature that trading activity is

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positively related to volatility but negatively related to risk-free rate and bid-ask

spreads.

We also note that the coefficients of TTM are significantly positive for the nearby

contract and significantly negative for the first deferred contract, which are fairly

consistent across different contracts (Panels A and B) and Models (1)–(8). For the

nearby contract, as it approaches the delivery date, trading activity gradually declines.

For the first deferred contracts, trading activity tends to increase as they approach the

delivery date. In Model (2), we include lagged open interest to control for its effects

on trading volume. As we expected, the coefficients of OIt-1 are significantly positive,

which shows that higher open interest generates more trading volume.

More important, from Models (1) and (2), we observe that the coefficients of

Margint-1 are all negative and significant at the 1% level, consistent across the

different contracts (Panels A and B). After controlling for other factors, we find that

trading activity is negatively related to margin changes. These results strongly support

Hypothesis 1, which predicts that positive margin changes increase trading costs and

thus decrease trading activity. It is worth noting that we find significantly negative

coefficients of Margint-1 for all contract maturities (both the nearby and the deferred).

To further explore the effects of margins on different traders, we estimate the

trading volume regressions separately for each trader type. From Models (3)–(8), we

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find that the coefficients of Margint-1 are negative and significant for all six types of

traders. Because all variables are in log forms, the coefficients of Margint-1 can be

interpreted as the elasticity of trading volume with respect to margin changes.

Take the nearby contract of FITX as an example: for each 1% increase in

margins, the trading volumes for foreign institutions, proprietary firms, domestic

institutions, and individual traders change monotonically as

follows: –3.145%, –1.605%, –1.133%, and –0.683%, respectively. These findings

suggest that margin changes affect the trading volume of institutional traders more

than that of individual traders. On average, institutional traders are more sensitive to

changes in trading costs caused by margin changes. Thus, our results do not support

Hypothesis 2, which predicts that margin changes will affect individual traders more

than institutional traders, as is usually assumed in the literature. This invalidates the

rationale that margin regulations are an effective policy tool for driving speculative

noise traders (individual traders) out of the market.

Furthermore, the decreases in trading volume for individual day traders and

individual non–day traders are –0.717% and –0.653%, respectively. The trading

reactions to margin changes for individual day traders and individual non–day traders

are similar. Overall, individual day traders also trade significantly less after margin

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increases, which does not support Fishe et al.’s (1990) argument that increased

margins will result in more day trading.

The analyses in Table 4 measure margin requirements as the ratio of initial

margins to futures contract values. To control for the influences of changing futures

contract values on this ratio, we alternatively use dummy variables to capture the

effect of margin changes. We repeat the analyses in Table 4 by replacing margins

ratios with a dummy variable, Dmargin, which is equal to one for the 15 trading days

after margin changes and zero otherwise.13 Table 5 reports the empirical results.

< Table 5 is inserted about here >

From Panel A (B) of Table 5, we find that the coefficients of Dmargin are all

negative (positive) for margin increases (decreases) and that the results are consistent

for both FITX and MTX and for different maturities. The results again confirm that

trading activity decreases (increases) significantly following margin increases

(decreases) and that margins impose significant trading costs on futures traders.

We next examine the effects of margin changes on the trader composition,

following the method proposed by Daskalaki and Skiadopoulos (2012). Columns 1–3

of Table 6 report the impacts of margin changes on the ratios of the foreign institutional

trader volume, the proprietary firm volume, and the domestic institutional trader volume

13 We also define the dummy by window lengths of 30 and 60 trading days after margin changes and find similar results. To save space, we do not report the results here, but they are available upon request.

26

to the individual trader volume, respectively. Column 4 reports the impacts of margin

changes on the ratios of the individual day trader volume to the individual non–day

trader volume.

< Table 6 is inserted about here >

We find that for both FITX and MTX, margin changes have significantly

negative impacts on the ratios of the institutional trader volume to the individual

trader volume. The sensitivities of trading activity to margins for different trader types

are consistent with the results of the elasticity of trader type volume to margin

changes in Table 4. Foreign institutions appear to be most sensitive to margin changes.

For example, from the FITX results in Panel A, the coefficient of lagged margins on

the ratio of the foreign institutional trader volume to the individual trader volume

is –0.246, which is significant at the 1% level and is the highest among the ratios of

all trader types. The coefficients of lagged margins on the ratios of other institutional

trader volume to the individual trader volume are also significantly negative.

Inconsistent with the predictions of Hypothesis 2, institutional traders appear to

be relatively more sensitive to margin changes than individual traders. As we show in

the following sections, the departure of institutional traders likely leads to increases in

price volatility and deterioration in market liquidity.

27

5.2 Effect of the Margin Changes on Market Volatility and Liquidity

Next we examine the effect of margin changes on market volatility and liquidity.

Table 7 presents the changes in price volatility and bid-ask spreads surrounding

margin changes. We use the Parkinson (1980) high-low volatility and realized

volatility as volatility proxies and effective spreads and realized spreads as spread

proxies.14 Panel A (Panel B) presents the results of margin increases (decreases).

Most of the results suggest that although there appears to be negative relationships

between margins and volatility, in general they are not statistically significant. We

obtained similar negative relationships between margins and bid-ask spreads, but

again, in general, the results are not statistically significant.


Before we control for other factors, note that our results seem to be consistent

with Hartzmark (1986), who finds an insignificant impact of margin changes on price

volatility. However, these results are likely unreliable, because we did not control for

other important factors shown in the literature to affect volatility. Table 8 reports the

regression results of the high-low volatility on margin changes and on other control

14 Following Andersen, Bollerslev, Diebold, and Ebens (2001), we calculate realized volatility as the square root of the sum of five-minute intraday squared returns. Effective spreads are 2Dt(Pt–Mt), and realized spreads are 2Dt(Pt–Mt+n), where Dt is equal to 1 for customer buy orders and –1 for customer sell orders, Pt is the transaction price, Mt is the bid-ask midpoint, and Mt+n is the midpoint of the quotations in effect n minutes after the trade. Following Bessembinder (2003), we set n=30.

28

variables.15 As Table 8 shows, all coefficients of Margint-1 for the nearby and the first

deferred contracts of FITX and MTX are significantly positive, which indicates that

higher margins induce higher volatility.


Our results are inconsistent with Hypothesis 3, which predicts that raising margin

requirements will cause noise speculators to be more likely to exit the market. We find

from our volume tests that individual trading activities are less sensitive to costs imposed

by increased margins. Thus, we conjecture that increases in market volatility due to

margin increases are at least partially attributable to the relative increases in individual

trading activity and decreases in institutional trading activity. This suggests that margin

increases are not an effective tool to reduce price volatility by driving noise speculators

out of the market.

As we expected, the coefficients of Volatilityt-1 are significantly positive, indicating

the persistence effects of market volatility. Most of the coefficients of VolTotal,t-1 are

significantly positive, which indicates that higher volatility is associated with larger

trading volume, a finding consistent with the positive volatility–volume relationship

15 The regression results of margin changes on the realized volatility are similar, and thus we omit them.

29

found in prior studies.16 Overall, we find that margins are negatively related to

volume and are positively related to volatility.

As a robustness check, we further examine how margin changes affect market

liquidity using the Amihud illiquidity measure, a composite liquidity measure that takes

into account the concurrent changes in both volume and price volatility. The Amihud

illiquidity measure is calculated as the absolute price changes divided by the daily

dollar trading volume. Table 9 reports the results, showing that the coefficients of

Margint-1 for both FITX and MTX are significantly positive. This confirms that margin

increases have significantly negative impacts on market liquidity (i.e., market liquidity

deteriorates after margin increases).


Next, we regress bid-ask spreads on margin changes and report the results in

Table 10. All coefficients of Margint-1 on spreads are significantly positive. As we have

shown, raising margin requirements causes all types of traders to exit the market, which

leads to reductions in volume, increases in volatility, and thus a less liquid market. This is

further evident by the increases in bid-ask spreads.


16 For a review of related studies, see Karpoff (1987).

30

For all models in Table 10, the coefficients of Volatilityt-1 are significantly

positive. This result is as we expected because an increase in price volatility implies

that market makers are faced with increased inventory risk and the risk of trading with

informed traders, so they tend to increase spreads.

The coefficients of TTM are significantly negative for the nearby contract and

significantly positive for the deferred contracts, which is fairly consistent across FITX

and MTX futures. These results confirm that for the nearby contract, as it approaches

the delivery date, spreads gradually increase, indicating a lower liquidity as the time

to maturity approaches for the nearby contract. However, for the first deferred

contracts, spreads tend to decrease as they approach the delivery dates, indicating

enhanced liquidity as the time to maturity approaches.

Overall, our results indicate that when margin requirements increase, trading volume

decreases and price volatility increases. We find that institutional traders are especially

sensitive to margin increases and are more likely to exit the market, leaving the market

with relatively more small noise speculators. As a result, the market liquidity deteriorates

in general, as shown by increases in the Amihud illiquidity measures and in bid-ask

spreads. Overall, market liquidity deteriorates significantly after margin increases.

31

5.3 Effect of the Margins Changes on Pricing Errors

We find that institutional traders are more sensitive to changes in margin

requirements. Due to either hedging or speculating needs, institutional traders are more

likely to trade simultaneously in the equity and futures markets. Institutional traders are

often viewed as informed traders, and their trading tends to improve the cross-market

pricing efficiency. Thus, it is interesting to examine how margin changes on the futures

market affect the pricing relationship between the spot and the futures markets.

In general, it is argued in the literature that informed traders prefer to trade on the

futures markets, which, compared with the spot markets, offer higher leverages, lower

costs, and fewer short-sale restrictions (Stoll and Whaley, 1990; Mayhew, Sarin, and

Shastri, 1995; Easley, O’Hara, and Srinivas, 1998). If institutional traders are more

sensitive to margin changes, such changes may have implications for the cross-market

pricing relationship.

We use the futures pricing errors as a measure for the pricing relationship between

the spot and futures markets. Following Kurov and Lasser (2002), we define pricing

errors as the absolute difference between the observed futures price and the theoretical

futures price from the cost-of-carry model, deflated by the value of the underlying

32

index.17 Control variables include lagged absolute pricing errors, lagged volatility,

and time to maturity.

We report the empirical results in Table 11. We find that the coefficients of Margint-1

are positive, although most of them are not significant. These results indicate that margin

changes appear to have a weak negative effect on the cross-market pricing efficiency,

although they are not significant enough to alter the pricing relationship between the spot

and futures markets.


6. SUMMARY AND CONCLUSIONS

Using an account-level data set, we investigate the effects of margin changes on

futures trading activity, the composition of traders, price volatility, and bid-ask

spreads. We derive several important conclusions. The market trading activity is

significantly lowered after margin increases, which implies that margin requirements

induce higher trading costs for all traders. We further show that trading activity is

negatively related to margin changes for contracts with various maturities, which

indicates that margins impose significant transaction and opportunity costs for all

17 In the cost-of-carry model, the present value of dividend is the sum of the dividends for holding the underlying index from time t to time T discounted by the risk-free rate. Because the Taiwanese government does not issue treasury bills regularly, as is the case in the United States, the risk-free rate is proxied by the average of the three-month certificate-of-deposit rates of the three largest commercial banks in Taiwan.

33

futures traders. We also examine the effects of margin changes on the trading volume

of different types of traders. We find that institutional traders are actually more

sensitive to margin changes than individual traders. This result is inconsistent with the

popular hypothesis proposed in the literature that margin changes affect individual

traders more than institutional traders.

Finally, we document that price volatility and bid-ask spreads are positively related

to margin changes. These findings suggest that raising margin requirements causes all

types of traders to leave the market, but because institutional traders are more sensitive to

such changes and are subsequently more likely to leave the market, markets are left with

relatively more noise speculators (individuals), which in turn leads to greater price

volatility and less market liquidity. Overall, our empirical results show that margin

requirements are not an effective policy tool to reduce market volatility by limiting

the trading activity of noise speculators.

34

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37

Figure 1 (a): Initial Margin Requirements of FITX and Volatility

Figure 1 (b): Initial Margin Requirements of MTX and Volatility

38

Table 1: Statistics and Distributions of Margin Requirements

This table presents the summary statistics of margins, ratios of margins to contract value, and frequencies of initial margins changes for the following index futures contracts: (1) the Taiwan Stock Exchange Index futures (FITX) and (2) the Taiwan Stock Exchange Mini Index futures (MTX). The sample period is from January 2002 to December 2008.

Panel A: Margins and Ratios of Margins to Contract Value

FITX MTX

Margins Margins/Value Margins Margins/Value

Mean 102,774 8.23% 26,066 8.35%

STD 21,024 1.67% 5,187 1.66%

Max 195,000 12.65% 49,000 12.64%

Min 75,000 4.62% 19,000 4.73%

Panel B: Distribution of Initial Margins Changes

FITX MTX

Increase Decrease Increase Decrease

2002 0 2 0 2

2003 1 1 1 1

2004 1 1 1 1

2005 0 1 0 1

2006 1 1 1 1

2007 3 5 3 5

2008 2 3 2 3

Total 8 14 8 14

39

Table 2: Percentage Margin Changes This table presents the percentage initial margin changes for the following index futures contracts: (1) the Taiwan Stock Exchange Index futures (FITX) and (2) the Taiwan Stock Exchange Mini Index futures (MTX). The percentage initial margin changes are calculated as the margin changes in dollar terms divided by the margin requirement prior to the change. The sample period is from January 2002 to December 2008.

Margin Change Dates Margin Change Percentage (%)

FITX MTX

2002/07/17 -12.50 -10.00

2002/09/09 -14.29 -14.81

2003/05/09 -16.67 -17.39

2003/10/09 20.00 21.05

2004/05/04 33.33 30.43

2004/09/29 -12.50 -10.00

2005/04/18 -14.29 -14.81

2006/04/21 33.33 30.43

2006/06/05 -12.50 -10.00

2007/02/09 -14.29 -14.81

2007/07/30 33.33 30.43

2007/08/03 25.00 26.67

2007/08/22 30.00 28.95

2007/10/09 -15.38 -15.82

2007/10/31 -9.09 -7.88

2007/11/26 -10.00 -10.53

2007/12/12 -17.78 -18.38

2008/02/18 18.92 18.92

2008/05/13 -15.91 -15.91

2008/06/13 -9.91 -9.91

2008/06/20 -13.00 -13.00

2008/12/11 26.44 26.44

40

Table 3: Trading Activity Surrounding Margin Changes This table presents open interest and trading volume averaged over the 15 trading days before and after margin changes. Panel A shows the results for margin increases, and Panels B shows the results for margin decreases. Traders are classified into six types: foreign institutions, proprietary firms, domestic institutions, individual traders, individual day traders, and individual non–day traders. An account is defined as a “day trader” account if the amounts of contracts purchased and sold on a particular day are the same. Diff (%) is the percentage differences of trading activity surrounding margin changes. ***, **, and * indicate significance at the 1%, 5%, and 10% levels, respectively.

Open

Interest

Volume

All Traders

By Trader Types

Foreign

Institutions

Proprietary

Firms

Domestic

Institutions

Individual

Traders

Individual

Day Traders

Individual

Non–Day Traders

Before After Diff (%) Before After Diff (%) Before After Diff (%) Before After Diff (%) Befor After Diff (%) Before After Diff (%) Before After Diff (%) Before After Diff (%)

Panel A: Margin Increase

(1) FITX

Nearby 47,345 37,887 -19.98 *** 113,364 100,722 -11.15 ** 8,584 8,302 -3.29 ** 21,27518,791 -11.68 * 1,851 1,604 -13.34 * 81,655 72,025 -11.79 ** 36,884 33,952 -7.95 ** 44,770 38,074 -14.96 ***

First deferred 6,937 5,754 -17.05 * 9,339 8,636 -7.53 * 1,674 1,638 -2.15 1,657 1,464 -11.65 337 218 -35.31 5,670 5,316 -6.24 1,672 1,660 -0.72 3,998 3,656 -8.55

(2) MTX

Nearby 7,723 6,765 -12.40 ** 34,842 32,449 -6.87 ** 88 61 -30.68 ** 4,821 4,218 -12.51 ** 67 51 -23.88 * 29,866 28,119 -5.85 * 13,878 13,394 -3.49 ** 15,988 14,726 -7.89 *

First deferred 1,354 1,203 -11.15 * 2,476 2,251 -9.09 * 12 9 -25.00 437 391 -10.53 3 2 -33.33 2,024 1,849 -8.65 761 722 -5.12 1,263 1,127 -10.77

Panel B: Margin Decrease

(3) FITX

Nearby 34,384 35,231 2.46 * 71,987 80,841 12.30 ** 5,178 6,153 18.83 * 13,54 15,42 13.85 ** 1,438 1,458 1.39 51,825 57,808 11.54 ** 22,667 26,026 14.82 ** 29,158 31,781 9.00 **

First deferred 3,922 5,174 31.92 * 5,585 7,355 31.69 1,154 1,439 24.70 807 1,094 35.56 166 199 19.88 3,457 4,622 33.70 1,115 1,453 30.31% 2,343 3,170 35.30

(4) MTX

Nearby 8,320 8,363 0.52 24,197 26,620 10.01 67 69 2.99 3,229 3,763 16.54 * 28 30 7.14 20,872 22,758 9.04 * 9,198 10,501 14.17 * 11,673 12,258 5.01

First deferred 1,173 1,479 26.09 * 1,837 2,484 35.22 1 3 200.00 383 522 36.29 2 3 50.00 1,450 1,956 34.90 438 594 35.62 1,012 1,362 34.58

41

Table 4: Regression of Trading Activity on Margin Changes This table reports the regressions of open interest and trading volume on margin changes. The sample period is from January 2002 to December 2008. Traders are classified into six types: foreign institutions, proprietary firms, domestic institutions, individual traders, individual day traders, and individual non–day traders. An account is defined as a “day trader” account if the amounts of contracts purchased and sold on a particular day are the same. Margin is the ratio of margins to futures contract value. Control variables include lagged Volatility, TTM, lagged RF, and lagged Spread. Volatility is measured by the Parkinson (1980) high-low volatility. TTM is time to maturity (in days), and RF is the risk-free rates. Spread is the ratio of effective spreads to the futures contract value. All variables are in log forms. ***, **, and * indicate significance at the 1%, 5%, and 10% levels, respectively.

Open

Interest

Volume

All

Traders

Foreign

Institutions

Proprietary

Firms

Domestic

Institutions

Individual

Traders

Individual

Day Traders

Individual

Non–Day Traders

Model (1) Model (2) Model (3) Model (4) Model (5) Model (6) Model (7) Model (8)

Coeff. t-stat Coeff. t-stat Coeff. t-stat Coeff. t-stat Coeff. t-stat Coeff. t-stat Coeff. t-stat Coeff. t-stat

Panel A: FITX

(1) Nearby contract

Intercept 6.162 *** 13.28 8.473 *** 29.78 -4.016 *** -2.85 2.851 *** 6.42 4.751 *** 11.43 8.582 *** 33.14 9.159 *** 23.58 7.183 *** 33.52

Margint-1 -1.769 *** -16.21 -0.866 ***-12.62 -3.145 *** -9.26 -1.605 ***-14.98 -1.133 *** -11.30 -0.683 *** -10.94 -0.717 *** -7.66 -0.653 *** -12.64

Volatilityt-1 0.118 *** 2.83 0.224 *** 9.34 0.309 *** 2.69 0.246 *** 6.57 0.180 *** 5.13 0.223 *** 10.22 0.328 *** 10.02 0.154 *** 8.52

TTM 0.071 *** 10.44 0.047 *** 11.91 0.020 * 1.77 0.017 *** 2.71 0.031 *** 5.38 0.065 *** 18.03 0.094 *** 17.36 0.057 *** 19.04

RFt-1 -0.180 ** -1.97 -0.092 * -1.76 0.081 0.31 -0.002 -0.03 -0.009 -0.07 -0.313 *** -5.06 -0.315 *** -4.16 -0.257 *** -6.51

Spreadt-1 -0.170 * -1.78 -0.105 * -1.85 -0.120 *** -2.88 -0.189 ** -2.06 -0.103 * -1.72 -0.072 -1.21 -0.089 ** -2.45 -0.061 -1.59

Open interestt-1 ---- ---- 0.261 *** 16.15 0.764 *** 9.53 0.454 *** 17.98 0.272 *** 11.52 0.217 *** 14.76 0.319 *** 14.46 0.149 *** 12.26

Adj. R2 0.2488 0.4984 0.3992 0.4981 0.3773 0.4991 0.4995 0.4643

F-statistics 78.61*** 195.07*** 163.43*** 194.89*** 119.38*** 195.64*** 195.91*** 170.31***

42

Table 4 (Contd.)

Open

Interest

Volume

All

Traders

Foreign

Institutions

Proprietary

Firms

Domestic

Institutions

Individual

Traders

Individual

Day Traders

Individual

Non–Day Traders



(2) First deferred contract

Intercept 12.654 *** 15.57 18.347 *** 28.24 15.182 *** 4.04 20.075 *** 10.17 -11.131 *** -2.84 18.215 *** 28.36 37.280 *** 14.68 17.004 *** 22.95

Margint-1 -2.726 *** -16.90 -0.801 *** -5.86 -5.646 *** -7.07 -1.682 *** -4.05 -2.856 *** -3.48 -0.574 *** -4.25 -1.182 ** -2.21 -0.698 *** -4.48

Volatilityt-1 0.200 *** 6.08 -0.001 -0.05 0.252 * 1.67 0.316 *** 4.00 -0.377 ** -2.43 -0.002 -0.07 0.443 *** 4.33 -0.030 -1.00

TTM -2.724 *** -27.37 -4.038 *** -49.33 -8.968 ***-18.60 -5.053 *** -20.11 -9.257 *** -18.58 -4.051 *** -50.06 -8.520 *** -26.62 -4.060 *** -43.49

RFt-1 0.011 0.07 0.266 1.33 0.416 0.62 0.553 1.41 -0.713 *** -3.14 -0.178 * -1.69 -0.535 *** -2.73 -0.064 -0.48

Spreadt-1 -0.108 * -1.85 -0.285 * -1.89 -0.492 *** -3.22 -0.192 *** -2.73 -0.042 -0.31 -0.153 * -1.79 -0.165 ** -2.23 -0.043 * -1.70

Open interestt-1 ---- ---- 0.508 *** 26.71 1.667 *** 15.12 0.809 *** 13.95 0.842 *** 7.41 0.474 *** 25.20 0.638 *** 8.57 0.481 *** 22.15

Adj. R2 0.5279 0.8365 0.5328 0.5359 0.4371 0.8339 0.5545 0.7922

F-statistics 258.84*** 984.07*** 214.81*** 219.39 146.05*** 965.62*** 240.14*** 733.60***

Panel B: MTX

(1) Nearby contract

Intercept 6.094 *** 11.30 8.812 *** 17.82 -1.591 -0.28 5.555 *** 7.00 -27.057 *** -8.78 8.697 *** 18.29 8.373 *** 12.81 7.673 *** 19.39

Margint-1 -0.974 *** -9.44 -0.782 *** -8.42 -1.120 * -1.86 -1.592 ***-10.70 -1.014 *** -6.97 -0.719 *** -8.06 -0.939 *** -7.66 -0.606 *** -8.16

Volatilityt-1 0.190 *** 4.91 0.320 *** 9.44 2.361 *** 6.09 0.383 *** 7.04 0.354 * 1.67 0.309 *** 9.47 0.424 *** 9.47 0.240 *** 8.84

TTM 0.070 *** 10.89 0.051 *** 9.12 -0.061 -0.95 0.011 1.18 0.138 *** 3.91 0.057 *** 10.58 0.077 *** 10.42 0.054 *** 12.06

RFt-1 -0.081 * -1.89 -0.081 * -1.72 -0.440 -0.50 -0.032 -0.75 -1.010 * -1.93 -0.082 * -1.94 -0.098 * -1.79 -0.064 * -1.95

Spreadt-1 -0.062 * -1.91 -0.011 -1.17 -0.771 ** -2.39 -0.226 ** -2.48 -0.427 * -1.65 0.013 0.52 -0.137 * -1.95 0.136 1.03

Open interestt-1 ---- ---- 0.364 *** 14.92 2.704 *** 9.72 0.484 *** 12.38 1.506 *** 9.92 0.350 *** 14.91 0.463 *** 14.37 0.281 *** 14.39

Adj. R2 0.3432 0.4481 0.3419 0.4042 0.3626 0.4484 0.4574 0.4215

F-statistics 135.93*** 159.58*** 132.05*** 133.59*** 118.83*** 159.79*** 165.67*** 143.31***

43

Table 4 (Contd.)

Open

Interest

Volume

All

Traders

Foreign

Institutions

Proprietary

Firms

Domestic

Institutions

Individual

Traders

Individual

Day Traders

Individual

Non–Day Traders




Intercept 10.501 *** 13.79 17.418 *** 23.53 -1.940 -0.51 18.556 *** 6.61 -6.841 -1.22 16.390 *** 25.41 33.021 *** 11.14 16.550 *** 20.30

Margint-1 -1.882 *** -14.76 -0.344 *** -2.66 -0.537 *** -8.07 -1.842 *** -3.77 -0.105 -0.10 -0.281 ** -2.50 -1.523 *** -2.94 -0.190 -1.34

Volatilityt-1 0.156 *** 7.72 0.051 ** 2.54 0.013 0.13 0.344 *** 4.53 -0.251 * -1.66 0.053 *** 3.01 0.673 *** 8.37 0.061 *** 2.76

TTM -2.211 *** -27.25 -3.522 *** -43.43 -2.130 *** -5.12 -4.399 *** -14.30 -5.348 *** -8.54 -3.605 *** -51.07 -8.282 *** -25.51 -3.557 *** -39.83

RFt-1 -0.142 -0.92 -0.252 * -1.66 -0.023 -0.89 -0.970 -1.26 -1.460 *** -4.10 -0.212 ** -2.19 -0.376 ** -2.12 -0.205 * -1.93

Spreadt-1 -0.169 -1.12 -0.141 -1.23 -0.360 ** -2.13 -0.303 *** -1.96 -0.637 * -1.71 -0.124 -1.29 -0.330 -0.64 -0.093 -0.72

Open interestt-1 ---- ---- 0.680 *** 28.74 0.796 *** 6.58 1.018 *** 11.41 1.534 *** 8.55 0.654 *** 31.76 0.897 *** 9.47 0.642 *** 24.63

Adj. R2 0.5432 0.8270 0.3470 0.4327 0.3825 0.8609 0.5850 0.7923

F-statistics 265.93*** 888.25*** 132.58*** 140.71*** 140.59*** 998.86*** 262.75*** 709.13***

44

Table 5: Regression of Trading Activity on Margin Changes This table reports the regressions of open interest and trading volume on margin changes. The sample period is from January 2002 to December 2008. Traders are classified into six types: foreign institutions, proprietary firms, domestic institutions, individual traders, individual day traders, and individual non–day traders. An account is defined as a “day trader” account if the amounts of contracts purchased and sold on a particular day are the same. Dmargin is a dummy variable, which takes the value of one for the 15 trading days after margin changes and zero otherwise. We run a regression for each margin change and then report the cross-sectional average of the regression coefficients, t-statistics, and adjusted R2. Control variables include lagged Volatility, TTM, lagged RF, and lagged Spread. Volatility is measured by the Parkinson (1980) high-low volatility. TTM is time to maturity (in days), and RF is the risk-free rates. Spread is the ratio of effective spreads to the futures contract value. All variables are in log forms. ***, **, and * indicate significance at the 1%, 5%, and 10% levels, respectively.

Open

Interest

Volume

All

Traders

Foreign

Institutions

Proprietary

Firms

Domestic

Institutions

Individual

Traders

Individual

Day Traders

Individual

Non–Day Traders




(1) FITX, nearby contract

Intercept 0.137 * 1.95 0.155 ** 1.97 0.106 * 1.77 0.102 * 1.72 0.129 * 1.77 0.145 * 1.95 0.112 * 1.79 0.118 * 1.74

Dmargin -0.374 ** -2.27 -0.295 ** -2.04 -0.344 ** -2.48 -0.398 * -1.78 -0.227 ** -2.08 -0.136 ** -1.97 -0.272 ** -2.21 -0.134 ** -1.97

Volatilityt-1 0.437 *** 8.34 0.232 * 1.94 0.259 ** 2.51 0.224 ** 2.20 0.254 ** 2.41 0.209 ** 2.28 0.179 ** 1.98 0.150 * 1.87

TTM 0.072 *** 7.60 0.035 *** 5.88 0.082 *** 4.07 0.026 * 1.86 0.021 *** 3.17 0.054 *** 9.54 0.082 *** 11.57 0.047 *** 9.87

RFt-1 -2.058 *** -29.60 -1.106 *** -19.43 0.429 1.23 -0.488 *** -7.23 -0.286 *** -4.50 -1.199 *** -22.36 -0.827 *** -12.27 -1.269 *** -27.98

Spreadt-1 -0.065 ** -2.46 -0.073 *** -4.39 -0.283 *** -5.07 -0.147 *** -7.47 -0.097 *** -5.26 -0.057 *** -3.66 -0.114 *** -5.80 -0.025 * -1.89

Open interestt-1 ---- ---- 0.665 *** 36.80 1.086 *** 17.79 0.780 *** 36.41 0.592 *** 29.33 0.598 *** 35.16 0.724 *** 33.80 0.481 *** 33.39

Adj. R2 0.6875 0.6958 0.6026 0.6911 0.6862 0.6961 0.6624 0.6969

45

Table 5 (Contd.)

Open

Interest

Volume

All

Traders

Foreign

Institutions

Proprietary

Firms

Domestic

Institutions

Individual

Traders

Individual

Day Traders

Individual

Non–Day Traders



(2) FITX, first deferred contract

Intercept 0.113 1.42 0.211 ** 1.99 -0.108 -1.39 0.124 1.47 0.129 1.49 0.133 1.41 0.168 * 1.73 0.127 1.38

Dmargin -0.554 ** -2.18 -0.253 ** -2.15 -1.380 *** -2.85 -0.605 *** -2.74 -2.371 ** -2.23 -0.217 ** -2.06 -0.220 ** -2.07 -2.044 ** -2.12

Volatilityt-1 0.136 *** 2.85 0.104 *** 2.83 0.034 0.22 0.186 ** 2.23 0.447 *** 2.92 0.094 *** 2.63 0.255 ** 2.26 0.123 *** 3.25

TTM -1.233 *** -9.86 -2.401 *** -25.11 -6.529 *** -15.93 -3.059 *** -13.99 -3.629 *** -23.88 -2.471 *** -26.48 -5.285 *** -17.97 -2.551 *** -25.80

RFt-1 -3.119 *** -20.77 -2.372 *** -19.28 -2.833 *** -5.39 -2.218 *** -7.88 -6.967 *** -13.47 -2.392 *** -19.92 -4.035 *** -10.66 -2.370 *** -18.63

Spreadt-1 -0.047 * -1.92 -0.064 ** -2.00 -0.500 *** -3.67 -0.179 ** -2.45 0.067 0.85 -0.131 ** -2.00 -0.156 ** -2.57 -0.124 ** -2.32

Open interestt-1 ---- ---- 0.846 *** 38.86 2.364 *** 25.65 1.243 *** 24.98 0.912 *** 10.00 0.790 *** 37.21 1.287 *** 19.22 0.790 *** 35.09

Adj. R2 0.6588 0.4883 0.7154 0.4354 0.6554 0.6550 0.6470 0.6588

(3) MTX, nearby contract

Intercept 0.119 1.48 0.134 1.52 -0.082 -0.97 0.091 1.05 0.132 1.47 0.106 1.13 0.072 0.98 0.113 1.27

Dmargin -0.126 ** -2.48 -0.456 * -1.93 -0.601 ** -2.29 -0.749 ** -2.27 -1.400 ** -2.23 -0.131 * -1.89 -0.252 ** -2.30 -0.203 ** -1.96

Volatilityt-1 0.232 *** 4.96 0.119 ** 2.22 3.087 *** 8.63 0.140 * 1.68 0.108 * 1.74 0.106 * 1.94 0.172 ** 2.44 0.131 * 1.92

TTM 0.071 *** 8.35 0.040 *** 5.29 -0.040 -0.63 -0.002 -0.21 0.142 *** 3.91 0.046 *** 6.35 0.065 *** 7.27 0.045 *** 7.22

RFt-1 -1.866 *** -28.11 -0.755 *** -10.14 1.187 * 1.86 0.120 1.16 1.384 *** 3.89 -0.785 *** -10.94 -0.399 *** -4.49 -0.866 *** -14.18

Spreadt-1 -0.129 * -1.92 -0.126 *** -5.01 -0.817 *** -3.79 -0.168 *** -4.80 -0.460 *** -3.82 -0.121 *** -4.97 -0.182 *** -6.02 -0.091 *** -4.40

Open interestt-1 ---- ---- 0.843 *** 33.44 1.890 *** 8.77 0.995 *** 28.42 1.246 *** 10.36 0.812 *** 33.42 0.955 *** 31.70 0.684 *** 33.06

Adj. R2 0.6913 0.5852 0.6702 0.5949 0.6917 0.6839 0.6734 0.6913

46

Table 5 (Contd.)

Open

Interest

Volume

All

Traders

Foreign

Institutions

Proprietary

Firms

Domestic

Institutions

Individual

Traders

Individual

Day Traders

Individual

Non–Day Traders



(4) MTX, first deferred contract

Intercept 0.097 1.36 1.142 * 1.69 1.025 1.55 1.293 * 1.68 1.028 1.43 1.117 1.48 1.228 * 1.75 1.103 1.49

Dmargin -0.289 *** -2.74 -0.180 ** -2.25 -0.942 *** -2.74 -0.576 *** -2.59 -0.331 ** -2.20 -0.172 ** -2.25 -0.254 ** -2.42 -0.163 ** -2.19

Volatilityt-1 0.199 *** 6.38 0.202 ** 2.06 0.168 ** 1.99 0.249 *** 3.14 0.238 *** 2.59 0.204 ** 2.16 0.244 *** 6.15 0.115 * 1.95

TTM -0.603 *** -5.71 -1.998 *** -22.25 -4.129 *** -11.92 -2.252 *** -8.66 -5.902 *** -11.76 -2.186 *** -27.04 -5.088 *** -17.49 -2.157 *** -23.53

RFt-1 -2.237 *** -17.68 -1.836 *** -16.31 -1.627 *** -3.74 -1.155 *** -3.54 -2.670 *** -4.26 -2.021 *** -19.96 -3.763 *** -10.32 -1.933 *** -16.83

Spreadt-1 -0.145 * -1.73 -0.116 *** -3.72 -0.351 *** -2.91 -0.283 *** -3.13 -0.662 *** -3.84 -0.101 *** -3.59 -0.280 *** -2.76 -0.069 ** -2.17

Open interestt-1 ---- ---- 1.091 *** 6.83 1.041 *** 5.42 1.639 *** 8.97 1.406 *** 10.06 1.034 *** 5.06 1.794 *** 21.75 1.013 *** 38.99

Adj. R2 0.6434 0.6584 0.8564 0.5835 0.4892 0.6633 0.5684 0.6493


(1) FITX, nearby contract

Intercept 0.142 ** 1.98 0.140 * 1.93 0.116 * 1.82 0.103 * 1.74 0.092 1.55 0.137 * 1.93 0.129 * 1.82 0.107 * 1.66

Dmargin 0.388 ** 2.45 0.207 ** 2.24 0.349 ** 2.54 0.219 ** 2.02 0.242 ** 2.21 0.188 ** 2.22 0.217 ** 2.10 0.162 ** 2.23

Volatilityt-1 0.434 *** 8.33 0.229 *** 2.86 0.243 ** 2.38 0.217 ** 2.43 0.250 ** 2.33 0.207 ** 2.23 0.084 ** 2.10 0.152 * 1.86

TTM 0.072 *** 7.57 0.035 *** 5.85 0.082 *** 4.08 0.026 * 1.84 0.021 *** 3.14 0.054 *** 9.52 0.082 *** 11.54 0.047 *** 9.84

RFt-1 -2.055 *** -29.77 -1.107 *** -19.53 0.410 1.14 -0.495 *** -7.37 -0.286 *** -4.52 -1.199 *** -22.47 -0.832 *** -12.38 -1.267 *** -28.08

Spreadt-1 -0.062 ** -2.35 -0.072 *** -4.33 -0.284 *** -5.09 -0.146 *** -7.45 -0.096 *** -5.20 -0.056 *** -3.60 -0.113 *** -5.79 -0.024 * -1.79

Open interestt-1 ---- ---- 0.665 *** 36.78 1.087 *** 17.78 0.780 *** 36.38 0.593 *** 29.33 0.598 *** 35.15 0.724 *** 33.77 0.481 *** 33.38

Adj. R2 0.6958 0.6025 0.6911 0.6862 0.6961 0.6924 0.6969 0.6958

47

Table 5 (Contd.)

Open

Interest

Volume

All

Traders

Foreign

Institutions

Proprietary

Firms

Domestic

Institutions

Individual

Traders

Individual

Day Traders

Individual

Non–Day Traders



(2) FITX, first deferred contract

Intercept -0.204 -1.55 0.191 * 1.72 -0.162 * -1.68 0.213 * 1.66 0.131 1.47 0.102 1.35 0.116 1.39 0.124 1.42

Dmargin 0.400 ** 2.40 0.256 *** 2.79 0.363 ** 2.11 0.592 *** 2.68 1.142 *** 2.82 0.268 *** 2.84 0.312 *** 2.63 0.260 *** 2.82

Volatilityt-1 0.138 *** 2.90 0.106 *** 2.88 -0.031 -0.20 0.185 ** 2.22 0.450 *** 2.93 0.196 *** 2.68 0.250 ** 2.22 0.125 *** 3.29

TTM -1.221 *** -9.79 -2.387 *** -24.98 -6.513 *** -15.94 -3.037 *** -13.92 -9.516 *** -23.64 -2.460 *** -26.38 -5.265 *** -17.94 -2.140 *** -25.73

RFt-1 -3.102 *** -20.77 -2.348 *** -19.12 -2.823 *** -5.40 -2.188 *** -7.80 -6.804 *** -13.20 -2.370 *** -19.79 -3.985 *** -10.57 -2.349 *** -18.52

Spreadt-1 -0.042 * -1.71 -0.059 * -1.85 -0.490 *** -3.60 -0.176 ** -2.41 -0.020 -0.15 -0.127 * -1.85 -0.139 * -1.74 -0.119 * -1.78

Open interestt-1 ---- ---- 0.847 *** 38.79 2.356 *** 25.59 1.245 *** 24.99 0.923 *** 10.10 0.791 *** 37.14 0.886 *** 19.18 0.790 *** 35.04

Adj. R2 0.6586 0.4897 0.7150 0.4340 0.6552 0.6547 0.6469 0.6586

(3) MTX, nearby contract

Intercept 0.095 1.17 0.113 1.49 0.146 1.62 0.109 1.33 0.103 1.12 0.138 1.59 0.088 1.26 0.129 1.62

Dmargin 0.482 * 1.92 0.223 ** 2.03 0.319 ** 2.24 0.301 ** 2.33 0.259 ** 2.25 0.208 ** 2.00 0.272 1.02 0.163 0.94

Volatilityt-1 0.231 *** 4.95 -0.005 -0.11 3.183 *** 8.91 -0.028 -0.48 0.133 0.66 -0.002 -0.05 0.079 1.58 -0.029 -0.85

TTM 0.071 *** 8.36 0.040 *** 5.27 -0.038 -0.59 -0.002 -0.21 0.142 *** 3.91 0.046 *** 6.33 0.065 *** 7.25 0.045 *** 7.20

RFt-1 -1.867 *** -28.36 -0.766 *** -10.30 0.886 1.39 0.093 0.90 1.341 *** 3.78 -0.795 *** -11.08 -0.415 *** -4.67 -0.872 *** -14.29

Spreadt-1 -0.129 * -1.91 -0.128 *** -5.07 -0.864 *** -4.01 -0.172 *** -4.91 -0.467 *** -3.88 -0.123 *** -5.03 -0.184 *** -6.10 -0.092 *** -4.44

Open interestt-1 ---- ---- 0.842 *** 33.25 1.837 *** 8.49 0.992 *** 28.24 1.247 *** 10.34 0.811 *** 33.22 0.953 *** 31.50 0.683 *** 32.89

Adj. R2 0.6913 0.5841 0.6701 0.6951 0.6917 0.6838 0.6789 0.6913

48

Table 5 (Contd.)

Open

Interest

Volume

All

Traders

Foreign

Institutions

Proprietary

Firms

Domestic

Institutions

Individual

Traders

Individual

Day Traders

Individual

Non–Day Traders



(4) MTX, first deferred contract

Intercept 0.102 1.39 1.422 * 1.77 0.093 1.19 1.027 1.33 0.099 1.02 1.217 * 1.66 1.239 * 1.69 1.103 1.58

Dmargin 0.598 *** 2.95 0.160 ** 2.63 0.270 ** 2.18 0.408 ** 2.36 0.732 *** 2.79 0.136 ** 2.63 0.464 ** 2.47 0.155 *** 2.60

Volatilityt-1 0.198 *** 6.37 0.203 ** 2.12 0.177 * 1.67 0.246 *** 3.10 0.243 *** 2.63 0.202 ** 2.09 0.540 *** 6.10 0.014 * 1.79

TTM -0.601 *** -5.72 -1.987 *** -22.16 -4.189 *** -12.08 -2.232 *** -8.61 -5.871 *** -11.72 -2.174 *** -26.94 -5.076 *** -17.51 -2.146 *** -23.46

RFt-1 -2.228 *** -17.73 -1.818 *** -16.19 -1.733 *** -3.99 -1.129 *** -3.47 -2.621 *** -4.20 -2.003 *** -19.82 -3.739 *** -10.30 -1.915 *** -16.72

Spreadt-1 -0.048 * -1.72 -0.114 *** -3.63 -0.373 *** -3.08 -0.279 *** -3.08 -0.654 *** -3.80 -0.098 *** -3.49 -0.275 *** -2.72 -0.066 ** -2.07

Open interestt-1 ---- ---- 1.091 *** 42.72 0.938 ** 1.98 1.639 *** 21.93 1.409 *** 10.06 1.034 *** 44.95 1.794 *** 21.72 1.014 *** 38.91

Adj. R2 0.6436 0.6583 0.8554 0.5837 0.4890 0.6631 0.5686 0.6492

49

Table 6: Regression of Relative Trading Activity by Trader Types on Margin Changes This table reports the regressions of margin changes on the ratios of foreign institutional trader volume, proprietary firm volume, and domestic institutional trader volume to individual trader volume, respectively, in the first three columns. The ratio of individual day trader volume to individual non–day trader volume appears in the last column. The sample period is from January 2002 to December 2008. An account is defined as a “day trader” account if the amounts of contracts purchased and sold on a particular day are the same. Margin is the ratio of margins to contract value. Control variables include lagged Volatility, TTM, lagged RF, lagged Spread, and lagged Open interest. Volatility is measured by the Parkinson (1980) high-low volatility. TTM is time to maturity (in days), and RF is the three-month risk-free interest rates. Spread is the ratio of the effective spreads to the futures contract value. ***, **, and * indicate significance at the 1%, 5%, and 10% levels, respectively.

Volume

Foreign Institutions/

Individual Traders

Proprietary Firms/

Individual Traders

Domestic

Institutions/

Individual Traders

Individual Day

Traders/Individual

Non–Day Traders

Coeff. t-stat Coeff. t-stat Coeff. t-stat Coeff. t-stat

Panel A: FITX

(1) Nearby contract

Intercept -0.318 ** -2.45 0.405 *** 16.99 0.546 *** 19.07 1.158 *** 43.57

Margint-1 -0.246 *** -7.85 -0.086 *** -14.91 -0.057 *** -8.25 -0.011 * -1.77

Volatilityt-1 0.016 1.44 0.005 *** 2.73 0.004 * 1.66 0.017 *** 7.70

TTM 0.010 *** 5.36 0.002 *** 5.90 0.001 0.75 0.004 *** 11.70

RFt-1 -0.012 -0.52 -0.013 *** -2.90 0.029 *** 5.57 -0.066 *** -13.41

Spreadt-1 -0.021 *** -4.21 -0.008 *** -8.21 -0.006 *** -5.04 -0.010 *** -9.94

Open interestt-1 0.055 *** 7.42 0.022 *** 16.55 0.010 *** 6.36 0.017 *** 11.55

Adj. R2 0.1775 0.4560 0.2031 0.4333

F-statistics 43.15*** 164.76*** 50.79*** 150.37***


Intercept 8.117 *** 5.35 5.140 *** 3.97 -2.409 -1.63 11.993 *** 8.24

Margint-1 -1.845 *** -5.73 -0.552 ** -2.03 -1.388 *** -4.49 -0.541 * -1.77

Volatilityt-1 0.400 *** 6.58 0.256 *** 4.96 0.206 *** 3.52 0.414 *** 6.89

TTM -3.187 *** -16.40 -1.268 *** -7.70 -2.583 *** -13.75 -2.450 *** -13.28

RFt-1 0.245 0.90 0.221 0.95 -1.958 *** -7.50 -0.573 ** -2.21

Spreadt-1 -0.106 ** -2.02 -0.032 -0.72 -0.028 -0.56 -0.050 -0.99

Open interestt-1 0.359 *** 8.07 0.149 *** 3.92 0.216 *** 5.04 0.124 *** 2.90

Adj. R2 0.4214 0.1539 0.3116 0.2669

F-statistics 137.57*** 35.41*** 85.57*** 70.42***

50

Table 6 (Contd.)

Volume

Foreign Institutions/

Individual Traders

Proprietary Firms/

Individual Traders

Domestic Institutions/

Individual Traders

Individual Day

Traders/Individual

Non–Day Traders


Panel B: MTX

(1) Nearby contract

Intercept -0.331 -0.56 0.588 *** 11.04 -3.186 *** -9.18 1.036 *** 25.50

Margint-1 -0.346 *** -3.14 -0.111 *** -11.12 -0.442 *** -6.78 -0.044 *** -5.73

Volatilityt-1 0.251 *** 6.21 0.014 *** 3.71 0.027 1.15 0.021 *** 7.57

TTM (10-1) -0.003 -0.05 -0.030 *** -4.81 0.160 *** 4.09 0.030 *** 7.55

RFt-1 0.014 0.16 0.082 *** 10.02 -0.160 *** -2.98 0.071 *** 11.37

Spreadt-1 -0.087 *** -3.89 -0.008 *** -4.17 -0.042 *** -3.16 -0.012 *** -7.69

Open interestt-1 0.295 *** 10.19 0.021 *** 8.02 0.156 *** 9.14 0.022 *** 10.82

Adj. R2 0.1510 0.3114 0.1463 0.3811

F-statistics 35.47*** 89.32*** 34.40*** 120.72***


Intercept 8.552 *** 4.55 6.830 *** 3.34 3.775 * 1.72 11.461 *** 5.29

Margint-1 -0.356 -1.08 -0.825 ** -2.32 -1.052 *** -2.68 -1.333 *** -3.53

Volatilityt-1 0.518 *** 10.17 0.405 *** 7.35 0.348 *** 5.90 0.731 *** 11.77

TTM -3.292 *** -15.89 -1.672 *** -7.47 -3.068 *** -12.53 -3.130 *** -13.18

RFt-1 -0.189 -0.66 0.468 1.52 -0.633 * -1.92 0.290 0.89

Spreadt-1 -0.127 ** -2.21 -0.097 -1.57 -0.192 *** -2.86 -0.143 ** -2.16

Open interestt-1 0.414 *** 6.88 0.168 *** 2.59 0.414 *** 5.90 0.149 ** 2.14

Adj. R2 0.4170 0.1729 0.2976 0.3287

F-statistics 132.16*** 39.28*** 76.14*** 91.09***

51

Table 7: Volatility and Spreads Surrounding Margin Changes This table presents volatility and spreads averaged over 15 trading days before and after margin changes. Realized volatility is calculated as the square root of the sum of five-minute intraday squared returns. Effective spreads are 2Dt(Pt–Mt) and realized spreads are 2Dt(Pt–Mt+n), where Dt is equal to 1 for customer buy orders and –1 for customer sell orders, Pt is the transaction price, Mt is the bid-ask midpoint, and Mt+n is the midpoint of the quotations in effect n minutes after the trade. Following Bessembinder (2003), we set n=30. Panel A shows the results for margin increases, and Panels B shows the results for margin decreases. Diff (%) represents the percentage differences surrounding margin changes. * indicates significance at the 10% level.

Volatility

Spread

High-Low

Volatility

Realized

Volatility

Percentage

Effective Spread

Percentage

Realized Spread

Before After Diff (%) Before After Diff (%) Before After Diff (%) Before After Diff (%)


(1) FITX

Nearby contract 0.0131 0.0141 7.63 * 0.0235 0.0248 5.53 * 0.0043 0.0046 6.98 * 0.0028 0.003 7.14 *

First deferred contract 0.0127 0.0138 8.66 * 0.0239 0.0234 -2.09 0.0124 0.0129 4.03 0.0105 0.0114 8.57 *

(2) MTX

Nearby contract 0.0132 0.0143 8.33 * 0.0241 0.0243 0.83 0.0048 0.0051 6.25 * 0.0034 0.0033 -2.94

First deferred contract 0.0130 0.0133 2.31 0.0233 0.0237 1.72 0.0122 0.0128 4.92 0.0096 0.0091 -5.21


(1) FITX

Nearby contract 0.0107 0.0102 -4.67 * 0.0308 0.0302 -1.95 0.0583 0.0462 -20.75 * 0.0016 0.0017 6.25

First deferred contract 0.0108 0.0104 -3.70 * 0.0215 0.0203 -5.58 * 0.0221 0.0213 -3.62 0.0066 0.0062 -6.06 *

(2) MTX

Nearby contract 0.0131 0.0125 -4.58 * 0.0514 0.0503 -2.14 0.0058 0.0057 -1.72 0.0015 0.0013 -13.33 *

First deferred contract 0.0106 0.011 3.77 0.0157 0.0162 3.18 0.0084 0.0078 -7.14 * 0.0066 0.0059 -10.61

52

Table 8: Regression of Volatility on Margin Changes This table reports the regressions of the effects of margin changes on volatility. The sample period is from January 2002 to December 2008. Margin is the ratio of margins to futures contract value. Control variables include lagged Volatility, Monday dummy, lagged Return, lagged Spread, TTM, and lagged Volume. Volatility is measured by the Parkinson (1980) high-low volatility. DRet is a dummy variable that is equal to one if lagged return is less than zero and zero otherwise. Spread is measured by the percentage effective spread, calculated as the ratio of effective spreads to the futures contract value. TTM is time to maturity (in days). ***, **, and * indicate significance at the 1%, 5%, and 10% levels, respectively.

FITX MTX

Nearby Contract First Deferred Contract Nearby Contract First Deferred Contract

Model (1)

Model (2) Model (3)

Model (4)


Intercept -0.003 ** -2.02 0.003 *** 2.83 -0.001 -0.52 0.003 ** 2.06

Margint-1 0.084 *** 6.62 0.043 *** 3.79 0.270 *** 6.02 0.168 *** 3.49

Volatilityt-1 0.227 *** 6.23 0.283 *** 9.83 0.219 *** 6.93 0.293 *** 9.76

Volatilityt-2 0.236 *** 8.07 0.235 *** 8.30 0.230 *** 7.93 0.232 *** 7.87

Monday dummy (10-4) -2.150 -0.46 1.031 1.27 -0.045 -0.01 4.305 0.80

Returnt-1 0.013 0.25 -0.004 -0.08 0.024 0.49 0.002 0.04

Returnt-1×DRet -0.016 -0.84 -0.006 -0.28 -0.026 -1.34 -0.017 -0.78

Returnt-1×Margint-1 -0.669 -1.28 -0.493 -0.89 -2.988 -1.45 -1.543 -0.68

Spreadt-1 (10-5) 2.807 * 1.90 0.836 0.17 7.740 1.01 3.480 0.67

TTM (10-5) -1.547 * -1.78 -2.884 *** -3.68 -2.431 -1.21 -2.394 *** -2.73

VolumeTotal, t-1 (10-8) 2.386 **** 4.51 0.248 * 1.66 4.699 *** 5.32 2.379 0.58

Adj. R2 0.2902 0.2637 0.3036 0.2536

F-statistics 44.53*** 38.38*** 47.41*** 34.89***

53

Table 9: Regression of the Amihud Illiquidity Measure on Margin Changes This table reports the regressions of the effects of margin changes on the Amihud illiquidity measure. The sample period is from January 2002 to December 2008. The Amihud illiquidity measure is calculated as the absolute price changes divided by the daily dollar trading volume. Margin is the ratio of margins to futures contract value. Control variables include lagged Volatility, Monday dummy, lagged Spread, TTM, and lagged Volume. Volatility is measured by the Parkinson (1980) high-low volatility. Spread is measured by the percentage effective spreads, calculated as the ratio of effective spreads to the futures contract value. TTM is time to maturity (in days). *** and ** indicate significance at the 1% and 5%, , respectively.

FITX MTX


Model (1)

Model (2) Model (3)

Model (4)


Intercept (10-8) 0.001 0.60 -17.086 *** -6.34 -0.005 -1.27 -25.062 *** -7.25

Margint-1 (10-7) 0.007 *** 3.99 12.000 *** 4.15 0.142 *** 7.19 88.900 *** 6.15

Volatilityt-1 (10-7) 0.018 *** 3.74 -17.100 ** -2.24 0.041 *** 2.89 -24.900 *** -2.64

Monday dummy (10-9) 0.016 ** 2.43 13.115 0.97 0.077 *** 3.65 11.955 0.70

Spreadt-1 (10-12) 0.623 0.63 87.906 0.07 -0.466 -0.14 71.122 0.04

TTM (10-11) -0.087 *** -3.06 221.472 *** 10.79 -0.452 *** -4.94 315.669 *** 11.69

VolumeTotal, t-1 (10-14) -0.053 *** -6.97 -29.630 -0.89 -0.372 *** -9.24 10.131 0.08

Adj. R2 0.1120 0.1116 0.1700 0.1484

F-statistics 22.10*** 21.60*** 35.27*** 28.34***

54

Table 10: Regression of Spreads on Margin Changes This table reports the regressions of the effects of margin changes on spreads. The sample period is from January 2002 to December 2008. Margin is the ratio of margins to futures contract value. Control variables include lagged Volatility, Monday dummy, lagged Spread, TTM, and lagged Volume. Volatility is measured by the Parkinson (1980) high-low volatility. Spread is measured by the percentage effective spreads, calculated as the ratio of effective spreads to the futures contract value. TTM is time to maturity (in days). ***, **, and * indicate significance at the 1%, 5%, and 10% levels, respectively.

FITX MTX


Model (1)

Model (2) Model (3)

Model (4)


Intercept -0.002 -1.47 0.002 1.40 -2.431 -0.35 -0.001 -0.56

Margint-1 0.031 ** 2.16 0.099 * 1.72 0.024 ** 2.12 0.248 * 1.90

Volatilityt-1 0.004 * 1.70 0.364 *** 8.26 0.062 *** 2.75 0.283 *** 5.39

Monday dummy (10-4) 1.230 0.21 1.501 0.81 -6.143 -1.27 1.612 1.47

Spreadt-1 (10-5) 1.091 * 1.73 5.563 0.71 2.309 0.42 6.744 0.70

TTM (10-4) -1.529 *** -6.12 1.525 *** 12.11 -0.363 ** -2.43 1.748 *** 10.80

VolumeTotal, t-1 (10-8) -5.921 *** -9.26 -1.486 -0.71 -6.128 * -1.67 -4.337 -1.47

Adj. R2 0.1279 0.1524 0.1332 0.1448

F-statistics 29.14*** 34.92*** 30.48*** 31.82***

55

Table 11: Regression of Pricing Errors on Margin Changes This table reports the regressions of the effects of margins on the absolute pricing error. The sample period is from January 2002 to December 2008. The pricing error is defined as the absolute difference between the actual futures price and the theoretical value from the cost-of-carry model, divided by the index value. Margin is the ratio of margins to futures contract value. Control variables include lagged absolute mispricing error, lagged Volatility, and TTM. Volatility is measured by the Parkinson (1980) high-low volatility. TTM is time to maturity (in days). ***, **, and * indicate significance at the 1%, 5%, and 10% levels, respectively.

FITX MTX


Model (1) Model (2) Model (3)

Model (4)


Intercept 0.002 0.44 0.001 0.71 0.002 0.85 0.001 0.84

Margint-1 0.002 0.19 0.011 1.12 0.007 0.24 0.009 0.70

|PEt-1| 0.491 *** 20.48 0.502 *** 20.82 0.416 *** 17.95 0.542 *** 23.40

|PEt-2| 0.274 *** 11.45 0.301 *** 12.68 0.268 *** 11.57 0.305 *** 13.19

Volatilityt-1 (10-7) 1.284 * 1.71 1.015 * 1.67 1.894 ** 2.10 0.657 0.86

TTM (10-5) 1.466 1.16 0.828 0.18 3.906 *** 3.75 5.440 1.46

Adj. R2 0.5007 0.5822 0.3993 0.6500

F-statistics 330.47*** 449.89*** 231.30*** 630.59***

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