The extant literature in financial research proposes various factors that affect the market microstructure of traded assets. This empirical study examines the impact of a factor that has not been analyzed previously, the asset characteristics of traded securities. When asset characteristics are dominated by debt (fixed claim) features, theory suggests that firm-specific private information has a smaller impact on prices. This would imply a less severe adverse selection problem, which, in turn, implies a lower level of transactions costs due to information asymmetry. On the other hand, if asset characteristics are dominated by equity (residual claim) features, theory suggests more reliance on private information, a more severe adverse selection problem and a correspondingly higher transactions cost due to information asymmetry.
Preferred stocks represent a combination of a fixed claim and a pure residual claim. Therefore, their cross-sectional analysis offers an excellent opportunity to investigate whether asset characteristics are reflected in market microstructure parameters. Two additional factors, however, must be considered when analyzing the market microstructure of preferred stocks. First, preferred stocks, in general, trade considerably less frequently than their corresponding common stocks, which, in turn, implies that the relative amount of liquidity trading is lower in preferreds. Second, the price of common stocks often leads that of convertible preferred and this has an impact on the information dissemination process for these preferreds.
The main result in the dissertation is that asset characteristics affect microstructure parameters. In particular, the higher the equity dominance in straight preferred stock, the lower the public information induced volatility and the higher the
information asymmetry induced transactions cost and the adverse selection component of the effective spread. Such relationship is not detected in the case of convertible preferred stock. This is attributed to the existence of a lead-lag
relationship between this security and its underlying common stock. Furthermore, the results from both the cross-sectional analyses and the comparisons between the group of common and preferred stocks are consistent with the hypothesis that infrequent trading has an impact on adverse selection. Specifically, infrequently traded assets are found to display a more severe adverse selection problem.
Although this study is limited to preferred stocks only, the findings can be indicative of the microstructure characteristics of the market for other securities that have fixed-income characteristics. Further investigation of the market microstructure and information dissemination process of debt-type securities can be a next step in that direction.
Figure 1. Basic Corporate Securities as Options
Figure 2. Straight Preferred Stock as Option
Figure 3. Convertible Preferred Stock as Option
Debt Common Stock
Firm Value Payoff
Debt Common Stock
Firm Value Payoff
Straight Pfd Stock
Debt
Common Stock
Firm Value Payoff
Convertible Pfd Stock
Table 1
Summary characteristics of preferred stocks
The percentage values in parenthesis indicate the relative frequency of the particular feature of the 310 preferred stocks issued by 185 firms in the sample.
Equity-like features Debt-like features
• Represents ownership • Generally, no voting rights (82%)
• Infinite investment horizon • Optional sinking fund provisions
• Convertibility provision (42%) • Exchangeability provision (7%)
• Distribution to holders is not
contractually obligated (omission is not ground for bankruptcy)
• ‘Indicated’ dividend: fixed, adjusted or reset (fixed: 88%)
• Dividend is cumulative (97%)
• Distribution in liquidation: only after debtholders and other creditors
• Distribution in liquidation: before common stockholders
• Dividend is not tax-deductible for the issuer
• 80% of dividend is tax-deductible for corporations and institutional
investors
• Fixed ‘cost’
Table 2
Predictions of the various hypotheses about the market microstructure of preferred stocks
Column 1 contains the various groups; Columns 2 through 4 present the three microstructure characteristics the study focuses on. The terms in parenthesis refer to the hypotheses that have the particular prediction. ASSET CHAR.: Hypothesis considering the effect of asset characteristics. LEAD-LAG: Hypotheses based on the argument that common stock prices lead that of preferred stock. LIQUIDITY:
Hypothesis that considers the effect of infrequent trading on adverse selection.
Abbreviations: PFD - Preferred Stock; SPS - Straight Preferred Stock; CPS - Convertible Preferred Stock; CMN - Common Stock.
Panel A: Between Group Analyses Price Reflects
Straight
(a) In this framework, market depth refers to the sensitivity of quotes to the trade flow. The market is deep, or λ is small, if large order flows induce small quote revisions by the market maker.
Table 2 (continued)
Predictions of the various hypotheses about the market microstructure of preferred stocks
Abbreviations: PFD - Preferred Stock; SPS - Straight Preferred Stock; CPS - Convertible Preferred Stock; CMN - Common Stock.
Panel B: Within Group Analyses Price Reflects (b) These relationships are predicted only for firms of medium and high quality
Table 3
Industry Distribution of Sample Firms
The distribution of industry classifications of the 185 firms having preferred stock in the sample, as defined by the NYSE. The sample period is October 1, 1993 - September 30, 1994.
INDUSTRIALS 81
Aerospace 1
Business Supplies and Services 4
Chemicals 2
Computers, Data Processing 6
Construction 4
Electronics 2
Environmental Control 1
Food, Beverages 2
Health Care Services 1
Household Goods 1
Lodging, Restaurants 1
Mining, Refining, Fabricating 12
Oil and Gas 13
Packaging 2
Paper Production 3
Pharmaceuticals 3
Recreation Services 1
Retail Trade 5
Textiles, Apparel 1
Tires, Rubber 1
Tobacco 1
Wholesalers, Distribution 3
Multi-industry 11
TRANSPORTATION 5
Air 2
Rail 2
Other Transportation 1
UTILITIES 36
Electric Services 20
Gas Services 7
Telecommunications 3
Water Supply Companies 1
Multi-service Companies 5
FINANCE, REAL ESTATE 63
Banks 28
Brokerage Services 2
Closed-End Investment Companies 5
Finance Companies 2
Insurance 11
Trusts 6
Real Estate 3
Diversified Financial Companies 6
Table 4
Size and Financing of Sample Firms
Size, long term financing and fraction of preferred stock of firms in the sample (as of December 31, 1993). Total Long Term Financing is defined as the sum of market value of common stock, book value of preferred stock(s) and book value of long term debt. Percentage of Preferred Financing is the fraction of preferred stocks (book value) as a percentage of total long term financing.
Panel A: Firms in the Sample
Market Value
Panel A: CRSP’s NYSE Population as of December 31, 1993 Market Value
Table 5
Trading Characteristics of Sample Stocks
Trading characteristics of 310 preferred and 185 corresponding common stocks;
October 1, 1993 - September 30, 1994. The reported means, standard deviations and percentiles are statistics of the individual means.
Panel A: Average Number of Daily Trades Straight Preferred
Panel B: Average Daily Volume (Round lots) Straight Preferred
Panel C: Average Daily Dollar Volume (in thousands) Straight Preferred
Table 6
Non-trading and Trading Volatility Ratios
Medians of non-trading to trading volatility ratios based on the method suggested by Jones, Kaul and Lipson (1994). The weekend and weekday volatility ratios are defined as non-trading and trading Mondays and non-trading and trading Tuesdays through Fridays, respectively. The process first estimates the residuals of regression
Rit ikDkt ilRi t l ihRm t h it
where Dkt, and Rm(t-l) denote the day-of-the-week dummies and market returns (as proxied by CRSP’s
value weighted index returns), respectively. The squared residual estimates then are conditioned on the four dummy variables representing the various trading day types
ε$it2 =σiNTM2 DNTM + σiTM2 DTM + σiNTTF2 DNTF +σiTTF2 DTTF +νit
The individual ratios are estimated for two 6-month periods between October 1, 1993 and September 30,1994. Only those securities are considered that didn’t trade on at least one Monday and Tuesday-Friday during a particular half-year period. ITM in the cross-sectional analysis is the moneyness measure (conversion value divided by current price).
Panel A: Convertible versus Straight Preferred Stocks
Straight preferred
Tuesday-Friday 0.222 0.288 1.88
(0.0604)
Table 6 (continued)
Non-trading and Trading Volatility Ratios
Cross-sectional analysis of the volatility ratios within the two groups of preferred stocks. The quarterly observations of the two groups are ranked by their relevant firm quality proxy and three sub-groups of equal size are formed with low, medium and high proxy values. The proxies are the quarterly dividend yield and moneyness (ITM) variables for straight and convertible preferred stocks, respectively. The dividend yield variable is calculated based on the perpetuity formula
Yield div
t P
s p t
=
where divsp is the (time invariant) perpetual payment and Pt is the stock price. The variable ITM is the ratio of the conversion value (i.e. conversion ratio times common stock price) and the preferred stock price. The prices are those prevailing at half-year midpoints. The reported values are the median volatility ratios in each subgroup.
Panel B: Cross-section of Straight Preferred Stocks High yield
Panel C: Cross-section of Convertible Preferred Stocks Low ITM
Table 7
Estimates of the Inverted Market Depth Parameter
Descriptive statistics of estimates of the inverted market depth parameter (Kyle’s λ) and fixed transaction costs, ψ. Individual parameters are estimated for the four quarters between October 1, 1993 and September 30, 1994. The reported parameters are based on OLS estimates of the regression
∆Pt = α + λ (SVOLt) + ψ (Dt - Dt-1) + εt
where independent variables ∆Pt, SVOLt and Dt are the transaction price change, the signed volume and the direction of the trade, respectively. The direction of trade is determined by the method suggested by Lee and Ready (1991). Coefficients λ and ψ are the inverted depth and the fixed transaction cost parameters, respectively. The inverted market depth parameter is standardized by the mid-quarter stock price and multiplied by 1,000. Negative estimates and estimates based on less than 180 observations per quarter are discarded.
(a) All reported means are statistically significantly different from zero at the 1% level.
Panel A: Descriptive Statistics
Straight preferred stock Convertible preferred stock Preferred
Panel B: t-tests on Equality of Means (t-scores and associated p-values) Straight
preferred vs.
Common stock
Convertible preferred vs.
Common stock
Straight vs. Conv.
preferred stock
1 0 0 0, × λ
P r i c e 12.40
(0.0001)
7.27 (0.0001)
7.21 (0.0001)
100 × ψ 16.57
(0.0001)
14.45 (0.0001)
-3.405 (0.0025)
Table 8
Regression Analysis of the Inverted Market Depth Parameter
Cross-sectional regression analysis of the inverted market depth parameter level, λ, and change, ∆λ. For straight preferred stocks, the following regression equations are estimated by OLS
λp = α + β (YIELD) + γ λc + δ (TRDVOLp) + ε
∆λp = α’ + β’ (∆YIELD) + γ’ ∆λc + δ’ (TRDVOLp) + ε’
while in the case of convertible preferred stocks, the regression equations are λp = a + b (ITM) + c λc + d (TRDVOLp) + η
∆λp = a’ + b’ (∆ITM) + c’ ∆λc + d’ (TRDVOLp) + η’
The independent variables YIELD, ITM, λc, and TRDVOL are the quarterly yield of the preferred stock, the moneyness measure (the ratio of the conversion value and the current preferred stock price), the inverted market depth parameter for the underlying common stock and the trading volume measured as the number of trades in the quarter (in thousands), respectively. Changes are calculated by differentiating quarterly numbers that are 6 months apart. The numbers in parenthesis are p-values. N is the number of quarterly observations.
Straight preferred stock Convertible preferred stock Independent
Table 9
Cross-sectional Analysis of the Adverse Selection Spread Component Cross-sectional analysis of the estimated information asymmetry component of the average quoted spread. Preferred stocks are assigned into three portfolios based on yield (YIELD) or moneyness (ITM). For each portfolio, the following regression equations are estimated by OLS
GKNSpi = αc + βc AVGQSpi + εpi
GKNSci = αc+ βc AVGQSci + εci
where GKNSp and GKNSc are the quarterly effective spread estimates for preferred and common stocks, respectively, calculated according to George, Kaul and Nimalendran (1991). AVGQSp and AVGQSc are the average quoted spreads for preferred and common stocks in each quarter. The numbers in parentheses are p-values. 1-π is the estimate of the information asymmetry induced spread component. The numbers in parenthesis are p-values. N is the number of quarterly observations in each portfolio.
Panel A: Straight Preferred and Corresponding Common Stocks Straight Preferred Stock
Table 9 (continued)
Cross-sectional Analysis of the Adverse Selection Spread Component Panel A: Straight Preferred and Corresponding Common Stocks (continued)
Corresponding Common Stock
Panel B: Convertible Preferred and Corresponding Common Stocks Convertible Preferred Stock
Table 9 (continued)
Cross-sectional Analysis of the Adverse Selection Spread Component Panel B: Convertible Preferred and Corresponding Common Stocks (continued)
Corresponding Common Stock N
Intercept AVGQSc
Adjusted R2 1-π
100 0.0019 (0.0001)
0.2382 (0.0001)
56.49%
0.7618 (0.0001)
97 0.0016 (0.0001)
0.2531 (0.0001)
57.38%
0.7967 (0.0001)
97 0.0001 (0.8869)
0.3853 (0.0001)
65.74%
0.6174 (0.0001)
Table 9 (continued)
Cross-sectional Analysis of the Adverse Selection Spread Component For the portfolio of straight and convertible preferred stocks, the following regression equations are estimated by OLS
GKNSpi = αp + βp (AVGQSpi) + γp (YIELDGRPpi×AVGQSpi) + δp (YIELDGRPpi) + εpi
GKNSpi = αp’ + βp’ (AVGQSpi) + γp’ (ITMGRPpi×AVGQSpi) + δp’ (ITMGRpi) + ε’pi
where ITMGRP and YIELDGRP take the value of 0, 1 or 2 depending whether the preferred stock falls into the low, medium or high group, respectively. The numbers in parenthesis are p-values.
Panel C: Pooled Regression Analysis of Straight and Convertible Preferred Stocks
Straight Preferred
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