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Journal articles on the topic 'Pricing of Securities'

Author: Grafiati

Published: 4 June 2021

Last updated: 12 February 2022

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1

Maxam, Clark L., and Jeffrey Fisher. "Pricing commercial mortgage‐backed securities." Journal of Property Investment & Finance 19, no. 6 (December 2001): 498–518. http://dx.doi.org/10.1108/14635780110406860.

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2

Duffie, Darrell, Nicolae Gârleanu, and Lasse Heje Pedersen. "Securities lending, shorting, and pricing." Journal of Financial Economics 66, no. 2-3 (November 2002): 307–39. http://dx.doi.org/10.1016/s0304-405x(02)00226-x.

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3

Hull, John, and Alan White. "Pricing Interest-Rate-Derivative Securities." Review of Financial Studies 3, no. 4 (October 1990): 573–92. http://dx.doi.org/10.1093/rfs/3.4.573.

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4

Sialm, Clemens. "Tax Changes and Asset Pricing." American Economic Review 99, no. 4 (August 1, 2009): 1356–83. http://dx.doi.org/10.1257/aer.99.4.1356.

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The tax burden on equity securities has varied substantially over time and remains a source of continuing policy debate. This paper investigates whether investors were compensated for the tax burden of equity securities over the period between 1913 and 2006. Taxes on equity securities vary over time due to changes in dividend and capital gains tax rates and due to changes in corporate payout policies. Equity taxes also vary across firms due to persistent differences in propensities to pay dividends. The results indicate an economically plausible and statistically significant tax capitalization over time and cross-sectionally. (JEL G10, G12, H22, H24, N21, N22)

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5

Su, Yi, and Michael Fu. "Optimal importance sampling in securities pricing." Journal of Computational Finance 5, no. 4 (2002): 27–50. http://dx.doi.org/10.21314/jcf.2002.081.

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6

Kao, Duen-Li. "Illiquid Securities: Pricing and Performance Measurement." Financial Analysts Journal 49, no. 2 (March 1993): 28–35. http://dx.doi.org/10.2469/faj.v49.n2.28.

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7

Chamberlain, Gary. "Asset Pricing in Multiperiod Securities Markets." Econometrica 56, no. 6 (November 1988): 1283. http://dx.doi.org/10.2307/1913098.

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8

SUN, You-fa, Cheng-ke ZHANG, Jing-guang GAO, and Fei-qi DENG. "Study of Modern Securities Pricing Model." Systems Engineering - Theory & Practice 27, no. 5 (May 2007): 1–11. http://dx.doi.org/10.1016/s1874-8651(08)60031-9.

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9

Broadie, Mark, and Paul Glasserman. "Pricing American-style securities using simulation." Journal of Economic Dynamics and Control 21, no. 8-9 (June 1997): 1323–52. http://dx.doi.org/10.1016/s0165-1889(97)00029-8.

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10

Lamoureux, Christopher G., and James W. Wansley. "The Pricing of When-Issued Securities." Financial Review 24, no. 2 (May 1989): 183–98. http://dx.doi.org/10.1111/j.1540-6288.1989.tb00338.x.

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11

Musiela, Marek. "General framework for pricing derivative securities." Stochastic Processes and their Applications 55, no. 2 (February 1995): 227–51. http://dx.doi.org/10.1016/0304-4149(94)00045-u.

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12

Guo, Jiequn. "Fair Value Adjusted Pricing of Mutual Funds Using Treasury Futures." Journal of International Commerce, Economics and Policy 09, no. 01n02 (February 2018): 1850006. http://dx.doi.org/10.1142/s1793993318500060.

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The U.S. Investment Company Act of 1940 requires mutual fund boards to determine fair value of their portfolios. With mutual fund investments on foreign securities, there is a potential market timing issue when markets evolve between foreign and domestic market close. However, there is little research to date relating to fair value pricing procedures for foreign fixed-income securities. In this paper, we discuss the market timing problems and present a statistical approach utilizing treasury futures to fair value pricing of foreign fixed income securities. Timely valuation adjustment of foreign fixed income securities is the best approach to fend off arbitrageurs than raising transaction fees or setting minimum holding period for mutual funds.

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13

Manola, Ana, and Branko Urosevic. "Option-based valuation of mortgage-backed securities." Ekonomski anali 55, no. 186 (2010): 42–66. http://dx.doi.org/10.2298/eka1086042m.

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Pure econometric approaches to pricing mortgage-backed securities (MBSs) - principal pricing vehicles used by financial practitioners - fail to capture their true risks. This point was powerfully driven home by the global financial crisis. Since prior to the crisis default rates of MBSs were quite modest, econometric pricing models systematically underestimated the possibility of default. As a result, MBSs were severely overvalued. It is widely believed that the global crisis was largely triggered by incorrect valuation of mortgage-backed securities. In the aftermath, it is important to revisit the foundations for pricing MBSs and to pay much closer attention to default risk. This paper introduces a comprehensive model for valuation of fixed-rate pass-through mortgagebacked securities in a simple option-based framework. In the model, we use bivariate binomial tree approach to simultaneously model prepayment and default options. Our simulation results demonstrate that the proposed model has sufficient flexibility to capture the two principal risks.

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14

BRANGER, NICOLE. "PRICING DERIVATIVE SECURITIES USING CROSS-ENTROPY: AN ECONOMIC ANALYSIS." International Journal of Theoretical and Applied Finance 07, no. 01 (February 2004): 63–81. http://dx.doi.org/10.1142/s0219024904002335.

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This paper analyses two implied methods to determine the pricing function for derivatives when the market is incomplete. First, we consider the choice of an equivalent martingale measure with minimal cross-entropy relative to a given benchmark measure. We show that the choice of the numeraire has an impact on the resulting pricing function, but that there is no sound economic answer to the question which numeraire to choose. The ad-hoc choice of the numeraire introduces an element of arbitrariness into the pricing function, thus contradicting the motivation of this method as the least prejudiced way to choose the pricing operator. Second, we propose two new methods to select a pricing function: the choice of the stochastic discount factor (SDF) with minimal extended cross-entropy relative to a given benchmark SDF, and the choice of the Arrow–Debreu (AD) prices with minimal extended cross-entropy relative to some set of benchmark AD prices. We show that these two methods are equivalent in that they generate identical pricing functions. They avoid the dependence on the numeraire and replace it by the dependence on the benchmark pricing function. This benchmark pricing function, however, can be chosen based on economic considerations, in contrast to the arbitrary choice of the numeraire.

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15

WU, SEN, LISHANG JIANG, and JIN LIANG. "INTENSITY-BASED MODELS FOR PRICING MORTGAGE-BACKED SECURITIES WITH REPAYMENT RISK UNDER A CIR PROCESS." International Journal of Theoretical and Applied Finance 15, no. 03 (May 2012): 1250021. http://dx.doi.org/10.1142/s0219024912500215.

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Under a reduced-form framework, we establish models for pricing mortgage-backed securities with prepayment risk by introducing a stochastic prepayment factor. In the zero-default scenario, the pricing pass-through securities and sequential-pay collateralized mortgage obligation structures are considered. To solve the problems, we introduce a path-dependent variable, from which partial differential equation problems are obtained when the prepayment rate is modeled by a CIR process. Numerical solution to the pricing problem is obtained by developing an explicit characteristics difference scheme.

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16

Boyarchenko, Nina, Andreas Fuster, and David O. Lucca. "Understanding Mortgage Spreads." Review of Financial Studies 32, no. 10 (February 8, 2019): 3799–850. http://dx.doi.org/10.1093/rfs/hhz004.

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Abstract Because most mortgages in the United States are securitized in agency mortgage-backed securities (MBS), yield spreads on MBS are a key determinant of homeowners’ funding costs. We study variation in MBS spreads in the time series and across securities and document that MBS spreads show a pronounced cross-sectional smile with respect to the securities’ coupon rates. We present a new pricing model that uses “stripped” MBS prices to identify the contribution of non-interest-rate prepayment risk to spreads and find that this risk explains the smile, whereas the time-series spread variation is mostly accounted for by nonprepayment risk factors. Received March 30, 2015; editorial decision November 21, 2018 by Editor Leonid Kogan. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

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17

Pitts, Mark. "The pricing of options on debt securities." Journal of Portfolio Management 11, no. 2 (January 31, 1985): 41–50. http://dx.doi.org/10.3905/jpm.1985.409001.

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18

French, Dan W., Bernard Dumas, and Blaise Allaz. "Financial Securities: Market Equilibrium and Pricing Methods." Journal of Finance 51, no. 4 (September 1996): 1565. http://dx.doi.org/10.2307/2329409.

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19

Frey, Rüdiger, and Thorsten Schmidt. "PRICING CORPORATE SECURITIES UNDER NOISY ASSET INFORMATION." Mathematical Finance 19, no. 3 (July 2009): 403–21. http://dx.doi.org/10.1111/j.1467-9965.2009.00374.x.

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20

Ait-Sahalia, Yacine. "Nonparametric Pricing of Interest Rate Derivative Securities." Econometrica 64, no. 3 (May 1996): 527. http://dx.doi.org/10.2307/2171860.

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21

Deng, Yinglu, Patrick L. Brockett, and Richard D. MacMinn. "Longevity/Mortality Risk Modeling and Securities Pricing." Journal of Risk and Insurance 79, no. 3 (February 8, 2012): 697–721. http://dx.doi.org/10.1111/j.1539-6975.2011.01450.x.

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22

Lin, Yijia, Sheen Liu, and Jifeng Yu. "Pricing Mortality Securities With Correlated Mortality Indexes." Journal of Risk and Insurance 80, no. 4 (July 20, 2012): 921–48. http://dx.doi.org/10.1111/j.1539-6975.2012.01481.x.

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23

Feng, Jianfen, Dianfa Chen, and Mei Yu. "Pricing Defaultable Securities under Actual Probability Measure." Journal of Systems Science and Information 2, no. 4 (August 25, 2014): 313–34. http://dx.doi.org/10.1515/jssi-2014-0313.

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AbstractIn this paper, a new approach is developed to estimate the value of defaultable securities under the actual probability measure. This model gives the price framework by means of the method of backward stochastic differential equation. Such a method solves some problems in most of existing literatures with respect to pricing the credit risk and relaxes certain market limitations. We provide the price of defaultable securities in discrete time and in continuous time respectively, which is favorable to practice to manage real credit risk for finance institutes.

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24

Bardhan, Indrajit, and Xiulu Chao. "Pricing options on securities with discontinuous returns." Stochastic Processes and their Applications 48, no. 1 (October 1993): 123–37. http://dx.doi.org/10.1016/0304-4149(93)90110-p.

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25

Bauer, Daniel, Matthias Börger, and Jochen Ruß. "On the pricing of longevity-linked securities." Insurance: Mathematics and Economics 46, no. 1 (February 2010): 139–49. http://dx.doi.org/10.1016/j.insmatheco.2009.06.005.

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26

Burtnyak, Ivan, and Anna Malytska. "Taylor expansion for derivative securities pricing as a precondition for strategic market decisions." Problems and Perspectives in Management 16, no. 1 (March 13, 2018): 224–31. http://dx.doi.org/10.21511/ppm.16(1).2018.22.

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The strategy of managing the pricing processes, in particular managing the dynamics of the price of the underlying asset and its volatility, the prices of indices, shares, options, the magnitude of financial flows, in the method of calculating the company’s rating based on the available quotations of securities, is developed. The article deals with the study of pricing and calculating the volatility of European options with general local-stochastic volatility, applying Taylor series methods for degenerate diffusion processes. The application of this idea requires new approaches caused by degradation difficulties. Price approximation is obtained by solving the Cauchy problem of partial differential equations diffusion with inertia, and the volatility approximation is completely explicit, that is, it does not require special functions. If the payoff of options is a function of only x, then the Taylor series expansion does not depend on t and an analytical expression of the fundamental solution is considerably simplified. Applied an approach to the pricing of derivative securities on the basis of classical Taylor series expansion, when the stochastic process is described by the diffusion equation with inertia (degenerate parabolic equation). Thus, the approximate value of options can be calculated as effectively as the Black-Scholes pricing of derivative securities. On the basis of the solved problem, it is possible to calculate their turns step-by-step. This enables to predict the dynamics of the pricing of derivatives and to create a strategy of behavior at options according to the passage of the process. For each approximation, price volatility is calculated, which makes it possible to take into account all changes in the market and to calculate possible situations. The step-by-step finding of the change in yield and volatility in the relevant analysis enables us to make informed strategic decisions by traders in the financial markets.

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27

Platen, Eckhard, and Rolando Rebolledo. "Pricing via anticipative stochastic calculus." Advances in Applied Probability 26, no. 04 (December 1994): 1006–21. http://dx.doi.org/10.1017/s0001867800026732.

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The paper proposes a general model for pricing of derivative securities. The underlying dynamics follows stochastic equations involving anticipative stochastic integrals. These equations are solved explicitly and structural properties of solutions are studied.

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28

Platen, Eckhard, and Rolando Rebolledo. "Pricing via anticipative stochastic calculus." Advances in Applied Probability 26, no. 4 (December 1994): 1006–21. http://dx.doi.org/10.2307/1427902.

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The paper proposes a general model for pricing of derivative securities. The underlying dynamics follows stochastic equations involving anticipative stochastic integrals. These equations are solved explicitly and structural properties of solutions are studied.

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29

Zeddouk, Fadoua, and Pierre Devolder. "Pricing of Longevity Derivatives and Cost of Capital." Risks 7, no. 2 (April 15, 2019): 41. http://dx.doi.org/10.3390/risks7020041.

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Annuities providers become more and more exposed to longevity risk due to the increase in life expectancy. To hedge this risk, new longevity derivatives have been proposed (longevity bonds, q-forwards, S-swaps…). Although academic researchers, policy makers and practitioners have talked about it for years, longevity-linked securities are not widely traded in financial markets, due in particular to the pricing difficulty. In this paper, we compare different existing pricing methods and propose a Cost of Capital approach. Our method is designed to be more consistent with Solvency II requirement (longevity risk assessment is based on a one year time horizon). The price of longevity risk is determined for a S-forward and a S-swap but can be used to price other longevity-linked securities. We also compare this Cost of capital method with some classical pricing approaches. The Hull and White and CIR extended models are used to represent the evolution of mortality over time. We use data for Belgian population to derive prices for the proposed longevity linked securities based on the different methods.

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30

Kiesel, Rüdiger. "Nonparametric statistical methods and the pricing of derivative securities." Journal of Applied Mathematics and Decision Sciences 6, no. 1 (January 1, 2002): 1–22. http://dx.doi.org/10.1155/s1173912602000019.

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In this review paper we summarise several nonparametric methods recently applied to the pricing of financial options. After a short introduction to martingale-based option pricing theory, we focus on two possible fields of application for nonparametric methods: the estimation of risk-neutral probabilities and the estimation of the dynamics of the underlying instruments in order to construct an internally consistent model.

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31

Ji, Hongdan. "Does the Underwriter Reputation Affect the Pricing of Local Government Bonds in China?" International Business Research 13, no. 7 (June 4, 2020): 45. http://dx.doi.org/10.5539/ibr.v13n7p45.

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As the product of the combination of fiscal and financial, local government bonds should also follow the pricing mechanism of the securities market even under the special financial system in China. This paper uses Heckman's two-stage model to investigate whether the mechanism of underwriter reputation affects the pricing of local government bonds. The empirical results show that local governments tend to choose securities company underwriters with high reputation when they issue bonds with large scale, long maturity, and call right which have high degree of information asymmetry, and this tendency has an obvious time trend. However, high-reputation securities company underwriters failed to play the role of information intermediary to reduce the cost of local governments. On the contrary, implicit guarantees and government interventions induced the commercial banks to depress their quotations even leading to “interest rate upside down”, which resulted in the lack of securities company underwriters. In order to play the mechanism of underwriter reputation to promote the marketization of local government bonds pricing, this paper proposes to eliminate government interference, guide underwriters to strengthen the construction of their reputation, promote the marketization of underwriting fees and strengthen the supervision of underwriters.

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32

Gonçalves, Franklin De O., and Luiz Otavio Calôba. "A dinâmica do spread ajustado por opções dos Brady bonds." Brazilian Review of Finance 1, no. 1 (April 1, 2003): 89. http://dx.doi.org/10.12660/rbfin.v1n1.2003.1126.

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Brady bond securities represent a substantial fraction of emerging markets countries internationally tradable sovereign debt. The credit risk spread above and beyond the U.S. treasury curve for these securities is usually large in size and volatility. Moreover, most Brady bonds carry embedded options that lead to the existence of an Option-Adjusted Spread, OAS, which increase their risk profiles. In this paper we present an empirical study of the dynamics of Brady bonds OAS using a heath, Jarrow and Morton term structure pricing model. The dynamics of the spread shows that the proper risk management and pricing of these securities require the consideration of volatility in addition to the magnitude of the sovereign risk spread. That is, the proper risk measure for these securities would be the pair (OAS, OAS Volatility). A study of implied default probabilities is also presented. Our analysis is illustrated with bonds from Brazil, Argentina, Mexico, Poland, Bulgaria and the Philippines.

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33

Chao, Yong, Chen Yao, and Mao Ye. "Discrete Pricing and Market Fragmentation: A Tale of Two-Sided Markets." American Economic Review 107, no. 5 (May 1, 2017): 196–99. http://dx.doi.org/10.1257/aer.p20171046.

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Security trading now fragments into more than ten almost identical stock exchanges in the United States. We show that discrete pricing is one economic force that prevents the consolidation of trading volume. The uniform one-cent tick size (minimum price variation), imposed by the SEC's Rule 612, leads to more dispersed trading for lower priced securities. When a security reverse splits, its price increases and relative tick size (one cent divided by the price) decreases. We find that reverse splits consolidate trading of securities, using securities with identical underlying fundamentals that do not reverse split as the control group.

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34

Childs, Paul D., Steven H. Ott, and Timothy J. Riddiough. "The Pricing of Multiclass Commercial Mortgage-Backed Securities." Journal of Financial and Quantitative Analysis 31, no. 4 (December 1996): 581. http://dx.doi.org/10.2307/2331361.

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35

Peake, Charles F. "The Pricing of Multiclass Commercial Mortgage-Backed Securities." CFA Digest 27, no. 3 (August 1997): 25–27. http://dx.doi.org/10.2469/dig.v27.n3.109.

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36

Ökten, Giray, and Warren Eastman. "Randomized quasi-Monte Carlo methods in pricing securities." Journal of Economic Dynamics and Control 28, no. 12 (December 2004): 2399–426. http://dx.doi.org/10.1016/j.jedc.2003.11.003.

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37

Jarrow, Robert A., and Fan Yu. "Counterparty Risk and the Pricing of Defaultable Securities." Journal of Finance 56, no. 5 (October 2001): 1765–99. http://dx.doi.org/10.1111/0022-1082.00389.

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38

Kau, James B., Donald C. Keenan, Walter J. Muller, and James F. Epperson. "Pricing commercial mortgages and their mortgage-backed securities." Journal of Real Estate Finance and Economics 3, no. 4 (December 1990): 333–56. http://dx.doi.org/10.1007/bf00178857.

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39

Tsai, Jerry, and Jessica A. Wachter. "Pricing long-lived securities in dynamic endowment economies." Journal of Economic Theory 177 (September 2018): 848–78. http://dx.doi.org/10.1016/j.jet.2018.07.008.

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40

Nielsen, Lars Tyge. "Dividends in the theory of derivative securities pricing." Economic Theory 31, no. 3 (March 9, 2007): 447–71. http://dx.doi.org/10.1007/s00199-006-0106-6.

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41

Tsai, Jeffrey T., and Larry Y. Tzeng. "THE PRICING OF MORTALITY-LINKED CONTINGENT CLAIMS: AN EQUILIBRIUM APPROACH." ASTIN Bulletin 43, no. 2 (May 2013): 97–121. http://dx.doi.org/10.1017/asb.2013.3.

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AbstractThis study introduces an equilibrium approach to price mortality-linked securities in a discrete time economy, assuming that the mortality rate has a transformed normal distribution. This pricing method complements current studies on the valuation of mortality-linked securities, which only have discrete trading opportunities and insufficient market trading data. Like the Wang transform, the valuation relationship is still risk-neutral (preference-free) and the mortality-linked security is priced as the expected value of its terminal payoff, discounted by the risk-free rate. This study provides an example of pricing the Swiss Re mortality bond issued in 2003 and obtains an approximated closed-form solution.

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42

Sun, Chen Yin. "The Impact of Margin and Short Selling on Stock Pricing Efficiency – Based on the Growth Enterprise Market and the Science and Technology Innovation Board." E3S Web of Conferences 292 (2021): 02051. http://dx.doi.org/10.1051/e3sconf/202129202051.

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This paper takes the margin and short selling targets of the science and technology innovation board and the growth enterprise board of China’s stock market as the research object, and selects the sample interval from July 2019 to November 2020, Uses the unbalanced data panel model, discusses the effect of short selling and margin trading on the pricing efficiency of stock from the perspectives of the reaction speed and information content of stock information. The results show that margin trading is generally beneficial to the improvement of the pricing efficiency of the stock market; the effect of margin trading and short selling on the improvement of pricing efficiency of different stocks is different. The imbalance of power between margin trading and margin trading has a negative impact on the pricing efficiency of the stock market. The conclusion is helpful for subsequent scholars to continue to study the development level of the securities market and provide suggestions for the development direction of China’s securities market.

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43

Janata, Georgas. "Validity of the Capital Asset Pricing Model (CAPM) for Securities Trading at the Nairobi Securities Exchange (NSE)." Business and Management Research 5, no. 4 (December 19, 2016): 62. http://dx.doi.org/10.5430/bmr.v5n4p62.

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This research undertakes an empirical analysis of the validity of the Capital Asset Pricing Model (CAPM) for securities trading at the Nairobi Securities Exchange (NSE). Based on the critical conditions of the CAPM model, the specific objectives of the research were: to evaluate the level of systematic risks for firms listed on the NSE, to evaluate the rate of return for individual stocks listed on the NSE, to evaluate the rate of return for the NSE, to analyze the relationship between systematic risk and expected returns for firms listed on the NSE, and to evaluate the value of the intercept term for firms listed on the NSE. Fama & Macbeth’s two-pass regression method is applied to a sample of eighteen firms trading at the NSE, with the most recent data (May 2013 –May 2016) being used. By virtue of finding a beta value that is statistically different from zero, the study concludes that the CAPM is not a valid model for explaining risk-return relationships at the NSE. Other critical conditions which the findings violate include: the hypothesized linear risk-return relationship, and the hypothesized zero value for the intercept. Some of the failures of the CAPM are attributed to its theoretical failings, and specifically, its many unrealistic and simplifying assumptions. Although this study addresses the methodological weaknesses of prior studies by basing analysis on portfolios rather than individual stocks (thus correcting measurement error problems) and carrying out month-by-month cross-section regression (thus correcting residual errors); the methodology adopted still fails to account for anomalies in asset pricing. Therefore, in addition to recommending that future studies adopt methodologies that account for pricing anomalies, this study also recommends that future studies consider expanding the number of firms to study as well as the period of study. This can help to generate more observations, and therefore, better data fit.

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44

Murphy, J. Austin. "An empirical test of an option pricing model of mortgage-backed securities pricing." Journal of Economics and Business 43, no. 1 (February 1991): 37–47. http://dx.doi.org/10.1016/0148-6195(91)90004-g.

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45

Tripathi, Gireesh Chandra. "Prepayment Risk Modeling for Residential Mortgage Backed Securities." International Journal of Information Systems in the Service Sector 4, no. 2 (April 2012): 72–86. http://dx.doi.org/10.4018/jisss.2012040105.

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The first public issue of securitized instruments is overdue in Indian capital market (SEBA 2008). Development of suitable pricing models would be helpful in trading of these instruments. This paper is focused on prepayment risk of housing loan pools. Prepayment estimation is useful to project the cash-flows, which are essential for pricing. A few prevalent models and their variations are tested and suitably adjusted to make them readily applicable on the Indian data. It is found that the prepayment can best be explained by an adjusted Chinloy model with contracted rate (and not the current rate), age of the mortgage and burnout. This behavior is unique because the current rate does not have any bearing on the prepayments in India.

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46

R. Anderson, Scott. "New MSRB fair-pricing rule effective July 7, 2014." Journal of Investment Compliance 15, no. 3 (August 26, 2014): 47–50. http://dx.doi.org/10.1108/joic-08-2014-0032.

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Purpose – To summarize revised MSRB Rule G-30, which governs municipal bond dealer fair-pricing obligations. Design/methodology/approach – Discusses background of previous MSRB fair-pricing rules and interpretive guidance. Outlines the basic dealer obligations arising under revised MSRB Rule G-30. Discusses three key aspects of the new rule and recent rulemaking effort: the obligation of dealers to exercise “diligence” in assessing a municipal security’s market value and reasonableness of compensation, the distinction between fair security pricing and reasonable dealer compensation, and previous MSRB guidance that is superseded by the rule change. Also discusses similar rule changes related to fair-pricing, mark-ups, markdowns and commissions that have been proposed by FINRA that would apply to non-municipal securities if adopted. Findings – Revised MSRB Rule G-30 generally preserves existing municipal bond fair-pricing obligations while consolidating obligations that previously existed in multiple MSRB rules and interpretive guidance. Practical implications – The MSRB generally sought to preserve the substance of existing dealer fair-pricing obligations in revised MSRB Rule G-30 but dealers should evaluate their existing compliance frameworks in light of the recent revisions. The recent changes include deletion of prior MSRB Rule G-18 and superseding of certain interpretive guidance. Originality/value – Practical explanation by experienced financial services lawyer.

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47

Blouin, Jennifer, Luzi Hail, and Michelle H. Yetman. "Capital Gains Taxes, Pricing Spreads, and Arbitrage: Evidence from Cross-Listed Firms in the U.S." Accounting Review 84, no. 5 (September 1, 2009): 1321–61. http://dx.doi.org/10.2308/accr.2009.84.5.1321.

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ABSTRACT: We examine how shareholder-level taxes affect the contemporaneous pricing of foreign firms' U.S. cross-listed and underlying home-country securities surrounding the 1997 reduction in U.S. capital gains tax rates. Consistent with tax capitalization, we find that the performance of cross-listed shares is negatively related to dividend yield, suggesting an abnormal price increase for shares with greater anticipated taxable capital gains. Due to barriers to cross-border arbitrage, underlying home-country securities, on average, do not react during the event, creating a temporary tax-induced pricing spread. When costs of arbitrage are low, the pricing disparity quickly dissipates and home-country shares closely mirror the pricing of their cross-listed counterparts. In further tests, we are unable to document lock-in behavior, which predicates a decrease in prices attributable to a surge in volume for shares with greater accrued taxable capital gains. Overall, our findings suggest that an exogenous shock to the U.S. tax regime reverberates in international asset prices, thereby affecting foreign firms' costs of capital.

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Mi, Yanhui. "Asset pricing under general collateralization." International Journal of Financial Engineering 04, no. 02n03 (June 2017): 1750019. http://dx.doi.org/10.1142/s2424786317500190.

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We consider the valuation of collateralized derivative contracts such as bond option or Caplet contracts. We allow for posting different collaterals such as securities or cash for the derivatives and its hedges. The pricing is based on modeling the joint evolution of collateral rate and the spread between collaterals. The Hull–White models are applied to collateral rate and spread to generate the closed pricing formula for zero coupon bond option. We also derive the pricing formula for Caplet under the Libor Market model and SABR model framework.

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Cagan, Leigh D., Nicholas J. Carriero, and Stavros A. Zenios. "A Computer Network Approach to Pricing Mortgage-Backed Securities." Financial Analysts Journal 49, no. 2 (March 1993): 55–62. http://dx.doi.org/10.2469/faj.v49.n2.55.

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Hughston, Lane P., and Andrea Macrina. "Pricing Fixed-Income Securities in an Information-Based Framework." Applied Mathematical Finance 19, no. 4 (September 2012): 361–79. http://dx.doi.org/10.1080/1350486x.2011.631757.

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