Quantal International

Research

Recent Research Papers by Quantal Personnel (chronological order):

"Analysis of the 2008-2009 Financial Crisis”
Terry Marsh and Paul Pfleiderer
Working Paper, November 2009
In this Preface, we offer some analysis of the 2008-2009 financial crisis and its implications for financial industry reform and research. We primarily focus on issues relating to transparency and the measurement of risk and how these are affected by management incentives that are often misaligned with the incentives of those who are exposed in various ways to the risk being measured. In the aftermath of the crisis many have called for increased transparency; we suggest that while transparency is no doubt a desirable goal in many ways, enhancing it could prove to be quite difficult.
Download

"The ‘Wall Street Walk’ as a Form of Shareholder Activism”
Anat R. Admati and Paul Pfleiderer
Working Paper, October 2005
The paper examines whether a large shareholder can alleviate the conflict of interest between shareholders and managers through his ability to sell his shares on the basis of private information. We show tha large shareholder exit often has a disciplinary impact, but that (i) the effectiveness of this mechanism can be quite different depending on whether the agency problem involves a desirable or an undesirable action from shareholders’ perspective; (ii) additional private information may increase or decrease the large shareholder’s effectiveness; and (iii) in some cases the presence of the large shareholder may exacerbate the agency problem.
Download

"Just-In-Time Monte Carlo for Path Dependent American Options”
Samir K. Dutt and Gerd M. Welke
Working Paper, October 3, 2005
The paper provides a simple analytical technique for generating lognormal paths in reverse, i.e., it shows how to propagate a terminal price distribution backwards in time, one step at a time to the initial value while satisfying all cross-sectional and time series requirements. It extends this technique to the Ornstein-Uhlenbeck process. General processes are tackled using either subordination or time-reversed Ito diffusion, and the time-reversed CIR process is worked out. This proves useful in dealing with complex path-dependent options with American triggers, where storing the history of the underlying can overwhelm system memory rapidly whenever a very large number of paths, a very long holding period, or a very fine time scale are called for. This “just in time method,” which can be thought of as stochastic involution, extends the reach and accuracy of Monte Carlo techniques beyond what has hitherto been possible.
Download

"The Relation between Fixed Income and Equity Return Factors”
Jaime Lee, Terry Marsh, Robert Maxim, and Paul Pfleiderer
Working Paper, August 29, 2005
The paper provides an analysis of the relation between equity and fixed income returns over time. As measured by realized correlation, this relation has changed substantially over the last decade, from positive to negative through the market collapse and is currently around zero. We find “jumps” in the co-movements of equity and bond returns at a daily frequency; these jumps can at times be attributed to “flight to liquidity” phenomena in the markets, and at other times, to apparent surprise announcements in expected inflation or related macro conditions. We find no evidence of short-run persistence in the jumps in daily co-movement of bond and equity returns, but there does seem to be a “regime-like” longer-run persistence in them, perhaps associated with Federal Reserve “management over the last decade.
Download

"Surprise volume and heteroskedasticity in equity market returns"
Niklas Wagner and Terry Marsh
Quantitative Finance, Vol. 5, No. 2 April 2005, 153-168.
Heteroskedasticity in returns may be explainable by trading volume. We use different volume variables, including surprise volume – i.e. unexpected above-average trading activity – which is derived from uncorrelated volume innovations. Assuming weakly exogenous volume, we extend the Lamoureux and Lastrapes (1990) model by an asymmetric GARCH in-mean specification following Golsten et al. (1993). Model estimation for the US as well as six large equity markets shows that surprise volume provides superior model fit and helps to explain volatility persistence as well as excess kurtosis. Surpirse volume reveals a significant positive market risk premium, asymmetry and a surprise volume effect in conditional variance. The findings suggest that e.g. a surprise volume shock (breakdown) – i.e. large (small) contemporaneous and small (large) lagged surprise volume – relates to increased (decreased) conditional market variance and return.
Download

"Measuring tail thickness under GARCH and an application to extreme exchange rate changes"
Niklas Wagner and Terry Marsh
Journal of Empirical Finance, 12 (2005), 165-185.
Accurate modeling of extreme price changes is vital to financial risk management. We examine the small sample properties of adaptive tail index estimators under the class of student-t marginal distribution functions including generalized autoregressive conditional heteroskedastic (GARCH) models and propose a model-based bias-corrected estimation approach. Our simulation results indicate that bias relates to the underlying model and may be positively as well as negatively signed. The empirical study of daily exchange rate changes reveals substantial differences in measured tail thickness due to small sample bias. Thus, high quantile estimation may lead to a substantial underestimation of tail risk.
Download

"Decomposing factor exposure for equity portfolios"
David Tien, Paul Pfleiderer, Robert Maxim, and Terry Marsh
Linear Factor Models in Finance, Chapter 13: Ed. by John Knight and Stephen Satchell, Elsevier Finance, Amsterdam.
This study addresses the problem of accurately forecasting and attributing risk in equity portfolios. It develops a hybrid methodology which takes advantage of the superior forecasting power of implicit factor models while also attributing portfolio risk to economic factors and firm-specific characteristics. It then compares the relative accuracy of risk attribution using this hybrid approach versus an explicit cross-sectional factor model. It presents simulation results which suggest, given realistic parameter values, that the estimation efficiency gained by using the hybrid approach yields substantial improvements over explicit models.
Download

"The Role of Country and Industry Effects in Explaining Stock Returns"
Terry Marsh and Paul Pfleiderer
Working Paper,
The relative role of industry and country factors in explaining global returns on individual stocks is studied. In contrast to past studies, e.g. Heston and Rouwenhorst (1994) and Roll (1992), the sensitivities of stocks' returns to these factors are allowed to differ across stocks. We find that the industry factor explains 20% - 30% of the variation in stock returns which can be accounted for by country and industry, and about 7% of the variation explained when a global factor is also included. This relative explanatory power for the industry factor is much higher than the 1%-or-less estimate reported by Heston and Rouwenhorst because, we argue, they focus on index returns. Strikingly, however, we find that the broad nine-segment "industrial classification" in the Dow Jones Global Index (DJGI®) explains as much return variation as the finer 68-industry classification, and that the 38-industry classification in the Morgan Stanley Capital International (MSCI®) World Index explains slightly more. Finally, we find that measuring global stock returns in a common currency decreases the return variation attributable to industry factors by about 15%.
Download

“Estimating Factor Models of Security Returns: How Much Difference Does it Make?"
by Indro Fedrigo, Terry Marsh, Paul Pfleiderer
Forthcoming...

Other Interesting Research Papers that we’ve noticed (chronological order):

"Parametric Portfolio Policies: Exploiting Characteristics in the Cross Section of Equity Returns”
Michael W. Brandt, Pedro Santa-Clara, and Rossen Valkanov
Working Paper, September 2005
The paper proposes a novel approach to optimizing portfolios with large numbers of assets. It models directly the portfolio weight in each asset as a function of the asset’s characteristics. The coefficients of this function are found by optimizing the investor’s average utility of the portfolio’s return over the sample period. The approach is computationally simple, easily modified and extended, produces sensible portfolio weights, and offers robust performance in and out of sample. In contrast, the traditional approach of first modeling the joint distribution of returns and then solving for the corresponding optimal portfolio weights is not only difficult to implement for a large number of assets but also yields notoriously noisy and unstable results. Our approach also provides a new test of the portfolio choice implications of equilibrium asset pricing models. We present an empirical implementation for the universe of all stocks in the CRSP-Compustat dataset, exploiting the size, value, and momentum anomalies.
Download

02.01.2010

QED Financial Systems, based in Marlton, New Jersey, and Quantal International, Inc. based in San Francisco, California, today announced the creation of strategic joint venture. Quantal's portfolio analysis including multifactor risk modeling, value at risk (VaR), performance measurement, dynamic attribution analysis, and portfolio planning will be seamlessly integrated for QED clients and the broader financial market as single hosted solution. Please click here for more details.

08.01.2010

Quantal Lighthouse Solutions provides cutting-edge risk management, portfolio optimization and trade execution solutions to Lighthouse trade clients. The solutions combine the strengths of Quantal International in investement R&D and custom applications with Lighthouse's rapidly growing and innovative trading services. Please click here for more details.