The History of the Quantitative Methods in Finance Conference Series. 1992-2007

This report charts the history of the Quantitative Methods in Finance (QMF) conference from its beginning in 1993 to the 15th conference in 2007. It lists alphabetically the 1037 speakers who presented at all 15 conferences and the titles of their papers.

Essays in Market Structure and Liquidity

Market structure concerns the mechanisms for negotiating trades and the composition of trading participants, and can affect liquidity and price efficiency. More gains from trade can be realized from an asset that is more liquid, and a better allocation of risk and capital can be achieved when an asset’s price is more efficient so it is important to understand market structure. This thesis uses theory and empirical methods to examine the effects of a few specific aspects of market structure. In Chapter 1, we study a novel market structure on the New York Stock Exchange (NYSE), the Retail Liqudity Program (RLP), that allows liquidity providers to trade specifically with retail traders. We test whether it affected the quality of trading opportunities for retail and non-retail traders by measuring transaction costs before and after the RLP was launched. We find transaction costs are slightly lower for both retail and non-retail traders. We also find evi- dence of an improved price-discovery process from allowing market participants to distinguish between retail trades, which contribute little to price discovery, and non-retail trades, which contribute more so. In Chapter 2, we extend a classic model of market microstructure to formalize the hypothe- ses and findings from Chapter 1 and to form new predictions. Under the models assumptions, prices are more efficient, and the effect on liquidity is ambiguous. We develop predictions of how informed traders adjust their trading strategies in the presence of the RLP. In Chapter 3, we consider a market where a significant amount of trading is motivated by hedging. We use a classic microstructure model to examine how a market makers willingness to provide liquidity is affected by the need to learn about the underlying value of an asset as well as the inventory of a hedging trader. Under our models assumptions, a market maker provides more liquidity in the presence of hedging. We test our prediction empirically by studying the effect of predictable increases in trading volume that occur near the expiry of stock options. We find the evidence that hedging trades result in improved liquidity

Stochastic volatility

Given the importance of return volatility on a number of practical financial management decisions, the efforts to provide good real- time estimates and forecasts of current and future volatility have been extensive. The main framework used in this context involves stochastic volatility models. In a broad sense, this model class includes GARCH, but we focus on a narrower set of specifications in which volatility follows its own random process, as is common in models originating within financial economics. The distinguishing feature of these specifications is that volatility, being inherently unobservable and subject to independent random shocks, is not measurable with respect to observable information. In what follows, we refer to these models as genuine stochastic volatility models. Much modern asset pricing theory is built on continuous- time models. The natural concept of volatility within this setting is that of genuine stochastic volatility. For example, stochastic-volatility (jump-) diffusions have provided a useful tool for a wide range of applications, including the pricing of options and other derivatives, the modeling of the term structure of risk-free interest rates, and the pricing of foreign currencies and defaultable bonds. The increased use of intraday transaction data for construction of so-called realized volatility measures provides additional impetus for considering genuine stochastic volatility models. As we demonstrate below, the realized volatility approach is closely associated with the continuous-time stochastic volatility framework of financial economics. There are some unique challenges in dealing with genuine stochastic volatility models. For example, volatility is truly latent and this feature complicates estimation and inference. Further, the presence of an additional state variable - volatility - renders the model less tractable from an analytic perspective. We examine how such challenges have been addressed through development of new estimation methods and imposition of model restrictions allowing for closed-form solutions while remaining consistent with the dominant empirical features of the data.Stochastic analysis

Innovations in Quantitative Risk Management

Quantitative Finance; Game Theory, Economics, Social and Behav. Sciences; Finance/Investment/Banking; Actuarial Science

Illiquidity and Derivative Valuation

In illiquid markets, option traders may have an incentive to increase their portfolio value by using their impact on the dynamics of the underlying. We provide a mathematical framework within which to value derivatives under market impact in a multi-player framework by introducing strategic interactions into the model of Almgren and Chriss (2001). Specifically, we consider a financial market model with several strategically interacting players that hold European contingent claims and whose trading decisions have an impact on the price evolution of the underlying. We establish existence and uniqueness of equilibrium results for risk neutral and CARA investors and show that the equilibrium dynamics can be characterized in terms of a coupled system of possibly non-linear PDEs. For the linear cost function used in Almgren and Chriss (2001), we obtain a (semi) closed form solution. Analyzing this solution, we show how market manipulation can be reduced

Three Essays on Variance Risk and Correlation Risk

This thesis focuses on variance risk and correlation risk in the equity market, and consists of three essays. The first essay demonstrates that the variance risk, mea- sured as the difference between the realized return variance and its risk-neutral expectation, is an important determinant of the cross-sectional variation of hedge fund returns. Empirical evidence shows that funds with significantly higher loadings on variance risk outperform lower-loading funds on average. However, they incur severe losses during market downturns. Failure to account for variance risk results in overestimation of funds' absolute returns and underestimation of risk. The results provide important implications for hedge fund risk management and performance evaluations. The second essay examines the empirical properties of a widely-used correlation risk proxy, namely the dispersion trade between the index and individual stock options. I find that discrete hedging errors in such trading strategy can result in incorrect inferences on the magnitude of correlation risk premium and render the proxy unreliable as a measure of pure exposure to correlation risk. I implement a dynamic hedging scheme for the dispersion trade, which significantly improves the estimation accuracy of correlation risk and enhances the risk-return profile of the trading strategy. Finally, the third essay aims to forecast the average pair-wise correlations between stocks in the market portfolio. I investigate a comprehensive list of forecasting models and find that past average correlation and the option-implied correlation provide superior out-of-sample forecasting performance compared to other predictors. I provide empirical evidence showing that the forecasts of average correlation can improve the optimal portfolio choices and substantially enhance the performance of active correlation trading strategies

Hedging strategies and price risk: An empirical analysis

This dissertation focused on the use of futures contracts as a hedge against price risk and is motivated by two key questions. First, will daily corn (soybean) futures prices consistently yield higher/lower prices than daily cash spot prices, after adjusting for an arbitrage bound? Second, does a hedge ratio exist that minimizes price risk for corn (soybean) producers? Data consisted of daily futures prices and daily cash spot prices for corn (September/December) and soybean (November/January) contracts for the period 1970 through 2000. These two commodities have the largest futures trading and highest production volume of all agricultural commodities. Two primary data analysis techniques were applied. First, price differences were analyzed using a timing model, adjusted for an arbitrage bound. The results from the timing model do not support the null hypothesis that “a time frame does not exist in which daily corn (soybean) futures prices are consistently higher/lower than the related daily cash spot price, after adjusting for an arbitrage bound.” In fact, the results suggest that futures prices more often fall “below” the arbitrage lower bound limit than they do within or above the bound. Second, the data was analyzed using a mean-variance framework and a logarithmic utility function to determine hedge ratios for corn (soybeans). The calculated hedge ratios do not support the null hypothesis that “a partial hedge will not consistently allow a producer to receive a higher average price than a full hedge of expected corn (soybeans) yield.” Specifically, the results for both corn contracts and the November soybean contract suggest that producers should hedge less than 100% of expected output while the results from the January soybean contract suggest that producers should hedge more than 100% of their expected output

Derivatives Trading and Negative Voting

This paper exposits a model of parallel trading of corporate securities (shares, bonds) and derivatives in which a large trader can sometimes profitably acquire securities with their corporate control rights for the sole purpose of reducing the corporations value and gaining on a net short position created through off-setting derivatives. At other times, the large trader profitably takes a net long position. The large trader requires no private information beyond its own trades. The problem is most likely to manifest when derivatives trade on an exchange and transactions give blocking powers to small minorities, particularly out-of-bankruptcy restructurings and freezeouts

Essays in market microstructure

Market making is central to the study of market microstructure. Market makers stand ready to provide liquidity, market stability and price discovery, issues of great importance to regulators, practitioners and academics. This thesis contributes to the literature by studying four topical issues related to market making. The thesis consists of four essays. In the first essay we develop a simple multi-period model of market making for a monopolistic stock market maker. The market maker tries to solve simultaneously the problems of managing his inventory and trading with informed traders. He uses a Kalman filter to update his estimates of the unknown market prices through his noisy order flow observation. We analytically characterize the optimal bid and ask prices and find that they depend on the beginning inventory, the estimated price, and the market maker's prior estimation error of the price process for each time period. We obtain desirable numerical results by using properly chosen parameters. The extensions to the continuous time and a competitive market making environment are also discussed. The second essay extends the model in the first essay to consider the market making of multiple stocks. The market maker still does not know the true prices but is assumed to know the return covariance structure of these stocks. When the market maker considers the correlated order flow information, his knowledge of the return covariance improves his estimation of the unknown price processes, resulting in higher cumulative profits and lower risks of the profits. The third essay analyzes the effect of option market makers' hedging on the informed trading strategy and the subsequent changes in the costs of liquidity provision in both stock and option markets. In a sequential trading framework, an option market maker uses the stock market to hedge his option position. His hedging trade affects the way that informed traders submit their orders in both the stock and the option market, which in turn changes the informed trading pressure faced by the market makers in each market. Furthermore, information in the option trading is passed to the stock market through the hedging trade. Both stock and option spreads are wider with option market maker's hedging. The increase in the spreads is more significant when the option market maker hedges in the underlying market than when it hedges with different options. The fourth essay provides a model of bookmaking in a horse race betting market. The bookmaker observes the noisy public betting flow and faces the risk of trading with possible informed traders, as well as the risk of his unbalanced liability exposures. Even the noisy demand can unbalance the bookmaker's book. In our model, the bookmaker revises his odds to mitigate the risk. Allowing the bookmaker to set odds over several rounds of betting gives a clear view of the bookmaker's price setting strategy and its impact on the public betting flow over time. The study of horse race bookmaking provides useful insights into the market making of state contingent claims such as options