Title: Fluctuation Analysis for the Loss From Default
Abstract:
We analyze the fluctuation of the loss from default around its large portfolio limit in a class of reduced-form models of correlated default timing. We prove a weak convergence result for the fluctuation process and use it for developing a conditionally Gaussian approximation to the loss distribution. Numerical results illustrate the accuracy of the approximation. Joint work with Konstantinos Spiliopoulos and Kay Giesecke.
Title: The Recent Financial Crisis and Two Related Financial Engineering Research Problems
Abstract:
Two main causes of the recent financial crisis are excessive risk taking due to the limited liability of fund managers and corporations, which means profits are shared, but not losses, and the inability of valuing housing market fairly, which partly leads to the housing bubble. In this talk we will present two papers related to these. (1) We investigate hedge fund performance fees via behavioral finance. In particular, we show that in most cases it is possible to improve the satisfaction of regulators, fund managers, and fund investors simultaneously by replacing the traditional 20% performance fee scheme with a new 10-30 first-loss scheme, in which fund managers take 30% performance fee in return for their 10% first-loss capital investment. (2) We propose an asset pricing model with spatial interaction for pricing real estate assets. The model connects the capital asset pricing model (CAPM) and arbitrage pricing theory (APT) with spatial statistics. An empirical test using the Case-Shiller U.S. regional real estate indices is also given, which suggests a new housing factor based on a mean-variance efficient portfolio. This is a joint work with Xuedong He, Xianhua Peng and Haowen Zhong.
3: 15 pm: Mikhail Dobrolioubov (American Express)
Title: A gold mine or a mine field? Practitioner’s perspective on using machine learning algorithms to predict consumer credit risk
Abstract:
After a brief review of strengths and weaknesses of the traditional, logistic regression based, approach to modeling default risk in consumer and small business credit card portfolios, we discuss new approaches to credit risk modeling based on machine learning algorithms. We provide a few examples of potential applications of such techniques and outline key challenges from the practitioner’s perspective:
• Ensuring stability of models based on machine learning algorithms under different economic conditions
• Leveraging machine learning algorithms to derive insights useful for analyst-based modeling
• Combining machine learning algorithms with time series aspects of consumer credit risk
4:30 pm: Yong Su (Stanford University)
Title: Dynamic Panel Data in Credit Risk Modeling
Abstract:
This talk gives an overview of a new approach to dynamic panel data in econometrics by using empirical Bayes principles that lead to generalized linear mixed models which are versatile and convenient to implement. Applications to default probabilities and loss given default in retail and wholesale loans are also given. This is joint work with T.L. Lai and Kevin Sun.
5 pm: Yingyu Ye (Stanford University)
Title: Risk Management in the Credit Card Business
Abstract:
We describe few decision problems/models arisen in the credit-card business. They include: segmenting business and personal spending; developing a probability of liquidation model framework; and determining optimal lines for OPEN high-spenders, etc.
5:30 pm: Kay Giesecke (Stanford University)
Title: Large Pools: Computational and Statistical Tools
Abstract:
We survey recent and ongoing work on large pools of securities, such as credit cards or mortgages. We treat computational tools, including various approximations, and tractable statistical methods for parameter estimation.
Title: Beyond VWAP
Subtitle:
1) Adaptive Trading with High Frequency Signals(Equity)
2) Market Making(FX)
Abstract:
In this talk, execution strategies with high frequency signals currently employed by Bank of America Merrill Lynch will be introduced and illustrated with actual orders. In addition, what statistical measures are computed, stored and maintained in DB in order to run performance analysis on strategies, order flows, and clients will be explained. Lastly, market making business will also be covered based on the speaker’s past experience, in particular in FX market.
Title: Probabilistic Approach to Mean Field Games and the Control of McKean-Vlasov Dynamics
Abstract:
We review a series of recent results on Mean Field Games, including existence and the construction of approximate Nash equilibria. We also present the analog of the stochastic maximum principle approach to the optimal control of stochastic dynamics of the McKean-Vlasov type. In both cases existence results are proven by solving forward-backward stochastic differential equations of the McKean-Vlasov type. (joint works with F. Delarue)
Title: The Flash Crash and High Frequency Trading.
Abstract:
The “Flash Crash” of May 6, 2010 saw some stocks and exchange-traded funds traded at pennies only to rapidly recover in price. We show that the impact of the Flash Crash across stocks is systematically related to prior market fragmentation. Interestingly, fragmentation measured based on quote competition – reflective of higher frequency activity – has explanatory power beyond a more standard volume-based definition. Using intraday trade data from January 1994-September 2011, we find that fragmentation now is at the highest level recorded. We also show divergent intraday behavior of trade and quote fragmentation on the day of the Flash Crash itself. The link to higher frequency quotation activity and the current high levels of fragmentation help explain why a Flash Crash did not occur before and offers a counterpoint to the view that the Flash Crash stemmed from an unlikely confluence of events. Controlling for fragmentation, exchange-traded products were differentially affected reflecting the difficulty in pricing component securities. Market structure reforms enacted since the Flash Crash should help mitigate future such market disruptions, but have not eliminated the possibility that another Flash Crash would occur, albeit with a different catalyst and perhaps in a different asset class.
Title: Can a Trend Follower Expect to Win?
Abstract:
In this talk we explore what can be said, from a purely theoretical perspective, about technically-based, model-free trending-following strategies. This is an area of finance that has long been considered "voodoo" by the academic finance community. We describe a specific trend-following strategy, referred to as Simultaneous-Long-Short (SLS), that adheres to the tenets of technical trend-following; namely it is direction independent, lets profits run, and cuts losses short. In particular, we highlight the fact that the SLS strategy is completely model-free (that is, it uses no predictive model of stock prices in its determination of an allocation) and instead relies on simple performance driven feedback loops. Surprisingly, we are able to prove that over the class of stock prices following geometric Brownian motion with rather arbitrary time varying drift and volatility, the SLS trend follower always has a positive expected trading gain. We believe that this remarkable robustness to price dynamics may be responsible for the popularity and longevity of simple trend-following strategies, thus demystifying some of the "voodoo" behind technically-based trend-following trading approaches.
Title: Systematic Inventory Management: Where Execution Meets Risk
Abstract: Market forces in Equities trading are driving the need for automation and flow internalization. Managing a large stock inventory in a systematic fashion will soon become a cornerstone of any equity trading business. In this talk we discuss the business drivers and the quantitative components that underlie Systematic Inventory Management and the challenges faced by the brave quant venturing in this complex subject, where systematic trading meets real-time risk management.
Title: Optimal portfolio allocation of commodity related assets in illiquid markets and a forward-backward algorithm to solve the stochastic control problem
Abstract: In the first part of the talk, an algorithm for solving continuous-time stochastic optimal control problems is presented. The numerical scheme is based on the stochastic maximum principle (SMP) as an alternative to the widely studied dynamic programming principle (DPP). We show possible performance advantages of the algorithm in the case of feedback control. In the second part, an investment-consumption problem with convex transaction costs and optional stochastic returns is presented. The model is a simplified approach for the investment in a portfolio of real options. We show numerical results that, on one hand, are consistent with the well-known investment-consumption theory and on the other hand, show an investment strategy that may seems counter intuitive.
3:15 pm: Garence Staraci (Stanford)
Title: Random Matrix Theory as a new tool For Financial Network Stability
Abstract:
4:15 pm: Charles Tapiero (New York University Polytechnic Institute)
Title: An Extended CCAPM: income Inequality, Debt and a Mean Field Like Games
Abstract:
Caveats of the complete markets theory of finance have been profusely researched, pointing out that its assumptions do not always hold. Yet, there are few if any, general, meaningful and explanatory theories that replace the Arrow-Debreu framework for complete state preferences or the CCAPM risk pricing framework. Its achievements have however, blurred the essential premise that financial models and theories are in fact only models of uncertainty, hypotheses - never confirmed and always in doubt. In a world where risks have multiple and interactive causes; where risks are both exogenous and endogenous—resulting from what we do; where risks are both associated to micro and macro events often leading to the neglect of one or the other and thus to their mismatch. Risks may also arise due to political agendas or to strategic consideration subjugated to complex financial and regulatory systems, etc. In such an environment, financial pricing models are necessarily only a “work in process”.
The purpose of this presentation is to provide an asset pricing model approach based on an extended and price sensitive CCAPM. In this framework, the CCAPM model is extended to account for the price effects of additional economic factors such as economic inequalities, debt, debt dependence etc. For simplicity, we consider only two period problems as well as a number of specific cases while extensions to inter-temporal pricing models, mean field Merton game type models as well as specific issues including the effects of regulation and rationing on asset prices, economic inequalities, etc. are discussed. When conditions for complete markets hold, the extended CCAPM model is reduced to the standard CCAPM model with future prices implied by current information. When incomplete markets prevail, the extended CCAPM model is shown to be coherent with a utility rationale that underlies the CCAPM as well as an implied pricing framework.