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8:30 am – 8:50 am – On site registration and coffee

8:50 am – 9:00 am – Welcome and Introduction

9:00 am – 9:50 am – Keynote Speaker (1)

Thomas F. Coleman, Ophelia Lazaridis University Research Chair Professor, Combinatorics and Optimization, University of Waterloo and Director, Waterloo Research Institute in Insurance, Securities and Quantitative Finance (WatRISQ) Fellow, Society for Industrial and Applied Mathematics (SIAM)

Title : Learning Minimum Variance Discrete Hedging Directly from the Market.

Option hedging is a critical risk management problem in finance. In the Black-Scholes model, it has been recognized that computing hedging position from the sensitivity of the calibrated model option value function is inadequate in minimizing variance of the option hedge risk, as it fails to capture the model parameter’s dependence on the underlying price, see e.g., [16, 37]. In this paper we demonstrate that this issue can exist generally when determining hedging position from the sensitivity of the option function, either calibrated from a parametric model from current option prices or estimated nonparametricaly from historical option prices. Consequently, the sensitivity of the estimated model option function typically does not minimize variance of the hedge risk, even instantaneously. We propose a data driven approach to directly learn a hedging function from the market data by minimizing variance of the local hedge risk. Using the S&P 500 index daily option data for more than a decade ending in August 2015, we show that the proposed method outperforms the parametric minimum variance hedging method proposed in [37], as well as minimum variance hedging corrective techniques based on stochastic volatility or local volatility models. Furthermore, we show that the proposed approach achieves significant gain over the implied BS delta hedging for weekly and monthly hedging.

10:00 am -11:15 am – Contributed sessions (25 minutes each)

  1. Speaker: Xiangjin Shen (Senior Economist, Financial Institutions Division, Financial Stability, Bank of Canada)
    Title: Joint tail risk analysis by the Vine Copula
    Abstract: In this research, we analyze financial tail risk by using multidimensional correlations among macro-economic variables, indices,  and bank’s  loan related variables.  By using the Vine Copula, we estimate the joint multiple distributions among different financial variables or model residuals to obtain the joint tail dependence, and then we use simulation to identify the systemic financial tail risk such as market aggerate VaR (Value at Risk) and other tail risk measurement such as aggregate credit losses under stressed scenario. Coauthor: Dezhao Han (TD Bank)
  1. Speaker: Jun Cai (Department of Statistics and Actuarial Science, University of Waterloo)
    Title:  Risk measures based on the behavioural economics theory
    Abstract: Coherent risk measures and convex risk measures characterize the desired axioms for risk measures. However, concrete or practical risk measures could be proposed from different perspectives. In this paper, we propose new risk measures based on the behavioural economics theory. We use the rank-dependent expected utility (RDEU) theory to formulate an objective function and propose the smallest solution that minimizes the objective function as a risk measure. We also employ the cumulative prospect theory (CPT) to introduce a set of acceptable regulatory capitals and define the infimum of the set as a risk measure. We show that the classes of risk measures derived from the RDEU theory and the CPT are equivalent and they are all monetary risk measures.  We present the properties of the proposed risk measures and give the sufficient and necessary conditions for them to be coherent and convex, respectively. The risk measures based on these behavioural economics theories not only cover important risk measures such as distortion risk measures, expectiles, and shortfall risk measures, but also produce other new interesting coherent risk measures and convex but not coherent risk measures. This talk is based on joint works with Dr. Tiantian Mao.
  1. Speaker: Marcos Escobar-Anel (Department of Statistical and Actuarial Sciences, Western University)
    Title: Robust Portfolio Choice with Derivative Trading in Continuous Time.
    Abstract:  We motivate the concept of model mis-specification (ambiguity) and determine the optimal portfolio for an ambiguity averse investor who has access to stocks, Bonds and the derivatives market. We explore three non-overlapping models with some stylized facts like: stochastic volatility, correlation, short rates or jumps. In all cases the investor is allowed to have different levels of uncertainty (ambiguity) about the various diffusion parts. We find strong evidence that Investors who ignore model uncertainty/derivatives incur in significant welfare losses of up to 90%, and optimal exposures are substantially affected by the ambiguity aversion parameters.

11:15 am – 11:40 am – Coffee break

11:40 am – 12:30 pm – Keynote Speaker (2)

Matt Davison, Professor, Statistical and Actuarial Sciences, Western University, Director – School of Mathematical & Statistical Sciences, Fields Institute Fellow

Title: Where Data Science meets the Dismal Science   

Banks and other financial institutions grant “Small” loans (up to and including half million dollar mortgages) are typically granted to applicants as the result of an automatic process in which the responses to a set of questions (about income, other assets debts, etc)  are combined into a score which is then compared to a threshold.  Applicants with a score better than a certain threshold are granted a loan with a given set of terms.   Exactly how the scoring algorithm works is, of course, to some degree confidential, but incentives to “game” the loan granting system nonetheless remain. In this talk I give an introduction to modern data-driven retail credit and discuss an iterated game in which some borrowers (or their agents) deliberately falsifies aspect of her application, while other borrowers do not. The third player here is the bank. High level strategy and policy conclusions are drawn.  (Joint with Cristian Bravo and Mimi Chong)

12:30 pm – 2:00 pm – Lunch break

2:00 pm – 3:15 pm – Contributed sessions (25 minutes each)

  1. Speaker: Jorge Cruz Lopez (Principal Researcher, Funds Management and Banking Department, Bank of Canada)
    Title: Residual Risk and Default Waterfalls in Central Counterparties
    Abstract: I develop a methodology to assess residual risk exposures in derivatives central counterparties (CCPs) relative to the coverage suggested in the CPSS-IOSCO Principles for Financial Market Infrastructures. These risk exposures can be used to evaluate the systemic risk contributions of CCPs and the effectiveness of regulations mandating central clearing. The proposed technique decomposes residual risk exposures into a quantity-based component, driven by individual trading decisions that lead to crowded trades, and more traditional price-based components, determined by the volatility and comovement of asset returns. Empirical results based on data from the Canadian Derivatives Clearing Corporation (CDCC) show that aggregate residual risk exposures reached record levels during the financial crisis, when price-based components were at their highest levels. However, the quantity-based component peaked six months prior to the crisis; thus, suggesting that trade crowdedness could serve as a leading indicator of the financial cycle and should be considered when designing risk management policies.
  1. Speaker: Maarten van Oordt (Senior Analyst, Financial Stability Department, Bank of Canada)
    Title: Systemic Risk and Bank Business Models
    In this paper, we decompose banks’ systemic risk into two dimensions: the risk of a bank (“bank tail risk”) and the link of the bank to the system in financial distress (“systemic linkage”). Based on extreme value theory, we estimate a systemic risk measure that can be decomposed into two subcomponents reflecting these dimensions. Empirically, we assess the relationships of bank business models to the two dimensions of systemic risk. The observed differences in these relationships partly explain why micro- and macroprudential perspectives sometimes have different implications for banking regulation. (with Chen Zhou from the Erasmus University Rotterdam and the Dutch Central Bank) 
  1. Speaker: Gareth Witten (Executive-in-Residence, Global Risk Institute, Toronto. Professor. Sugnet Lubbe, Department of Statistics and Actuarial Science, University of Stellenbosch, South Africa.)
    Title: Visualizing variables in Covariance Analysis with biplots: applications in risk management
    Abstract: The covariance matrix of two sets of variables can be visualized graphically using the biplot. The resulting biplot, termed the covariance biplot, graphically reveals the relationships between variables. If one set of variables is used in the covariance analysis then the resulting graphical representation is called a covariance monoplot. We use the covariance biplot in order to illustrate the relationship between and within each set of variables and provide several examples in risk management to illustrate the technique.

3:15 pm – 4:05 pm – Keynote Speaker (3)

Henry Lam, Associate Professor, Department of Industrial Engineering and Operations Research, Columbia University

Title: Robust Extreme Risk Analysis

Understanding extremal risks is central to financial and insurance management. One bottleneck in analyzing extreme events is that, by its own definition, tail data is often scarce. Conventional approaches fit data using justified parametric distributions, but the inherent bias-variance tradeoff in the parametric fitting can hinder the estimation reliability. We discuss approaches using robust optimization as a nonparametric alternative that, through a different conservativeness-variance tradeoff, can mitigate some of the statistical challenges in estimating tails. Our framework uses optimization imposed over probability distributions to compute confidence bounds on extremal performance measures, under constraints that capture tail geometries and other obtainable information. We discuss the solution approaches and statistical performances compared to the conventional methods, and present some extensions such as applications in rare-event simulation.

4:05 pm -4 :30 pm – Coffee break

4:30 pm – 5:20 pm – Keynote Speaker (4)

Luis Seco, Professor, Department of Mathematics, University of Toronto, Director, Mathematical Finance Program, Director of RiskLab Toronto, President and CEO Sigma Analysis and Management

Title: Postmodernism in Finance: The Mathematics of Management Fees

Low negative rates and the low performance environment are putting pressure on the investment business. In this talk we will analyze the valuations of fee structures, and propose frameworks where the Black- Scholes valuation of new fee structures delivers value to managers and investors alike.

5:30 pm – 7:30 pm – Networking Reception – 12th Floor, DMS 12102



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