Speaker Affiliation UK EST Iran Welcome Hirbod Assa Conference Chair 800815 300315 11301145 Opening Younes Mazlumi Taavon Insurance Co CEO 815830 315330 11451200 Rama Cont Uni Of Oxford 830930 330430 12001300 Hirbod Assa Kent Business School 9301030 430530 13001400 Break 10301100 530600 14001430 Ruodu Wang Uni of Waterloo 11001200 600700 14301530 Azadeh Ghasemifard Uni of Mazandaran 12001230 700730 15301600 Break 12301300 730800 16001630 Laleh Samarbakhsh Ryerson University 13001400 800900 16301730 Hassan Omidi Firouzi JP Morgan 14001500 9001000 17301830 Parisa Davar Concordia University 15001530 10001030 18301900 Robab Kalantari Khatam University 15301600 10301100 19001930 Schedule 1st day 7th International FinAct conference httpsus06webzoomusj88055095218pwdVFdPc0FHYWNuZnpJdGNLckJUM1hwUT09 Meeting ID 880 5509 5218 Passcode 210810 COVID19 and Hedge Funds Equity Ownership Tuesday August 10 2021 Mordad 19 1400 Time Zone Lecturers and Titles of Talks Liquidity at Risk joint stress testing of bank liquidity and solvency Pooling and valuation revisited Goodharts law and risk optimization On the Multilevel MonteCarlo Simulation JumpDiffusion Assets with Superlinear Drift Central Bank Digital Currency CBDC From Research to Implementation by Central Banks A Forecasting Model for LOB in TSX Using Attentionbased in LSTM Network Optimizing Dynamic Copulas Parameters and Portfolio VaR Estimation Iran Speaker Affiliation Time Zone Fatemeh Atatalab 900920 Hamed Ahmadnezhad 920940 Vahid Esmaeili 9401000 Sajad Jamalian 10001020 Break 10201040 Donya Kholghi 10401100 Mina Roostapour Deilamany 11001120 Mostafa Abbaszadeh 11201200 Speaker Affiliation UK EST Iran Corina Constantinescu Uni of Liverpool 830930 330430 12001300 Tim Boonen Uni of Amsterdam 9301030 430530 13001400 Break 10301100 530600 14001430 Karim Barigou Université de Lyon 11001200 600700 14301530 Saeid Safarveisi Katholieke Uni Leuven 12001230 700730 15301600 Break 12301300 730800 16001630 Liyuan Lin Uni of Waterloo 13001330 800830 16301700 Maryam Vahid École des ponts Paris 13301400 830900 17001730 Samin Ghamamiy New York University 14001500 9001000 17301830 Mohsen Rezapour University of Texas 15001600 10001100 18301930 Tarbiat Modares University Credit risk stress test The case of an Iranian bank Automated trading system using machine learning Tarbiat Modares University Schedule 2nd day Wednesday August 11 2021 Mordad 20 1400 National Session In Farsi Shahid Beheshti University Prediction IBNR and RBNS loss reserve net of reinsurance treaties NoBetting ParetoOptima under RankDependent Utility Actuarial and financial valuation of catastrophe bonds On highdimensional heavy tailed Lèvy process with possibly different tail indices Pricing equity linked life insurance contracts with multiple risk factors by neural networks International Session Time Zone Subsidizing Inclusive Insurance to Reduce Poverty Zerointerest green loans in France Effectiveness and candidate barriers The Impact of Collateral and Stays on Financial Stability On VaRES distortion and its application in risk management Granger causality analysis on five main cryptocurrencies oil and gold markets Tarbiat Modares University Joint Prediction of Stock PriceCorrelation Pair Using Deep MultiTask Networks Institute for Advanced Studies in Basic Science Studying the efficiency of portfolio selecting models and comparing them from the perspective of Sharpe and Treynor ratios Amirkabir University of Technology A reducedorder model based on the cubic Bspline functions to investigate option pricing under jumpdiffusion model Amirkabir University of Technology Iran Speaker Affiliation Time Zone Masoud Ghahremani 900920 Abolfazl Mighani 920940 Saman Vahabi 9401000 Zahra Majedi 10001020 Break 10201040 Nader Karimi 10401100 Vazhe Rahimi 11001120 Davood Ahmadian 11201200 Speaker Affiliation UK EST Iran Amir Payandeh Shahid Beheshti Uni 10301130 530630 14001500 Ali Safdari Allameh Tabatabai Uni 11301230 630730 15001600 Mostafa Pouralizdeh 12301330 730830 16001700 Hassan Omidi Firouzi JP Morgan Hirbod Assa KBS Davood Damircheli Mississippi State Uni 14301500 9301000 18001830 Hassan Dadashi IASBS 15001600 10001100 18301930 Saghar Heidari Shahid Beheshti Uni 16001630 11001130 19302000 Optimal investmentconsumption problem postretirement with minimum guarantee Evaluation of Bond Options 13301430 830930 17001800 Schedule 3rd day Thursday August 12 2021 Mordad 21 1400 National Session In Farsi Kharazmi University Applying deep learning algorithms based on a new spatial neural network for limit order book Institute for Advanced Studies in Basic Science IASBS Shahid Beheshti University Saman Insurance Company Optimal trading strategy from an agricultural producer perspective Calibration and regularization RBF based multilevel meshfree approximation in model including market illiquidity Optimal Investment Strategy for a DC Pension Fund Plan in a Finite Horizon Time ApplicaƟons of Actuarial Model in Automobile Insurance Claim Amirkabir University of Technology Diagonally drift and diffusionimplicit balanced stochastic RungeKutta methods of strong Secondorder for stiff stochastic differential systems Numerical Analysis for European options under a new stochastic volatility model with a stochastic longterm mean Panel on machinelearning in finance where ML benefits and where not Galerkin Finite Element Method for Credit Rating Migration Problem Model with Galerkin Finite Element Method University of Tabriz University of Tabriz International Session Time Zone On Credibility Premium for Finite Mixture Distributions Some aspects of stock price movements and option pricing models Miniworkshop on fraud ditection A sample article title 1 Liquidity at Risk joint stress testing of bank liquidity and solvency1 Rama Cont2 University of Oxford England United Kingdom Artur Kotlicki University of Oxford England United Kingdom Laura Valderrama International Monetary Fund United States Abstract The traditional approach to the stress testing of financial institutions focuses on capital adequacy and solvency Liquidity stress tests have been applied in parallel to and independently from solvency stress tests based on scenarios which may not be consistent with those used in solvency stress tests We propose a structural framework for the joint stress testing of solvency and liquidity our approach exploits the mechanisms underlying the solvencyliquidity nexus to derive relations between solvency shocks and liquidity shocks These relations are then used to model liquidity and solvency risk in a coherent framework involving external shocks to solvency and endogenous liquidity shocks arising from these solvency shocks We define the concept of Liquidity at Risk which quantifies the liquidity resources required for a financial institution facing a stress scenario Finally we show that the interaction of liquidity and solvency may lead to the amplification of equity losses due to funding costs which arise from liquidity needs 1 httpswwwsciencedirectcomsciencearticlepiiS0378426620301370via3Dihub 2 Speaker A sample article title 1 Pooling and valuation revisited Hirbod Assa1 Kent Business School England United Kingdom Abstract Abstract In light of the COVID19 outbreak and the associated economic losses we aim to revisit the fundamental insurance paradigms in particular pooling and valuation in the presence of systematic risk We consider a pool of policyholders whose losses can be widely correlated through common shock We have observed that from a mathematical standpoint insurance as a pooling approach can manage the risk if the principle of insurance POI that is to keep the systematic risk secure holds Our study suggests that valuation cannot be independent of the risk pool and the premium needs to be adjusted according to the systematic risk Expost policies are another consideration that can vanish the systematic safety loading by introducing contingent premiums This approach is rather novel and is motivated by systematic events like COVID19 economic losses Finally we look at the upper bounds for the pool valuation for two cases first when we have no specific information about the dependency structure of the pool member losses and second when the pool is influenced by a common shock 1 Speaker A sample article title 1 Goodharts law and risk optimization Ruodu Wang1 University of Waterloo Canada Abstract Goodharts law named after British economist Charles Goodhart states that When a measure becomes a target it ceases to be a good measure We discuss this law in the context of risk optimization in banking regulation where the target measure is a regulatory risk measure The two most important regulatory risk measures ValueatRisk VaR and Expected Shortfall ES have given rise to many debates over the past few years on their comparative advantages where robustness issues become a crucial consideration By introducing and analyzing the concept of robustness in optimization we obtain a second Goodharts law for risk measures As regulatory target all risk measures cease to be good but some risk measures are much worse than the others In particular VaR is seriously problematic in this regard in sharp contrast to commonly used convex risk measures like ES This talk is based on joint work with Paul Embrechts ETH Zurich and Alexander Schied Waterloo 1 Speaker A sample article title 1 On the Multilevel MonteCarlo Simulation JumpDiffusion Assets with Superlinear Drift Azadeh Ghasemifard1 University of Mazandaran Babolsar Iran Mahdieh Tahmasebi Tarbiat Modares University Tehran Iran Abstract This article is about the strong convergence of the Multilevel MonteCarlo MLMC algorithm when applying with splitstep backward Euler SSBE scheme to nonlinear jumpdiffusion stochastic differential equations SDEs The importance of this research is that the underlying process does not enjoy from globally Lipschitz condition and we consider the drift term as one sided Lipschitz and the payoff function as only locally Lipschitz We also confirm these theoretical results by numerical experiment for the jumpdiffusion process Keywords multilevel MonteCarlo onesided Lipschitz splitstep scheme strong approximation Mathematics Subject Classi_cation 2018 65C3065C0591G80 1 Speaker A sample article title 1 COVID19 and Hedge Funds Equity Ownership Laleh Samarbakhsh1 Ryerson University Canada Abstract This study investigates hedge funds equity ownership in light of the COVID19 pandemic Using the merged dataset of Lipper TASS hedge funds and the corresponding 13F filings we find that with the start of the pandemic hedge funds increased their equity ownership toward firms with less financial constraints such as larger firms firms with lower leverage and more profitability Moreover hedge funds increased their ownership in firms which had higher overall risk political and non political and lower overall sentiment Hedge funds also care about firms exposuresensitivity toward different political issues such as health care technology infrastructure and security and defense This suggests that hedge funds seek equity ownership in riskier stocks as a result of pandemic uncertainties Keywords COVID19 Equity Ownership Hedge funds 1 Speaker A sample article title 1 Central Bank Digital Currency CBDC From Research to Implementation by Central Banks Hassan Omidi Firouzi1 JP Morgan Chase Bank USA Abstract Central banks around the world are exploring the design and implications of central bank digital currencies CBDCs Various research projects dedicated to the design of CBDC for retail and wholesale applications have been carried out by central banks as well as by academics In this talk well discuss the economical and technological underpinnings for a CBDC design and will cover the current status of CBDC developments by the major players Keywords Central Bank Digital Currency CBDC CrossBorder Payments Cryptocurrency 1 Speaker A sample article title 1 A Forecasting Model for Limit Order Book in Tehran Stock Exchange Using Attentionbased in LSTM Network Parisa Davar1 Concordia University Canada Ali Foroush Bastani Institute for Advanced Studies in Basic Sciences Iran Parvin Razzaghi Institute for Advanced Studies in Basic Sciences Iran Hirbod Assa Kent Business School UK SeyedMohammadMahdi Kazemi Kharazmi University Iran Abstract In this paper we propose an attention mechanism in deep learningbased model to predict price movements in Limit Order Book LOB data of Tehran Stock Exchange TSE Our model is trained on the data from top30 listing companies utilizing an attention mechanism in stacked Long ShortTerm Memory LSTM to capture longer time dependencies Our paper addresses different issues missing in the literature by applying the attention mechanism for the first time to the high frequency market data We have observed that how the volume of the LOB plays a major role in accurately predicting the midprices However we found out that the optimal numbers of the LOB levels are fewer than the total number of the reported levels We observe that training a deep neural network that is a combination of LSTM and attention mechanism based on the top30 will lead to an optimal structure of 2layer stacked LSTM with one layer attention mechanism Furthermore we see a universal phenomenon that the algorithm can generalize the prediction of the companies prices outside the group of top30 1 Speaker A sample article title 1 Optimizing Dynamic Copulas Parameters and Portfolio VaR Estimation Shirin Robaty Khatam University Tehran Iran Mohamad ali Rastegar Tarbiyat Moalem University Tehran Iran Robab Kalantari1 Khatam University Tehran Iran Abstract The goal of this research is to determine the optimal dynamic dependency of a Bitcoin and three important commodity markets portfolio The dynamic dependency between the assets is evaluated using three Archimedean and two elliptical copula models and then the portfolios valueatrisk VaR is estimated To determine dynamic dependency structure and parameters the Copula models are optimized using the particle swarm optimization PSO algorithm The rolling window method is used for this The findings demonstrate a weak correlation between Bitcoin and other assets as well as changes in dependency over time When Bitcoin is employed this observation validates the effect of portfolio diversity The results also reveal that in order Studentst and Gumbel copula perform the best and worst in estimating the dependency structure of the assets under consideration Keywords ValueatRisk Bitcoin Dynamic Copula Particle Swarm Optimization Mathematics Subject Classification 2018 13D45 39B42 1 Email rkalantarikhatamacir Prediction IBNR and RBNS loss reserve net of reinsurance treaties Fatemeh Atatalab1 Shahid Beheshti University Tehran Iran Amir Teimour Payandeh Najafabadi Shahid Beheshti University Tehran Iran Abstract This article considers the problem of predicting claims amounts that have been incurred but not re ported IBNR and reported but not settled RBNS whenever a reinsurance contract exists We examine the impact of several reinsurance treaties on loss reserve from the cedent companys viewpoint Moreover under each reinsurance treaty the cedents loss reserve has been predicted and their corresponding pre diction errors will be estimated The application of our findings has been given for a car collision insurance loss portfolio Keywords Loss reserve Insurance Reinsurance treaty Mean square error of prediction Mathematics Subject Classification 2018 G22 C13 1speaker Espino notebook Text Box Farsi Talk 1 Credit risk stress test The case of an Iranian bank Hamed Ahmadnezhad1 Tarbiat Modares University Tehran Iran Mohamad Ali Rastegar Tarbiat Modares University Tehran Iran Reza Baradaran Kazemzadeh Tarbiat Modares University Tehran Iran Abstract One of the main goals of banks is financial stability over time To achieve this goal banks need to identify and control the risks they may face in the future One of the practical tools in this regard is Stress Test Stress tests are effective tools in crisis management identifying possible destructive events They are one of the most important requirements for banks in Basel 1 and 2 There are many ways to do a stress test from a simple sensitivity analysis to a variety of scenario analyses This article aims to perform a credit risk stress test using a scenario analysis method for an Iranian bank First macroeconomic and financial variables affecting the performance of the bank loan portfolio are selected In the following a linear regression between the loan performance variables and the selected variables is performed A Vector AutoRegression VAR model is then implemented on the independent variables to discover the relationship between them and to generate scenarios After generation of the scenarios finally the probability of default values are evaluated under the baseline and stressed scenarios The results show that consumer price index gold price rental rate money volume and longterm interest rate have the most impact on credit portfolios Keywords Stress Test Credit Risk Wilson Model Vector AutoRegression Mathematics Subject Classification 2018 13D45 39B42 1 Speaker Espino notebook Text Box Farsi Talk 1 Automated trading system using machine learning Vahid Esmaeili1 Tarbiat Modares Tehran Iran Mohammad Ali Rastegar Tarbiat Modares Tehran Iran Abstract In this study in order to predict the next minutes closing price of Ethereum we use six technical Indicators and the close price of BTC as inputs of several machine learning models After that we design an automated trading system to take short or long positions Finally the models evaluate in terms of performance Results show that the performance of models can beat the buy and hold model The random forest model has the best performance among all models with 90 accuracy After the random forest model the XGBoost model decision tree and support vector machine had the best to the weakest performance respectively Keywords Algorithmic Trading Machine Learning Cryptocurrencies Mathematics Subject Classification 2018 13D45 39B42 1 Speaker Espino notebook Text Box Farsi Talk 2 Sajad jamalian Granger causality analysis on five main cryptocurrencies oil and gold markets Sajad Jamalian1 Tarbiat modares university Tehran Iran Mohammad Ali Rastegar Sorkheh Tarbiat modares university Tehran Iran Reza Baradaran Kazemzadeh Tarbiat modares university Tehran Iran Abstract This paper analyses the Granger causality test between the five crypto currency with largest market cap BTC ETHXRP BNB ADA and oilgold markets by using Ftest Chi squaretest Likelihood ratio test for research the relationship between them also implement ARMAGARCH models to find which model is most effective for forecasting future returns Our findings verify the existence of relation between time series of the five cryptocurrency and oilgold markets Furthermore the results imply the following1 Bitcoin has the most impact on other time series and can be used for predicting future returns of other asset except BNB 2 ARMAGARCH model are best fitted model for our all seven asset 3 No time series can predict the future return of Bitcoin and XRP is most influenced of Granger causality It should be noted that these are the preliminary results In the future we will use the Markov switching time varying copula method to construct joint distribution of time series and compute covars for calculate risk spillover among the named assets The data used in this article are the price returns of the listed assets from April 26 2017 to July 15 2021 Keywords Granger causality Bitcoin ARMAGARCH Mathematics Subject Classification 2018 13D45 39B42 1 Speaker Espino notebook Text Box Farsi Talk Joint Prediction of Stock PriceCorrelation Pair Using Deep MultiTask Networks Donya Kholghi1 Institute for Advanced Studies in Basic Science Zanjan Iran Parvin Razzaghi Institute for Advanced Studies in Basic Sciences Zanjan Iran Ali Fourosh Bastaani Institute for Advanced Studies in Basic Sciences Zanjan Iran Stock price prediction is a great challenge due to the volatile and uncertain nature of the market The correlation coe icient is a crucial issue in portfolio selection which depends on price history Our aim here is to build a model that is capable of predicting correlation coe icient and price movement of stocks at the same time To this end we use the MultiTask Learning MTL framework The MTL model learns multiple tasks in parallel to make more accurate predictions 1 The raw data used in this study is the adjusted closing price of 30 companies listed in Tehran Stock Exchange TSE Experimental results confirm that the proposed model performs well in predicting the pricecorrelation pair Keywords Stock Market Prediction MultiTask Learning LSTM Model ARIMA Model Convolutional LSTM Model AMS Mathematical Subject Classi ication 2018 91G99 68T99 1speaker Abstract Espino notebook Text Box Farsi Talk Mina Roostapour Deilamany 1 Studying the efficiency of portfolio selecting models and comparing them from the perspective of Sharpe and Treynor ratios Mina Roostapour Deilamany1 Amirkabir University of Technology Tehran Iran Abstract Optimizing portfolio is about maximizing return while controlling or reducing risk for which various models have been created Three of the bestknown models are Markowitz Sharpe and Treynor that the risk measure is used in them are variance standard deviation and beta coefficient In this paper we study four innovative models and three abovementioned models in selecting portfolio problem The risk measure used in innovative models is based on both systematic and unsystematic risks At the end we implement each model and evaluate their performance on 30 companies of Iran Stock Exchange which have the highest market values and compare them from two perspectives Sharpe ratio and Trainor ratio Keywords Markowitz Sharpe ratio Treynor ratio beta coefficient Mathematics Subject Classification 2021 13D45 39B42 1 Speaker Espino notebook Text Box Farsi Talk A reducedorder model based on the cubic Bspline functions to investigate option pricing under jumpdiffusion model Mostafa Abbaszadeh1 Department of Applied Mathematics Faculty of Mathematics and Computer Sciences Amirkabir University of Technology No 424 Hafez Ave15914 Tehran Iran Abstract The main aim of the current paper is to find a fast stable and efficient numerical method for solving option pricing under jumpdiffusion models The consider model is a partial integrodifferential equation with diffusion and advection terms The first and secondorder derivatives are approximated by com bining the cubic Bspline functions with the local pseudospectral technique First we discrete the space derivatives by the mentioned formulation which this procedure yields a system of ODEs So the second order difference scheme is employed for solving the system of ODEs To get an appropriate solution we have to increase number of collocation points and also time steps to reach the final time This procedure increases the used CPU time To overcome this issue we employ the proper orthogonal decomposition POD method to reduce size of final algebraic system of equation Keywords Option pricing under jumpdiffusion model Cubic Bspline functions Proper orthogonal decomposition Mathematics Subject Classification 2018 65L60 1 Introduction It is seen that the Black Scholes model has not real stock price for stock price behavior For this reason several models are proposed including some models with jump diffusion presented by Merton 3 and Kou 2 The corresponding model is based upon the partial integrodifferential equation PIDE including a nonlocal integral term Assume V S τ denotes the value of a contingent claim which depends on the underlying asset price S with current time τ Thus V S τ can be computed by solving the following backward partial integrodifferential equation V τ 1 2 σ2S2 2V S2 r λκ1V S r λV λ 0 V Sξgξdξ 0 S τ 0 0 T 1 where r represents the risk free interest rate and gξ is the probability density function of the jump in which ξ we have gξ 0 and 0 gξdξ 1 Let K be the strike price and t T τ Defining the new variables x ln S K and ϑ lnξ and fixing κ1 pξ1 ξ1 1 1 pξ2 ξ2 1 1 model 1 will be changed as u t 1 2 σ2 2u x2 r σ 2 2 λκ1u x r λu λ uϑ tKϑ xdϑ 0 2 1speaker Espino notebook Text Box Espino notebook Text Box Farsi Talk A sample article title 1 Subsidizing Inclusive Insurance to Reduce Poverty Corina Constantinescu1 University of Liverpool UK Abstract Considering a compound Poissontype model for households capital and using risk theory techniques we determine the probability of a household falling under the poverty line Microinsurance is then introduced to analyze its impact as an insurance solution for the lower income class Our results validate those previously obtained with this type of model showing that microinsurance alone is not sufficient to reduce the probability of falling into the area of poverty for specific groups of people since premium payments constrain households capital growth This indicates the need for additional aid particularly from the government As such we propose several premium subsidy strategies and discuss the role of government in subsidizing microinsurance to help reduce poverty 1 Speaker A sample article title 1 NoBetting ParetoOptima under RankDependent Utility Tim J Boonen1 University of Amsterdam The Netherlands Mario Ghossoub University of Waterloo Canada Abstract In a pureexchange economy with no aggregate uncertainty we characterize in closedform and in full generality Pareto optimal allocations between two agents who maximize rankdependent utilities RDU We then derive a necessary and sufficient condition for Paretooptima to be nobetting allocations ie deterministic allocations or full insurance allocations This condition depends only on the probability weighting functions of the two agents and not on their concave utility functions Hence with RDU preferences it is the difference in probabilistic risk attitudes given common beliefs rather than heterogeneity or ambiguity in beliefs that is a driver of a bet As byproduct of our analysis we answer the question of when sunspots matter in this economy Key Words and Phrases Betting RiskSharing ParetoOptimality Sunspots RankDependent Utility 1 Speaker A sample article title 1 Pricing equitylinked life insurance contracts with multiple risk factors by neural networks Karim Barigou1 Université de Lyon France Abstract This paper considers the pricing of equitylinked life insurance contracts with death and survival benefits in a general model with multiple stochastic risk factors interest rate equity volatility unsystematic and systematic mortality We price the equitylinked contracts by assuming that the insurer hedges the risks to reduce the local variance of the net asset value process and requires a compensation for the nonhedgeable part of the liability in the form of an instantaneous standard deviation risk margin The price can then be expressed as the solution of a system of nonlinear partial differential equations We reformulate the problem as a backward stochastic differential equation with jumps and solve it numerically by the use of efficient neural networks Sensitivity analysis is performed with respect to initial parameters and an analysis of the accuracy of the approximation of the true price with our neural networks is provided 1 Speaker A sample article title 1 Actuarial and financial valuation of catastrophe bonds Saeid Safarveisi1 Katholieke Universiteit Leuven Belgium Hirbod Assa Kent Business School UK Jia Shao Coventry Universoty UK Abstract Among different types of insurancelinked security instruments existing in capital markets catastrophe bonds are important for insurance companies Such a contract includes both financial and actuarial risks making their valuation procedure quite complicated from a theoretical perspective The financial valuation of catastrophe bonds is based on the idea of arbitragefree pricing and a riskneutral measure approach In this paper we provide a valuation based on the actuarial methodology in which the best estimate of discounted loss plus a risk margin are computed under the physical measure To do so we introduce the variance premium principle and achieve a closedform formula for the catastrophe bond price Keywords Catastrophe bonds Physical measure Riskneutral measure Variance premium principle MonteCarlo simulation Subject 91G20 91G30 1 Speaker A sample article title 1 On VaRES distortion and its application in risk management Liyuan Lin1 University of Waterloo Canada Hirbod Assa Kent Business School UK Ruodu Wang University of Waterloo UK Abstract In quantitative risk management value at risk VaR and expected shortfall ES are known as the major risk measures The former has gained its popularity due to its simplistic approach toward risk as the risk quantile and the second one is perceived to be very useful as a modification of VaR with more appealing properties such as tailsensitivity and subadditivity However VaR is not in general promoting the major idea of reducing risk by diversification and ES cannot be defined on all risk variables As a result there have been always a tendency to explore the relationship between the two In this paper we study this relationship in a novel manner by exploring how ES transforms the distribution of a risk variable This is essentially done by a distortion function The main objective of the paper is that for a given distribution find numerical and theoretical ways to identify the distorted distribution Particularly this is important for us to explore the tail behavior of the distorted distribution and compare it with the original one 1 Speaker A sample article title 1 Zerointerest green loans in France Effectiveness and candidate barriers Maryam Vahid1 École des ponts ParisTech France Abstract Since 2009 France has been running a zerointerest green loan ZIGL program to encourage home energy retrofits The number of ZIGLs issued on a yearly basis however is an order of magnitude lower than initially planned Exploiting a differenceindifference design we estimate the causal effect of the program on home energy retrofits We find a significant positive effect that vanishes after two years We discuss candidate barriers for underparticipation in the program including debt aversion and lack of information on the demand side obfuscation on the supply side and interactions with other subsidy programs on the regulatory side 1 Speaker A sample article title 1 The Impact of Collateral and Stays on Financial Stability1 Samim Ghamamiy2 New York University UC Berkeley and SOFR Academy USA Abstract We study the spread of losses and defaults in financial networks with two features collateral requirements and resolution and bankruptcy stay rules When collateral is committed to a firms counterparties a solvent firm may default if it lacks sufficient liquid assets to meet its payment obligations Collateral requirements can thus increase the risk of contagion Moreover one firm may benefit from the failure of another if the failure frees collateral committed by the surviving firm giving it additional resources to make other payments Contract termination at default may also similarly improve the ability of other firms to meet their obligations As a consequence of these features the timing of payments and collateral liquidation must be carefully specified to establish the existence of payments that clear the network Using this framework we show that committed collateral in the form of initial margin in overthecounter derivatives markets may increase contagion and risks to financial stability We also compare networks under different stay rules in OTC markets Our analysis shows that when _rms are not highly leveraged in terms of derivatives transactions full contract termination may reduce contagion 1 This presentation is based on a recent paper titled Collateralized Networks joint with Paul Glasserman at Columbia Business School and Peyton Young at the London School of Economics It is also based on two Risk articles Ghamami 2020a and Ghamami 2020b 2 Speaker A sample article title 1 On highdimensional heavy tailed Lèvy process with possibly different tail indices Mohsen Rezapour1 Department of Biostatistics and data science The university of Texas Health Science center at Houston USA Vahed Maroufy Department of Biostatistics and data science The university of Texas Health Science center at Houston USA Hirbod Assa Kent Business School UK Abstract Rapid improvement in data collection electronic devices has granted access to a large amount of timedependent data with high resolution and frequency These data sets are realizations of continuoustime random processes recorded on an incredibly fine time resolution High dimensional highfrequency data with extreme values commonly appear in various fields of science such as the study of extreme events big Electronic Health Records EHR gene expression analysis using RNASeq data and high dimensional portfolio optimization Lèvy process with heavytailed components as a class of continuoustime random process were widely used in finance literature In this talk we are concerned with the dimensional reduction of data from a multivariate Lèvy process with heavytailed components in the domain of attraction of a stable law with possibly different stability indices which allows us to model high dimensional continuous time series with different tail indices For dimensionality reduction instead of considering the sample variancecovariance matrix we consider a scaled version of it which enabled us to show that under some mild conditions the asymptotic behavior of eigenvalues of this matrix is in the domain of attraction of a stable law with possible different tail indices This achievement reveals that any statistical inference related to eigenvalues depends on the tail index of original random variables Finally we propose an algorithm to find the most critical variables based on our achievements The novel algorithm is implemented in portfolio optimization for SP 500 data A comparison of Markowitz portfolio optimization based on our novel algorithm and the principal components is provided for more illustration 1 Speaker Applying deep learning algorithms based on a new spatial neural network for limit order book Ghahremani Masoud Kharazmi University Tehran Iran Kazemi SeyedMohammadMahdi Associate Professor Kharazmi University Tehran Iran Assa Hirbod Associate Professor Kent Business School Canterbury England Abstract Based on the idea presented in Justin A Sirignano Deep learning for limit order books Quantita tive Finance 2018 This paper applies a new neural network architecture spatial neural network for modeling in limit order book data of tehran stock exchange to check the performance of this model The design of the architecture takes advantage of the specific structure of limit order books The spatial neural network models the joint distribution of the state of the limit order book at a future time conditional on the current state of the limit order book The models are trained and tested on the data of 30 companies of tehran stock exchange Techniques from deep learning such as dropout are employed to improve per formance and finally the results showed that The spatial neural network outperforms a standard neural network architecture Keywords Limit order book Deep learning Machine learning Big data AMS Mathematical Subject Classi ication 2018 13D45 39B42 1Speaker 1 Espino notebook Text Box Farsi Talk RBF Based Multilevel Meshfree Approximation in Model Including Market Illiquidity Abolfazl Mighani1 Institute for Advanced Studies in Basic Sciencesy Zanjan Iran Ali Foroush Bastani Institute for Advanced Studies in Basic Sciencesy Zanjan Iran Abstract This paper addresses application of multilevel Newton iteration along with the radial basis functions to be used for solving the parabolic partial dierential equations derived from pricing European options in the Frey and Patie model The linearization of the nonlinear PDE applied at each iteration helps to solve a system of linear PDEs by a multilevel collocation scheme Finally in order to evaluate the accuracy and robustness of the results gained in this paper they are compared with the results from former numerical studies Keywords Frey and Patie Model Radial Basis Function European Call Option Multilevel Newton Iteration AMS Mathematical Subject Classication 2018 91G80 65N35 1speaker Espino notebook Text Box Farsi Talk Optimal Investment Strategy for a DC Pension Fund Plan in a Finite Horizon Time Saman Vahabi1 Shahid Beheshti University Tehran Iran Amir T Payandeh Shahid Beheshti University Tehran Iran Abstract This paper obtains an optimal strategy in a nite horizon time for a portfolio of a DC pension fund for an investor with the CRRA utility function It employs the optimal stochastic control method in a nancial market with two dierent asset markets one risk free and another one risky asset with its jump follows either a nite or innite activity Levy process Sensitivity of jump parameters in a uncertainty nancial market has been studied Keywords Optimal Strategy Pension Plans FiniteInnite activity Levy Processes Pension Fund AMS Mathematical Subject Classication 2018 60G51 11A55 42A38 60J50 60E10 1speaker Espino notebook Text Box Farsi Talk Applications of Actuarial Model in Automobile Insurance Claim Zahra Majedi 1 Saman Insurance Company Tehran Iran Oreinab Afrooz Kelardehi Razi Insurance Company Tehran Iran Abstract In this paper we apply actuarial models to detailed microlevel automobile insurance records As we know third party insurance is an important major for both policyholders and insurance companies We model claim frequency type and severity of third party insurance claims by incorporating different individual and vehicle risk factors such as vehicle age vehicle usage vehicle capacity and number of claim discount This allows the actuary to differentiate prices based on policyholder characteristics In addition by using various risk measures including value at risk and tail value at risk we predict the insurance company capital requirement Finally we assess the effects of dependence structure on these measures by using copula models The results show that the copula effect increases with the percentile Keywords Third party liability insurance Risk factors Copula Risk measures Capital requirement Mathematics Subject Classification 2020 91G70 62H05 1 Speaker Espino notebook Text Box Farsi Talk Optimal trading strategy from an agricultural producer perspective Calibration and regularization Karimi Nader1 Amirkabir university Tehran Iran Assa Hirbod Kent Business School UK Salavati Erfan Amirkabir university Tehran Iran Adibi Hojatollah Amirkabir university Tehran Iran Abstract We study the decision problem of storing commodity for an agricultural producer who aims to sell the production in the futures market under the continuous time speculative storage model in the infinite horizon time To do so first we consider the logOrnsteinUhlenbeck process as the demand process and provide a novel demand function capable of being an Snell envelope over all stopping times Second we propose novel calibration method which combines the quasi maximum likelihood method and Milstein method Then we apply our method on both simulated and actual data for two families of value functions Eventually we use the Likelihood Ratio Test LRT for comparison of two models storage model and nostorage model Our results show that the proposed storage model is more efficient than the nostorage model Keywords LogOrnsteinUhlenbeck process Snell envelope Quasi maximum likelihood method AMS Mathematical Subject Classification 2018 13D45 39B42 1speaker Espino notebook Text Box Farsi Talk Numerical Analysis for European options under a new stochastic volatility model with a stochastic longterm mean Rahimi Vazhe1 University of Tabriz Tabriz Iran Ivaz Karim University of Tabriz Tabriz Iran Ahmadian Davood University of Tabriz Tabriz Iran Abstract The paper analyzes the European call option prices under stochastic longterm mean in the Heston model numerically First discretization is performed using θ method The proposed discrete equation reduces in three dimensions to one dimension by using the von Neumann method along with the Fourier transform The consistency and stability of the method have been stablished and subsequently conver gence is concluded by the Lax theorem At final numerical results are performed by the wellknown Crank Nicolson by setting the θ 12 Keywords Stochastic volatility Stochastic longterm mean viscosity solution 3dimensional discrete Fourier transform Mathematics Subject Classification 2018 13D45 39B42 1 2 νS2 2U S2 1 2 νσ21 2U ν2 1 2 σ22 rS U S κα νU ν λ U α 1speaker Espino notebook Text Box Espino notebook Text Box Espino notebook Text Box Farsi Talk Diagonally drift and diffusionimplicit balanced stochastic RungeKutta methods of strong Secondorder for stiff stochastic differential systems Rahimi Vazhe University of Tabriz Tabriz Iran Ahmadian Davood University of Tabriz Tabriz Iran Abstract The paper aims to obtain the convergence and meansquare MS stability analysis of the second order balanced stochastic RungeKutta method for the Itoˆ multidimensional stochastic linear scalar and additive test differential equations The control functions are used to improve and enhance the convergence and stability properties of the method The strong convergence of the secondorder balanced stochastic RungeKutta methods is analyzed Moreover the meansquare stability is investigated using the properties of Kronecker product Finally to check their convergence order and stability properties some numerical experiments are performed Keywords Stochastic differential equations Numerical solutions Balanced stochastic RungeKutta methods Meansquare stability Strong convergence Mathematics Subject Classification 2018 13D45 39B42 1speaker Espino notebook Typewritten Text 1 Espino notebook Text Box Farsi Talk A sample article title 1 On Credibility Premium for Finite Mixture Distributions Amir T Payandeh Najafabadia1 Shahid Beheshti University Iran Ehsan Jahanbania Shahid Beheshti University Iran Abstract Suppose random claim 𝑋1 𝑋𝑛 are sampled from a Kcomponent finite mixture distribution Moreover supposed that claim information 𝑋1 𝑋𝑛 are accompanied with additional information 𝑍1 𝑍𝑛 where using such additional information one may identify the probability of a given random claim belongs to a certain component Under these assumptions this article provides 1 the credibility premium for finite mixture distributions and 2 the exact credibility premium for the finite mixture distributions whenever claim distributions of all components are belong to the exponential family of distributions and their corresponding prior distribution conjugates with such a claim distribution Keywords Finite mixture distributions Credibility premium Bayes estimator Exponential family of distributions Classifications 62F15 62E15 91B05 91G99 1 Speaker A sample article title 1 Some aspects of stock price movements and option pricing models Ali Safdari Vaighani1 Allameh Tabatabai University Iran Abstract In most cases pure diffusion models are not flexible enough to fit the empirical observations concerning the movements of stock prices Many studies have been conducted to overcome the limitations of the BlackScholes model The main aspects of these researches involve three empirical stylized facts namely the leptokurtic feature volatility clustering effect and implied volatility smile The aim of this talk is to develop computational schemes and simulation methods for more realistic models arising in financial application Keywords Financial data Jumpdiffusion BlackScholes model AMS Mathematical Subject Classification 2018 65M70 91G80 1 Speaker A sample article title 1 Galerkin Finite Element Method for Credit Rating Migration Problem Model with Galerkin Finite Element Method Davood Damircheli1 Mississippi State University Starkville USA Abstract In this presentation we propose a finite element method to study the problem of credit rating migration problem narrowed to a free boundary problem Free boundary indeed separates the high and low rating region for a rm and causes some difficulties including discontinuity of secondorder derivative of the problem Exploiting the weak formulation of the problem utilized in the Galerkin method the discontinuity of secondorder derivative is averted we show some convergence and stability of the proposed method Numerical results illustrate how derived convergence results are consistent into practice ones Keywords Credit rating migration problem free boundary problem Galerkin methods Convergence analysis Error estimate Stability 1 Speaker Optimal investmentconsumption problem postretirement with minimum guarantee1 Hassan Dadashi2 Institute for Advanced Studies in Basic Science IASBS Zanjan Iran Abstract We study the optimal investmentconsumption problem for a member of defined contribution plan during the decumulation phase For a fixed annuitization time to achieve higher final annuity we consider a variable consumption rate Moreover to have a minimum guarantee for the final annuity a safety level for the wealth process is considered To solve the stochastic optimal control problem via dynamic programing we obtain a HamiltonJacobiBellman HJB equation on a bounded domain The existence and uniqueness of classical solutions are proved through the dual transformation We apply the finite difference method to find numerical approximations of the solution of the HJB equation Finally the simulation results for the optimal investmentconsumption strategies optimal wealth process and the final annuity for different admissible ranges of consumption are given Furthermore by taking into account the market present value of the cash flows before and after the annuitization we compare the outcomes of different scenarios Keywords Defined contribution plan Decumulation phase Final annuity guarantee HJB equation Policy iteration method AMS Subject Classification 60J70 93E20 65N06 1 httpsdoiorg101016jinsmatheco202007006 2 Speaker Evaluation of Bond Options Saghar Heidari1 Shahid Beheshti University Tehran Iran Abstract In this paper we study one of the interest rate contingent claims bond options that the valuation of these financial instruments have been investigated extensively in recent work in computational finance research These options are written on bonds that their prices depend on interest rates We consider the Hull and white model as a singlefactor affine model to describe the dynamic of interest rate Among bond options American bond options whose their early exercise feature requires special treatment have become more attractive in recent research In pricing problem of American bonds options the early exercise opportunity leads to free boundary problem which no analytical solution is available To face these difficulties and to find the free boundaries as well as the options price with partial differential equation approach we apply a numerical method to solve the resulted partial differential equation with free boundary Our numerical results demonstrate efficient robust and accurate approximations of the free boundaries and option prices in comparison with some other approaches Keywords American bond option Hull and White model free boundary problem frontfixing method Mathematics Subject Classification 2018 13D45 39B42 Email s heidarisbuacir 2speaker Schedule of FINACT Conference 2021 Page 1 Page 2 Page 3 Booklet of FINACT Conference 2021 Booklet of FINACT Conference 2021 Schedule of FINACT Conference 2021 Page 1 Page 2 Page 3 Day 1English Day 2farsi 01Atatalab1 02Ahmadnezhad1 03Esmaiili1 04jamalian1 05Kholghi1 06Roostapour1 07Abbasszadeh AUT1 Day 2English Day 3farsi 01Ghahremani1 02Mighani1 03Vahabi1 04Majedi1 05Karimi1 06Vazhe1 07Ahmadian SDE1 Day 3English 01Payande 02Ali 03Davoud 04Dadashi finactHeidari