Shashi Jain
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View article: Event-Time Anchor Selection for Multi-Contract Quoting
Event-Time Anchor Selection for Multi-Contract Quoting Open
When quoting across multiple contracts, the sequence of execution can be a key driver of implementation shortfall relative to the target spread~\cite{bergault2022multi}. We model the short-horizon execution risk from such quoting as variat…
View article: Machine Learning-Based Digital Twin for Water Distribution Network Anomaly Detection and Localization
Machine Learning-Based Digital Twin for Water Distribution Network Anomaly Detection and Localization Open
This paper presents the development of a Digital Twin (DTwin) to detect and localize the leaks in water distribution networks (WDNs), using single-stage and two-stage data-driven models. In the single-stage model, we test the anomalies in …
View article: Forecasting High Frequency Order Flow Imbalance
Forecasting High Frequency Order Flow Imbalance Open
Market information events are generated intermittently and disseminated at high speeds in real-time. Market participants consume this high-frequency data to build limit order books, representing the current bids and offers for a given asse…
View article: Neural Networks for Portfolio-Level Risk Management: Portfolio Compression, Static Hedging, Counterparty Credit Risk Exposures and Impact on Capital Requirement
Neural Networks for Portfolio-Level Risk Management: Portfolio Compression, Static Hedging, Counterparty Credit Risk Exposures and Impact on Capital Requirement Open
In this paper, we present an artificial neural network framework for portfolio compression of a large portfolio of European options with varying maturities (target portfolio) by a significantly smaller portfolio of European options with sh…
View article: A static replication approach for callable interest rate derivatives: mathematical foundations and efficient estimation of SIMM–MVA
A static replication approach for callable interest rate derivatives: mathematical foundations and efficient estimation of SIMM–MVA Open
The computation of credit risk measures such as exposure and Credit Value Adjustments (CVA) requires the simulation of future portfolio prices. Recent metrics, such as dynamic Initial Margin (IM) and Margin Value Adjustments (MVA) addition…
View article: Optimizing Neural Networks for Bermudan Option Pricing: Convergence Acceleration, Future Exposure Evaluation and Interpolation in Counterparty Credit Risk
Optimizing Neural Networks for Bermudan Option Pricing: Convergence Acceleration, Future Exposure Evaluation and Interpolation in Counterparty Credit Risk Open
This paper presents a Monte-Carlo-based artificial neural network framework for pricing Bermudan options, offering several notable advantages. These advantages encompass the efficient static hedging of the target Bermudan option and the ef…
View article: Non-Parametric Estimation of Multi-dimensional Marked Hawkes Processes
Non-Parametric Estimation of Multi-dimensional Marked Hawkes Processes Open
An extension of the Hawkes process, the Marked Hawkes process distinguishes itself by featuring variable jump size across each event, in contrast to the constant jump size observed in a Hawkes process without marks. While extensive literat…
View article: Multi-period static hedging of European options
Multi-period static hedging of European options Open
We consider the hedging of European options when the price of the underlying asset follows a single-factor Markovian framework. By working in such a setting, Carr and Wu \cite{carr2014static} derived a spanning relation between a given opt…
View article: A Semi-Static Replication Method for Bermudan Swaptions under an Affine Multi-Factor Model
A Semi-Static Replication Method for Bermudan Swaptions under an Affine Multi-Factor Model Open
We present a semi-static replication algorithm for Bermudan swaptions under an affine, multi-factor term structure model. In contrast to dynamic replication, which needs to be continuously updated as the market moves, a semi-static replica…
View article: A Two-Stage Model for Data-Driven Leakage Detection and Localization in Water Distribution Networks
A Two-Stage Model for Data-Driven Leakage Detection and Localization in Water Distribution Networks Open
Water utilities face the challenge of reducing water losses by promptly detecting, localizing, and repairing leaks during their operational stage. To address this challenge, utilities are exploring alternative approaches to detect leaks wi…
View article: A Probabilistic Digital Twin for Leak Localization in Water Distribution Networks Using Generative Deep Learning
A Probabilistic Digital Twin for Leak Localization in Water Distribution Networks Using Generative Deep Learning Open
Localizing leakages in large water distribution systems is an important and ever-present problem. Due to the complexity originating from water pipeline networks, too few sensors, and noisy measurements, this is a highly challenging problem…
View article: Precision versus Shrinkage: A Comparative Analysis of Covariance Estimation Methods for Portfolio Allocation
Precision versus Shrinkage: A Comparative Analysis of Covariance Estimation Methods for Portfolio Allocation Open
In this paper, we perform a comprehensive study of different covariance and precision matrix estimation methods in the context of minimum variance portfolio allocation. The set of models studied by us can be broadly categorized as: Gaussia…
View article: A neural network based model for multi-dimensional nonlinear Hawkes processes
A neural network based model for multi-dimensional nonlinear Hawkes processes Open
This paper introduces the Neural Network for Nonlinear Hawkes processes (NNNH), a non-parametric method based on neural networks to fit nonlinear Hawkes processes. Our method is suitable for analyzing large datasets in which events exhibit…
View article: Data-driven Approach for Static Hedging of Exchange Traded Options
Data-driven Approach for Static Hedging of Exchange Traded Options Open
This paper presents a data-driven interpretable machine learning algorithm for semi-static hedging of Exchange Traded options, considering transaction costs with efficient run-time. Further, we provide empirical evidence on the performance…
View article: Analysis on Emissions of Gasoline Engine with Different Ethanol Blends at Different Compression Ratio
Analysis on Emissions of Gasoline Engine with Different Ethanol Blends at Different Compression Ratio Open
Alcohol fuels do have some extra benefit compare to other alternative fuels, like the capability to work in existing engines also have the ability to decrease harmful emissions. Among the various alcohols, ethanol is considered most approp…
View article: A semi-static replication approach to efficient hedging and pricing of callable IR derivatives
A semi-static replication approach to efficient hedging and pricing of callable IR derivatives Open
We present a semi-static hedging algorithm for callable interest rate derivatives under an affine, multi-factor term-structure model. With a traditional dynamic hedge, the replication portfolio needs to be updated continuously through time…
View article: Likelihood of observing transformative learning amongst profession changers: a predictive analysis
Likelihood of observing transformative learning amongst profession changers: a predictive analysis Open
In this paper, we explore the possibility of whether the likelihood of observing transformative learning may be predicted using information related to personal history and current and previous professions. We examine empirical data collect…
View article: Method of lines for valuation and sensitivities of Bermudan options
Method of lines for valuation and sensitivities of Bermudan options Open
In this paper, we present a computationally efficient technique based on the \emph{Method of Lines} (MOL) for the approximation of the Bermudan option values via the associated partial differential equations (PDEs). The MOL converts the Bl…
View article: Experimental Investigation on Triple Concentric Tube Heat Exchanger with Helical Baffles
Experimental Investigation on Triple Concentric Tube Heat Exchanger with Helical Baffles Open
A heat exchanger is a device used to transfer thermal energy between two or more liquids, between a solid surface and a liquid, or between solid particles and a liquid at different temperatures and in thermal contact where shell and tube h…
View article: Neural network for pricing and universal static hedging of contingent\n claims
Neural network for pricing and universal static hedging of contingent\n claims Open
We present here a regress later based Monte Carlo approach that uses neural\nnetworks for pricing high-dimensional contingent claims. The choice of specific\narchitecture of the neural networks used in the proposed algorithm provides for\n…
View article: Can Machine Learning-Based Portfolios Outperform Traditional Risk-Based Portfolios? The Need to Account for Covariance Misspecification
Can Machine Learning-Based Portfolios Outperform Traditional Risk-Based Portfolios? The Need to Account for Covariance Misspecification Open
The Hierarchical risk parity (HRP) approach of portfolio allocation, introduced by Lopez de Prado (2016), applies graph theory and machine learning to build a diversified portfolio. Like the traditional risk-based allocation methods, HRP i…
View article: Can machine learning based portfolios outperform traditional risk-based portfolios? The need to account for covariance misspecification
Can machine learning based portfolios outperform traditional risk-based portfolios? The need to account for covariance misspecification Open
The Hierarchical risk parity (HRP) approach of portfolio allocation, introduced by Lopez de Prado (2016), applies graph theory and machine learning to build a diversified portfolio. Like the traditional risk-based allocation methods, HRP i…