A cardinality-constrained portfolio caps the number of stocks to be traded across and within groups or sectors. These limitations arise from real-world scenarios faced by fund managers, who are constrained by transaction costs and client preferences as they seek to maximize return and limit...

An optimization approach is proposed to construct sparse portfolios with mean-reverting price behaviors. Our objectives are threefold: (i) design a multi-asset long-short portfolio that best fits an Ornstein-Uhlenbeck process in terms of maximum likelihood, (ii) select portfolios with desirable...

We study an optimization-based approach to construct a mean-reverting portfolio of assets. Our objectives are threefold: (1) design a portfolio that is well-represented by an Ornstein-Uhlenbeck process with parameters estimated by maximum likelihood, (2) select portfolios with desirable...

In this article we suggest a new method for solutions of stochastic integrals where the dynamics of the variables in integrand are given by some stochastic differential equation. We also propose numerical simulation of stochastic differential equations which is based on iterated integrals method...

We discuss the results of the statistical tolerance test of the General Administration Management component of the Capital Expenditure of the Bangalore Municipal Corporation which carries ahead our two previous connected studies (A. Sathyavathi (2023(a)), Analysis of the General Administration...

We introduce a model-free approach based on {\it excursions} of trading signals for analyzing the risk and return for a broad class of dynamic trading strategies, including pairs trading and other statistical arbitrage strategies. We propose a mathematical framework for the risk analysis of such...

In continuation of our previous study (A. Sathyavathi (2023). Analysis of the General Administration Management Expenditure of the Bangalore Municipal Corporation https://www.ssrn.com/abstract=4403863 ; http://dx.doi.org/10.2139/ssrn.4403863 ) we propose to further analyze the sample of the...

In this study, we present an empirical comparison of statistical models and machine learning models for daily electricity price forecasting in the New Zealand electricity market. We demonstrate the effectiveness of GARCH and SV models and their t-distribution variants when paired with feature...

A Hidden Markov Model (HMM) is used to model the VIX (the Cboe Volatility Index). A 4- state Gaussian mixture is fitted to the VIX price history from 1990 to 2022. Using a growing window of training data, the price of the S&P500 is predicted and two trading algorithms are presented, based on the...

In this very first paper of a series of forthcoming research papers of ours, which we propose to bring out in near future regarding the detailed statistical and mathematical analysis of the financial resources and the budget of the Bangalore Municipal Corporation (more appropriately now called...