Ameya AbhyankarBond Risk Sensitivities with Python (Part 1)Duration is a popular measure of interest rate risk sensitivity for bondsSep 25Sep 25

Ameya AbhyankarOverview of the Simplified Standardized Approach (SSA) for Market RiskSimplified Standardized Approach for market risk measurement for banksApr 26Apr 26

Ameya AbhyankarFundamentals of Numerical Methods in Quant FinanceWhile there are a plethora of numerical methods out there, in this article we will focus on a few of the numerical methods for pricing…Mar 9Mar 9

Ameya AbhyankarFoundations of FRTB for Market Risk — Part IIWe discuss the Internal Models Approach (IMA) for market risk capital charge under the FRTB ruleDec 17, 2023Dec 17, 2023

Ameya AbhyankarFoundations of FRTB for Market Risk — Part IFRTB is a new guideline for market risk management for banksDec 4, 2023Dec 4, 2023

Ameya AbhyankarFoundations of Interest Rate modelling — the simplified wayThe level of interest rates and the volatility in rates is a matter of “great interest” in the industry.Jul 11, 2023Jul 11, 2023

Ameya AbhyankarProbability toolbox for quant financeProbability theory and related concepts are one of the key building blocks for a variety of concepts in quant finance.Apr 20, 2023Apr 20, 2023

Ameya AbhyankarFoundations of Martingales for quant financeMartingale may be defined as a stochastic process whose trajectories do not display any discernible trendsApr 6, 2023Apr 6, 2023

Ameya AbhyankarSimulation of correlated random walks for a basket of stocks using PythonIn many quantitative finance applications, we frequently generate random walks to build the path of a certain asset that follows processDec 2, 2022Dec 2, 2022

Ameya AbhyankarFoundations of Numerical Methods — the Pythonic wayNumerical Methods by definition mean the application of a certain analytical technique to solve a certain problem.Oct 19, 2022Oct 19, 2022