Aman Bajaj Regional Sales Manager at Palisade speaks at Cypher 2017 - Part1/2
summary
Live demo shows @RISK as an Excel add‑in running Monte Carlo with 10,000 simulations, a library of 75+ probability distributions, time‑series fitting for stock forecasting, and a correlation matrix (examples set at ±0.6) to link inputs. The model outputs include quantified probabilities (e.g. 0.1% chance profit < $2.0M, 3% < $2.05M, ~67% ≥ $2.17M), a Pareto of top drivers, and portfolio scenario paths — all generated interactively from spreadsheet models.
AI-written summary · about
chapters (7)
- 0:00Introduction
- 3:07Software
- 8:08Monte Carlo simulations
- 14:58Alternative diagram
- 16:09Input assumptions
- 16:51Correlation matrix
- 25:32End
related talks
22mUsing Cyber Data To Financially Quantify Cyber Risk Decisions
55mDerivatives Analytics with Python & Numpy
40m"Clojure in the Fintech Ecosystem"
20m15 Years of R in Quantitative Finance
32mMLDS 2019: Pradeep Gulipalli of Tiger Analytics at Machine Learning Developers Summit 2019
29mHow to use Data Science Superpowers in real life, a Bayesian perspective
20mThe force behind decision-making – data, wisdom, and the crowds
23mSecurity Outgunned: Measuring Software Defined Attack Surface
