It’s been a long time since I quit from P&G China. The happiness of geting an offer from P&G seems to be a false memory at this moment. Disappointment, anger, confusion… are the most frequently occured feeling during the 1 year work experience. In this article, I’ll try to draw some positive stuff from it.

1. P&G provided me an opportunity to obtain a whole view of how a global company is organized. In my past workload, I got chance to cross-functionally collaborate with IT(BI/DevOps/DS/Data) and Biz(Sales/Mkt), as well as some founctional team (Finance/Leagal/HR).
2. Along with the complicated colloabration senario, I got to know many people with different background and work desciplines. Some I like, Some I don’t… The discomfort at that period forced me to learn more flexible ways to get along with people.
3. P&G allowed me to chance my career path within the company, from Project manager to Analytical roles. This is the most precious opportunity even though this also triggered me to leave the company ;)

Stories goes on. See you next post.

This is a backup of some useful resources

1. STREETOFWALLS, CONSULTING CASE STUDY 101: AN INTRODUCTION TO FRAMEWORKS
2. Accenture, Case Interview Workbook
3. STREETOFWALLS, CONSULTING INTERVIEW QUESTIONS & ANSWERS
4. consultingcase101

Investments

Net profits in year 5: 375K
Valuation/profits = 20
Valuation = 20 profits = 20 * 375K = 7.5 M
The expected valuation in 5 years is 7.5M

Content

Toolkit

Reference

4/4 Objectives:

1. explore more general risk management tools. These advanced techniques are pivotal when attempting to understand extreme events, such as losses incurred during the financial crisis, and complicated loss distributions which may defy traditional estimation techniques.
2. discover how neural networks can be implemented to approximate loss distributions and conduct real-time portfolio optimization.

3/4 objectives:

1. estimate risk measures using parametric estimation and historical real-world data.
2. discover how Monte Carlo simulation can help you predict uncertainty.
3. learn how the global financial crisis signaled that randomness itself was changing, by understanding structural breaks and how to identify them.

2/4 Object:

1. expand your portfolio optimization toolkit with risk measures such as Value at Risk (VaR) and Conditional Value at Risk (CVaR)
2. use specialized Python libraries including pandas, scipy, and pypfopt.
3. how to mitigate risk exposure using the Black-Scholes model to hedge an options portfolio.

Datacamp: https://campus.datacamp.com/courses/quantitative-risk-management-in-python

Course Description
Managing risk using Quantitative Risk Management is a vital task across the banking, insurance, and asset management industries. It’s essential that financial risk analysts, regulators, and actuaries can quantitatively balance rewards against their exposure to risk. This course introduces you to financial portfolio risk management through an examination of the 2007—2008 financial crisis and its effect on investment banks such as Goldman Sachs and J.P. Morgan. You’ll learn how to use Python to calculate and mitigate risk exposure using the Value at Risk and Conditional Value at Risk measures, estimate risk with techniques like Monte Carlo simulation, and use cutting-edge technologies such as neural networks to conduct real time portfolio rebalancing.

1/4 Object:

1. understanding of risk and return
2. how risk and return are related to each other,
3. identify risk factors, and use them to re-acquaint ourselves with Modern Portfolio Theory applied to the global financial crisis of 2007-2008.

Introduction

• Quantitative Risk Management: Study of quantifiable uncertainty
• Uncertainty: (1) Future outcome (2) Outcomes impact planning decisions
• Risk Management: mitigate (reduce effects of) adverse outcomes
• Quantifiable uncertainty: identify fators to measure risk (what factors can cause the uncertainty)
• This project: Focus upon risk associated with a financial portfolio

This project

The Great Recession (2007-2010)

• Global growth loss more than $2 trillion
• United States: nearly $10 trillion lost in household wealth
• U.S. stock markets lost c. $8 trillion in value

Global Finacial Crisis (2007-2009)

• Large-scale changes in fundamental asset values
• Massive uncertainty about future returns
• High asset returns volatility
• Risk management critical to success or failure

Unlock Value of Disparate and Complex Data

Azure Databricks: Unlock Value of Disparate and Complex Data Powered by Azure Databricks Luke Pritchard Avanade, Inc

Vision of Avanade Inc.

To be the leading digital innovator realizing results for our clients through the power of people and the Microsoft ecosystem

The market and clients

• Unlock the value of data at scale
• Get off restrictive legacy systems and create new business models
• Differentiate in the market

The approach

1. Value and design led approach
2. Outcome-based experiments using fast flexible technology
3. Once value is proven, scale and industrialize
4. Continue to expand to multiple value

Inbound Marketing

Inbound marketing position the company as a target that consumers are searching for.

Why Inbound Marketing:

1. the diminished influence of advertising
2. the rise of consumer search

Inbound marketing is a way to engage consumers by creating content, including blogs, podcasts, white papers, and search engine optimization (SEO), so that a company - its brand, products, and services - is found when consumers search for information.