IRENE ALDRIDGE is managing director and quantitative portfolio manager at ABLE Alpha Trading and president of ABLE Markets. She is author of Searching for High-Frequency Trading Opportunities and High-Frequency Trading.

STEVE KRAWCIW is CEO of ABLE Markets, a leader in market microstructure analytics. His experience comes from such firms as McKinsey & Co. and Credit Suisse, and he is coauthor (with Irene Aldridge) of Quant Investor Almanac 2011.

Risk management solutions for today's high-speed investing environment
Real-Time Risk is the first book to show regular, institutional, and quantitative investors how to navigate intraday threats and stay on-course. The FinTech revolution has brought massive changes to the way investing is done. Trading happens in microsecond time frames, and while risks are emerging faster and in greater volume than ever before, traditional risk management approaches are too slow to be relevant. This book describes market microstructure and modern risks, and presents a new way of thinking about risk management in today's high-speed world. Accessible, straightforward explanations shed light on little-understood topics, and expert guidance helps investors protect themselves from new threats. The discussion dissects FinTech innovation to highlight the ongoing disruption, and to establish a toolkit of approaches for analyzing flash crashes, aggressive high frequency trading, and other specific aspects of the market.
Today's investors face an environment in which computers and infrastructure merge, regulations allow dozens of exchanges to coexist, and globalized business facilitates round-the-clock deals. This book shows you how to navigate today's investing environment safely and profitably, with the latest in risk-management thinking.
* Discover risk management that works within micro-second trading
* Understand the nature and impact of real-time risk, and how to protect yourself
* Learn why flash crashes happen, and how to mitigate damage in advance
* Examine the FinTech disruption to established business models and practices
When technology collided with investing, the boom created stratospheric amounts of data that allows us to plumb untapped depths and discover solutions that were unimaginable 20 years ago. Real-Time Risk describes these solutions, and provides practical guidance for today's savvy investor.

Preface
Chapter 1: Silicon Valley is Coming!
Everyone is into FinTech
The Millenials Are Coming
Social Media
Mobile
Cheaper and Faster Technology
Cloud Computing
Blockchain
Fast Analytics
FinTech
In the End, It's All About Real-Time Data Analytics
End of Chapter Questions
Chapter 2: This Ain't Your Grandma's Data
Data
The Risk of Data
Technology
Blockchain
What elements are common to all blockchains?
Conclusions
End of Chapter Questions
Chapter 3: Dark Pools, Exchanges and Market Structure
The New Market Hours
Where do my orders go?
Executing Large Orders
Conclusions
End of Chapter Questions
Chapter 4: Who Is Front-Running You?
Spoofing, Flaky Liquidity and HFT
Order-Based Negotiations
Conclusions
End of Chapter Questions
Chapter 5: High-Frequency Trading in Your Backyard
Implications of Aggressive HFT
Aggressive High-Frequency Trading in Equities
Aggressive HFT in U.S. Treasuries
Aggressive HFT in Commodities
Aggressive HFT in Foreign Exchange
Conclusions
End of Chapter Questions
Chapter 6: Flash Crashes
What Happens During Flash Crashes?
Detecting Flash-Crash Prone Market Conditions
Are HFTs responsible for flash crashes?
Smart Beta and Flash Crashes
Conclusions
End of Chapter Questions
Chapter 7: The Analysis of News
The Delivery of News
Pre-announcement risk
Data, Methodology and Hypotheses
Conclusions
End of Chapter Questions
Chapter 8: Social Media and the Internet of Things
Social Media and News
Timeliness of Data Analysis
What Are Other Investors Thinking? If You Knew, Would That Be A Great Benefit To You?
Internet Sentiment: How FinTech Decides How You Are Feeling with Natural-Language Processing
The Internet of Things
Tracking shipments, fleets and supplies in real time
Conclusions
End of Chapter Questions
Chapter 9: Market Volatility in the Age of Fintech
Too Much Data, Too Little Time - Welcome, Predictive Analytics
Is Volatility a Trend to just Live With?
Want to Lessen Volatility of Financial Markets? Express Your Thoughts Online!
The Market Microstructure Frontier Is the New Variable in Portfolio Optimization
Yes, You Can Predict T+1 Volatility
Market Microstructure as a Factor? You Bet.
Case Study: Improving Execution in Currencies with AbleMarkets Aggressive HFT Index
For Longer-Term Investors, Following Aggressive HFT Pays
Conclusions
End of Chapter Questions
Chapter 10: Why Venture Capitalists Are Betting on FinTech to Manage Risks
Opportunities for Disruption Are Present and They May Not Be What They Seem
Data and Analytics in FinTech
FinTech as an Asset Class
FinTech Success Factors
The Investment Case for FinTech
How do FinTech Firms Make Money?
Conclusions
End-of-Chapter Questions
About the Author
Index