The document discusses algorithmic trading, detailing trends, strategies, and the development of an advanced forecasting algorithm by I Know First, which predicts movements across over 1,400 markets and achieved a 60.66% return in 2013. It contrasts high-frequency trading and quantitative trading methods while highlighting the implications of recent regulatory scrutiny aimed at high-frequency trading practices. Additionally, it emphasizes the importance of machine learning, genetic algorithms, and maintaining competitiveness in a rapidly evolving market landscape.

1. Algorithmic
Trading
Latest
Trends &
Developments
Dr. Lipa Roitman
Yaron Golgher
Founder
CEO
www.iknowfirst.com
© I Know First 2014. All rights reserved.

2. is a financial startup that
provides daily investment foresight based on
an advanced self-learning algorithm

3. We developed an advanced algorithm
based on artificial intelligence and machine
learning that also incorporates elements of
artificial neural networks and genetic
algorithms
Dr. Lipa Roitman, a scientist with over 20
years of experience, led our R&D team to
develop and consistently enhance the
algorithm
Our live portfolio from 2013 returned 60.66%
in 12 months beating the S&P 500 by 31.27%

4. A unique financial market forecasting algorithm that analyses, models and
predicts over 1,400 markets for short and long term:
Stocks
Commodities
ETF’s
Interest Rates
Currencies
World Indices
Firms that can consistently recognize the most opportunities and
overall trends has the key to the market

5. What is Algorithmic Trading? General
Market
Data
Market
Data
Market
Data
Algorithms
An Advanced Mathematical Model
Market
Data
Market
Data
Buy & Sell Orders
60% -70% of the US equity market volume

6. Two Methods of Algotrading,
High-Frequency and Quantitative Trading
1. High-Frequency Trading (HFT)
Real time intelligence, in milliseconds:
 Place and quickly cancel small orders to find at what price the
buyers and sellers are ready to trade.
 Price-volume info to catch developing trends.
 Simultaneously process volumes of information - human traders
can’t compete.
 Liquidate positions at the end of the day.
Technological costs of HFT are enormous.
High competition-low profit.

7. Two Methods of Algotrading,
High-Frequency and Quantitative Trading
2. Quantitative Trading, or Longer Term Trading
Algorithms analyze the structure and the trends in the market, find
predictable patterns, and trade upon the machine derived
forecasts.
Suitable for most investors
Some of the trading strategies:
Trend following vs. mean reversion:

When to use which?
Market neutral
Delta neutral
Arbitrage

8. Advantages of Algotrading
Human
Factors
Costs
Objective
valuation of
the stock
Psycholgical
Pressures
Risk
Algotrading
Quantitative
forecasting
the future
stock trend
Lower cost of
trading due to
the high
volumes
Volatility
Reduced
buy-sell
spreads, esp.
in most liquid
securities

9. Why Governments are Clamping Down on HFT?
HFT is unfair to retail investor

The HFT traders have the first choice in the trade - a form of
scalping
Level field needed to give everyone an equal chance.
Several European countries and Canada are curtailing or banning HFT
due to concerns about volatility and fairness.

In crisis the algos liquidate positions in seconds, causing huge
imbalances and price swings

10. HFT and Volatility
Has algotrading evolved in recent years to pose less risk on the general
market?
The risk is still present.

Notable examples:

May 6, 2010 Flash Crash. The algorithms may have
caused it, but also quickly corrected it.

January 23, 2013 AAPL plunge

11. Latest in Algotrading
Interpreting news and automatic trading by the
machines.

12. It’s all about speed!

13. It’s All About Speed!
Advertising campaign by Dow Jones on March 1, 2008:

Claimed that their service had beaten other news services by 2 seconds
in reporting an interest rate cut by the Bank of England.

14. What is Machine Learning?
Mathematics, statistics and logics are the crucial tools in studying
the markets.
They offer testable, verifiable and predictive hypothesis.
Number crunching allows finding hidden laws, not obvious to
humans.

15. Steps in Machine Learning
Provide
Framework
Mathematical
Tools
Programming
Tools
Give
Examples
To Learn From
Input
Output
Fitness
Function
Sequential
What should be An algorithm is a
optimized?
step-by-step
procedure
Example: Make
more good
predictions than
bad ones
Generalization
Requirement
Discover the laws
connecting the input and
output, cause and effect
Critical for forecasting
ability

16. Example Goal: Minimize the
Fitness Function

17. What is a Genetic Algorithm?
There are a number of search algorithms, from simple to complex, and
genetic is one of them.
Genetic algorithm is used for the most difficult problems, where exact
relationships are unknown, and maybe non-existent.
Many solutions are in the “gene” pool, some good, some not so.
Each solution is like a chromosome in genetics, hence the analogy.
Genetic is a circular iterative algorithm.

18. Genetic Algorithm
Reject
Gene
Pool
Select
Genetic
Algorithm
Mutate

19. Steps in Genetic Algorithm
Genetic algorithm uses these ways to improve the gene (solutions) pool:
Combination:
 Combine two or more solutions in hope of producing a better solution.
Mutation:
 Modify a solution in random places in hope of producing a better
solution.
Crossover:
 Import a solution from a similar problem
Selection:
 Survival of the fittest

20. A unique financial market forecasting algorithm that analyses, models and
predicts over 1,400 markets for short and long term:
Stocks
Commodities
ETF’s
Interest Rates
Currencies
World Indices
Firms that can consistently recognize the most opportunities and
overall trends has the key to the market

21. Loyal and Growing Client Base
Larger Institutions
Hedge Funds
Family Offices
Investment managers
– Fund manager & I Know First subscriber
Financial advisors
Professional investors
Hundreds Of Clients
Worldwide
I Know First grew 400% in
2013 from all over the world

22. Academic Cooperation
Dr. Roitman lecture in Tel-Aviv
University (View it Here)
Projects with Harvard Business
School
Partner with international
Universities-internship programs,
lectures

23. Market Trends
Transparency
S&P 500
Competition
There is more transparency than ever of fund
performance
To retain and attract new investors as well as other
mutual funds, a firm should be able to beat the S&P
500 on a regular basis
• Competition amongst investment firms is higher
than before
• To stay competitive investment banks are looking
for the most advanced tools to enhance their
performance

24. Customer Challenges
Complex
Market Evolution
The market is evolving beyond
previously established theories
however customers still expect
strong and consistent returns
of Traditional Tools and
Fundamental Analysis
Investment Firms
Traditional tools and fundamental
analysis are not enough to stay
competitive in the contemporary
market
Investment firms need to stay one
step a head in order to be the first
to recognize trends and take
advantage of opportunities

25. The Algorithm
Tracks and predicts
the flow of money
from one market or
investment channel
to another
Artificial
Intelligence
(AI)
The system is a
predictive model based
on Artificial Intelligence,
Machine Learning, and
incorporates elements of
Artificial Neural Networks
and Genetic Algorithms
I Know First
predicts 1,400+
investment
channels daily
Artificial
Neural
Networks
The results are constantly improving as the algorithm learns from its
successes and failures

26. Synopsis of the algorithm
Daily data is
added to our 15
years historical
file
Run a learning & prediction
cycle with new combined data.
Daily predictions for
each stock, currency,
commodity, etc..

27. Daily Market Heat Map
Two indicators:
Signal – Predicted movement of the
asset
Predictability Indicator – Historical
correlation between the prediction and the
actual market movement

28. XOMA returned 61.45% in
1 month from this forecast
Two indicators:
Signal – Predicted movement of the asset
Predictability Indicator – Historical correlation between the
prediction and the actual market movement

29. Forecast vs. Actual

30. I Know First Sample Portfolio
60.66% Return in 1-year beating
the S&P by over 30%
Click To View

31. Main Features of the Algorithm
Identifies The Best Market Opportunities Daily
6 Time Frames
Tracks Over 1,400 Markets
Self-Learning
Adaptable
Always Learning New Patterns
Scalable
A Decision Support System (DSS)
Predictability Indicator
Strong Historical Performance – 60.66% gain in 2013
The algorithm becomes more and more accurate with every prediction as it
constantly tests multiple models in different market circumstances

32. Algorithmic Trading Strategies
To Implement With Mutual Funds
Top
Stocks
Forecast
Currencies
Prediction
Interest
Rates
Forecast
Industry
Forecast
Customized
Algorithmic
Forecast
Dividend’s
Forecast
Gold
Prediction
Commodities
Prediction
Conservative
Stock
Forecast
ETF’s
Forecast
World
Indexes
Forecast
Aggressive
Stock
Forecast
European
Stock
Forecast

33. Algorithmic Trading
Strategies To Implement With
Mutual Funds
Assess Risk
Aggressive Stock Forecasts
Conservative Stock Forecasts
Assets That Carry A Dividend
Aggressive Dividend Forecasts
Conservative Dividend Forecasts
Recognize Top Performers In Each Industry
Bank Stocks Forecasts
Best Tech Stocks
International Opportunities
European Stock Forecast
Custom Forecasts
Customized Algorithmic
Forecast

34. Algorithmic Trading
FIVE Strategies To Implement
With Mutual Funds
Buy All Assets In The Forecast
Of Equal Weights
* Live Portfolio is based on this strategy *
Only Buy Stocks With High Predictabilities
* A predictability of .2 is good but .5 is excellent *
Buy Stocks That Have A Strong
Signal In Each Time Horizon
Multiply the Signal And The
Predictability Indicator Together
Identify New Opportunities and
Double-Check Your Analysis
Optimize Returns
&
Reduce Risk

35. Algorithmic Trading Tactical
Approach
The first appearance of a stock does not mean buy it at any price that
same day

Put it in a watch list, unless there is significant discount of at least
3%
Recognize the general color of the heat map
Consider the forecasts for major indexes to get an overall picture of the
market trend

We advise not to trade against
the general market trend
When analyzing stocks, review the specific industry
forecast as well

36. Algorithmic Output Chart: ALU

37. Apple Inc. AAPL Bubble Crash
Financial Bubble Detection

38. Algorithmic Output Chart: NOK

39. Two different types of algorithmic outputs
 Heat maps
 Charts
Algorithmic trading is becoming more popular as it has
proven more effective than traditional forms of analysis
alone.
 Algorithm’s are the future of financial analysis
Network Virtualization
S&P 500
Level of Confidence
 The self-learning algorithm not only gives you a
prediction but its level of confidence as well
Investing
Track record of regularly beating the S&P 500
 I Know First beat the S&P 500 by over 30% in
2013
Exchanges
1,400+ assets are forecasted
Forecasting
Key Advantages of I Know First:
Algorithmic Trading
39

40. Recent Publications
How Can We Predict The Financial Markets By
Using Algorithms? Tel-Aviv University Lecture –
Dr. Roitman
Seeking Alpha articles – Dr. Roitman
Seeking Alpha articles –I Know First Research

41. Algorithmic Trading With