Algorithmic Trading: How to Trade Using Algorithms

A Tech Stock Algorithmic Forecasting Performance Analysis from June 30th – September 30th

Stock analysts and investors are quickly being substituted by powerful computerized algorithms. Unlike traditional algorithms, todays advancements utilize advanced self-learning algorithms to analyze, model and predict markets. Unlike analysts who look mainly at the specific company’s performance they are analyzing, the algorithm supervises the movement of money in all markets. This allows it to forecast not only stocks, but also ETF’s, world indices, gold, currencies, interest rates, and commodities. It holds a significant advantage over analysts in many ways, such as:

  • Algorithms can continuously look at the money movement between markets, they require no sleep and no rest.
  • Algorithms never forget any information they have gathered, and past lessons they have learned.
  • Algorithms are never biased, corrupt, or serve hidden interest.

One of the fastest growing among these is the IKF Algorithm. It is unique in that it predicts the flow of money in almost 2,000 markets from 3-days to a year.  It is managed by I Know First holding, which is attempting to break the stigma of HFT (high frequency trading) to show that an accurate long term forecast can yield similar earnings with much lower risks than HFT. These long term predictions are also much more suitable for long term investors such as pension funds, insurance companies, and banks. Clients receive an output table with three indicators: the ticker, the signal, and the predictability.

Algorithmic Trading

IKF analystAlgorithmic Tradings ask the Algorithm for a particular stock, or type of stock, with a particular time period.  A client looking to invest in the tech industry for the three months period July, August, and September requested a breakdown of the systems forecast. The algorithms then generates a table, and sorts the tickers by signal strength (from positive to negative) for that particular time period. When assets do not reach the necessary predictability threshold (the algorithm is not confident enough in its own results) they get filtered out of the table.  Below are the top 10 forecasts for June 30th, 2014.

The June 30th three months forecast recommends the client the following tech stocks as the top 10 strongest signals (highest expected yield):

Tech Stocks Summary

Algorithmic Trading

Himax Technologies Inc.

Himax (HIMX) is a fabless semiconductor company headquartered in Tainan City. Their technologies are used in the OLPC XO-1 subnotebook laptop computer, more commonly known as the 100$ laptop. Himax stocks began to soar after Google announced it will take a 6.3% stake in Himax technologies as a future investment for their Google glass technology.

Algorithmic Trading


Google (GOOG) is an American multinational cooperation specializing in internet related services. The bulk of googles income is gathered through Google AdWords, which is the native advertising within its search engine, which is often embedded in other websites as well.

Algorithmic Trading

Aixtron SE

Aixtron (AIXG) although registered in Europe under the SE legal entity (European Corporation) is a German based company, traded on the Frankfurt stock exchange as AIXA and on NASDAQ as AIXG. The company specializes in manufacturing metal organic chemical vapor deposition (MOCVD) equipment, for clients in the semiconductor industry.

Algorithmic Trading

Yahoo! Inc.

Yahoo (YHOO) is an American multinational Internet corporation most noteably known for its web portal offering varying services such as search, mail, news, and finance. Yahoo stock has been steadily rising since October 2013 after a 5 year period of stagnation.

Algorithmic Trading

Check Point Software Technologies Ltd.

Check Point Software Technologies (CHKP) is an international provider of hardware and software IT security solutions such as:  network security, endpoint security, data security and security management. CHPK stock has been rising throught the economic recession steadily since 2008.

Algorithmic Trading

ARM Holdings plc

ARM Holding (ARMH) is a British multinational semiconductor and software design company with its head office in Cambridge, England. ARM processors are used as the main CPU for most mobile phones, including those manufactured by Apple, HTC, Nokia, Sony Ericsson and Samsung.

Algorithmic Trading

Priceline (PCLN) is an American website based company which facilitates between suppliers and costumers of airline tickets and hotel bookings. In October 2008 stock value was at 52$, the price soared to a peak on may 5th of 1370$. After its IPO in 1999 the company soared and lost all its value (Dot-com bubble and 9/11 which was particularly bad for any air travel related company), however after surviving the recent financial crisis the company proved to a be a solid asset to any investor who doubted it., Inc.

Algorithmic Trading

Amazon (AMZN) is the world’s largest internet company based on revenue and employees; however, its operating income is much smaller than Google’s. Nonetheless, since 2008 Amazon stock value has been rising, largely due to their diversification into services such as internet and logistic solutions, which is a large potential growth sector for the company.

Algorithmic Trading

EMC Corporation (stylized as EMC²)

EMC (EMC) is an American multinational corporation which offers data storage, information security, virtualization, analytics, cloud computing and other products and services that enable businesses to store, manage, protect, and analyze data. EMC has 60,000 employees and is considered the world’s largest provider of data storage systems, competing against NetApp, IBM, Hewlett-Packard, and Hitachi Data Systems.

Algorithmic Trading

International Business Machines Corporation

IBM (IBM) is an American multinational technology and consulting corporation specializing in the manufacturing and marketing of computer hardware and software, and offers infrastructure, hosting and consulting services in areas ranging from mainframe computers to nanotechnology. IBM has history ranging from the late 1800’s and is is one of the oldest technology companies.

Analysts continuously compare the results of the algorithm to the actual market outcomes. In order to do so the table below displays 4 columns.

  • Column 1. The Symbol
  • Column 2. The Algorithms Forecast
  • Column 3. The Actual Percent Change
  • Column 4. The accuracy


What has the algorithm forecast right, and what wrong:

  • An investor who invested all his money in the systems strongest signal (HIMX) would have made a return of 55.91% in 3 months.
  • An investor who spread his money evenly between the top 5 signals would have made a return of 16.7% in 3 months.
  • An investor who spread his money between the top 10 signals would have made a return of 9.21% in 3 months.
  • The system was wrong on 3 forecasts (ARMH, PCLM, AMZN); however, too a maximum degree of 3.89% (in comparison to the positive 55.91% of the best stock).
  • An investor with a typical S&P 500 portfolio would have made a return of 0.58% during this particular 3 months period.


The impressive results are only a small fraction of what the IKF Algorithm can do. Technology has been taking over every problem humans had over the last century. It was only the high unpredictability of financial markets that prevented computers from replacing human traders and analysts; however, with the advancement of neurological and DNA programming it is now a new era for financial trading. Although IKF is the most advanced and accurate algorithm yet, it is interesting to see when large trading firms and banks enter the market of long term algorithmic forecasting, and if they do so, if it wont be too late (Neurological and DNA algorithms require many years to evolve themselves into an accurate consistent trading algorithm).

I Know First Research is the analytic branch of I Know First, a financial start up company that specializes in quantitatively predicting the stock market. This article was written by Daniel Hai one of our interns. We did not receive compensation for this article, and we have no business relationship with any company whose stock is mentioned in this article.