Big Data in Finance - The Daily Reckoning
The Daily Reckoning by Bill Bonner
On This Day - 26 April 2014
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- By Asad Dossani, Author, The Lucrative Derivative Report

Asad Dossani
The financial industry has experienced rapid change and development in recent years. One of the important revolutions taking place is the impact of big data in finance. Big data refers to the analysis of large datasets. In the technology sector, this has been primarily used to market custom products to each consumer based on their past behavior.

In finance, the data revolution has resulted in the increased prominence of algorithmic trading. Algorithmic trading is rule based trading with specific buy and sell instructions for any given trade based on previous price behavior. In many ways, it is a sophisticated form of technical analysis, something that has been around for a long time.

The rise in algorithmic trading has occurred for two reasons. The first is increased availability of data. It is possible for anyone to get daily data for free for any asset you could want to trade. Live intraday charts are also freely available to anyone with a brokerage account. The second reason is the increased computing power and ability to process large datasets. As our computers become powerful, it is easier and faster to crunch numbers and develop numerical trading strategies.

The primary advantage of algorithmic trading is its rule based approach that rules out discretionary trading decisions. This means that all emotion is removed from the trading process, and once a trading strategy has been determined; there is no room for human intervention. This type of approach is increasingly popular due to its positive results.

The primary engine of algorithmic trading is backtesting. Backtesting is when we test our trading strategies on historical data to see how they would perform. This is really where the big data comes into play. We can only create these algorithms by analyzing large datasets of historical price data.

We won't know for sure whether big data in finance will remain in place forever. What we do know is this: the use of big data in finance is rising, and the use of algorithmic trading in finance is increasingly popular. For now, the big data and algorithmic trading are here to stay.

As investors, we have a great opportunity to take advantage of this data revolution in finance. I am working on algorithmic trading strategies, and I hope to share some of these with you in the future.

In this week's Equitymaster club forum, we are asking the question: "How do you plan to take advantage of the data revolution in finance?" Please login and post your views.

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is a financial analyst and columnist. He actively trades his own and others' funds, investing primarily in currency, commodity, and stock index derivative products. Prior to this, he worked at Deutsche Bank as an analyst in the FX derivatives team. He is a graduate of the London School of Economics. Asad is a keen observer of macroeconomic trends and their effects on global financial markets. He is deeply passionate about educating investors, and encouraging individuals to take part in and profit from financial markets. To put it colloquially, he wishes to take Wall Street products and turn them into Main Street profits!

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3 Responses to "Big Data in Finance"

Binodgopal Mukherjee

May 2, 2014

Thanks Asad.

The advantage of new technology, if it helps to reduce risk and increase our income, we the retail investors should try to know the same and then apply.

So, why don't you take us to a step by step guide for algo trading.

Regards
Binod

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Anil R. Punjabi

Apr 27, 2014

Hello Asad !

i read your weekend editions of 'The Daily Reckoning'. Thanks for writing such sensible stuff.

As Warren Buffett has said: We need to know only two investing theories: one, how to value a business and two, the meaning of market prices. Such a valuable insight.

Why do we need to know about algorithmic trading and so many other techniques, which have a value of their own but may not be suited for many, if not most of us.

Long term investing is what your fund house has been advocating and i am fully in agreement with that.

Keep up the good work !

Regards

Anil

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Raviraj

Apr 27, 2014

Thanks Asad for sharing the details regarding algorithmic trading.
In my opinion algorithmic trading is best applicable for Financial institutes / Banks and not for retail investors as backtesting usually works on historic data. As Investors/Mid-term traders we may need to apply discretion to take decisions based on how price action unfolds.

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