New research helps predict stock market

February 20, 2009
stock market

(PhysOrg.com) -- Researchers from Massey University have developed a new way to predict stock markets that has been recognised with an award from New Zealand finance specialists.

Professor Ben Jacobsen, Associate Professor Ben Marshall and Dr Nuttawat Visaltanachoti have found that analysing data on a daily basis or other shorter intervals - rather than monthly - offers a much higher success rate of stock market predictions.

Traditionally, institutional investors, such as hedge funds or mutual and pension funds, try to predict stock markets one month ahead relying on information also measured at monthly levels.

The academic researchers have moved away from that convention with what they have described as “amazing results”.

The research was awarded best investments paper by the Institute of Financial Professionals at the New Zealand Finance Colloquium this month.

The team studied how changes in prices of energy, such as oil, and industrial metals, such as aluminium and zinc, strongly influence world stock markets.

Dr Marshall says the paper, Return Predictability Revisited, is an eye-opener both practically and academically. “While the change of intervals seems innocent enough, this new approach suggests that stock market returns are much more predictable than previously thought. Economic variables that seemed unimportant now may warrant a second look, but measured at a different interval.

“Professional investors in Europe are already starting to implement this approach. Theoretically, the study is of interest because it shows how an innocuous change in observation intervals has a dramatic impact on the way we think about financial markets in the academic world.

“With hindsight, it seems surprising that many professional investors and academics alike have overlooked the possibility that the interval of observation would make a huge difference in trying to predict markets.”

Dr Marshall says the traditional approach to use monthly observations to predict monthly returns is a “crude” approach based on convention rather than theory. “When predicting March, we are saying look at the last week or even the last day of February because that could be more relevant,” he says. “Using a full month of data to predict may increase noise levels and understate - or even fully mask, the actual predictability present.”

It is the third time Professor Jacobsen has received the investments paper award and the second time for Dr Visaltanachoti.
Researchers from Massey University have developed a new way to predict stock markets that has been recognised with an award from New Zealand finance specialists.

Professor Ben Jacobsen, Associate Professor Ben Marshall and Dr Nuttawat Visaltanachoti have found that analysing data on a daily basis or other shorter intervals - rather than monthly - offers a much higher success rate of stock market predictions.

Traditionally, institutional investors, such as hedge funds or mutual and pension funds, try to predict stock markets one month ahead relying on information also measured at monthly levels.

The academic researchers have moved away from that convention with what they have described as “amazing results”.

The research was awarded best investments paper by the Institute of Financial Professionals at the New Zealand Finance Colloquium this month.

The team studied how changes in prices of energy, such as oil, and industrial metals, such as aluminium and zinc, strongly influence world stock markets.

Dr Marshall says the paper, Return Predictability Revisited, is an eye-opener both practically and academically. “While the change of intervals seems innocent enough, this new approach suggests that stock market returns are much more predictable than previously thought. Economic variables that seemed unimportant now may warrant a second look, but measured at a different interval.

“Professional investors in Europe are already starting to implement this approach. Theoretically, the study is of interest because it shows how an innocuous change in observation intervals has a dramatic impact on the way we think about financial markets in the academic world.

“With hindsight, it seems surprising that many professional investors and academics alike have overlooked the possibility that the interval of observation would make a huge difference in trying to predict markets.”

Dr Marshall says the traditional approach to use monthly observations to predict monthly returns is a “crude” approach based on convention rather than theory. “When predicting March, we are saying look at the last week or even the last day of February because that could be more relevant,” he says. “Using a full month of data to predict may increase noise levels and understate - or even fully mask, the actual predictability present.”

It is the third time Professor Jacobsen has received the investments paper award and the second time for Dr Visaltanachoti.

Provided by Massey University

Explore further: Facebook profit dips as expenses bite into revenue

Related Stories

Venture funding for startups still surging

July 23, 2015

Investors pumped some $32.5 billion into more than 1,800 venture-backed companies around the world in the past quarter, amid feverish interest in tech startups, a survey showed Thursday.

Recommended for you

Earliest evidence of reproduction in a complex organism

August 3, 2015

Researchers led by the University of Cambridge have found the earliest example of reproduction in a complex organism. Their new study has found that some organisms known as rangeomorphs, which lived 565 million years ago, ...

Model shows how surge in wealth inequality may be reversed

July 30, 2015

(Phys.org)—For many Americans, the single biggest problem facing the country is the growing wealth inequality. Based on income tax data, wealth inequality in the US has steadily increased since the mid-1980s, with the top ...

French teen finds 560,000 year-old tooth (Update)

July 28, 2015

A 16-year-old French volunteer archaeologist has found an adult tooth dating back around 560,000 years in southwestern France, in what researchers hailed as a "major discovery" Tuesday.

3 comments

Adjust slider to filter visible comments by rank

Display comments: newest first

Soylent
5 / 5 (2) Feb 20, 2009
The recursive nature of stock markets makes them exceedingly difficult to predict. Your model needs to be designed to include the behaviour of other stock market participants. If other stock market participants begin using your model their actions will distort the stock-market so that your predictions become less accurate. It's red queen's race, need to keep running as fast as you can just to stay in the same place.
googleplex
4 / 5 (1) Feb 20, 2009
I agree.
It is like a technological war between large trading houses. Yesterdays models won't work today. They hire the brightest academic minds to build the models.
Another point is that if the model is so good how come they aren't billionaires already instead of wasting time writing research papers.
It is no suprise to me that a 30 day moving average is worse at forecasting tomorrow than a 7 day moving average. Any serious investor knows that moving averages are not designed for daily predicting a spot price. They are designed to signal a change in trend and figure out support levels/trading ranges etc. Trend is your friend.
menkaur
not rated yet Feb 21, 2009
The recursive nature of stock markets makes them exceedingly difficult to predict.

not difficult.... it's impossible...
once research on some regularity in market becomes public, it's useless
so, i'd call the article bullshit...

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.