Jun
25
Many thanks to Anthony who emailed me the link to this competition.
So you are a quant-gambler? time to stand out!
Traders, analysts, investors and hedge funds are always looking for techniques to better predict stock price movements. The 2010 INFORMS Data Mining Contest takes aim at this goal, requiring participants to build models that predict the movement of stock prices over the next 60 minutes.
Knowing whether a stock will increase or decrease allows traders to make better investment decisions. Moreover, good predictive models allow traders to better understand what drives stock prices, supporting better risk management. The results of this contest could have a big impact on the finance industry.
The submission deadline is October 10th 2010. Final results will be announced on October 12th. The winners of this contest will be honoured at a session of the INFORMS Annual Meeting in Austin-Texas (November 7-10).
Check the detail of this competition at http://kaggle.com/informs2010
So you are a quant-gambler? time to stand out!
Traders, analysts, investors and hedge funds are always looking for techniques to better predict stock price movements. The 2010 INFORMS Data Mining Contest takes aim at this goal, requiring participants to build models that predict the movement of stock prices over the next 60 minutes.
Knowing whether a stock will increase or decrease allows traders to make better investment decisions. Moreover, good predictive models allow traders to better understand what drives stock prices, supporting better risk management. The results of this contest could have a big impact on the finance industry.
Quotation
Competitors will be provided with intraday trading data showing stock price movements at five minute intervals, sectoral data, economic data, experts' predictions and indices. We have provided a training database to allow participants to build their predictive models. Participants will submit their predictions for the test database (which doesn't include the variable being predicted). The public leaderboard will be calculated based on 10 per cent of the test dataset.
The submission deadline is October 10th 2010. Final results will be announced on October 12th. The winners of this contest will be honoured at a session of the INFORMS Annual Meeting in Austin-Texas (November 7-10).
Check the detail of this competition at http://kaggle.com/informs2010
Jun
24
Quotation
Writing program code is a good way of debugging your thinking - Bill Venables
Believe it or not, on average programmers spend 70% of their working time in debugging (I don't know where this number is from but I do believe so). A good debug tool, command or even habit will definitely improve your work efficiency, shorten working hour, and enjoy more the world cup. When it comes to Matlab and R, I have to say the debugging in Matlab is straightforward but is more comprehensive in R. Here is an introductory video demonstrating how to debug and understand Matlab codes:
Also a very good PDF document for debugging in R with detailed examples at http://www.biostat.jhsph.edu/~rpeng/docs/R-debug-tools.pdf. Enjoy.
Jun
22
There are multiple ways of profiting in forex, including swing trading or trend following. However, scalping is the method with the shortest trading periods. With this method, traders usually open a trade for 1-2 minutes, or 5 minutes at the very most. The idea is to benefit from short fluctuations in the market.
This series of articles will serve as a guide for scalping, but for the purpose of introduction, we can ask what makes this strategy popular and effective. Many of these considerations will then serve as the topics of further articles.
The first major reason for scalping is perceived safety. Scalping has a far shorter time frame than the other forex methods, and many traders argue that this limits their exposure to the market.
Of course, this limited exposure leads to a second major characteristic of scalping—a large number of trades. Some scalpers may open and close as many as several hundred trades within a single trading day.
This points to one of the major challenges for this style of trading. Since the number of trades is extraordinarily high, scalpers must find forex brokers with low transaction costs and fees. Before considering this style, make sure that your broker’s commission structure allows for you to be profitable.
A third characteristic is the fact that scalpers rely on some type of leverage. The profit from each trade is generally quite small, and even with a huge number of orders, the results would hardly be worthy of the effort. Depending on the amount of leverage you use, this can eliminate any real security. In spite of their arguments to the contrary, scalpers can lose a day’s work in a few bad transactions.
This series of articles will serve as a guide for scalping, but for the purpose of introduction, we can ask what makes this strategy popular and effective. Many of these considerations will then serve as the topics of further articles.
The first major reason for scalping is perceived safety. Scalping has a far shorter time frame than the other forex methods, and many traders argue that this limits their exposure to the market.
Of course, this limited exposure leads to a second major characteristic of scalping—a large number of trades. Some scalpers may open and close as many as several hundred trades within a single trading day.
This points to one of the major challenges for this style of trading. Since the number of trades is extraordinarily high, scalpers must find forex brokers with low transaction costs and fees. Before considering this style, make sure that your broker’s commission structure allows for you to be profitable.
A third characteristic is the fact that scalpers rely on some type of leverage. The profit from each trade is generally quite small, and even with a huge number of orders, the results would hardly be worthy of the effort. Depending on the amount of leverage you use, this can eliminate any real security. In spite of their arguments to the contrary, scalpers can lose a day’s work in a few bad transactions.
Jun
21
Although I have shared several ways to download data from Yahoo Finance, for instance, Yahoo chinese historical stock data, download option price data from Yahoo, I have to admit the one I recommend today is the best and most comprehensive ever. It supports dozens of tags to download, besides what we normally need for closing price, volumn, daily high, and daily low, including (click the graph to see a clearer picture):
Massive, isn't it? download the csv file and also a file for option data at http://www.gummy-stuff.org/Yahoo-data.htm
Massive, isn't it? download the csv file and also a file for option data at http://www.gummy-stuff.org/Yahoo-data.htm
Jun
16
Any expert in R please educates me. I have got a problem about the sapply (or lapply), it made me headache for over two hours.
As "for loop" is very slow in R, we should try best to avoid using it, and to use vectorization instead. sapply is designed for this, for example, instead of:
we could use
It went well, but what if besides computing z, I need to update another variable, for example, with loop, it is
in this case, temp is changing every step (it doesn't have to be a function of z[i]). How to vectorize that and use sapply then? since sapply can't return two variables z and temp.
I tried to define a matrix and store z in the first column and temp in the second column and return the matrix, however, failed.
Many thanks.
As "for loop" is very slow in R, we should try best to avoid using it, and to use vectorization instead. sapply is designed for this, for example, instead of:
for (i in 1:10) {
z[i] <- mean(x[1:i])
}
z[i] <- mean(x[1:i])
}
we could use
z <- sapply(1:10, function(i, x) {mean(x[1:i])}, x)
It went well, but what if besides computing z, I need to update another variable, for example, with loop, it is
temp <- 3
for (i in 1:10) {
x[i] <- x[i]-temp
z[i] <- mean(x[1:i])
temp <- x[i]-z[i]
}
for (i in 1:10) {
x[i] <- x[i]-temp
z[i] <- mean(x[1:i])
temp <- x[i]-z[i]
}
in this case, temp is changing every step (it doesn't have to be a function of z[i]). How to vectorize that and use sapply then? since sapply can't return two variables z and temp.
Many thanks.
Quantitative Finance Collector is simply a record of my financial engineering learning journey as a master in quantitative finance, a PhD candidate in finance and a Quantitative researcher, with most of the entries written at school. 
