You need to account for time of the day. Randomize that as well. Also, I would use multiple coins. If you want historical data pm me.
I'll look into randomizing the time for trading if I get around to figuring out how to use Bitcoinica's API and automate this trading. What do you mean by multiple coins? The coin you use could be biased. Maybe part of the coin is worn down leaving one side heavier than the other. To truly test for stochasticity there should also be 1000 people tossing the coin. I will run a simulation within the week and post my results here. Basically what I will do is take 5 dice using random.org's algorithm. If 3 out of 5 of the dice are even numbers then that is buy bitcoins with USD, if 3 out of the 5 dice are odd then sell bitcoins for USD. If a buy position is already set then further buys will be a hold position. If a sell position is already set then further sells will be a hold position. Keep up the experiment. I love stochastic processes. It is what I work on in my day job. |
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I'm thinking of starting a trading experiment based on randomness. I tend to believe markets, like complex systems in general, are mostly chaotic and unpredictable. If this is true, then a random trading strategy should be as good as any. So, I figure it's time to put to practice an idea I've considered, as dictated by fine, ancient Persian customs, both sober (earlier) and inebriated (now): Starting 7th January 2012, 10 AM GMT, I intend to start a trading account, fund it with, say, 100 dollars (dollars to keep better protected from BTC volatility, 100 to make it a bit more interesting), and choose, by flipping a coin, every 24 hours whether to buy or sell. If I hold BTC and the coin says sell, I'll sell, if it says buy, I'll hold on, and vice versa.
I'd like input on a few things, keeping in mind I'm obviously willing to take total loss on my investment here:
-Is there any difference to starting an account on Bitcoinica or Mt. Gox, given that I intend to take a very low risk profile to prevent some sudden zhoutonging from mucking up the experiment. Currently I'm leaning towards simply making a new Gox account, but having a 1:1 Bitcoinica account would let me just take a screenshot of the current net value every day.
-How much should I trade with? I guess without leverage I may as well go all in, simply trading my entire balance at a time either way, as dictated by the coin toss.
-Apart from "this is a tremendously bad idea", is there anything I'm not considering here?
You need to account for time of the day. Randomize that as well. Also, I would use multiple coins. If you want historical data pm me. |
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There must be some delay between the customer accepting the quoted price and exchanging the coins. There probably aren't any merchants with sale volume high enough for it to matter right now though. I remember the silk road people complaining about it awhile back.
Volatility is a big problem for merchants. Say I have a crowdfunding website where people contribute bitcoins to projects. If a bitcoin has lost 25% of its value from the USD in one day then that is a problem for a project that just finished being funded. Unless they only purchase all items and labor with bitcoins, they will have to go back and get more money. Margins are already small as it is and volatility makes it worse. Silk Road hedges their risk so that the merchant will pull out more or less bitcoins based on the volatility of bitcoins. |
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It's totally illegal now because the parlament just approved laws that impose the use of cash up to 1000 eur, for more you have to use a bank account. So bitcoin = money laundering in italy = jail.
In that case I hope you are connecting to this forum using Tor. |
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People here is really crazily paranoid but we understand.
There is a difference between paranoia and vigilance. Paranoia (par·a·noi·a) - Baseless or excessive suspicion of the motives of others. Vigilance (vig·i·lance) - The state or quality of being keenly watchful to detecting danger. |
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Awesome... I've been meaning to look into R. This will be a great starting place.
R is nice to use. When you play around leave some comments here about your R adventures. |
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They said they got 1000 bitcoins so far and on their website they say they made about 39 bitcoins. That is 3.9%. I wonder where that 3.9% is coming from...
So here is a question. They take a 1.75% fee when you withdraw. Lets say you put in 100 bitcoins but you nothing happens, No return is made. You withdraw your money. Is the 1.75% withdraw fee on all your money or only on a profit you generate? In this hypothetical account of 100 bitcoins, does the client get her 100 bitcoins back or is she only able to withdraw 98.25 bitcoins?
I am not saying it is a scam but I am not going to put my money in there because I don't see enough transparency in bitscalper.com. They claim their country has strict financial laws, but they don't claim their country. Since their laws are so overbearing, the site management has to stay anonymous. There is a way to stay anonymous and still have a reputation. They can build a reputation on the btc-OTC web of trust and still not use a real name. The site can be completely legit, but someone hacks it. You don't know who you are sending money to already and if you contact them how do you know if you are talking to the right people?
Another way in building trust is to open up part of your model to everyone to see. I don't like black boxes. I am sure your model is proprietary, but Bernard Madoff would say the same thing. His model was to get money from X, Y, and Z then take x% of Z's money and give to X and Y.
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I am about to use the R platform to do some back-testing on bitcoin trading on MTGOX and wanted to share some of the ways to input the data into R. R is a programming language for statistical computing and graphics. It is free and can be downloaded at R-project. First we need to get some data. The only data I found was the raw data from MTGOX and bitcoincharts. So I got the data from bitcoincharts and formatted so I could use it in a financial analysis package. getMTGOX <- function ( days ) {
url1 = "http://bitcoincharts.com/t/trades.csv?symbol=mtgoxUSD"
url2 = "&start="
url3 = "&end="
a = Sys.Date()
b = as.POSIXlt(a) #Convert to unixtime
time = days * 86400
past = b - time
c = b - 0
together = sprintf("%s%s%d%s%d", url1, url2, past, url3, c)
data = read.csv(together, header=FALSE)
colnames(data)<-c("time","price","volume") #Change column names
data$time=as.POSIXct(data$time, origin="1970-01-01") #change to time format
return(data)
}When getMTGOX() is called. Just enter the number of days you want to use in the data. For example if you want 200 days type in: This function does not take into account the trading that is happening today. It uses yesterday as the last trading day. If you want to include the current trading then use: getMTGOXcurrent <- function ( days ) {
url1 = "http://bitcoincharts.com/t/trades.csv?symbol=mtgoxUSD"
url2 = "&start="
a = Sys.Date()
b = as.POSIXlt(a) #Convert to unixtime
time = days * 86400
past = b - time
together = sprintf("%s%s%d", url1, url2, past)
data = read.csv(together, header=FALSE)
colnames(data)<-c("time","price","volume") #Change column names
data$time=as.POSIXct(data$time, origin="1970-01-01") #change to time format
return(data)
}This function downloads the data, puts it in a dataframe, makes some column names, formats the unixtime into POSIX, and then returns the data frame. Now what can we do with this data? I like to use the Quantmod library for financial trading modeling and graphics. (Installing packages is simple. If you don't know how send a reply and I can direct you.) You can get a preview of what quantmod can do here. Right now the data is like ticker data. We could run it in quantmod but we won't be able to do cool things like technical indicators. So we need to change it to a format it can use really well. Use the following function to change the current data downloaded from bitconcharts.com into OHLCV (Open, High, Low, Close, Volume) format. ohlc <- function(ttime,tprice,tvolume,fmt)
{
ttime.int <- format(ttime,fmt)
data.frame(time = ttime[tapply(1:length(ttime),ttime.int,function(x) {head(x,1)})],
.Open = tapply(tprice,ttime.int,function(x) {head(x,1)}),
.High = tapply(tprice,ttime.int,max),
.Low = tapply(tprice,ttime.int,min),
.Close = tapply(tprice,ttime.int,function(x) {tail(x,1)}),
.Volume = tapply(tvolume,ttime.int,function(x) {sum(x)}),
.Adjusted = tapply(tprice,ttime.int,function(x) {tail(x,1)}))
}
x <- getMTGOX( 200 )
x.1day <- ohlc(x$time,x$price, x$volume,"%Y%m%d") We still are not done. x.1day <- xts(x[,-1], order.by=x[,1])
x.1day <- as.xts(x.1day) After doing that enter: and have fun modeling!  |
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I have been using bitcoins to pay translators located in other countries. I eventually hope to have a site that links translators to clients with bitcoin as the payment service.
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I am more worried about a Stuxnet style virus created by a state that searches out bitcoin wallets and deletes them. Don't forget to not only encrypt your wallet, but also set the access permissions. |
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check out bitpay. It is a simple bitcoin payment processor. I have been integrating that into my sites and it seems to be working pretty good. Never mind. I just checked the link and they seem to be not working. |
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Ah, they insulted us for months and now there is profit and they are all jumping on the bandwagon  Profit is a great motivator. |
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check out bitpay. It is a simple bitcoin payment processor. I have been integrating that into my sites and it seems to be working pretty good. |
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I have been watching bitcoins for the last few months. It has helped me have projects while I practice learning python and php. Anyway, I am drawn to its ability to facilitate transactions across borders and break down capital barriers.
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