Following on from my post about mining ZCash I decided to mine some Akroma coin, I like the look of the project as it has some nice features and who knows. Maybe it will take off! I don’t have a lot of mining hardware, but I have a test system for messing about with this stuff. I do mining more for interest, and I buy some coins for investments. Which are doing ok.
I downloaded the miner from here, it is a version that has the dev fee, but I am fine with that as making software is hard work. You need to get a wallet, I chose the web wallet as that seems like a reasonable option at the minute. In general I prefer stand alone wallets but this is fine until there is a better option for Akroma.
I am running the miner in eth only mode on Ubuntu Linux using the following command:
./ethdcrminer64 -epool stratum+tcp://geo.pool.akroma.eu:8001 -ewal YOURWALLETADDRESS -eworker workerx -epsw x -asm 1 -allpools 1 -di 1
On the K40 I get about 11.6 Mh/s, which is slightly less than I get with a K20 (12.14 Mh/s). No idea why that might be, it could be differences with the Cuda install perhaps. I think the system with the K20 is more up-to-date. If I leave both systems running I will get about 7-8 coins in 24hrs, I will probably only run them together for a day or so and the leave one going for about 4 coins a day.
I will leave this mining for a while, generate some coins and then perhaps go back to ZCash, or try something new! I would like to build a small rig, I have an old system that could have about 3 GPUs in it. That might be the place to start, it would be cool to get one of those multi-gpu cases that could have about 4 GPUs in.
I have two Nvidia Telsa cards that I use for work, they are good for certain tasks around data mining and machine learning, and I have been interested in trying to use them for Zcash mining. I have a Antminer U3 that mines Bitcoins (slowly, and not that well sometimes), however I fancied a go at mining Zcash too. How hard could it be? Harder than it should have been.
Being Cuda cards I would obviously need a cuda enabled miner to use them. I already mine with Antpool, and they allow users to mine Zcash so that bit was easy. What wasn’t easy was trying to get a miner to compile. I tried nheqminer, that wouldn’t compile and also the newest version doesn’t work with the tesla cards I have as they are not compute 5. The older versions wouldn’t compile either. I also had a few problems with getting cuda running on Kubuntu 16.04 as I needed to upgrade the nvidia drivers which was a pain!
I got there in the end as I found a binary of nanopool’s ewbf-miner that works with cuda cards! This works great, I get about 70 Sol/s on the K20 and 95Sol/s on the K40. So that is pretty good, you would get about 40 Sol/s on a i7-6700K CPU @ 4.00GHz. I am sure that with a newer telsa or CPU you would get more. This only an experiment however, not a mining operation so I am happy.
I have finished building a virtual trading platform. The idea is that this can be used to learn trading algorithms for shares on UK and US markets, and then later be coupled to a real trading platform using an API provided by a company such as Interactive Brokers. For now it just takes virtual positions, so no real money at risk.
The algorithm currently in use is pretty naive and needs to be replace. The question is with what. In many ways I would like the system to learn its own method for trading, and in true complex systems style, perhaps I don’t even have to be able to understand what it is doing. I intend to take an agent based approach by having a population of agents running different algorithms or the same algorithms with different learnt parameters. Successful agents will be allowed to duplicate and persist, unsuccessful with be removed from the population. Essentially a evolutionary approach not a million miles away from a genetic algorithm.
Multiple sources of information will be able to the agents to inform their trading. From sentiment analysis (twitter etc), to a large database of historical share prices and realtime market data. The intention is that the learning part of the system will learn what subset of the available information is useful for trading share. The system only needs to be able to be slightly better than random chance.
So, I have been thinking of dipping my toe into the pool of sentiment analysis for a while now. I made the first positive steps the other day. I found a list of positive and negative words on the internet. I have a Java library that works as a basic dictionary and I have created mini dictionaries of these words. The idea is that I can make some assessment of the sentiment of what people are saying about a share for example and then use this as part of a trading algorithm. People have been doing this for years, but I would like to try it myself. I want to see what the problems, pitfalls, limitations are firsthand. I suspect the key will be making the connection between share price movements and certain key individual’s or group’s sentiment. This is similar to that throw away line in the film The Social Network. Something like, “..he made $300,000 trading oil based on the weather…”. If weather is a key indicator of oil price changes I need to find the equivalent key persons for shares that I am interested in trading. Classic old problem of finding the signal in the noise, and there is a lot of noise.
I changed the banner picture to one I took of my computer screen. It’s some of the programs/data/output from the programs I have written to gather share price data. I finally got round to moving the scrubbing programs onto my rackpsace server. Saves me running computers all day, and rackspace is more reliable . I had problems with my internet connection dropping out etc etc. The basic cloud server isn’t expensive either, about $10 plus traffic a month.
Getting data is crucial to doing any sort of modelling on shares/markets. The way that data is tightly controlled by financial and trading companies is a very good indication of what it is worth. However, I often think that it might not be worth as much as they think. The raw price data alone is not that helpful. I think more information is required if you want to predict future market movements. Its all about the people involved, that it was you need the data on. Markets are unpredictable; large groups of people however, they are very predictable.
I sold my Copper ETFS shares today (COPA:LSE). Exchange traded funds are just a vehicle for trading commodities on markets. You don’t buy the commodity itself, rather you buy into a fund which is supposed to buy the commodity. Some say that ETFS are the next derivative bubble. The next collateralized debt obligations (CDO) if you will. I’m not so sure about that, I will give it some thought some other time.
Anyway, I made $480 on the sale. Not at good as I was hoping. I did much better on the rise of crude (ETFS OILD:LSE) after the crisis, I got into copper too late. Commodities have been fairly volatile recently and there are worries and rumours that they are, in general, over priced. So I decided to sell. It means that I have about £700 to invest now and I think my portfolio could do with some more stable stocks. I might think about some food companies. If commodity prices do fall then we might see their margins increase over the next year. Could be a good time to buy…