What's the best application, software or tool that can be used to track time?
People rave about Basecamp by 37signals.  The impressive part is all the add-ins you can get for it.  There are add-ins for invoicing, billing, accounting, and time tracking. Time Tracker I'm a software engineer and have been using this tool. It is free and has a good user interface. I believe it can very well be used by professional of other areas too. It does support the features that you're looking for regarding project and task tracking. "There are tonnes, and tonnes of things out there, but you have to be careful what you search for.  Be specific about what you want.  If you search for ""time sheet"" for example, you'll just get a bucket of stuff having to do with stylesheets, because there's more of that around. The most common type of small tool for tracking time is usually a timer-type thing that runs as a widget, gadget, or System Tray tool.  You have to click it on, then off again, and the nice ones produce a usable output file.  CSV, or XLS, or some such. There are tools that track what documents you have open, when you opened them, and when you closed them, and you can sort it out from there.  They're a bit resource-heavy, so be careful if you have a low power system. Quickbooks has a little utility that will make file which can be imported into your accounting.  Quickbooks is NOT for the average business person.  You almost have to be a bookkeeper to get the most out of it.  On the other hand, you can have a bookkeeper set it up for you, and at the end of the year your taxes are a one button affair. For Windows software I like to use the site snapfiles.com.  It's always been reliable, the rating systems are pretty accurate, they mostly maintain their own copies of the software, they test for viruses, and the let you specify a ""freeware only"" search ;-) For Mac software I like versiontracker.com.  If you're a massive freeware user, like me, sign up for an account, so you can receive alerts regarding updates, and such. Currently I do most of my computer-based organization on a Mac with piece of software by CircusPonies.com called NoteBook.  There's a command to insert the time, date, or both, and I just use that when I have a need to record elapsed time. I have even run across (and I forget the name) a piece of software for tracking time on Windows, which had multiple timers which you could set so either they were allowed to run concurrently (lawyers), or only one would run at a time. Anyway…  Personally I think freeware is fun, but be careful.  It's still the wild frickin west out there.  If you don't trust the site you're downloading from, scan it with your anti-virus software before you install it, create a Restore Point, do a full, offsite backup of all your hard drives, unplug your computer from the Internet, send your wife to her mother's, lock the kids in the basement, cross your fingers, and phone the local bishop for a dispensation (http://en.wikipedia.org/wiki/Dispensation_(Catholic_Church))." The best one I've found is TimeSnapper, I have the worst memory but this basically allows me to visually play back the day. It has a bunch of reporting functionality too. Surprised nobody has mentioned Freshbooks yet. It's lightweight, easy to use, and free for low-end use (scaling up price-wise as you scale up). "A free solution that I've been using is Task Coach. It has tasks, subtasks, categories, and all the stuff you would expect from a time tracking program. It also counts each distinct period spent on a task as a separate ""effort"" that you can add comments, for example to remind you what that chunk of time was spent on." I've been using Tick at work now for several months and have really enjoyed it.  It's got a nice, simple interface with good time-budgeting and multi-user/project features.  It can be used on several platforms, too (website, desktop widgets, and phone apps).
"Unfortunately I don't think any of the online personal finance applications will do what you're asking. Most (if not all) online person finance software uses a combination of partnerships with the banks themselves and ""screen scraping"" to import your data. This simplifies things for the user but is typically limited to whenever the service was activated. Online personal finance software is still relatively young and doesn't offer the depth available in a desktop application (yet). If you are unwilling to part with historical data you spent years accumulating you are better off with a desktop application. Online Personal Finance Software Pros Cons Desktop Personal Finance Software Pros Cons In my humble opinion the personal finance software industry really needs a hybrid approach. A desktop application that is synchronized with a website. Offering the stability and tools of a desktop application with the availability of a web application." "&gt; I'm not aware of anyone making a screening tool that can integrate all of these things simultaneously. What is the best environment to create a tool like this?  Everyone has one but they're all proprietary. Most common new stuff I've seen in the HF space are C# or Python. R is growing significantly in the space, but it lends itself to one-off data analysis better than writing large applications that have to do a lot of other ""stuff"", where Python's module universe is more exhaustive.  Everyone is going to recommend whatever languages *they* are comfortable with, but the correct answer is probably whatever *you* are most comfortable with." I'll just add this: In the best hedge funds and proprietary trading funds, stock selection is approached very scientifically in order to minimize losses/maximize gains. Researchers think of a trading idea and carefully test it to see which methods of stock selection work and how well, and finally they combine them. Every day researchers update their models based on the past performance of each indicator.  All this is just too much work to be done manually. Firms use machine learning methods to understand markets. They try to figure out what is normal, what did not happen correctly at a specific time, what will happen in future. For instance, they use deep learning networks to look at unlabeled data, and figure out what is normal and what is not. These networks can analyze an unstructured haystack of noise, and separate out the signal. This is very relevant to finance and markets because finding the patterns and anomalies in market data has been the bread and butter of traders for decades. Deep learning networks give us applications like feature learning. By 'features,' I'm referring to certain attributes in data that indicate an event. By anticipating them, we can help predict future price movements. New technology is allowing us to break new ground in managing risk, to be a-typical and manage risk in ever-improving ways. It's the responsibility of every trader, whether working for themselves or others, to take advantage of this technology to improve the collective investing experience. I care very deeply about this. I have many close friends, in the finance world and without, who have lost large amounts of money to poor trade tools and lack of transparency. Jamie Dimon, calling bitcoin a fraud for price bubbling is hilarious considering JP Morgan literally got bailed out by US tax dollars for investing in trash mortgage loans. Ok.  Knocks aside, I'm just buying low. The problem with financial analysis on bitcoin is that inevitably, financiers don't know anything about computer science, and they aren't in the business of making applications. Bitcoin is an application of an interesting concept: the distributed ledger, and the ability to have a distributed ledger verify and lock the ledger. The problem with this analysis is that he doesn't have application knowledge to infer the positive externalities of having a distributed ledger, and most of those use cases for the applications are in their infancy, or haven't been though of yet. Blockchain is an idea that can later power other tools. It's like when the Microsoft CEO said Apps aren't useful on phones. He didn't see the big picture, because the use cases weren't defined yet, and the same thing is going on here. We haven't really fleshed out all the possible use cases of a distributed ledger with a decentralized oracle.  Does it work for payments? Yes, bitcoin is proof of that, and the fact that it's been bailed out a total of zero times by American taxpayers is so far a strong indicator that it works. Are there other applications that are being developed? Yes. Are there some applications out there that are absolute shit? Yes. Are there some applications out there that are absolute gold? Yes. Python or C are the most useful if you're on the quantitative side of things, that space can be a bit difficult to break in to without a quantitative degree, though.  Outside of that, excel, SQL, VBA etc. are useful tools if you're in a more spreadsheet-y role.  Your question has been asked more than a few times, so a subreddit search will probably turn up more detailed answers. I've used BigCharts (now owned by MarketWatch.com) for a while and really like them. Their tools to annotate charts are great. This looks pretty good. Do you use their payroll software at all? Currently I am using Gusto and it is pretty automatic with some nice integrations (time tracking software, etc.).  It sounds like if you can accomplish everything with Wave's platform it is a really good option. "I interned for about six months at a firm that employed a few technical analysts, so I'll try to provide what little information I can. Since the bulk of the intra-day trading was decided algorithmically, technical analysts had two main functions: This basically boils down to my answer to your question. There are still enough people, trading firms, etc. who believe in candlestick charting and other visually subjective patterns that if you notice a trend, pattern, etc. before the majority of traders observing, you may be able to time the market successfully and profit. This is becoming increasingly dangerous, however, because of the steps I outlined above. Over time, the charting patterns that have been proven effective (often in many firms individually since the algorithms are all proprietary) are incorporated into computer algorithms, so the ""traders"" you're competing with to see the pattern are increasingly low-latency computer clusters less than a few blocks from the exchange. Summary: Candlestick charting, along with other forms of subjective technical analysis, has its believers, and assuming enough of these believers trade the standard strategies based on the standard patterns, one could conceivably time the market with enough skill to anticipate these traders acting on the pattern and therefore profit. However, the marginal benefits of doing so are decreasing rapidly as computers take over more trading responsibility.  Caveats:  I know you're in Australia, where the market penetration of HF/algo traders isn't as high as in the US, so it might be a few more years before the marginal benefits cease to be profitable; that being said, if various forms of technical analysis proved wildly profitable in Australia, above and beyond profits available in other markets, rest assured that large American or British trading firms would already have moved in.  My experience is limited to one trading firm, so I certainly can't speak for the industry as a whole. I know I didn't address candlestick charts specifically, but since they're only one piece of visual technical analysis, I tried to address the issue as a whole.  This somewhat ties into the debate between fundamental or technical analysis, which I won't get into. Investopedia has a short article on the subject. As I said, I won't get into this because while it's a nice debate for small traders, at large trading firms, they don't care; they want to make profit, and any strategy that can be vetted, whether it's fundamental, technical, or astrological, will be vetted.  I want to add more information to my answer to clear up some of the misconceptions in the comments, including those talking about biased studies and a lack of evidence for or against technical analysis (and candlestick charts; I'll explore this relationship further down).  It's important to keep in mind that charting methods, including candlestick charts, are visually subjective ways of representing data, and that any interpretations drawn from such charts should, ideally, represent objective technical indicators. A charting method is only as good as the indicators it's used to represent. Therefore, an analysis of the underlying indicators provides a suitable analysis for the visual medium in which they're presented.  One important study that evaluates several of these indicators is Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation by Lo, Mamaysky, and Wang. Lest anyone accuse its authors of bias, I should point out that not only is it published by the National Bureau of Economic Research (a highly reputable organization within economics and finance), but also that the majority of its authors come from MIT's Sloan school, which holds a reputation second to none. This study finds that several technical indicators, e.g. head-and-shoulder, double-bottom, and various rectangle techniques, do provide marginal value. They also find that although  human judgment is still superior to most computational algorithms in the area of visual pattern recognition, ... technical analysis can be improved by using automated algorithms Since this paper was published in 2000, computing power and statistical analysis have gained significant ground against human ability to identify and exploit for visual pattern detection like candlestick charts.  Second, I suggest you look into David Aaronson's book, Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals. He finds similar results to the Lo, et. al. paper, in that some technical indicators do add value to the investment process, but those that do are those that can be represented mathematically and thus programmed directly into trading algorithms (thus bypassing visual tools like candlestick charts).  He describes how studies, including Lo, et al., have found that head and shoulders patterns are worse than random, i.e. you would earn higher returns if you simply traded at random. That point is worth than repeating. If a day-trader is using a candlestick chart and using head-and-shoulders patterns as part of their toolkit, he's rolling the dice when he uses that pattern and returns that come from its application come from chance. This reminds me of that old story about a company that sends out pamphlets predicting the results of sports games, complete with ""strategies"" and ""data"" to back up the predictions. The company sends out several versions of the pamphlet every game, each predicting a different winner. Given a large enough sample size, by the end of the season, there are a few people who have received a pamphlet that accurately predicted the winner for every game and they're convinced the system is perfect. The others weren't so lucky, however. Relying on candlestick charts and TA patterns that are relics from the pre-computerized era is reassuring to some traders and gives them a sense of control and ""beating the market,"" but how long will chance remain on your side? This is why I maintain that visual tools like candlestick charts are a slowly dying medium. They certainly still add value to some trading firms, which is why Bloomberg terminals still ship with this functionality built in, but as more and more research shows, automated algorithms and statistical indicators can provide more value. It's also important to think about whether the majority of the value added by visual tools like candlestick charts comes in the form of profit or a sense of security to traders who learned the field using them over the past few decades.  Finally, it's extremely important to realize that the actions of retail investors in the equities market cannot begin to represent the behaviors of the market as a whole. In the equities markets alone, trading firms and institutional investors dwarf retail investors, and the difference in scale is even more vastly pronounced in derivatives and currency markets. The fact that some retail investors use candlestick charts and the technical indicators they (hope) underlie them provides nothing but minor anecdotal evidence as to their effectiveness."