Recommendation on Options Back Testing tool please
Power Options is one such example of what you seek, not cheap, but one good trade will recover a year's fee.  There's a lot you can do with the stock price alone as most options pricing will follow Black Scholes.  Keep in mind, this is a niche, these questions, while interesting to me, generate little response here. "As JoeTaxpayer says, there's a lot you can do with just the stock price. Exploring that a bit: Stock prices are a combination of market sentiment and company fundamentals. Options are just a layer on top of that. As such, options are mostly formulaic, which is why you have a hard time finding historical option data -- it's just not that ""interesting"", technically. ""Mostly"" because there are known issues with the assumptions the Black-Scholes formula makes. It's pretty good, and importantly, the market relies on it to determine fair option pricing. Option prices are determined by: Relationship of stock price to strike. Both distance and ""moneyness"". Time to expiration. Dividends. Since dividend payments reduce the intrinsic value of a company, the prospect of dividend payments during the life of a call option depresses the price of the option, as all else equal, without the payments, the stock would be more likely to end up in the money. Reverse the logic for puts. Volatility. Interest rates. But this effect is so tiny, it's safe to ignore. #4, Volatility, is the biggie. Everything else is known. That's why option trading is often considered ""volatility trading"". There are many ways to skin this cat, but the result is that by using quoted historical values for the stock price, and the dividend payments, and if you like, interest rates, you can very closely determine what the price of the option would have been. ""Very closely"" depending on your volatility assumption. You could calculate then-historical volatility for each time period, by figuring the average price swing (in either direction) for say the past year (year before the date in question, so you'd do this each day, walking forward). Read up on it, and try various volatility approaches, and see if your results are within a reasonable range. Re the Black-Scholes formula,  There's a free spreadsheet downloadable from http://optiontradingtips.com. You might find it useful to grab the concept for coding it up yourself. It's VBA, but you can certainly use that info to translate in your language of choice. Or, if you prefer to read Perl, CPAN has a good module, with full source, of course. I find this approach easier than reading a calculus formula, but I'm a better developer than math-geek :)" Based on my experience with OpenQuant, which is a development platform for automated trading strategies (and therefore can be easily be used for backtesting your personal strategy), I can give a little insight into what you might look for in such a platform.  OpenQuant is a coding environment, which reads data feeds from a variety of sources (more on that in the second point), and runs the code for your strategy on that data and gives you the results. The data could be imported from a live data feed or from historical data, either through numerous API's, CSV/Excel, etc. You can write your own strategies using the custom C# libraries included with the software, which spares you from implementing your own code for technical indicators, basic statistical functions, etc. Getting the data is another issue. You could use joe's strategy and calculate option prices yourself, although you need to exercise caution when doing this to test a strategy. However, there is no substitute for backtesting a strategy on real data. Markets change over time, and depending on how far back you're interested in testing your strategy, you may run into problems. The reason there is no substitute for using real data is that attempting to replicate the data may fail in some circumstances, and you need a method of verifying that the data you're generating is correct and realistic. Calculating a few values, comparing them to the real values, and calibrating accordingly is a good idea, but you have to decide for yourself how many checks you want to do. More is better, but it may not be enough to realistically test your strategy. Disclaimer: Lest you interpret my post as a shameless plug for the OpenQuant platform, I'll state that I found the interface awful (it looked vaguely like Office 2000 but ten years too late) and the documentation woefully incomplete. I last used the software in 2010, so it may have improved in the intervening years, but your mileage may vary. I only use it as an example to give some insight into what you might look for in a backtesting platform. When you actually begin trading, a different platform is likely in order.  That being said, it responded fairly quickly and the learning curve wasn't too steep. The platform wasn't too expensive at the time (about $700 for a license with no data feeds, I think) but I was happy that the cost wasn't coming out of my pocket. It's only gotten more expensive and I'm not sure it's worth it.
"I have personally invested $5,000 in a YieldStreet offering (a loan being used by a company looking to expand a ridesharing fleet), and would certainly recommend taking a closer look if they fit your investment goals and risk profile. (Here's a more detailed review I wrote on my website.) YieldStreet is among a growing crop of companies launched as a result of legislative and regulatory changes that began with the JOBS Act in 2012 (that's a summary from my website that I wrote after my own efforts to parse the new rules) but didn't fully go into effect until last year. Most of them are in Real Estate or Angel/Venture, so YieldStreet is clearly looking to carve out a niche by assembling a rather diverse collection of offerings (including Real Estate, but also other many other categories). Unlike angel/venture platforms (and more like the Real Estate platforms), YieldStreet only offers secured (asset-backed) investments, so in theory there's less risk of loss of principal (though in practice, these platforms haven't been through a serious stress test). So far I've stuck with relatively short-term investments on the debt crowdfunding platforms (including YieldStreet), and at least for the one I chose, it includes monthly payments of both principal and interest, so you're ""taking money off the table"" right away (though presumably then are faced with how to redeploy, which is another matter altogether!) My advice is to start small while you acclimate to the various platforms and investment options. I know I was overwhelmed when I first decided to try one out, and the way I got over that was to decide on the maximum I was willing to lose entirely, and then focus on finding the first opportunity that looked reasonable and would maximize what I could learn (in my case it was a $1,000 in a fix-and-flip loan deal via PeerStreet)." When you are saving for money you need in 5 years or less the only real option is a savings account. I know the return is nothing at this point, but if you cannot take the risk of losing all of your money that's the only thing I would recommend.  Now you could try a good growth stock mutual fund if, when you look up in 2 - 3 years and you have lost money you wait it out until it grows enough to get what you lost back then buy your house. I would not do the second option because I wouldn't want to be stuck renting while waiting for the account to recover, and actually thinking about it that way you have more risk. 3 years from now if you have lost money and don't yet have enough saved you will have to continue paying rent, and no mutual fund will out preform that. "The Model S is comfortable, luxurious and it feels substantial on the road. And it is fast. Like supercar fast.  ""2013 Tesla Model S: It Sells Itself""  ""I'm going to miss our Model S. It wasn't perfect, but it was like nothing else out there. Take heart, Tesla fans: Sometime in early 2015, we will be one of the first to buy a Model X.""  ""Bear in mind that the experiences with our test cars are purely anecdotal and never factor into our reliability ratings. After all, it's a sample size of one.""  ""the Model S earned Consumer Reports’ recommendation""  ""Car nut or not, EV fan or not, everyone has raved about this car, impressed with its smoothness, effortless glide, and clever, elegant simplicity""  ""One of the cool things about this car is that when it does need to be serviced by a mechanic, a company rep comes with a trailer and picks it up, delivering it back when the work is done—all free. ""  I could go on.  Or you could just try actually reading the reviews." "I struggled with this one at first.   It's easiest if you temporarily ignore the mathematical machinery of martingales and go back to the derivation that Black and Scholes provide in their 1973 paper. They basically show that when you construct a portfolio consisting of a long position in the option (the one being priced) and a short position on the replicating portfolio (consisting of shares of stock and cash in the risk-free bank account), then that portfolio will be entirely risk-less, and hence will earn the risk-free rate of interest. This makes intuitive sense if you think about it - every change in the value of the option is going to be countered by an opposite change in the replicating portfolio; by no arbitrage, that composite portfolio (the option + the replicating portfolio) must therefore earn the risk-free rate.   The fact that the composite portfolio earns the risk-free rate provides the connection to martingale pricing.   Recall that a martingale is basically* a stochastic process that has no drift, only volatility. Here, it's useful to think of the drift as being the ""risk  premium"" or ""return"" of a particular asset (like the stock).   What martingale pricing theory says is that to find the price of the option we (1) discount the value of the replicating portfolio by the cash bond (the numeraire asset), and (2) turn the stochastic process of the risky asset in the replicating portfolio into a martingale. This move intuitively makes sense because the Black-Scholes derivation shows that the replicating portfolio + the option must earn the risk-free rate, but if you divide the value of the Black-Scholes replicating portfolio by the numeraire asset, you're going to cancel out that risk-free rate -- e.g. have a Martingale.  (I'm not a mathematician, so please correct me if I've mucked something up in my explanation).   *I say basically because there are some technical conditions that need to be fulfilled, but that's generally true." Not that I am aware. There are times that an option is available, but none have traded yet, and it takes a request to get a bid/ask, or you can make an offer and see if it's accepted. But the option chain itself has to be open. "Yes, there is a very good Return vs Risk graph put out at riskgrades.com.  Look at it soon, because it will be unavailable after 6-30-11.  The RA (return analysis) graph is what I think you are looking for. The first graph shown is an ""Average Return"", which I was told was for a 3 year period.  Three period returns of 3, 6 and 12 months, are also available.  You can specify the ticker symbols of funds or stocks you want a display of.  For funds, the return includes price and distributions (total return), but only price movement for stocks - per site webmaster. I've used the graphs for a few years, since Forbes identified it as a ""Best of the Web"" site.  Initially, I found numerous problems with some of the data and was able to work with the webmaster to correct them.  Lately though, they have NOT been correcting problems that I bring to their attention.  For example, try the symbols MUTHX, EDITX, AWSHX and you'll see that the Risk Grades on the graphs are seriously in error, and compress the graph results and cause overwriting and poor readability. If anyone knows of a similar product, I'd like to know about it.  Thanks,  George" "It's interesting that you use so many different risk measures. Here's what I'd like to know more in detail:  1) About the use of VaR. I've heard (from a friend, may be unreliable) that some investment managers like Neuberger Berman doesn't use VaR for assessing risk and maintaining capital adequacy requirements. Rather, some firms only rely on tracking error, beta, standard deviation, etc. Why do you think is this so? Isn't VaR supposed to be a widely accepted risk measure.  2) The whole ""Expected Shortfall vs. VaR"" debate. I've read some papers comparing Expected Shortfall and VaR. Mainly, they criticize VaR for not being able to consider the 1% probability left where losses can (probably) skyrocket to infinity. If I need to choose between the two, which do you think is better and why?" I recall the name Martin Pring. As my fundamental analysis book from grad school was the work of Graham and Dodd titled Security Analysis, Pring was the author of the books I read on technical analysis. If you've not read his work, your education has a ways to go before you hit the tools.