Wouldn’t you like to know, before you make an investment or trade:

• what its MINIMAL worst case risk scenarios are?  In other words, given what we already know, how bad should we reasonably expect things to get?
• if you use a stop loss, what the chances are that you'll hit it?
• whether the technicals (the distance from moving averages and ranked returns) are suggesting that you take action immediately, or with a delay?
• what the risks are over various time frames (a week, a month, six months, one year)?
• whether at least some of of the "tail" risks (i.e., large and/or long, sustained movements that account for almost all the risk) are accounted for?

RiskPic's reports answer these and other questions, and do so in a way that is simple, intuitive, and easy to understand.

RiskPic's reports have one main, overriding, concern: if things get really bad, how much could you lose? What if this happens over an extended period of time, not just the one day? After all, just about all significant losses take place due to a sequence of events.  Rarely is the one day risk of such massive, overriding concern.  Such a sequence is the result of 'fat tails' in the distribution of the security in question.  Roughly speaking, this means that extreme things happen far more often in financial markets than you would expect.  Therefore, to answer this question, the 'fat tails' must be accounted for in some way.

To do so, RiskPic's reports use state-of-the-art analytics via a technique called resampling.  Resampling makes no assumption about the underlying return distribution of a security: it infers it from the data.  This is important because we do not have any satisfactory theory of financial markets (where theory means an accepted, well tested, body of knowledge and rules that conform to all known facts).  Therefore, we do not know what distribution to use for any given security.  As a result, it is better to proceed empirically rather than forcing the assumption of a distribution onto the data (the general tendency with other approaches is to use a normal or lognormal distribution, although, other distributions are occasionally used).

RiskPic's reports present the MINIMAL worst case scenarios.  In other words, based on what we already know (the 'known unknowns'), they estimate the risk of a given security.  However, by definition, since we cannot model the 'unknown unknowns' (to use a now infamous phrase), the actual risk will be even higher than this.  But it is at least a start, and the results when compared to conventional analysis can be quite startling (conventional analyses typically are unable to handle even the 'known unknowns' and will tend to substantially underestimate the true risk of a security).

RiskPic produces reports on many different stocks, for the purpose of letting you get a handle on these risks and to give you reasonable answers to the various questions raised above.