Dealing with event driven market volatility
If you're worried about volatility, and you're in mostly long positions, you should be looking to diversify your portfolio (meaning, buying some stocks that will do better in a bear market) if it's not already diverse, but you shouldn't be looking to abandon your positions, unless you anticipate a short-term need for cash.  Other than that, you may want to hold off on the short-term positions for a while if you're concerned about volatility, though many traders see volatility as a great time to make money (as there is more movement, there's more opportunity to make money from mispriced stocks in both directions).  Unless you think the market will be permanently down due to these reasons, anyway, but I don't see any reason to believe that yet.  Even World War Two wasn't enough to permanently hurt the market, after all! Remember that everyone in the market knows what you do.  If there were a sure thing that the market was going to crash, it already would have. Conservative positions tend to involve holding onto a well diversified portfolio rather than simply holding onto cash, unless the investor is very conservative (in which case the portfolio should be cash anyway). The fact that you say this is your rainy day fund does make me a little curious, though; typically rainy day funds are better in cash (and not invested) since you might hit that rainy day and need cash quickly (in which case you could take significant losses if the time isn't right). If you are worried about an increase in volatility, then go long volatility. Volatility itself can be traded. Here in the US there is an index VIX that is described as tracking volatility. What VIX actually tracks is the premium of S&P 500 options, which become more expensive when traders want to hedge against volatility. In the US you can trade VIX options or invest in VIX tracking ETFs like VXX. Apparently there are similar ETFs listed in Canada, such as HUV. Volatility itself is quite volatile so it is possible that a small volatility long position would cover the losses of a larger long position in stocks. If you do choose to invest in a volatility ETF, be aware that they experience quite a lot of decay. You will not want to hold it for very long. If you are worried about elections think about writing some calls against your long positions to help hedge.   If you have MSFT (@ $51.38 right now) you could write a MSFT Call for lets say $55. You can bank $170 per 100 shares (let's say you write it at 1.70) (MSFT 01/20/2017 55.00 C 1.73 +0.01 Bid: 1.69 Ask: 1.77) If MSFT goes down a lot you will have lost $170 less per 100 shares than you would have because you wrote an option for $170.  You will in fact be break even if the stock falls to 49.68 on the Jan Strike Date. If MSFT goes up $3.50 you will have made $170 and still have your MSFT stock for a net gain of $520.  $170 in cash for the premium and your stock is now worth $350 more. If MSFT goes up $3.62 or more you will have made the max $530ish and have no MSFT left potentially losing additional profit if the stock goes up like gang busters.   So is it worth it for you to get $170 in cash now and risk the stock going up more than $5 between now and Jan.  That is the decision to make here.
"As I understand it, Implied Volatility represents the expected gyrations of an options contract over it's lifetime.  No, it represents that expected movement of the underlying stock, not the option itself.  Yes, the value of the option will move roughly in the same direction the value of the stock, but that's not what IV is measuring. I even tried staring at the math behind the Options pricing model to see if that could make more sense for me but that didn't help. That formula is correct for the Black-Scholes model - and it is not possible (or at least no one has done it yet) to solve for s to create a closed-form equation for implied volatility.  What most systems do to calculate implied volatility is plug in different values of s (standard deviation) until a value for the option is found that matches the quoted market value ($12.00 in this example).  That's why it's called ""implied"" volatility - the value is implied from market prices, not calculated directly. The thing that sticks out to me is that the ""last"" quoted price of $12 is outside of the bid-ask spread of $9.20 to $10.40, which tells me that the underlying stock has dropped significantly since the last actual trade.   If the Implied Vol is calculated based on the last executed trade, then whatever algorithm they used to solve for a volatility that match that price couldn't find a solution, which then choose to show as a 0% volatility.   In reality, the volatility is somewhere between the two neighbors of 56% and 97%, but with such a short time until expiry, there should be very little chance of the stock dropping below $27.50, and the value of the option should be somewhere around its intrinsic value (strike - stock price) of $9.18." In a secular bull market, strong investor sentiment drives prices higher, as participants, over time, are net buyers. Secular markets are typically driven by large-scale national and   worldwide events... demographic/ population shifts,   governmental policies... bear market periods occur within   the longer interval, but do not reverse the trend. There are still many reasons to buy the long bond, despite the lack of yield (nearly flat term structure of interest rates). Despite the recent credit ratings agency downgrades of U.S. sovereign risk, the T-bond offers greater relative security than many alternatives.  If Germany were NOT part of the EU, its government bonds would be issued by the Bundesbank, denominated in Deutsche Marks. German government bonds would probably be a better choice than the U.S. Treasury's 30-year bond.  Long-term maturity U.S. Treasuries are in demand by investment and portfolio managers because: "Certainly no one knows in advance how much a stock is going to swing around. However, there are measures of how much it has swung around in the past, and there are people who will estimate the probability. First of all, there's a measure of an individual stock's volatility, commonly referred to as ""beta"". A stock with a beta of 1 tends to rise and fall about as much as the market at large. A stock with a beta of 2, in the meantime, would rise 10% when the market is up 5%. These are, of course, historical averages. See Wikipedia: http://en.wikipedia.org/wiki/Beta_(finance) Secondly, you can get an implied measure of volatility expectations by looking at options pricing. If a stock is particularly volatile, the chance of a big price move will be baked into the price of the stock options. (Note also that other things affect options pricing, such as the time value of money.) For an options-based measure of the volatility of the whole market, see the Volatility Index aka the ""Fear Gauge"", VIX.  Wikipedia: http://en.wikipedia.org/wiki/VIX Chart: http://finance.yahoo.com/q?s=%5EVIX Looking at individual stocks as a group (and there's an oxymoron for you), individual stocks are definitely much more likely to have big moves than the market. Besides Netflix, consider the BP oil spill, or the Tokyo Electric Power Company's Fukushima incident (yow!). I don't have any detailed statistics on quantitatively how much, mind you, but in application, a standard piece of advice says not to put more than 5% of your portfolio in a single company's stock. Diversification protects you. (Alternatively, if you're trying to play Mr. Sophisticated Stock-Picker instead of just buying an index fund, you can also buy insurance through stock options: hedging your bets. Naturally, this will eat up part of your returns if your pick was a good one)." "It depends on the volatility of the underlying stock. But for ""normal"" levels of volatility, the real value of that option is probably $3.50! Rough estimates of the value of the option depending on volatility levels: Bottom line: unless this is a super volatile stock, it is trading at $3.50 for a reason. More generally: it is extremely rare to find obvious arbitrage opportunities in the market." CFDs (Contracts for Difference) are basically a contract between you and the broker on the difference in price of the underlying between the time you open a position and close a position. You are not actually buying the underlying. With share CFDs, the outcome is a bit like buying the underlying shares on margin. You pay interest for every day you hold the CFDs overnight for long CFDs. However, with short positions, you get paid interest for every day you hold your short position overnight. Most people use CFDs for short term trading, however they can be used for medium to longer term trading just as you would hold a portfolio on margin. What you have to remember is that because you are buying on margin you can lose more than your initial contract amount. A way to manage this risk is by using position sizing and stop loses. With your position sizing, if you wanted to invest $10,000 in a particular share trading at $10 per share, you would then buy 1000 shares or 1000 CFDs in that share. Your initial expense with the CFDs might be only $1000 (at a margin rate of 10%). So instead of increasing your risk by having an initial outlay of $10,000 with the CFDs you limit your risk to the same as you were buying the shares directly. This link does it ok:  http://investexcel.net/1979/calculate-historical-volatility-excel/ Basically, you calculate percentage return by doing stock price now / stock price before.  You're not calculating the rate of return hence no subtraction of 100%.  The standard is to do this on a daily basis: stock price today / stock price yesterday. The most important and most misunderstood part is that you now have to analyze the data geometrically not arithmetically.  To easily do this, convert all percentage returns with the natural log, ln(). Next, you take the standard deviation of all of those results, and apply exp().  This answers the title of your question. For convenience's sake, it's best to annualize since volatility (implied or statistical) is now almost always quoted annualized.  There are ~240 trading days each year.  You multiply your stdev() result by (240 / # of trading days per return) ^ 0.5, so if you're doing this for daily returns, multiply the stdev() result by 240^0.5; if you were doing it weekly, you'd want to multiply by (240 / ~5)^0.5; etc.  This is your number for sigma.  This answers the intent of your question. For black-scholes, you do not convert anything back with exp(); BS is already set up for geometric analysis, so you need to stay there. The reason why analysis is done geometrically is because the distribution of stock returns is assumed to be lognormal (even though it's really more like logLaplace). Ok, so disregarding passivity, could you help me through a simplified example?   Say I only had two assets, SPY and TLT, with a respective weight of 35 and 65% and I want want to leverage this to 4x.  Additionally, say daily return covar is:  * B/B .004% * B/S -.004% * S/S .02%   Now, if I read correctly, I should buy ATM calls xxx days in the future.  Which may look like: Ticker, S, K, Option Price, Delta, Lambda  * TLT  $126.04  $126.00  $4.35  0.50  14.5 * SPY  $134.91  $134.00  $6.26  0.55  11.8  ^ This example is pretty close but some assets are far off.   I feel like I'm on the wrong track so I'll stop here.    I just want to lever up my risk-parity. Margin rates are too high and I'm docked by Reg-T. You need to track every buy and sell to track your gains, or more likely, losses. Yes, you report each and every transactions. Pages of schedule D.