Seems Low Vol stocks are going to outperform. Chart is a volatility-adjusted pair USMV (low vol stocks) vs SPY. pic.twitter.com/dnQeHNoiX2
— Alexander Kurguzkin (@mehanizator) October 23, 2018
VOLATILITY FIGHTER
Quantitative approach to riding the stock market volatility
Wednesday, October 24, 2018
Low Volatility Stocks to Outperform
Thursday, September 27, 2018
What makes the edge
Your edge against the market is a product of two things: pain (failures) and boredom (research). The more of pain and boredom you absorbed, the more chances you're above the market, cause normal people do their best to escape them. #trading #investing
— Alexander Kurguzkin (@mehanizator) September 27, 2018
Wednesday, September 26, 2018
Roots of a price action
Most of price action dynamics comes from a simple behavioral feature: pretty much noone is strong enough to enter third time where you've just been hit twice. #trading
— Alexander Kurguzkin (@mehanizator) September 27, 2018
Monday, May 8, 2017
Thursday, March 10, 2016
Volatility Premium Paradox
Most of the market volatility exist because the market crowd is being biased and irrational and consistently fails to estimate the future.
At the other hand, the same market crowd wants a premium for being exposed to market volatility.
It sounds a paradox: the market crowd wants to be paid for consistently failing to do its job of correctly pricing the assets. They want to be paid - and, actually, are paid - for the failure.
At the other hand, the same market crowd wants a premium for being exposed to market volatility.
It sounds a paradox: the market crowd wants to be paid for consistently failing to do its job of correctly pricing the assets. They want to be paid - and, actually, are paid - for the failure.
Stocks and Volatility: Possible Regime Change
One of the indicators I pay particular attention to is an indicator of a relationship between stock ETF and VIX ETFs. In the long run, VIX ETFs are just proxies to leveraged SPY short position, but their relationship is remarkably cyclical. Last time I noticed an extreme position in August 2015 and it worked perfectly.
The indicator is a basket of 3 ETFs: SPY for stocks and VXX, VXZ for volatility. Each part is normalized on realized 21-day volatility.
It seems like the indicator is going down in coming months. This may be when the market stays in regimes like:
- volatility is down, VIX futures are in a steep contango, market upside as usual or narrow range like in first half of 2015 (but I must say that was quite unusual).
- stocks are falling steadily, but no significant surges of volatility, VIX futures curve is flat.
In these market regimes volatility selling with stock index hedging could be a good idea.
The indicator is a basket of 3 ETFs: SPY for stocks and VXX, VXZ for volatility. Each part is normalized on realized 21-day volatility.
It seems like the indicator is going down in coming months. This may be when the market stays in regimes like:
- volatility is down, VIX futures are in a steep contango, market upside as usual or narrow range like in first half of 2015 (but I must say that was quite unusual).
- stocks are falling steadily, but no significant surges of volatility, VIX futures curve is flat.
In these market regimes volatility selling with stock index hedging could be a good idea.
Wednesday, March 9, 2016
Simplest Way to Improve Your Return to Risk Ratio
There is an industry standard to understand price volatility as a measure of risk. Most traders are too serious about it, they think it is a must to adopt the same understanding for their own. Actually, a risk is a pretty vague a notion, you can define it various ways. This is an advantage for a private investor, you can define what a risk exactly means for you.
You can understand a risk as a probability to underperform some risk-free benchmark on some time horizon. And now we have a parameter here - the time horizon.
If you hold a stock portfolio, the more the time horizon, the less the chances to underperform a risk-free benchmark because most factors creating local volatility have cyclical, mean-reverting nature. The longer you wait, the less are the losses they inflict to your portfolio. They may create a local volatility, but the overall action along the time horizon may be insignificant.
For example, you may observe periodical risk-off/risk-on trends, created only by massive emotional contagions. They create volatility spikes, extreme price actions, ruining your Sharp ratio. But they are cyclical and mean-reverting on scales rarely beyond a year.
So, the simplest way to improve your return to risk ratio is to redefine your risk to exclude local volatility as a measure, and to extend your time horizon so you could ignore short-time cyclical price actions.
You can understand a risk as a probability to underperform some risk-free benchmark on some time horizon. And now we have a parameter here - the time horizon.
If you hold a stock portfolio, the more the time horizon, the less the chances to underperform a risk-free benchmark because most factors creating local volatility have cyclical, mean-reverting nature. The longer you wait, the less are the losses they inflict to your portfolio. They may create a local volatility, but the overall action along the time horizon may be insignificant.
For example, you may observe periodical risk-off/risk-on trends, created only by massive emotional contagions. They create volatility spikes, extreme price actions, ruining your Sharp ratio. But they are cyclical and mean-reverting on scales rarely beyond a year.
So, the simplest way to improve your return to risk ratio is to redefine your risk to exclude local volatility as a measure, and to extend your time horizon so you could ignore short-time cyclical price actions.
Subscribe to:
Posts (Atom)