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In mathematical finance, the Greeks are the quantities representing the sensitivity of the price of derivatives such as options to a change in underlying parameters on which the value of an instrument or portfolio of financial instruments is dependent. The name is used because the most common of these sensitivities are denoted by Greek letters (as are some other finance measures). If your looking for troubleshooting assistance, make sure you checked the FAQ first (It typically has what you need:). The #general channel is a great place to ask questions. If you do need to reach me directly, you can shoot me a direct message in the Slack. I go by, @CircusDad.

Colors and texts appear washed out and difficult to comfortably see even when on the maximum brightness setting. The hinges allow for a wide lid angle of up to degrees, but this pairs rather poorly with the aforementioned limited viewing angles. The stars of the show are the 3. It's rare enough to find one of these in a notebook let alone both in the same shell. When considering that this is the best quad-core Bristol Bridge has to offer for notebooks, overall processor performance is very poor for a budget gaming notebook.

Single-core performance is especially poorer than expected as even an iU can outperform our Asus by about 30 percent according to CineBench R This doesn't mean that clock rates are perfectly flat, however, as our Stress Test section will detail.

Clock rates fluctuate between 3. The differences in scores only grow larger when running the newer PCMark 10 benchmark. Subjectively, navigating through the operating system is smooth and without issues, but applications and especially games take noticeably longer to launch due to the weaker processing power.

Internal storage bays include 2x 2. Much of the performance discrepancy can be attributed to the slower clock speed and memory speed on our mobile RX when under load. In other words, AMD's budget Polaris 11 offering is roughly equivalent to Nvidia's mid-range offering from the last generation. When compared to the current Pascal lineup, however, the RX is significantly behind in both performance and performance-per-Watt.

See our review on the desktop RX for more information on the Polaris series. The gaming benchmarks below were performed with Radeon Crimson version Our attempts to update Crimson or the video drivers resulted in errors each and every time even after a fresh install or reset.

While we didn't experience any game-ending issues at p, the GPU was unable to output at x resolution and we were thus unable to test gaming performance at p. Beyond these software issues, users can also expect excruciatingly long l oading times since the processing power of the FXP is embarrassingly slow.

Most titles will be playable at the native p resolution so long as other settings are tuned to low-medium. More CPU-intensive games like Ashes of the Singularity will suffer from extreme frame rate dips irregardless of the graphics settings. When compared to the desktop RX , the performance gap when gaming is wider than what the 3DMark benchmarks above would suggest due to the CPU bottleneck.

We stress the notebook with unrealistic benchmark loads to test for potential stability or throttling issues. It's strange that clock rate is not steady at some intermediate value like 3. Otherwise, core temperature remains relatively cool at a steady 66 C. GPU stress with FurMark is less stable in terms of performance.

Since the cooling solution is small and shared evenly across the CPU and discrete GPU, the CPU can reach temperatures warmer than 66 C at up to 85 C and will climb back and forth between the two temperatures. GPU temperature is otherwise steady throughout the test. The CPU will alternate between 1.

Running Witcher 3 is more representative of real-world gaming loads. When under such conditions, the CPU can be observed maintaining a steady 3.

Our graph below shows frame rates steadily falling over time from 35 FPS to around 29 FPS because the GPU is only able to maintain high clock rates of MHz for the first few minutes or so before reaching a slower steady state. GPU temperature remains acceptably cool at 74 C. A 3DMark Fire Strike run on batteries returns Physics and Graphics scores of and points, respectively, compared to and points when on mains.

The system fan is always active no matter the load. At its quietest, fan noise is barely audible at about 30 dB A and light tasks may bump this up to 33 dB A. The fan is more likely to stabilize at 33 dB A if on the High Performance profile and so we recommend running on Power Saver if noise is a concern. Fortunately, fan RPM will not pulsate frequently during use. Medium load with 3DMark06 will bump fan noise to a steady While still very load, the system is no louder than most notebooks with GTX graphics and is even quieter than the newer Asus FX or Sabre Max-Q notebooks are both quieter and more powerful, but they currently retail for over twice the price of our FXUI.

Surface temperature measurements reveal that the left half of the notebook will become warmer than the right half when under load conditions. This behavior is not unusual for notebooks with optical drives. Higher-end gaming notebooks tend to favor symmetrically arranged fans and heat pipes for more even temperature development.

As shown by our temperature maps below, users can expect the center of the keyboard to be significantly warmer than the rest of the notebook during medium or higher loads at up to 47 C. At the very least, the palm rests and NumPad should never become uncomfortably warm. Sound quality is not bad for a budget gaming notebook. There is an apparent lack of bass as expected from most notebooks without dedicated subwoofers and treble is overemphasized at higher volume settings. We can otherwise observe no static or major chassis vibrations from audio playback.

Headphones are still recommended when gaming due to the relatively loud fan noise. Frequency Comparison Checkbox selectable! We've shown that the RX in our Asus can be about 20 percent slower than the GTX in a competing notebook according to our above Fire Strike benchmarks.

Will this translate to lower power consumption readings as well? Unfortunately for AMD, the answer is a resounding no. Thanks for publishing this interesting article. May I know when the other two articles of this mini-series will be published? What a nice article! I am currently trading 1 year expiry call options of specific stocks.

Intuitively, this might make some sense, since calls and puts are almost opposite contracts, but being short a call and long a put are not the same. When you are long a put, you have to pay the premium and the worst case will result in a loss of only the premium. So when you write naked calls your risk is unlimited. The short expiry time period 30 days is saves you in most cases, but this is a self-delusion.

Long call or put traders risk is limited and they choose out-of-the-money options to multiply their winnings and parallel they reduce their winning chance. The script will then need a bit more time for the data generation. They have stocks, ETFs, and options contracts. SC] Call SC] Expired 1 Call SC] Write 1 Call SP] Put SP] Expired 1 Put SC] Cover 1 Call SP] Cover 1 Put I see that the positions are all opened with zero volume, as if you had set the number of contracts to 0.

Have you used the unmodified script from the repository? It is not a noob question, it is in fact my fault.

That did not matter with the previous Zorro version since the multiplier was by default, but it must now be set because options can have very different multipliers. QECx05,The url you requested is incorrect. Please use the following url instead: Sorry, actually that file was from Quandl, and need a paid subscription. Anyone having the same problem?

I guess all are having the same problem, as Yahoo changed their protocol last week. If you run into issues like that, look for a solution not only on my blog, but first on the Zorro forum:. Having accurate volatility is essential. Yes, option price changes due to expectation of volatility, maybe when company news approach, belongs to the mentioned anomalies.

The general rule is: Theoretically, as good or bad as the daily data, since the priciple is the same. The R overhead is probably negligible. The problem is not the code, but the math. Numerically solving differential equations is slow. Black-Scholes is much faster, but for European options only. If you have really lots of data to generate, it might make sense to check the speed of different approximation methods for American options.

I notice volatility is fixed at 20 in the above script for generating synthetic option prices. Might there not be an argument for volatility to be a rolling 30 days and calculated programatically from the underlying? You use a one time estimate of Volatility I think: But on a rolling basis it will very widely which is of course part of the reason why option prices change so much: But there again that is what you do perhaps?

A question not a statement. Perhaps the whole scheme is invalid. It may be invalid to use manufactured data at all. Except if you treat it as a sort of Monte Carlo test: Anthony, the script is calculating the current price of an option.

The current price depends on current volatility. Not on volatility from 24 months ago. You calculate the value of European options with the Black Scholes formula, and American options, as in the script above, with an approximation method. Both methods normally use 20 days volatility. The volatility sampling method can differ, but the 20 days are pretty common to all options trading software that I know.

And you can see from the comparison with real prices above that this period works rather well. No, you can not calculate the current price of an option on any given day in that way. There is no way to accurately reproduce implied volatility hence price on any given date in the past. And it is the implied volatility we are interested in, not the historic.

I totally agree on Black Scholes of course and its uses but it is cart before horse to expect to plug in 20 day volatility as at 3rd January and expect it to come up with an accurate price as traded at the close on that day for the SPX for any given strike or expiry. For instance you might use 5 day historic volatility for an option expiring in a week and day volatility for an option expiring in a year.

Or you might imply volatilities by looking at the term structure of VIX futures contracts from Or at least use the VIX index itself going back to as input for 30 day volatility. Or at least not consistently and accurately over all expiries and strikes. I believe that the process you describe does have a value but that the outcome of both the prices produced and the back tests resulting therefrom will be more akin to a random moet carlo process than to a back test on actual traded price data.

It is mathematically equivalent to DdeltaDvol , the sensitivity of the option delta with respect to change in volatility; or alternatively, the partial of vega with respect to the underlying instrument's price.

Vanna can be a useful sensitivity to monitor when maintaining a delta- or vega-hedged portfolio as vanna will help the trader to anticipate changes to the effectiveness of a delta-hedge as volatility changes or the effectiveness of a vega-hedge against change in the underlying spot price.

Charm [4] or delta decay [13] measures the instantaneous rate of change of delta over the passage of time. Charm has also been called DdeltaDtime. Charm is a second-order derivative of the option value, once to price and once to the passage of time.

It is also then the derivative of theta with respect to the underlying's price. It is often useful to divide this by the number of days per year to arrive at the delta decay per day. This use is fairly accurate when the number of days remaining until option expiration is large. When an option nears expiration, charm itself may change quickly, rendering full day estimates of delta decay inaccurate.

Vomma , [4] volga , [14] vega convexity , [14] or DvegaDvol [14] measures second order sensitivity to volatility. Vomma is the second derivative of the option value with respect to the volatility, or, stated another way, vomma measures the rate of change to vega as volatility changes. With positive vomma, a position will become long vega as implied volatility increases and short vega as it decreases, which can be scalped in a way analogous to long gamma.

And an initially vega-neutral, long-vomma position can be constructed from ratios of options at different strikes. Vomma is positive for options away from the money, and initially increases with distance from the money but drops off as vega drops off.

Veta [15] or DvegaDtime [14] measures the rate of change in the vega with respect to the passage of time. Veta is the second derivative of the value function; once to volatility and once to time. It is common practice to divide the mathematical result of veta by times the number of days per year to reduce the value to the percentage change in vega per one day. Vera [16] sometimes rhova [16] measures the rate of change in rho with respect to volatility.

Vera is the second derivative of the value function; once to volatility and once to interest rate. Vera can be used to assess the impact of volatility change on rho-hedging.

Speed [4] measures the rate of change in Gamma with respect to changes in the underlying price. This is also sometimes referred to as the gamma of the gamma [2]: Speed can be important to monitor when delta-hedging or gamma-hedging a portfolio. Zomma [4] measures the rate of change of gamma with respect to changes in volatility.

Zomma has also been referred to as DgammaDvol. Zomma can be a useful sensitivity to monitor when maintaining a gamma-hedged portfolio as zomma will help the trader to anticipate changes to the effectiveness of the hedge as volatility changes. Color , [12] [note 1] gamma decay [17] or DgammaDtime [12] measures the rate of change of gamma over the passage of time.

Color is a third-order derivative of the option value, twice to underlying asset price and once to time. Color can be an important sensitivity to monitor when maintaining a gamma-hedged portfolio as it can help the trader to anticipate the effectiveness of the hedge as time passes. It is often useful to divide this by the number of days per year to arrive at the change in gamma per day.

When an option nears expiration, color itself may change quickly, rendering full day estimates of gamma change inaccurate. Ultima [4] measures the sensitivity of the option vomma with respect to change in volatility.

Ultima has also been referred to as DvommaDvol. If the value of a derivative is dependent on two or more underlyings , its Greeks are extended to include the cross-effects between the underlyings. Correlation delta measures the sensitivity of the derivative's value to a change in the correlation between the underlyings.

Cross gamma measures the rate of change of delta in one underlying to a change in the level of another underlying. Cross vanna measures the rate of change of vega in one underlying due to a change in the level of another underlying. Equivalently, it measures the rate of change of delta in the second underlying due to a change in the volatility of the first underlying.

Cross volga measures the rate of change of vega in one underlying to a change in the volatility of another underlying. Note that the gamma and vega formulas are the same for calls and puts.

In trading of fixed income securities bonds , various measures of bond duration are used analogously to the delta of an option. The closest analogue to the delta is DV01 , which is the reduction in price in currency units for an increase of one basis point i.

Analogous to the lambda is the modified duration , which is the percentage change in the market price of the bond s for a unit change in the yield i. Unlike the lambda, which is an elasticity a percentage change in output for a percentage change in input , the modified duration is instead a semi -elasticity —a percentage change in output for a unit change in input. Bond convexity is a measure of the sensitivity of the duration to changes in interest rates , the second derivative of the price of the bond with respect to interest rates duration is the first derivative.

In general, the higher the convexity, the more sensitive the bond price is to the change in interest rates. Bond convexity is one of the most basic and widely used forms of convexity in finance.

For a bond with an embedded option , the standard yield to maturity based calculations here do not consider how changes in interest rates will alter the cash flows due to option exercise.

It is not a noob question, it is in fact my fault. Retrieved February 15,

Thanks for notifying me!