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Custom Risk Ranges For Today 7-04-2021


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Good Afternoon peeps .

Here are my volatility adjusted Risk ranges for today 

SPY (Bullish) 393.032 - 410.218  prev. close: 406.12

QQQ (Bullish) 315.822 - 335.269  prev. close: 330.82

IWM (Bullish) 206.225 - 230.352  prev. close: 224.31

XLK (Bullish) 131.229 - 139.923  prev. close: 137.69

XLF (Bullish) 33.28 - 35.433  prev. close: 34.67

XLE (Bullish) 45.833 - 51.185  prev. close: 48.98

XLU (Bullish) 63.106 - 65.874  prev. close: 65.02

XLI (Bullish) 95.799 - 101.954  prev. close: 99.76

XLC (Bullish) 72.378 - 77.351  prev. close: 76.34

XLP (Bullish) 67.918 - 70.797  prev. close: 69.14

XLB (Bullish) 77.305 - 82.807  prev. close: 80.65

XLY (Bullish) 165.771 - 175.936  prev. close: 174.02

XLV (Bullish) 115.213 - 119.07  prev. close: 116.75

XLRE (Bullish) 39.206 - 41.288  prev. close: 40.43

XRT (Bullish) 82.639 - 93.874  prev. close: 90.8

GLD (Bearish) 157.381 - 164.397  prev. close: 163.22

Good luck out there.

Courage 

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On 07/04/2021 at 08:25, Courage said:

Good Afternoon peeps .

Here are my volatility adjusted Risk ranges for today 

SPY (Bullish) 393.032 - 410.218  prev. close: 406.12

QQQ (Bullish) 315.822 - 335.269  prev. close: 330.82

IWM (Bullish) 206.225 - 230.352  prev. close: 224.31

XLK (Bullish) 131.229 - 139.923  prev. close: 137.69

XLF (Bullish) 33.28 - 35.433  prev. close: 34.67

XLE (Bullish) 45.833 - 51.185  prev. close: 48.98

XLU (Bullish) 63.106 - 65.874  prev. close: 65.02

XLI (Bullish) 95.799 - 101.954  prev. close: 99.76

XLC (Bullish) 72.378 - 77.351  prev. close: 76.34

XLP (Bullish) 67.918 - 70.797  prev. close: 69.14

XLB (Bullish) 77.305 - 82.807  prev. close: 80.65

XLY (Bullish) 165.771 - 175.936  prev. close: 174.02

XLV (Bullish) 115.213 - 119.07  prev. close: 116.75

XLRE (Bullish) 39.206 - 41.288  prev. close: 40.43

XRT (Bullish) 82.639 - 93.874  prev. close: 90.8

GLD (Bearish) 157.381 - 164.397  prev. close: 163.22

Good luck out there.

Courage 

how do you calculate these - if you don't mind..?  

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12 hours ago, HMB said:

how do you calculate these - if you don't mind..?  

    That would be giving away the secret sauce😂. Jking. I can't give you my math because it's customised to my taste in terms of duration of investments, ( I can however tell you the principles and ideas behind the math. If you put it together you can build your own personalised one  ( a major component of my model is actually on my profile page 😁) 

 

Price Observations  ;

Price moves in a horizontal range in smaller or larger time frames before moving higher or lower. 

The objective is to capture the statistical “best price”  of a security by purchasing it at or near the bottom end of the volatility adjusted price range if bullish, and sell at or near the top if bearish. ( time frame is user dependent )

 

Volatility Observations;

Volatility is an important input because it's the measure of dispersion in returns and is always mean reverting. 

Implied volatility is also an important component because it is what the market expects volatility in the future to look like. (Time frame of forward outlook is user dependent ).

Calculating this for the VIX AND THE VXN AND BOND MARKET AND OIL SUPER IMPORTANT.

 

Liner Interpolation ;

Volatility and price generally have an inverse correlation and the ranges are constantly changing, so I use liner interpolation to give me a rough estimate of what range the price could be statistically. 

   This is one component of my customised risk management approach. Then there is the macroeconomic conditions to consider as well. 

  Then comes the rest; execution AND PAITIENCE. ie. Having the confidence in the math to buy when people are afraid and sell/reduce exposure when people are euphoric. 

I can't  attached the paper I derived this calculation for on the platform. But you can find the paper here 

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2023066

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8 hours ago, Courage said:

    That would be giving away the secret sauce😂. Jking. I can't give you my math because it's customised to my taste in terms of duration of investments, ( I can however tell you the principles and ideas behind the math. If you put it together you can build your own personalised one  ( a major component of my model is actually on my profile page 😁) 

 

Price Observations  ;

Price moves in a horizontal range in smaller or larger time frames before moving higher or lower. 

The objective is to capture the statistical “best price”  of a security by purchasing it at or near the bottom end of the volatility adjusted price range if bullish, and sell at or near the top if bearish. ( time frame is user dependent )

 

Volatility Observations;

Volatility is an important input because it's the measure of dispersion in returns and is always mean reverting. 

Implied volatility is also an important component because it is what the market expects volatility in the future to look like. (Time frame of forward outlook is user dependent ).

Calculating this for the VIX AND THE VXN AND BOND MARKET AND OIL SUPER IMPORTANT.

 

Liner Interpolation ;

Volatility and price generally have an inverse correlation and the ranges are constantly changing, so I use liner interpolation to give me a rough estimate of what range the price could be statistically. 

   This is one component of my customised risk management approach. Then there is the macroeconomic conditions to consider as well. 

  Then comes the rest; execution AND PAITIENCE. ie. Having the confidence in the math to buy when people are afraid and sell/reduce exposure when people are euphoric. 

I can't  attached the paper I derived this calculation for on the platform. But you can find the paper here 

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2023066

thanks.  the ranges you provide are not symmetric around the previous close - so there is a mean return assumption?

(interesting paper  - providing some evidence for vol of vol being a return driver - can't see the connection to the risk ranges immediately - except maybe the general insight that the width of the ranges needs to be updated frequently - you "wrote paper I derived this calculation for" - you're one of the authors?

Edited by HMB
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2 hours ago, HMB said:

 

thanks.  the ranges you provide are not symmetric around the previous close - so there is a mean return assumption?

(interesting paper  - providing some evidence for vol of vol being a return driver - can't see the connection to the risk ranges immediately - except maybe the general insight that the width of the ranges needs to be updated frequently - you "wrote paper I derived this calculation for" - you're one of the authors?

Nah I didn't write the paper, took multiple reads to understand the concept and I'm sure someone is going to one day tell me I'm wrong haha. Got a monkey brain my friend 😆.  What I meant to say was I derived the formula as in I "borrowed" it . And yes there are assumptions impeded in the math also, Its not perfect because it doesn't seem to work on securities that don't have options data. Which is a huge limitation. I am currently working on with someone with bigger brains than I have to come up with a solution to fix that.

    Think of the ranges as moving targets , the calculation takes vol and price into consideration. The most important thing to watch is the the change of the width. Not necessarily the width itself. If the range is stable and a security is making higher highs and higher lows , with volatility slipping = super bullish, opposite = bearish. 

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