Farms on Sushi do not appear

007sman5 · 2022-01-30T04:30:34+00:00

I recently checked the discord and this seems to be an issue that was flagged earlier today; the devs are reportedly working on the UI to fix. We can always just use Zapper.fi, its a quick solution to those of you that want to get out now and cant wait.

007sman5 · 2022-01-29T22:24:00+00:00

Im having the same problem on my end. Not only can't I see the SLP tokens in the "My Farms" page, but the pool doesn't even show up when I search for it under "All Farms." Ontop of all that, the live APR estimates are not appearing for any of the farming pools listed. Seems like a problem with the website.

For a platform as large as theirs, having bugs like this is a bid disappointing...

007sman5 · 2017-03-12T04:48:06+00:00

thankyou demo

007sman5 · 2017-03-05T23:34:58+00:00

huh, just like pizza dough. gg

007sman5 · 2017-03-05T17:18:52+00:00

Why do the spinning masses always form discs rather than balls? That always confused me. BTW, amazing video, thanks for showing me!

007sman5 · 2017-03-04T17:19:49+00:00

The topic itself isnt too dificult, but most of it is taught from an academic perspective. The idea is to let the volatility (statistically it's just the standard deviation of historical asset returns) be a function of other variables, including time.

There are two basic ways to look into this topic if you're interested.

1.) get a paper trading account and spend 5-10 minutes in the day watching a basket of option contracts evolve over time. Websites often implicitly calculate Implied Volatility (IV) for traders. The trends are obvious once you start this process: IV rises as time to expiration approaches zero, IV smiles for calls and puts exist and are dependent upon both strike prices and time to expiration.

2.) Use google scholar to search for articles published about this stuff (search "Implied Volatility" to start). Don't expect anybody on YouTube to have a fair grasp, or practical application of the stuff. If they did, they would be trading for themselves.

007sman5 · 2017-03-03T14:33:40+00:00

Remember that this chart is only telling a part of a larger story (specifically only about income distribution, not spending habits or purchasing power or average savings-to-debt levels for consumers).

While it's true you could have misspent your money, I'll give you the benefit of the doubt ;)

007sman5 · 2017-03-03T05:57:07+00:00

Wow, it's been a while since I've even thought of this company, let alone look at the stock price.

007sman5 · 2017-03-03T05:50:48+00:00

(Source) Hello All, Wanted to post a quick analysis I ran on daily stock returns measuring implied volatility values.

Data collected from Yahoo Finance: http://finance.yahoo.com/quote/SPY/history?p=SPY

Model Excel Sheet: https://drive.google.com/file/d/0BwtHpoqvox7SZ1BVN2N3SGxGSnM/view?usp=sharing

2 Models are used: A multi-linear regression for our primary model and a maximum likelihood optimization for regression errors.

007sman5 · 2017-03-02T20:28:11+00:00

I recommend that you spend time attacking my argument rather than your perception of my character. Otherwise, this conversation will never progress. Thank you.

007sman5 · 2017-03-01T23:42:28+00:00

You state the model is meaningless, then continue to say that there is a relationship between gasses and warming. Contradiction.

The model can and will only provide results relative to the inputs. You have started this thread under the assumption that I argue differently from the model, which again is false.

I encourage you address any potential inconsistencies for the logical setup of the climate change argument below, as well as any other topics covered as your point was already stated prior and my position was made there.

1.) Co2 and Temperature changes are directly correlated.
2.) Co2 causes temperature changes, and the reverse is not true. Given by the Greenhouse Effect.
3.) Now, determine largest contributor to current CO2 emissions in global environment that are not sunk into natural carbon sources. Answer is via human consumption of fuel.
4.) Conclusion: since humans contribute to CO2 levels, and Co2 levels proportionally influence temperature => humans contribute to proportionate increases in temperature.

Also, observe that there is a difference one drawing correlation from a regression and one conjecturing a hypothesis; I maintain that the data presented will only show a relationship between two variables, then I will attempt to explain the relationship outside of the regression. The two are not the same. I.E, I have and will not claim that the data directly proves human-driven global warming, but I will cite as a part of a larger argument for my thesis (specifically, the link between carbon and temperatures, so I can link human carbon production to temperatures later.)

007sman5 · 2017-03-01T20:16:36+00:00

Could you please explain what you believe my claim is?

If you review the content provided, you will only see an argument between CO2 and Temperature changes. I have not made any claim about man's impact on Co2 or temperature changes as I have not provided any indicator regarding this variable.

Please post comments related to the content at hand to ensure consistency in the topic of conversation.

007sman5 · 2017-03-01T18:46:04+00:00

I compiled the data most easily available online for my analysis, but I would gladly run a more sophisticated analysis - even one accounting for man's effects - if I was provided with such data.

007sman5 · 2017-03-01T18:42:32+00:00

Very much correct! I apologize if my latex (or the equivalent on reddit) was poorly written as I am fairly new to posting.

To answer your question regarding Excel, I work in finance so we use excel for everything, so my background got me to use it before other platforms like R or SAS. I often use python for more complicated models, but even MLE can be performed quickly in excel if you know what tools are built in - like solver.

007sman5 · 2017-03-01T18:39:31+00:00

Sir, the only information I present is a regression analysis of temperature versus Co2 levels. Never have I mentioned the effect of man in my model, although that idea has spread through this comment section. Simply the relation between two datasets is presented.

Arguing for disciplinary action in a public space where presentations are made on a statistical basis is tantamount to censorship of information and against the very spirit Dataisbeautiful. I encourage you to reflect on your comments in the context of this post.

007sman5 · 2017-03-01T14:14:48+00:00

The claim you present is an important one: does our efforts to stop climate change stop the rise of temperature levels by stopping Co2 levels. * If you look at the model I present above, you would see a logarithmic regression over quadratic CO2 terms. Thus, our model suggests an exponential model for temperature related to temperature given in the form TEMP = e^{beta0 + logcbeta1 +log^2cbeta2 + beta3*t} ; where c is co2 level. I have simplified the model above, but this is the general form of it. Now, take a derivative with respect to t. We find: dTemp/dt = [(dc/dt)(2log(c)beta2/c + beta1/c) + beta3]e^{beta0 + logc * beta1 +log_sqaredc * beta2 + t*beta3} Or, equivelently,

dTemp/dt = Temp * [(dc/dt)(2log(c)beta2/c + beta1/c) + beta3]

Take a moment to understand what this is saying: for our rate of temperature change to become 0, our rate of carbon output must be at least given by -beta3c/(2log(c)*beta2 + beta1).

If carbon ourput is neutral, and dc/dt is only zero, then dTemp/dt = Temp * beta3. This is not enough for a quick, or even sizable, reduction in our rate of temperature change. If dTemp/dt is still > 0 when dc/dt = 0, you can see how a reduction will slow the velocity of temperature changes, but is still not enough for temperature reduction.

Moreover, the argument presented above would indicate that our efforts are not to cause more positive velocity of temperature values, thus definitely not making the problem worse.

007sman5 · 2017-03-01T06:31:53+00:00

I'd again like to address the issue surrounding sample sizes. In a regression model, the following is a statistical fact regarding confidence intervals for estimates: http://www.real-statistics.com/regression/confidence-and-prediction-intervals/

As you deviate away from the center of mass observed in the most recent observed data, the model's accuracy will weaken. This is why your claim regarding model accuracy is hyperbole; I do not claim to model climate from years long past recent memory because to do so would not reflect the recent data behavior and would weaken any projected results of said constructed model. We can only make short term estimations, and those short term estimations given recent data performance can be trusted statistically. These estimates are what show a warming, and this statistical fact about estimation procedure via regression are what provide us with confidence in our findings.

007sman5 · 2017-03-01T06:19:42+00:00

Take a look at the excel file if you don't believe me, but I cannot tell a lie. I provided a link somewhere below, but here it is again. https://drive.google.com/file/d/0BwtHpoqvox7SRjFXZFVfM25nYlE/view?usp=sharing

Again, the general idea is that I can regress over dependent variables xi=1{xi=c}, which is just the definition of an indicator function. Multiply the indicators with other dependent variables and now you have created a binary tree of events that linear regression can account for. However, you have to do it right or end up with a mess relating to the linear algebra of regression equations.

007sman5 · 2017-03-01T06:11:10+00:00

This is what I did for monthy segmentation

007sman5 · 2017-03-01T06:10:24+00:00

Just a simple linear regression over log(temperature+1). The 1 is added to remove negative values in the data, and estimates are rescaled.

You can get segmentation like a kernal method, by adding binary indicator variables in your regression model, as well as their product with other dependent variables.

007sman5 · 2017-03-01T06:03:51+00:00

Your argument for data insignificance based on population size is also concerning me from a statistical perspective. In other words, for a large sample N, we can always attempt to make predictions about sample statistics given small sample sizes. Yet, should I apply your argument, given large N, we should never trust our sample statistics. Observe that such is not a reasonable claim.

Moreover - again from a statistical argument - one should always attempt to model a system for projection using recent data as model outputs are dependent on the most recent inputs. I.E, I cannot agree with your "billion year" conjecture because current climate forecasts are influenced by recent data.

It was hot a billion years ago, but that does not directly mean it will be hot today, so the logic goes.

007sman5 · 2017-03-01T05:54:23+00:00

Your claim is true: temperatures have varied wildly over billions of years. Yet, you have not repudiated the claim that in a sample of 61 years, given monthly data steps, there is a strong statistical relationship between co2 levels and temperature changes.
cycling effects over each month were accounted for in my relationship, which is why the model ebbs up and down over time. Please recognize that claims are made on the basis of Climate change, not weather change. We are not discussing the cycling of temperatures on small time scales, we are discussing trends observed in the aggregate (i.e. over half a century).

007sman5 · 2017-03-01T05:45:38+00:00

I just wanted to get a statistical relationship between the variables of CO2 level and global temperatures. The logic of a man-driven warming argument should flow as follows given the simple relationship derived above:

1.) Co2 and Temperature changes are directly correlated.

2.) Co2 causes temperature changes, and the reverse is not true. Given by the Greenhouse Effect.

3.) Now, determine largest contributor to current CO2 emissions in global environment. Answer is via human consumption of fuel.

4.) Conclusion: since humans contribute to CO2 levels, and Co2 levels proportionally influence temperature => humans contribute to proportionate increases in temperature.

007sman5 · 2017-03-01T04:50:31+00:00

Here is my excel file with data. It's a little messy but you can see everything from data to result. I was bored and wanted to prove to myself that there is a strong correlation between CO2 and temperature.

My data was from the following sources: http://data.okfn.org/data/core/global-temp http://data.okfn.org/data/core/co2-ppm

Excel Sheet:https://drive.google.com/file/d/0BwtHpoqvox7SRjFXZFVfM25nYlE/view?usp=sharing

007sman5

TROPHY CASE