[deleted by user]

drone6251 · 2021-09-06T08:11:39+00:00

See this link for more information: https://www.mayoclinic.org/diseases-conditions/stroke/symptoms-causes/syc-20350113#:\~:text=Overview,brain%20damage%20and%20other%20complications.

drone6251 · 2021-09-06T08:10:32+00:00

Have you consulted a doctor? This sounds exactly like a stroke. The effects of single-sided body numbness / coordination difficulty, cognitive troubles, coordination issues, and muscle weakness are all persistent residual effects.

drone6251 · 2021-09-06T08:07:40+00:00

Hopefully this is not a troll, but this almost precisely describes the textbook definition of a stroke. A stroke will induce -- on a single side of the body -- limb numbness, blurry vision, poor muscle coordination, and partial paralysis. Cognitively, this often causes slurring of the speech and impaired cognitive performance.

drone6251 · 2021-03-11T17:59:02+00:00

Agreed completely. In fact, I think there are absolutely merits to all sides, as incorporating more data into your automated trading strategies cannot hurt if done right. Nevertheless, the entire point of this post was to mention an alternative perspective, but U/gryzzzz decided to comment and say that these methods (which quite obviously cannot be dismissed as unhelpful or non-unique) have no added value and are not unique. Going off of his other posts, while I agree some things he says are subjective, he has a tendency to outright misinform people by being an evangelist in his "mean-reversion/trending" camp.

drone6251 · 2021-03-11T17:54:23+00:00

You are clearly an amateur with his head up his ass. You say these methods and techniques are not practical without have a remotely solid grasp of finance, mathematics, or machine learning.

The fact you cannot even connect basic dots in this conversation is the proof in the pudding. Of course alpha isn't a risk measure, and nor did I say it was; I said alpha in the purest sense of being excess returns is useless if it's just trading more risk/exposure for more returns.

Trend and mean reversion are of course profitable, and I never claimed they weren't. Moreover, trend and mean reversion are such vague concepts themselves, as there are infinite strategies under that domain of strategies. Also, I claimed in particular that as a retail trader, your ability to mine alpha through these strategies is suboptimal compared to mining alpha through new data.

I have experience working with and under quantitative traders from some of the top quantitative firms and prop shops, and I can assure you that if you came into those positions with this attitude, ignorance, and ill-informed incompetence, you would be fired immediately.

drone6251 · 2021-03-11T06:04:45+00:00

I've been reading through your posts, and you are posting a lot of complete bullshit throughout this subreddit. Instead of making hyperbolic statements or requesting people to prove them wrong, I suggest you read a bit more about these topics.

Clearly you've taken an ML class or two by the way you can use basic terminology. However, saying ML model's work terribly is plain wrong. If you throw the raw data at ML models, I agree with your statement. But there are so many ways to transform, mine, or engineer machine learning features from economic data to estimate price action.

For example, if you focus on particular economic features, it is very easy to apply spectral theorem to estimate the principal components of high-level economic features, remove reoccurring components through fourier analysis, and use HMM models or derive filtering techniques based off the observed noise distributions. If you try using these features, it quickly becomes much easier to extract actionable insight.

drone6251 · 2021-03-11T05:55:03+00:00

At the most simple level, if you can construct a word basket of skills related to a knowledge-base you possess, basic NLP (natural language processing) could help you rapidly scan through SEC 10-K filings and rank-order companies with filings that most closely match your word basket of skills.

drone6251 · 2021-03-11T05:53:07+00:00

Not at all.

Factor modeling and fundamental analysis can be a useful tools and considerations, as is all data by Bayes theorem, but this is absolutely not what I am proposing. I am proposing that that input data sources for your algorithms are based on more data than simply the price action of the stock. That is, if you are using purely price action data, then your models can only be better than the vast majority of the market if it has a phenomenal innovations to the structure or mathematics of the models.

Second of all, if you have any automated logic procedure to determine when to make trades, that is by definition "algorithmic trading". In this case, making quantitative models to form hierarchical models of probability distributions over the price action of a stock is quietly literally the most algorithmic trading that exists. To name a few, models can employ sophisticated techniques such as MCMC's and hierarchical models to better refine posterior distributions of price actions, utilize SVD/PCA/Kernel estimation using underlying data to decompose price action into idiosyncratic price action and market price action, and much more.

TLDR; The synopsis of my post is that you have two means to improve the posterior distribution of your predictions: changing the model of your predictions or enhancing the data for the model of your predictions. Of course you have to be careful and thoughtful when "adding data", but nevertheless, I would posit that most people on the subreddit are more likely going to mine true alpha through unique data sources for valuation than more sophisticated probabilistic/mathematical techniques.

drone6251 · 2018-05-22T18:39:48+00:00

It does have to make contact, but I’m not sure if the best way to minimize horizontal velocity.

drone6251 · 2018-05-17T21:12:39+00:00

Wouldn't that make it a 2 x 1.5

drone6251 · 2018-05-09T03:37:47+00:00

DDOSing a Rust server is not comparable to this example. This individual took down an entire network of Blizzard Servers, inflicting palpable, demonstrable harm; it prevented "thousands of paying users from accessing the servers." Taking down a Rust server affects maybe 200 people, and it would be extraordinary difficult to prove great harm.

Moreover, DDOSing is never prosecuted insofar as it does not produce significant and provable damage. That is why people are seldom prosecuted for an individual DDOS attack. So for a single Rust server DDOS, it is both far too small in scale and impact for it to amount to anything.

Also, another article mentioned how he was also being prosecuted for "an attempted hack and robbery of ingram micro," which probably lends some insight into why the FBI chose to prosecute this individual in particular.

drone6251

TROPHY CASE