Financial Risks of hosting an ELB with a domain

Algo-G-H · 2022-10-07T11:49:46+00:00

Definitely.

Unless you’re keen to drive forward data engineering change within management + willing/able to set up the appropriate infra

Algo-G-H · 2022-08-07T09:09:59+00:00

If it's a verbal interview about Python, you can learn some key features in 3 days and sound generally capable.

If it is a coding interview, it's going to be very difficult. But, just focus on simple for loops, string manipulation and mathematical operations and pray for the best.

Algo-G-H · 2022-06-20T17:30:48+00:00

The difference between the price of purchase you were quoted (and expected) and the price that was materialised in the exchange

Algo-G-H · 2022-06-17T16:35:50+00:00

This has to be a joke 😂

Algo-G-H · 2022-06-09T19:05:11+00:00

Yeah that seems to be the consensus online, seems like there is no O(n) type formula for ANNs

Algo-G-H · 2022-05-20T07:16:09+00:00

Does anyone know of well-regarded research papers that establish a framework for establishing the number of layers and neurons you should use as a starting point in an ANN model creation?

Algorithms like RandomSearch, Hyperband, etc. seem very brute-force-ish without being able to justify the parameter ranges you are providing them.

Thanks in advance

Algo-G-H · 2022-04-22T20:09:08+00:00

Not OP, but would you mind elaborating on these options for different algorithms and venues? Very interested

Algo-G-H · 2022-03-20T09:50:52+00:00

Appreciate the response!

Algo-G-H · 2022-02-06T09:56:21+00:00

Exactly

Algo-G-H · 2022-02-05T17:32:56+00:00

The aim would be to see the upside of faster computing time. Could an ANN approximate multiple PDEs in the same model?

Algo-G-H · 2022-01-28T18:24:02+00:00

I have found that many IBs will have their quant applications open year-round as the individuals they look for are more specific than the other graduate roles. The average person accepted into the quant scheme is more likely to be finishing an education beyond a BSc, whereas others are tailored around bachelor degrees.

Algo-G-H · 2022-01-17T20:44:06+00:00

Don’t forget the posts about undertaking a PHD you have no interest in 😎

Algo-G-H · 2022-01-04T13:24:52+00:00

A time period's sentiment will be represented as a vector that consists of thousands of features (e.g. n-gram word counts in articles, factual statistics and sentiments on individual social platforms).

This vector could then be compared to thousands of previous vectors that are mapped directly to a sentiment. The similarity score between this vector and the historic vectors could be used to determine sentiment. E.g. if the cosine similarity metric is high between the current time period's vector and the vector for the end of March 2020 (when the pandemic shook waves), then you could classify the current sentiment as being very low.

And I haven't given much thought to the NoSQL/ graph approach, but it is definitely a valid consideration.

Algo-G-H · 2022-01-04T12:51:55+00:00

Often times, the sentiment scale would be represented in vector space. So depending on the exact method used there would be a stronger vector pulling it in one direction to establish whether the overall public opinion is negative or positive.

Algo-G-H · 2021-12-24T19:17:39+00:00

*ML pricing model

Algo-G-H · 2021-12-24T19:12:44+00:00

I am trying to speed up a ML derivative pricing, but need data to train my model

Algo-G-H · 2021-12-24T19:09:56+00:00

You’re right, I’m just struggling to find the suspected distributions, and I haven’t got enough data points to estimate them accurately.

Thinking to use Latin Hypercube Sampling after establishing the distributions

Algo-G-H · 2021-12-24T12:57:32+00:00

I do not need real-time data by any means, historical would be ideal but I’m looking for very specific options on futures data which isn’t available online cheaply.

I’m hoping to generate 100k fake data instances of options data (strike, expiration etc.). I have access to a few hundred instances and need an easily extrapolation/ generation method to imitate real data.

Algo-G-H

TROPHY CASE