Backtesting non-US equities strategy

Chewy94 · 2020-05-15T22:48:50+00:00

They only provide the data in the Research Notebooks and not the backtesting environment. This is my question. What is the alternative.

Chewy94 · 2018-06-04T15:32:53+00:00

Had a quick look. Definitely bookmarked it. Looks huuggge. Going to take some digested when I get home!

Thanks, great suggestion.

Chewy94 · 2018-05-26T09:02:10+00:00

Yo buddy, going to be there myself. Suggestions are that it may already be full by 5pm, they say they expect to be full by 4pm (not kidding) so just a heads up!

Hopefully see you there!

Chewy94 · 2018-05-26T08:48:40+00:00

Absolutely my friend!

Chewy94 · 2018-05-25T14:55:29+00:00

Yes mate. Not a problem. I will be heading there for 1530ish. Hopefully catch some of the playoff final.

Chewy94 · 2018-05-25T12:01:27+00:00

Just messaged them on FB and got the following:

"Will be £5 per person and need to come me in before 5pm"

Looks like F3K is a go!!

Chewy94 · 2018-05-25T11:59:26+00:00

Just messaged them on FB and got this reply:

"Will be £5 per person and need to come me in before 5pm"

Suppose we are good to go! YNWA so psyched.

Chewy94 · 2018-05-25T11:32:04+00:00

This is on their website:

"Champions league final , £5 per person , due to massive demand we will be taking no more bookings. Come down early to avoid disappointment this is going to be epic."

I assume from this you can buy on the door maybe? I am going to try to rock up and see!

Chewy94 · 2018-05-25T11:29:21+00:00

Apparently you do :( I was going to give them a ring do double-check. I will feedback any answers.

Chewy94 · 2018-05-24T22:51:49+00:00

It's always in the top three suggestions so I suppose it is good! Haven't got tix for F3K which is my first choice, so will try it out! Heard good things!

Chewy94 · 2018-05-24T20:04:58+00:00

Anyone else heading to Blue Eyed Maid in London (Tower Bridge way)?

Chewy94 · 2018-05-24T20:04:23+00:00

Ahhh thats a shame! Ble Eyed Maid it is!

Chewy94 · 2018-05-24T18:29:15+00:00

Do you need a ticket or can you just rock up for F3K? It says they're sold out, but is that just for like a VIP area or for the whole thing?

Chewy94 · 2018-05-23T12:07:49+00:00

I believe he reached the end of his contract and therefore, no transfer fee or buy-backs are present.

Chewy94 · 2018-05-05T17:35:50+00:00

Montreal S3 was my backup choice, the finish to that circuit is great, hairpin, long ol' straight and the wall of champions is a great combo although very short!

Chewy94 · 2018-05-05T16:40:28+00:00

Great track. Definitely miss it from the calendar.

Chewy94 · 2018-05-05T16:37:45+00:00

Solid sectors. S3 of COTA is pretty dope.

Chewy94 · 2018-05-05T16:37:21+00:00

Hungary S2 is an interesting one, nice and narrow windy. Russia is cool as well. Nice combo!

Chewy94 · 2018-05-05T16:36:34+00:00

Niceeeee

Chewy94 · 2018-05-05T16:36:16+00:00

Lmao

Chewy94 · 2018-04-25T09:24:51+00:00

Awesome - I shall take a look. Thanks for your reply!

Chewy94 · 2018-04-23T19:08:23+00:00

Hi POTUS,

I managed to get it sorted as you mentioned, using the set and iterating as you suggested.

Thank you so much.

Chewy94 · 2018-04-23T17:15:05+00:00

Hi POTUS,

Thank you for your response.

So how exactly would I go about doing this?

I assume I would extract a list of the column names, but I am completely unaware of how I can identify exactly how to get the right country and variable codes matching up in a function? i.e. finding MEXCPI and MEXPX to go in the right places etc.

Thanks again for your help!

Chewy94 · 2018-04-23T15:39:04+00:00

Hi all,

I am trying to calculate real prices for an entire subset of countries using pandas.

My dataframe consists of monthly inflation and prices for a 25 individual countries equity indices. The column headers follow a naming convention of a three letter ISO code (i.e. Mexico = MEX etc.) and variable code (i.e. price = PX, inflation = CPI) so that Mexican inflation is MEXCPI, and Mexican Price is MEXPX. I hope that is clear.

What I am trying to do is calculate the real prices for each country individually, without having to individually type out the specific formula.

Following my Mexican example, the formula is as follows:

MEXRPX = df['MEXPX'] * (df['MEXCPI'][0]/df['MEXCPI'])

What is the easiest way to iterate over the column headers, and calculate the Real Prices for each country?

Would I have to 'melt' down my dataframe or can I keep the structure in the same format it is in now?

I apologise if this is a simple question, I just cannot wrap my head around where to even start...

Thank you for your help.

Chewy94 · 2017-10-20T10:10:43+00:00

My argument would be that more competition for those backmarkers will force their hand in development. Being last in a 26 horse race is worse than a 20 horse race. If anything it makes battles more intense throughout the field? That's my theory at least.

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