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The computer programs are evaluating the following expression:
$FV(i,N,PMT,PV)=-PMT[\frac{(1+i)^N-1}{i}]-PV(1+i)^N$
the test case you are running is the special case where you choose $PMT=-i\cdot PV$
If we evaluate the formula symbolically (as opposed to numerically) we get a fortunate cancellation:
$FV(i,N,-i \cdot PV,PV)= PV(1+i)^N-PV(1+i)^N-PV=-PV$
the ...
4
This is not a bug, just how computers work. Would have been better to ask in a non finance forum though. It is called (Integer) Overflow. If you are into reading humorous chats, you can have a look here.
You can find an explanation in most documentations. Numpy is a funny one as Python does not have this issue.
I assume it is fair to say the author's did ...
4
"How do they choose the forex price number's precision?"
By convention. And/or by vendor, e.g. BBG has 4dp for some pairs where Oanda has 5. And of course convention for forwards differs from spot, even for the same pair.
There is some colour on the move to 'fractional pips' in the book "Why Aren't They Shouting?".
EDIT: perhaps also ...
3
As @noob2 posted, al these libraries do is to apply this formula:
$FV(i,N,PMT,PV)=-PMT[\frac{(1+i)^N-1}{i}]-PV(1+i)^N$
However, the same formula can be rewritten as:
$-PMT \frac{c}{i} + \frac{PMT}{i} - PV \cdot c$ , where $c=(1+i)^N$,
which can be rearranged as:
$-c \left( \frac{PMT}{i}+PV \right) + \frac{PMT}{i}$
A possible solution is to use a function ...
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I had to deal with discrete FX quotes a long time ago. My answer may be badly out of date, sorry.
For each currency pair, there is a "PIP", which stands for "point in percentage" or "price interest point" or "percentage in point", and used to be the smallest amount by which the quote can change. It is usually 1 basis ...
2
In addition to @user42108's great answer:
Maybe you already had a look on the 'usual' sources. Wiki states that the convention is still 4 to 6 digits, and Bank of Canada states the same, i.e. up to six digits. There may be currency pairs that are quoted with less digits, this seems to be the case when the exchange rate is above 80 or so.
Depending on your ...
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Looking at the dates in your DataFrame (they're all parsed as the first day of a month), it appears that you need to add dayfirst=True in your read_csv statement.
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Same as you did for the other instance of the index, except you'll also have to pass the term structure:
index = IborIndex('TIIE', Period(28, Days), 2, MXNCurrency(),
NullCalendar(), Following, False, Actual360(),
forecastTermStructure)
As Dimitri commented, you might also use Mexico() instead of NullCalendar() in both ...
1
Why do you not ask the help desk? They would have shown you where to find code examples and guides: WAPI- "API Developer's Guide" - "Core developer guide", 13.5. REQUESTING INTRADAY TICK DATA
The data is the same - if it works in excel it must work in Python. Bloomberg's API website shows that both use C++.
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This will NOT work.
You cannot get ICVS curves in API. Excel has a curves toolkit for excel. However, for WAPI, you need enterprise licenses (not part of terminal subscription). Your account manager can help you with that if that is truly needed.
What you do here, is simply a FLDS field. Check out YCSW0045 Index FLDS CURVE_TENOR_RATES on the terminal. You ...
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Moodys own CreditEdge API gives credit ratings for corporates as well as other other credit risk data.
https://developer.moodysanalytics.com/products/creditedge
You have to sign up for an account and the documentation is sparse but it appears to be free, at least for now.
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Simplest way to check is to load on the terminal.
BCSWFPD BGN Curncy GP MAX
vs
BCSWFPD CMPN Curncy GP MAX
You are querrying data that does not exist. CMPN has more history.
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How are these distributed? $\epsilon_{t+1}\sim\text{SGED}(\mu_{t+1},\sigma_{t+1},\text{skew},\text{shape})$.
For a $(1-\alpha)$ level $1$-step-ahead forecast interval that is consistent with the model
obtain the $\alpha/2$ and $1-\alpha/2$ quantiles of the distribution of the standardized innovation $e$ (regardless of the time index, since $e_t$s are i.i.d.)...
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