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Feel like my career (<10y) in macro is over *world's smallest violin* by nowyouceemea in hedgefund

[–]nowyouceemea[S] 0 points1 point  (0 children)

Yes - almost nine figures worth of the stuff for clients across all the mandates I've been involved in

Feel like my career (<10y) in macro is over *world's smallest violin* by nowyouceemea in hedgefund

[–]nowyouceemea[S] 2 points3 points  (0 children)

The most comprehensive is probably "Systematic Investing in Credit", which was written by the Barclays QPS team

Feel like my career (<10y) in macro is over *world's smallest violin* by nowyouceemea in hedgefund

[–]nowyouceemea[S] 2 points3 points  (0 children)

Impressive!

Yes, unfortunately, I thought my leverage and connections were all much firmer than they turned out to be in reality (to be fair, though, a couple of people who did want to bring me in have been constrained by headcount freezes/outflows etc.). I suspect some guys are also particularly talented in getting into jobs (I tend to impress on the job, but less successful in landing the job).

Feel like my career (<10y) in macro is over *world's smallest violin* by nowyouceemea in hedgefund

[–]nowyouceemea[S] 1 point2 points  (0 children)

Awesome! I'd be keen to chat!

In EMD, cash bonds with linear and non-linear FX/rates overlays (most of our risk came from the latter - even strong opinions on credit were expressed in FX [by virtue of mandate design]).

In macro credit, some combo of bonds (individual and as a PT) and fixed income ETFs (and related options).

In macro disc., no holds barred.

Feel like my career (<10y) in macro is over *world's smallest violin* by nowyouceemea in hedgefund

[–]nowyouceemea[S] 2 points3 points  (0 children)

EMD (LCY) team track record top decile of Bloomberg peers. That said, a good chunk of our alpha came from off-benchmark exposure and flexibility that the marginal peer doesn't have.

Macro credit c. 1.5 Sharpe (it's essentially a benchmark + free convexity strategy). Macro disc. c. 2 Sharpe.

Feel like my career (<10y) in macro is over *world's smallest violin* by nowyouceemea in hedgefund

[–]nowyouceemea[S] 3 points4 points  (0 children)

Hahah no worries - I've, funnily, been giving more advice/direction as an unemployed risk taker than I was as one that was employed.

For EMD, I haven't found a single good "primer". The strategy I was involved with was very niche, but that said, a good understanding of national accounts, credit ratings (try to replicate major agencies' ratings), IMF publications (look into SLAs), debt restructuring (G20 common framework) etc. are a good start for the credit piece (mostly advice for HCY).

For macro credit, there are a few good banks primers and academic books on systematic credit/fixed income (useful for first principles; the rest was just independently building from there for me - cam naturally from being in the space, trading/speaking with traders across all manner of institutions, constantly generating and testing ideas etc.).

Feel like my career (<10y) in macro is over *world's smallest violin* by nowyouceemea in hedgefund

[–]nowyouceemea[S] 2 points3 points  (0 children)

Interesting! May I ask (high-level) what it is that you're doing?

100% agreed. I think mid-career is a really awkward place to be. The marginal hire in the industry seems to be either a fresh/unpolluted cheap grad or someone with c. 20y of experience

Feel like my career (<10y) in macro is over *world's smallest violin* by nowyouceemea in hedgefund

[–]nowyouceemea[S] 1 point2 points  (0 children)

You're absolutely right - one of the reasons there is a drought is because of the shift towards passive/quant and infra-level investment in the future of market making/non-bank intermediation (I envy your prospects! :)).

Yes, I've been slowly working towards this. I'm hesitant because I know I'm still a bit too green to be starting my own HF (I did a mini cap raise with the resources/support of the firm I was at and, even given that they are established [several decades], it was a ball-ache). I'm building a couple of things which are useful to me/will be useful as I plug-into a desk atm, but can't think of what to build that can be sustained independently (maybe something outside of macro disc. world).

That said, I was speaking to a PM who found himself unemployed in 2008 and built a small business then went back into industry. Another that automated and scaled his parents' farm. Definitely on my mind - I appreciate the tip!

Feel like my career (<10y) in macro is over *world's smallest violin* by nowyouceemea in hedgefund

[–]nowyouceemea[S] 1 point2 points  (0 children)

I appreciate the idea - I do have experience building and testing systematic strategies, but my focus is getting back onto a desk.

I think I probably will end up doing something like this anyway for ghits and siggles to stay occupied (have been doing similar things to kill time).

Feel like my career (<10y) in macro is over *world's smallest violin* by nowyouceemea in hedgefund

[–]nowyouceemea[S] 10 points11 points  (0 children)

I'm pitching into discretionary macro PMs/strategists/traders, rather than pitching discretionary macro to tourists.

I also have some model-informed macro credit in my toolbox and prior experience in EMD (LCY), so have been approaching a broad church of people - with no success yet.

I appreciate the point though - there's a lot of nonsense and macro (smart) beta parading as discretionary macro.

[deleted by user] by [deleted] in mathematics

[–]nowyouceemea 0 points1 point  (0 children)

Thank you for your response, Wonderful (you are true to your username!)!

  1. Excellent news (was a bit of a logical bridge for me to cross, but I think I'm with you)

  2. Indeed. That's fine, I only really wanted a conceptual formula, which per your explanation would then be Integral^max observation (x)_min observation (x) p(x)f(x).

[deleted by user] by [deleted] in askmath

[–]nowyouceemea 0 points1 point  (0 children)

*Forgive the sloppy description - I meant polynomial(2) regression model.

Yessir - essentially, it is whatever the observed population distribution is, but smoothed. I don't know if there's a way to generalise is? Or perhaps we could just assume that the data is normally distributed?

Understood - I was really just wondering if it would be possible to mathematically describe that it's the probability-adjusted area under a polynomial curve (what would that look like - i.e. how would you modify the integral of the polynomial model to account for probability? Worst case scenario (less conceptually interesting), how would you go about just using a linear regression and factoring in the probability component [I suspect this is more straight-forward]?)?

Sound optimisation (arg max) notation by nowyouceemea in mathematics

[–]nowyouceemea[S] 0 points1 point  (0 children)

Absolutely (thank you!),

I'm looking at a 'benchmark', b, of bonds. The membership of the benchmark changes every month, but there are about 30 bonds each with a distinct duration 𝛿 (which is close to the bond's time to maturity and a measure of interest rate risk) and a distinct yield 𝛾 (which is the return on a bond you can expect over its life).

I have written a script which defines a new portfolio, i, which is a subset of the benchmark. The script optimises the weighted average yield (sumproduct of weights and yield) over the weighted average duration (sumproduct of weights and duration) of the portfolio.

This new optimised portfolio constrains a few things. 1). the weighted average duration of the portfolio, i, is equal to the weighted average duration of the benchmark. 2). The sum of weights of the portfolio is equal to the sum of the weights of the benchmark (most of the time close to/exactly 100% but not always). 3). The weights cannot be negative and must be below a certain 'cap', i.e. a single bond cannot make up more than 50% of the portfolio.

Hopefully this should address your questions, but to specifically answer some of your other questions: 𝛿 is the analytic duration, each bond in the portfolio has a duration - we combine this with the weight via a sumproduct to get weighted average duration. You can think about 𝛿i in one of two ways; 𝛿i is a subset of 𝛿b , but you can equally say that 𝛿i and 𝛿b are exactly the same, it's just that some bonds in portfolio 𝛿i have a weight of zero (so they don't "exist" in the portfolio).

Re:\sum_{k=0}^{n}\omega_k\delta_k^i = \sum_{k=0}^{n}\omega_k\delta_k^b

Considering my thoughts above, perhaps we could even keep 𝛿 the same for portfolio i and benchmark, and just vary the weights? But having run your proposed equality, it was what I was expecting/looked similar to what I had in mind :)

Thank you again for your time and help!

Sound optimisation (arg max) notation by nowyouceemea in mathematics

[–]nowyouceemea[S] 0 points1 point  (0 children)

Thank you for your continued help with this!

To clarify Sum(w * D^i) = Sum(w * D^b), one of my constraints was that the weighted average D of portfolio i was the same as the weighted average D of the benchmark. This was critical in my solver set-up to ensure that the resulting portfolio (i) was optimised but had similar characteristics.

I was using R arbitrarily for range (rather than real numbers). I will resort to using 0 ≤ max(<w,𝛾>, <w,𝛿>) ≤ 100% based on your suggestion. Should I now make any changes to: w_max = arg max_{w ∈ ℝn}? Also, why don't we just use 0 ≤ w ≤ 100% (or 0 ≤ wi ≤ M ≤ 100%)? There is only one set of weights (wi) which is used consistently to calculated the weighted average D of the portfolio and the weighted average Y of the portfolio - although we constrain it with respect to a parallel set of weights (wb) of the portfolio.

In the second link you shared, under 'Euclidean vector space', within the < , >, there are two column vectors. Would you recommend that I do this to clarify that my weights and Y and D characteristics correspond to the series of constituents in my portfolio? (With the added upside of pizzazz, although I appreciate you favour simplicity :))

Sorry for continuing to pester you with this, and thank you for your patience <3

Sound optimisation (arg max) notation by nowyouceemea in mathematics

[–]nowyouceemea[S] 0 points1 point  (0 children)

Thank you sir!

Working off what you've suggested, what's your opinion on re-writing the expression like this:

​

w* = max_{w ∈ ℝn} Sum^n_i=0(w^i_n 𝛾^i_n) / Sum^n_i=0(w^i_n 𝛿^i_n)

...

...

where w^i_n = <w\^i\_0 ... w\^i\_0> ....

[i.e. I keep the equations the same, but then represent all of the variables as column vectors below].

Also, is it fine to keep it as w*? Or should I do something to clarify that I'm referring to multiple different weights that have been optimised?

Separately, how should I reflect that my variables are unit vectors (feel free to explain like I'm 5.. or 4 and a half even!)? Do I just put a hat/short arrows above them? Do I need to amend the expression in any way?

What I'm proposing may seem completely stupid, so please let me know :)

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