Črno-bela rešitev za čim večji izkoristek sivega trga

Črno-bela rešitev za čim večji izkoristek sivega trga

Izvorno vozlišče: 2987374

Vodilni upravljavci premoženja si prizadevajo razviti tehnološke rešitve, ki jim bodo pomagale premagati ključne izzive na primarnih trgih za obveznice, da bodo pridobile več dodelitev in sledile avtomatizaciji, ki so jo v zadnjih desetih letih uvedle sindicirane banke.

Prejšnja zgodba pojasnjuje, kako združevanje podatkov, integracija sistemov, povezanih s trgovino, in olajšanje sodelovanja pomagajo upravljavcem sredstev

spremljanje trga novih izdaj, ocenjevanje priložnosti in usklajevanje odločanja
med upravitelji portfelja, kreditnimi analitiki in trgovci.

However, achieving a complete view of primary markets requires more than just analysing data from official channels.  The next stage is to explore all the data options available to traders, portfolio managers and analysts – and this can be facilitated by
introducing intelligence from the grey market.

Osvetlitev sivega trga

Sivi trg je mogoče opredeliti kot neformalen trg, kjer je mogoče kupiti ali prodati vrednostne papirje, ne da bi bili na voljo na uradnih trgih.  

There are grey markets for equities and commodities as well as fixed income instruments.  Any trading that occurs in the grey market cannot be settled until official trading begins after the listing of the security, which can create settlement risk, but
that risk should be viewed separately from the potential value of the price data expressed in transactions offered in the grey market.

A good example of grey market activity is buying stocks or bonds before they are even issued by the company during the IPO or bond offering.  In the grey market for pre-IPO instruments, trades involve something like unofficial forwards on the instruments,
facilitating traders’ views on whether the issue will be over- or underpriced when it enters the official market.

Cenovna inteligenca in sivi trg

Tako kot uradni trgi je lahko sivi trg bogat vir podatkov za merjenje povpraševanja po novi izdaji in morebitnih cen.

When an instrument is being offered in the primary market, the spread tightens or widens based on the appetite for that instrument and a book size is published and updated with the interest in the instrument. For a deal size of $100 million, if the book
size is at $200 million then the book is already oversubscribed and it will be clear to the participants that they are unlikely to receive a full allocation.  In this scenario, an investment manager looking for the asset, might turn to the grey market to build
svoj položaj. 

Zavarovanje inštrumenta zunaj uradnega kanala zahteva dodatne stroške. To je znano kot premija sivega trga.

For example, a deal originally offered at midswap + 32 and then amended to midswap + 28 (based on strong demand) would probably trade a little higher in the secondary market as traders trying to build a larger position than what they will be allocated are
likely to pay a premium.  The grey market anticipates this and the premium in the grey market will help set the secondary market price for the bond.

A high premium in the grey market tells a portfolio manager that the bond is in high demand and could lead the investment firm to turn to the secondary market to source bonds similar to the technical profile of the new issue.  In doing so, the firm might
get the type of asset it desires at a price lower or equal to the new issue while gaining greater control over the quantity it is able to acquire. 

Nizka premija na sivem trgu bi lahko pomenila nizko povpraševanje po novi izdaji. V tem scenariju ima lahko upravitelj portfelja visoko stopnjo zaupanja glede verjetnosti popolne dodelitve, vendar se lahko odloči za zavarovanje nastalega položaja.

Vnos podatkov o sivem trgu v investicijski proces

In these ways, the grey market augments an investor’s view of new bond deals coming to market.  Yet, the data need to be considered in parallel with deal data coming directly from syndicates via official sources.  Bringing grey market data into the decision-making
process can be complicated because grey market activity takes place on informal channels such as Instant Bloomberg (IB) Chat or Liquidnet’s data stream for new issue trading.  In the case of chats, the data are unstructured and, thus, a challenge to aggregate,
normalize and otherwise format to present alongside more traditional sources of deal data.  Fortunately, AI and related advanced data parsing techniques can come into play to efficiently present grey market data alongside structured data from formal sources.

In conclusion, the grey market offers investment firms another set of demand and price indicators when bonds are set to come to market.  Bringing that intelligence into the investment decision-making process creates advantage, especially when it’s part of
a centralized system that aggregates multiple sources of new issue data available to the asset manager.  

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