headerdesktop libfest19mar24

MAI SUNT 00:00:00:00

MAI SUNT

X

headermobile  libfest19mar24

MAI SUNT 00:00:00:00

MAI SUNT

X

Promotii popup img

LIBfest e on!

Reduceri, carti cu Autograf si

Dialoguri cu scriitori

Plaseaza comanda!

Machine Learning for Asset Managers

Machine Learning for Asset Managers - Marcos M. L�pez De Prado

Machine Learning for Asset Managers


Successful investment strategies are specific implementations of general theories. An investment strategy that lacks a theoretical justification is likely to be false. Hence, an asset manager should concentrate her efforts on developing a theory rather than on backtesting potential trading rules. The purpose of this Element is to introduce machine learning (ML) tools that can help asset managers discover economic and financial theories. ML is not a black box, and it does not necessarily overfit. ML tools complement rather than replace the classical statistical methods. Some of ML's strengths include (1) a focus on out-of-sample predictability over variance adjudication; (2) the use of computational methods to avoid relying on (potentially unrealistic) assumptions; (3) the ability to "learn" complex specifications, including nonlinear, hierarchical, and noncontinuous interaction effects in a high-dimensional space; and (4) the ability to disentangle the variable search from the specification search, robust to multicollinearity and other substitution effects.
Citeste mai mult

LIBfest

-20%

transport gratuit

PRP: 193.23 Lei

!

Acesta este Pretul Recomandat de Producator. Pretul de vanzare al produsului este afisat mai jos.

154.58Lei

154.58Lei

193.23 Lei

Primesti 154 puncte

Important icon msg

Primesti puncte de fidelitate dupa fiecare comanda! 100 puncte de fidelitate reprezinta 1 leu. Foloseste-le la viitoarele achizitii!

Livrare in 2-4 saptamani

Plaseaza rapid comanda

Important icon msg

Completeaza mai jos numarul tau de telefon

Poti comanda acest produs introducand numarul tau de telefon. Vei fi apelat de un operator Libris.ro in cele mai scurt timp pentru prealuarea datelor necesare.

Descrierea produsului


Successful investment strategies are specific implementations of general theories. An investment strategy that lacks a theoretical justification is likely to be false. Hence, an asset manager should concentrate her efforts on developing a theory rather than on backtesting potential trading rules. The purpose of this Element is to introduce machine learning (ML) tools that can help asset managers discover economic and financial theories. ML is not a black box, and it does not necessarily overfit. ML tools complement rather than replace the classical statistical methods. Some of ML's strengths include (1) a focus on out-of-sample predictability over variance adjudication; (2) the use of computational methods to avoid relying on (potentially unrealistic) assumptions; (3) the ability to "learn" complex specifications, including nonlinear, hierarchical, and noncontinuous interaction effects in a high-dimensional space; and (4) the ability to disentangle the variable search from the specification search, robust to multicollinearity and other substitution effects.
Citeste mai mult

De pe acelasi raft

Parerea ta e inspiratie pentru comunitatea Libris!

Acum se comanda

Noi suntem despre carti, si la fel este si

Newsletter-ul nostru.

Aboneaza-te la vestile literare si primesti un cupon de -10% pentru viitoarea ta comanda!

*Reducerea aplicata prin cupon nu se cumuleaza, ci se aplica reducerea cea mai mare.

Ma abonez image one
Ma abonez image one