The objective of the report is to develop a bidirectional gap filling strategy that will be used in the "Quantitative Investment Strategy" field lab's common part, which will create a portfolio of three investment strategies. The dataset here used was obtained from Trade station and includes historical 1-minute prices of the cash session of the E-miniS&P500 futures from 01/03/2000 to 10/27/2021. For the validation, an innovative methodology is used, which increases the OOS performance stability. All the outcomes and the back test were carried out by coding an entire engine in Python and accelerating it with Numba
This paper describes a forecasting exercise of close-to-open returns on major global stock indices, ...
The systemic impact of the global financial crisis of 2008 reveals that there are periods of uncerta...
This work focuses on trading on stock exchanges, namely on the futures markets from the perspective ...
The aftermath of the recent financial crisis has caused the narrowing of investment opportunities fo...
Paper [I] tests the success rate of trades and the returns of the Opening Range Breakout (ORB) strat...
This study is motivated by the theoretical framework that suggests market timing and other algorithm...
This is the fourth of nine NebGuides laying the foundation for producers who want to study the techn...
[[abstract]]This study investigates the out-of-sample hedging effectiveness and dynamic hedge ratios...
This article examines the determinants of trading decisions and the performance of trader types, in ...
This paper develops a fully-fledged statistical arbitrage strategy based on a mean-reverting jump...
Most financial firms use algorithms to buy and sell financial assets. It is possible for amateur inv...
In an efficient market, prices of stocks reflect all relevant information. Efficient Market Hypothes...
This project takes several common strategies for algorithmic stock trading and tests them on the cry...
This paper develops a fully-fledged statistical arbitrage strategy based on a mean-reverting jump–di...
Includes bibliographical references.This research report documents an example of evidence of investo...
This paper describes a forecasting exercise of close-to-open returns on major global stock indices, ...
The systemic impact of the global financial crisis of 2008 reveals that there are periods of uncerta...
This work focuses on trading on stock exchanges, namely on the futures markets from the perspective ...
The aftermath of the recent financial crisis has caused the narrowing of investment opportunities fo...
Paper [I] tests the success rate of trades and the returns of the Opening Range Breakout (ORB) strat...
This study is motivated by the theoretical framework that suggests market timing and other algorithm...
This is the fourth of nine NebGuides laying the foundation for producers who want to study the techn...
[[abstract]]This study investigates the out-of-sample hedging effectiveness and dynamic hedge ratios...
This article examines the determinants of trading decisions and the performance of trader types, in ...
This paper develops a fully-fledged statistical arbitrage strategy based on a mean-reverting jump...
Most financial firms use algorithms to buy and sell financial assets. It is possible for amateur inv...
In an efficient market, prices of stocks reflect all relevant information. Efficient Market Hypothes...
This project takes several common strategies for algorithmic stock trading and tests them on the cry...
This paper develops a fully-fledged statistical arbitrage strategy based on a mean-reverting jump–di...
Includes bibliographical references.This research report documents an example of evidence of investo...
This paper describes a forecasting exercise of close-to-open returns on major global stock indices, ...
The systemic impact of the global financial crisis of 2008 reveals that there are periods of uncerta...
This work focuses on trading on stock exchanges, namely on the futures markets from the perspective ...