OptiRisk’s Sentiment Enhanced Signals (SES) Model for Hang Seng

>>OptiRisk’s Sentiment Enhanced Signals (SES) Model for Hang Seng

OptiRisk’s Sentiment Enhanced Signals (SES) Model for Hang Seng

OptiRisk’s SES (Sentiment Enhanced Signals) Strategy for Hang Seng 50 uses Second Order Stochastic Dominance as its backbone.

This asset allocation strategy has been running on Interactive Brokers since 16 May 2019 and is currently at a profit of 38.92% while the index is at 4.61%

Our strategy uses RSI Threshold Filter with SSD optimization in its foundation. Sentiment Enhanced Signals (SES) optimize the equity portfolio composition using a powerful optimization model known as Second Order Stochastic Dominance (SSD). SSD approach is considered to be a ‘game changer’ in asset allocation and portfolio construction.

The strategy is a result of the extensive academic research, followed by multiple tests in back testing, virtual trading and live trading by OptiRisk. Based on our research, the methodology of SSD has emerged as a primary method of asset allocation with ‘down-side risk control’.

SSD solves the asset allocation problem by constructing a portfolio that dominates a given reference distribution, that is, the distribution of a benchmark portfolio. In our case, the benchmark is set to be one of the major market indices – HANGSENG50. By concentrating on the minimization of downside risk in asset allocation, a combination of assets is formed to produce the optimal portfolio that achieves the highest returns. You can find more information about the optimization model here.

Please find summary statistics for this strategy below:

Initial Portfolio Value – 1.9 M
Final Portfolio Value – 2.623 M
Net PnL – 723K HKD

PortfolioHP Return (%)Annualized Return (%)Volatility (%)Sharpe RatioMax Draw Down (%)Recovery DaysWin DaysLoss Days
HANGSENG504.612.7220.10-0.0626.04248212210
OPTIRISK38.9221.6321.450.8218.95113226196

Get in touch with us at info@optirisk-systems.com for more details about the strategy.

2021-01-29T07:40:08+00:00 29 January 2021|Blog|