Methods and tools for guranteeing portfolio expected return while minimizing risks

A software tool that is based on the aforesaid portfolio optimization method, the characteristics of which include at least the following:

• a. The system creates a new portfolio optimisation processing thread and provides user with a User Interface (UI) which is capable of and ready to collect user data;
• b. When user clicks the “Optimise Portfolio” button, analyse user input and check whether the user has specified expected returns for all securities in the given portfolio, if the answer is yes, enter step d;
• if not, notify the user of the securities the expected returns of which have not been specified and offer the user the option to let the system automatically estimate the expected returns of those securities;
• in the case of the user choose to fulfill those missing data and click the “Optimise Portfolio” button again, restart step b and re-analyse user data to determine whether to proceed to step d;
• if the user choose to let the system estimate expected returns, proceed to step c;
• c. Quantitatively estimate the expected returns for all securities the expected return of which have not been specified by the user, then proceed to step d;
• d. Analyse user input and check whether the user has specified any position size boundary limit on any security in the concerned portfolio, if so, proceed to step e;
• if not, enter step f;
• e. If user specified position size limits are greater than 0% or less than 100%, and the upper limit is greater than the lower limit, proceed to step f;
• if that is not the case, return to step b and re-collect user data;
• f. Check user data for the risk appetite factor, if it is specified, proceed to step g;
• if not, return to step b and re-collection user data;
• g. Check whether the user chooses to add optimisation P&L as a calculation factor in the mathematical quest for the optimum weight ratios, if the answer is yes, add this factor in the input factor list, proceed to step h;
• if not, enter step h directly without adding optimisation P&L into the factor list;
• h. In this pre-optimisation estimation step, analyse user specified expected return, position size upper/lower limits, VaR time horizon and VaR calculation results, estimate whether the given user input can theoretically produce a logical optimisation result that satisfies the user's expected portfolio return, if so, enter step j;
• if not, proceed to step i;
• i. Automatically adjust the expected portfolio return value base on the given user input so that all input to the optimisation calculation are logically valid, then proceed to step j;
• j. Check whether the user allows long/short positions in the optimisation result, if so, store the user preference on this long/short positions and corresponding size limits which is utilized later during the optimisation process, then proceed to step k;
• if not, set the default preference as allowing both long and short positions, then proceed to step k;
• k. Calculate VaR for all user specified securities base on time-horizon, historical scenarios and Monte-Carlo simulation, produce the hybrid VaR in accordance to the correlation factors between each VaR factor. If time-horizon or historical scenario is not specified, the system sets the default time horizon as 1 day and default scenario as the 2007 subprime mortgage crisis initiated global financial meltdown, proceed to step 1;
• l. Conduct portfolio optimisation calculation base on user data collected from steps b to k and corresponding market data, produce the optimum weight combination for securities in the portfolio, the portfolio expected return and portfolio risk on completion of the optimisation calculation, proceed to step m;
• m. Calculate pre-optimisation portfolio P&L and portfolio risk, produce a comparison report on pre and post optimisation portfolio performance store for later UI presentation and search facilities, proceed to step n;
• n. If dynamic optimisation P&L is not specified as a calculation input factor, then analyse the differences between positions pre and post optimisation on each security, calculate and produce the trades necessary to bring the current portfolio to the optimum, together with the corresponding P&L generated by those trades, enter step o after storing the results;
• in the case of user specified expected return for each security and the portfolio fall outside of the optimisation P&L, then reduce the optimisation P&L to 0 and restart step m;
• If optimisation P&L is added as a calculation factor and the optimisation result satisfies the optimisation P&L boundary, the optimisation is considered a success under this specific condition and result stored for later presentation, proceed to step o;
• o. Present calculation and optimisation results at UI.