This document provides examples of customized investment portfolios that can be created using optimization tools to meet specified risk, return, and constraint criteria. Example 1 creates a portfolio of 70-100 global stocks optimized for a target return of 12-15% with sector and exposure limits. Example 2 adds constraints on geography, market capitalization and price-to-earnings ratio. Later examples optimize portfolios for negative or positive correlation to market indices, thematic investments in Japanese stocks, and other specialized criteria. The examples demonstrate how optimization tools can be used to construct portfolios tailored to specific investment objectives or risk profiles.
This document provides a performance analysis of an algorithm company over several periods from 2016-2020. It includes key financial metrics such as sales, operating profit, net income, operating and net income rates, return on equity, debt ratio, and quick ratio on an annual and quarterly basis. It also analyzes the company's stock price performance, providing the current price and indication price ranges. Finally, it evaluates the company and provides a stock price rise probability score and investment opinion.
This document analyzes mergers and acquisitions in the apparel retail industry from 2010 to 2015. It finds that the average deal value was $278 million, with average price-to-revenue and price-to-EBITDA multiples of 0.9x and 11.4x, respectively. Transaction multiples trended down from 2010 to 2012 but increased in 2014 and 2015. The largest portion of deals were under $100 million. Geographically, deals were distributed across Asia Pacific, Europe/MENA/Africa, and the Americas.
RTL Group is a European broadcasting company headquartered in Luxembourg. The document analyzes RTL Group as an investment opportunity, providing an industry overview, business overview, financial analysis, valuation, and discussion of risks. It recommends buying RTL Group stock, with a current price of €77 and a target price of €89.5, representing 17% upside potential. The analysis finds RTL Group to have a strong position in European TV markets and forecasts continued revenue and margin growth.
This document analyzes the performance and financial metrics of Algorithm company over several periods from 2017-2020. It shows sales, operating profit, net income, operating rate, net rate, ROE, debt ratio, quick ratio and other metrics on a quarterly and annual basis. It also provides the company's current stock price, indication price range, and evaluation. A chart shows the indication price range. Tables also show the company's industry, ranking, a suggested purchase amount and number of stocks to purchase at different price levels. Graphs show the stock price rise probability score and increase rates over time for the company versus industry averages.
This document provides a performance analysis of an algorithm company over several time periods from 2015-2019. It includes key financial metrics such as sales, operating profit, net income, operating rate, net rate, return on equity, debt ratio, quick ratio, and earnings per share. It also analyzes the company's stock price against indication price ranges and provides strategies for purchasing the company's stock over the next 3 months based on probability scores of the stock price rising.
2023 0819 True Blue Partners - Investor Conference Presentation.pdfSunil Grover
The slide highlights the keynote message from Sunil Grover, Managing Partner, True Blue Partners a boutique Merchant Bank that provides M&A advisory services and manages an early stage venture capital fund headquartered in Silicon Valley. It is actively engaged in early stage investing from its fund in entrepreneurs developing AI in the Enterprise SaaS companies. The presentation reviews the recent trends on interest rates, Inflation (CPI, Core PCE) Fed Fund rates and its impact on valuations, money supply and availability of venture capital for growth investing. It reviews the various companies in the TBP Venture Fund 1 portfolio and the success they have been having in their respective company building journeys. It digs deeper into key driving factors for valuation in publicly traded SaaS companies and why HCM / HR Tech companies are receiving the highest valuations today. It reviews the impact of growth rate, gross margins and company size and its impact on TEV/Revenue valuation mutliples over the last four years. For more information please visit www.truebluepartners.com
This document provides a performance analysis of an algorithm company over several time periods from 2017-2020. It includes key financial metrics such as sales, operating profit, net income, operating rate, net rate, ROE, debt ratio, quick ratio, and EPS. It also analyzes the company's recent quarterly performance, estimates an indication price range, and provides charts analyzing the company's stock price rise probability score over time compared to sector averages. The document concludes with a compliance notice regarding the use of the analysis for investment decisions.
This document provides a performance analysis of an algorithm company over several periods from 2016-2020. It includes key financial metrics such as sales, operating profit, net income, operating and net income rates, return on equity, debt ratio, and quick ratio on an annual and quarterly basis. It also analyzes the company's stock price performance, providing the current price and indication price ranges. Finally, it evaluates the company and provides a stock price rise probability score and investment opinion.
This document analyzes mergers and acquisitions in the apparel retail industry from 2010 to 2015. It finds that the average deal value was $278 million, with average price-to-revenue and price-to-EBITDA multiples of 0.9x and 11.4x, respectively. Transaction multiples trended down from 2010 to 2012 but increased in 2014 and 2015. The largest portion of deals were under $100 million. Geographically, deals were distributed across Asia Pacific, Europe/MENA/Africa, and the Americas.
RTL Group is a European broadcasting company headquartered in Luxembourg. The document analyzes RTL Group as an investment opportunity, providing an industry overview, business overview, financial analysis, valuation, and discussion of risks. It recommends buying RTL Group stock, with a current price of €77 and a target price of €89.5, representing 17% upside potential. The analysis finds RTL Group to have a strong position in European TV markets and forecasts continued revenue and margin growth.
This document analyzes the performance and financial metrics of Algorithm company over several periods from 2017-2020. It shows sales, operating profit, net income, operating rate, net rate, ROE, debt ratio, quick ratio and other metrics on a quarterly and annual basis. It also provides the company's current stock price, indication price range, and evaluation. A chart shows the indication price range. Tables also show the company's industry, ranking, a suggested purchase amount and number of stocks to purchase at different price levels. Graphs show the stock price rise probability score and increase rates over time for the company versus industry averages.
This document provides a performance analysis of an algorithm company over several time periods from 2015-2019. It includes key financial metrics such as sales, operating profit, net income, operating rate, net rate, return on equity, debt ratio, quick ratio, and earnings per share. It also analyzes the company's stock price against indication price ranges and provides strategies for purchasing the company's stock over the next 3 months based on probability scores of the stock price rising.
2023 0819 True Blue Partners - Investor Conference Presentation.pdfSunil Grover
The slide highlights the keynote message from Sunil Grover, Managing Partner, True Blue Partners a boutique Merchant Bank that provides M&A advisory services and manages an early stage venture capital fund headquartered in Silicon Valley. It is actively engaged in early stage investing from its fund in entrepreneurs developing AI in the Enterprise SaaS companies. The presentation reviews the recent trends on interest rates, Inflation (CPI, Core PCE) Fed Fund rates and its impact on valuations, money supply and availability of venture capital for growth investing. It reviews the various companies in the TBP Venture Fund 1 portfolio and the success they have been having in their respective company building journeys. It digs deeper into key driving factors for valuation in publicly traded SaaS companies and why HCM / HR Tech companies are receiving the highest valuations today. It reviews the impact of growth rate, gross margins and company size and its impact on TEV/Revenue valuation mutliples over the last four years. For more information please visit www.truebluepartners.com
This document provides a performance analysis of an algorithm company over several time periods from 2017-2020. It includes key financial metrics such as sales, operating profit, net income, operating rate, net rate, ROE, debt ratio, quick ratio, and EPS. It also analyzes the company's recent quarterly performance, estimates an indication price range, and provides charts analyzing the company's stock price rise probability score over time compared to sector averages. The document concludes with a compliance notice regarding the use of the analysis for investment decisions.
This document provides a performance analysis and financial information for an algorithm company over several periods from 2017-2020. It includes key metrics like sales, operating profit, net income, debt ratios, and stock price information. It also provides an investment opinion on the company, suggesting purchase price ranges for the stock and estimating return probabilities based on sector comparisons.
This document provides a summary of financial and stock performance data for a company called Algorithm over several periods from 2016-2020. It includes tables with metrics like sales, profits, debt ratios, stock prices and more. It also evaluates the company's current stock price compared to an indication price range and assigns a probability score for the stock price rising. Finally, it provides strategies and calculations for purchasing the company's stock.
The document analyzes market sizing and structure for various industries including:
- The total addressable global marketing market is estimated at $1.3 trillion with digital advertising representing $330 billion.
- The document breaks down additional specialized marketing industries like direct selling, lead generation, social media marketing and their estimated market sizes.
- It provides a bottom-up analysis of LeadZen's potential target market over a 10 year period, estimating total revenue could reach $194.8 million with 45% annual growth on average.
- Revenue streams are identified as user and company subscriptions, as well as user and company fees.
This document contains performance data and financial information for a company over several quarters and years. It also includes stock price data, analysis of the company's stock price rise probability compared to industry averages, and recommendations for purchasing the company's stock based on its current price relative to the analysis' indicated price ranges. Compliance information at the bottom notes that while the analysis is from a reliable source, its accuracy is not guaranteed and users are responsible for their own investment decisions based on the reference information provided.
This document contains performance data and financial information for Algorithm company from 2016 to 2019. It also includes stock price indicators and analysis, and recommendations to purchase Algorithm stock. The analysis scores the company's performance as "normal" and suggests purchasing 162 stocks of Algorithm at the current price of 28,800 won per stock.
This document provides a quarterly performance summary and analysis of an algorithm company from December 2017 to September 2020. It includes key financial metrics such as sales, operating profit, net income, operating rate, and debt ratio. It also analyzes the company's stock price performance, probability of price increases, and provides an investment opinion and suggested purchase amount. Compliance notices are provided at the end regarding the use and accuracy of the analysis.
The document discusses investment strategies and ideas that carry significant risk and may not be suitable for all investors. It notes that BofA Securities does business with issuers covered in its research reports, so there may be a conflict of interest. Investors should consider this report as just one factor when making investment decisions. The rest of the document provides analysis and forecasts regarding the stock market, sectors, interest rates, consumer spending trends, labor market, and corporate strategies for reducing carbon emissions.
This document provides financial and stock performance data for a biotechnology company over several periods between 2018 and 2021. It includes metrics such as sales, operating profit, net income, debt ratio, and earnings per share. It also shows the company's stock price history and analyses this data to provide an indication price range and purchasing recommendations. Compliance notices are included, stating that the analysis is for reference only and the user is responsible for investment decisions based on the information.
This document provides a performance analysis of an algorithm (Separate) over a 3 month period from 2017-2020. It includes key financial metrics such as sales, operating profit, net income, operating rate, net rate, and debt ratio on a quarterly and annual basis. It also provides the stock price, earnings per share, book value per share, and dividends. The second part provides the algorithm's stock indication price, evaluation score, suggested purchase amount and price, and investment opinion. It compares the algorithm's performance to sector averages. The final section provides compliance notices for the algorithm analysis.
This document provides a performance analysis of an algorithm company over various periods from 2017-2020. It includes key financial metrics such as sales, operating profit, net income, debt ratio, and stock price. It also evaluates the company's stock against an indication price and recommends purchase amounts at different price levels. Charts show the stock's probability score of rising compared to sector averages and past increase rates. The analysis is from a consulting firm called The Algorithm Company Analysis Consulting and includes compliance notices about the accuracy and appropriate use of the information.
This proposal recommends that Caring Incorporated develop an enhanced telehealth station. It analyzes the growing telehealth market, especially demand for home self-monitoring. The proposed product targets multiple customer groups and offers advanced features. Financial projections over 6 years estimate a positive NPV, 32% IRR, and 4 year payback period, indicating profitability. Sensitivity analysis shows the project remains profitable under different cost scenarios. Management is recommended to approve the project.
This document contains performance data and financial information for an algorithm company over several periods from 2017-2021. It also includes the company's current stock price, an indication price range analysis, and a proposed investment strategy to purchase the company's stocks at different price levels within the indication range. The final section provides compliance notices regarding the use of the information and analysis.
This document contains performance data and financial analysis of the Algorithm company from 2016-2019. It includes quarterly sales, profit, debt, and other metrics. It also contains stock price history and analysis showing the current stock price, indication price ranges and probabilities, and investment recommendations. The analysis suggests purchasing Algorithm stocks in the mid price range.
This document provides financial and stock performance data for a company over several years and quarters. It also includes the company's current stock price, the algorithm's indicated price range, and purchase recommendations based on the price range. Additional sections give historical and sector-specific data on stock price rise probabilities to support the analysis.
The document provides year-end targets and current market data for various metrics such as the S&P 500 index level, treasury yields, commodity prices, and sector weights and returns. It also lists equities from various sectors with company details including price, dividend, earnings estimates, and market capitalization. Target levels are generally provided as ranges for the end of 2016.
Proposed minimum wage impact estimates using 2012 oes data guamWages Guahan
The document provides data on occupations including estimated employment numbers, wages, and the potential impact of proposed minimum wage increases. It includes fields for the occupation code, title, estimated employment, current and proposed minimum wages, and the estimated number of workers impacted by each proposed increase. Percentiles and median wages are also provided for each occupation.
This document provides a summary of financial performance and stock price analysis for a company called Algorithm over several periods. It includes tables with metrics like sales, operating profit, net income, debt ratios, and earnings per share from 2020-2023. Graphs show the company's current stock price is significantly below the indicated price range, with a sell recommendation. Additional analysis of two sectors shows stock price rise probability scores and increase rates over time.
This document provides a performance analysis of an algorithm (consolidated) over a 3 month period from 2020-2023. It includes key financial metrics such as sales, operating profit, net income, debt ratio, and earnings per share. It also evaluates the company's stock price against an indication price range, estimates future stock performance, and provides suggested purchase amounts. The document is for reference and users are responsible for their own investment decisions based on the information.
This document provides a summary of financial performance and stock price data for an algorithm company over several quarters and years:
- Sales increased from 550 in 2016 to 662 in 2018 but have since declined, while operating and net income fluctuated over time. Debt and liquidity ratios show debt levels rose then fell from 2016-2020.
- Recent quarterly performance shows fluctuating sales, profits, and stock price rise probability for sectors A and B.
- Based on the current stock price of 13,000 won, the analysis recommends a normal purchase rating and buying 106 shares for 1.38 million won.
This document provides a performance analysis of the Algorithm company over several periods from 2017-2020. It includes key financial metrics such as sales, operating profit, net income, debt ratio, and stock price. It also evaluates the company's current stock price compared to an indication price range and provides strategies for purchasing the company's stocks, including suggested purchase amounts for different price ranges.
This document provides a performance analysis and financial information for an algorithm company over several periods from 2017-2020. It includes key metrics like sales, operating profit, net income, debt ratios, and stock price information. It also provides an investment opinion on the company, suggesting purchase price ranges for the stock and estimating return probabilities based on sector comparisons.
This document provides a summary of financial and stock performance data for a company called Algorithm over several periods from 2016-2020. It includes tables with metrics like sales, profits, debt ratios, stock prices and more. It also evaluates the company's current stock price compared to an indication price range and assigns a probability score for the stock price rising. Finally, it provides strategies and calculations for purchasing the company's stock.
The document analyzes market sizing and structure for various industries including:
- The total addressable global marketing market is estimated at $1.3 trillion with digital advertising representing $330 billion.
- The document breaks down additional specialized marketing industries like direct selling, lead generation, social media marketing and their estimated market sizes.
- It provides a bottom-up analysis of LeadZen's potential target market over a 10 year period, estimating total revenue could reach $194.8 million with 45% annual growth on average.
- Revenue streams are identified as user and company subscriptions, as well as user and company fees.
This document contains performance data and financial information for a company over several quarters and years. It also includes stock price data, analysis of the company's stock price rise probability compared to industry averages, and recommendations for purchasing the company's stock based on its current price relative to the analysis' indicated price ranges. Compliance information at the bottom notes that while the analysis is from a reliable source, its accuracy is not guaranteed and users are responsible for their own investment decisions based on the reference information provided.
This document contains performance data and financial information for Algorithm company from 2016 to 2019. It also includes stock price indicators and analysis, and recommendations to purchase Algorithm stock. The analysis scores the company's performance as "normal" and suggests purchasing 162 stocks of Algorithm at the current price of 28,800 won per stock.
This document provides a quarterly performance summary and analysis of an algorithm company from December 2017 to September 2020. It includes key financial metrics such as sales, operating profit, net income, operating rate, and debt ratio. It also analyzes the company's stock price performance, probability of price increases, and provides an investment opinion and suggested purchase amount. Compliance notices are provided at the end regarding the use and accuracy of the analysis.
The document discusses investment strategies and ideas that carry significant risk and may not be suitable for all investors. It notes that BofA Securities does business with issuers covered in its research reports, so there may be a conflict of interest. Investors should consider this report as just one factor when making investment decisions. The rest of the document provides analysis and forecasts regarding the stock market, sectors, interest rates, consumer spending trends, labor market, and corporate strategies for reducing carbon emissions.
This document provides financial and stock performance data for a biotechnology company over several periods between 2018 and 2021. It includes metrics such as sales, operating profit, net income, debt ratio, and earnings per share. It also shows the company's stock price history and analyses this data to provide an indication price range and purchasing recommendations. Compliance notices are included, stating that the analysis is for reference only and the user is responsible for investment decisions based on the information.
This document provides a performance analysis of an algorithm (Separate) over a 3 month period from 2017-2020. It includes key financial metrics such as sales, operating profit, net income, operating rate, net rate, and debt ratio on a quarterly and annual basis. It also provides the stock price, earnings per share, book value per share, and dividends. The second part provides the algorithm's stock indication price, evaluation score, suggested purchase amount and price, and investment opinion. It compares the algorithm's performance to sector averages. The final section provides compliance notices for the algorithm analysis.
This document provides a performance analysis of an algorithm company over various periods from 2017-2020. It includes key financial metrics such as sales, operating profit, net income, debt ratio, and stock price. It also evaluates the company's stock against an indication price and recommends purchase amounts at different price levels. Charts show the stock's probability score of rising compared to sector averages and past increase rates. The analysis is from a consulting firm called The Algorithm Company Analysis Consulting and includes compliance notices about the accuracy and appropriate use of the information.
This proposal recommends that Caring Incorporated develop an enhanced telehealth station. It analyzes the growing telehealth market, especially demand for home self-monitoring. The proposed product targets multiple customer groups and offers advanced features. Financial projections over 6 years estimate a positive NPV, 32% IRR, and 4 year payback period, indicating profitability. Sensitivity analysis shows the project remains profitable under different cost scenarios. Management is recommended to approve the project.
This document contains performance data and financial information for an algorithm company over several periods from 2017-2021. It also includes the company's current stock price, an indication price range analysis, and a proposed investment strategy to purchase the company's stocks at different price levels within the indication range. The final section provides compliance notices regarding the use of the information and analysis.
This document contains performance data and financial analysis of the Algorithm company from 2016-2019. It includes quarterly sales, profit, debt, and other metrics. It also contains stock price history and analysis showing the current stock price, indication price ranges and probabilities, and investment recommendations. The analysis suggests purchasing Algorithm stocks in the mid price range.
This document provides financial and stock performance data for a company over several years and quarters. It also includes the company's current stock price, the algorithm's indicated price range, and purchase recommendations based on the price range. Additional sections give historical and sector-specific data on stock price rise probabilities to support the analysis.
The document provides year-end targets and current market data for various metrics such as the S&P 500 index level, treasury yields, commodity prices, and sector weights and returns. It also lists equities from various sectors with company details including price, dividend, earnings estimates, and market capitalization. Target levels are generally provided as ranges for the end of 2016.
Proposed minimum wage impact estimates using 2012 oes data guamWages Guahan
The document provides data on occupations including estimated employment numbers, wages, and the potential impact of proposed minimum wage increases. It includes fields for the occupation code, title, estimated employment, current and proposed minimum wages, and the estimated number of workers impacted by each proposed increase. Percentiles and median wages are also provided for each occupation.
This document provides a summary of financial performance and stock price analysis for a company called Algorithm over several periods. It includes tables with metrics like sales, operating profit, net income, debt ratios, and earnings per share from 2020-2023. Graphs show the company's current stock price is significantly below the indicated price range, with a sell recommendation. Additional analysis of two sectors shows stock price rise probability scores and increase rates over time.
This document provides a performance analysis of an algorithm (consolidated) over a 3 month period from 2020-2023. It includes key financial metrics such as sales, operating profit, net income, debt ratio, and earnings per share. It also evaluates the company's stock price against an indication price range, estimates future stock performance, and provides suggested purchase amounts. The document is for reference and users are responsible for their own investment decisions based on the information.
This document provides a summary of financial performance and stock price data for an algorithm company over several quarters and years:
- Sales increased from 550 in 2016 to 662 in 2018 but have since declined, while operating and net income fluctuated over time. Debt and liquidity ratios show debt levels rose then fell from 2016-2020.
- Recent quarterly performance shows fluctuating sales, profits, and stock price rise probability for sectors A and B.
- Based on the current stock price of 13,000 won, the analysis recommends a normal purchase rating and buying 106 shares for 1.38 million won.
This document provides a performance analysis of the Algorithm company over several periods from 2017-2020. It includes key financial metrics such as sales, operating profit, net income, debt ratio, and stock price. It also evaluates the company's current stock price compared to an indication price range and provides strategies for purchasing the company's stocks, including suggested purchase amounts for different price ranges.
2. Page | 2
EXAMPLE 1
Create a portfolio of 70-100 stocks from Global developed markets, choosing from an IRP’s
(here it is MorningStar) actively researched 1700+ stocks.
Risk Profile: Target Return 12-15%, Draw-down Tolerance 6%, Vol Target: 8%-10%
Overall Structure: Market Neutral, Net Exposure +/- 10%, Gross Exposure 150-200%
Sector Limits: No GICS sector more than 40% gross , Sector Net Exposures limited -10% to +10%
Rebalance: Monthly
Constraint Table:
Optional Inputs 2: Group level Constraints
Sub Portfolio Gross and Net Limits
Category Group minNet maxNet minGross maxGross
Sector Information Technology-10.0% 10.0% 0.0% 40.0%
Sector Industrials -10.0% 10.0% 0.0% 40.0%
Sector Financials -10.0% 10.0% 0.0% 40.0%
Sector Health Care -10.0% 10.0% 0.0% 40.0%
Sector Consumer Discretionary-10.0% 10.0% 0.0% 40.0%
Sector Materials -10.0% 10.0% 0.0% 40.0%
Sector Utilities -10.0% 10.0% 0.0% 40.0%
Sector Consumer Staples -10.0% 10.0% 0.0% 40.0%
Sector Telecommunication Services-10.0% 10.0% 0.0% 40.0%
Sector Energy -10.0% 10.0% 0.0% 40.0%
Portfolio Portfolio -10.00% 10.00% 150.00% 200.00%
3. Page | 3
BACK TESTED RESULTS FOR EXAMPLE 1: BETTER SHARPE FROM OPTIMISED PORTFOLIO
ORS Set Compliance with Constraints: 100%
Original Set Compliance with Constraints: 87%
80
130
180
230
280
330
380
1-Jan-07
1-May-07
1-Sep-07
1-Jan-08
1-May-08
1-Sep-08
1-Jan-09
1-May-09
1-Sep-09
1-Jan-10
1-May-10
1-Sep-10
1-Jan-11
1-May-11
1-Sep-11
1-Jan-12
1-May-12
1-Sep-12
1-Jan-13
1-May-13
1-Sep-13
1-Jan-14
1-May-14
1-Sep-14
1-Jan-15
1-May-15
1-Sep-15
Cumulative P&L, Equally Sized and ORS sized with only
GICS sector constraints +/- 10%
ORS Sized, Sharpe = 125%
Equally Sized Portfolio,
Sharpe=95%
4. Page | 4
EXAMPLE 2
Same base case, but add constraints to ensure the portfolio is geographically spread and has
very low net Market Cap or PE Ratio Factor exposure.
Constraint Set:
Optional Inputs 2: Group level Constraints
Sub Portfolio Gross and Net Limits
Category Group minNet maxNet minGross maxGross
Sector Information Technology -10.0% 10.0% 0.0% 40.0%
Sector Industrials -10.0% 10.0% 0.0% 40.0%
Sector Financials -10.0% 10.0% 0.0% 40.0%
Sector Health Care -10.0% 10.0% 0.0% 40.0%
Sector Consumer Discretionary -10.0% 10.0% 0.0% 40.0%
Sector Materials -10.0% 10.0% 0.0% 40.0%
Sector Utilities -10.0% 10.0% 0.0% 40.0%
Sector Consumer Staples -10.0% 10.0% 0.0% 40.0%
Sector Telecommunication Services-10.0% 10.0% 0.0% 40.0%
Sector Energy -10.0% 10.0% 0.0% 40.0%
Area US -10.0% 10.0% 50.0% 125.0%
Area EU -10.0% 10.0% 0.0% 40.0%
Area CN -10.0% 10.0% 0.0% 40.0%
Area JP -10.0% 10.0% 0.0% 10.0%
Area AU -10.0% 10.0% 0.0% 10.0%
Area LA -10.0% 10.0% 0.0% 10.0%
Area IN -10.0% 10.0% 0.0% 10.0%
Area AF -10.0% 10.0% 0.0% 10.0%
Area AS -10.0% 10.0% 0.0% 10.0%
Mkt_Cap Mkt_Cap (5,000) 5,000 44,000 64,000
PE_Ratio PE_Ratio (5) 5 50 80
Portfolio Portfolio -10.00% 10.00% 150.00% 200.00%
Market Cap and PE ratio are
Factors that have ‘loadings’ for
each stock.
The portfolio is constructed to
have the weighted sum of the
loadings constrained.
In this case we have set the
Portfolio Net PE Ratio to be
centred on and close to zero,
ensuring the portfolio is not
just a play on high PE vs low PE
stocks.
5. Page | 5
RESULTS : PORTFOLIO CONSTRAINTS REDUCE RETURNS, BUT ALPHA IS PRESERVED
Note that there are some dates on which the constraints are impossible, for which ORS
minimizes the errors. The equally weighted portfolio is never compliant with the constraints.
ORS Set Compliance with Constraints: 79%
Original Set Compliance with Constraints: 0%
50
75
100
125
150
175
200
225
250
275
300
1-Jan-07
1-Apr-07
1-Jul-07
1-Oct-07
1-Jan-08
1-Apr-08
1-Jul-08
1-Oct-08
1-Jan-09
1-Apr-09
1-Jul-09
1-Oct-09
1-Jan-10
1-Apr-10
1-Jul-10
1-Oct-10
1-Jan-11
1-Apr-11
1-Jul-11
1-Oct-11
1-Jan-12
1-Apr-12
1-Jul-12
1-Oct-12
1-Jan-13
1-Apr-13
1-Jul-13
1-Oct-13
1-Jan-14
1-Apr-14
1-Jul-14
1-Oct-14
1-Jan-15
1-Apr-15
1-Jul-15
1-Oct-15
Cumulative P&L, Equally Sized and ORS sized with further constraints on
Geography, PE Ratio and Market Cap
ORS Sized, Sharpe = 121%
Equally Weighted Portfolio, Sharpe=95%
6. Page | 6
EXAMPLE 3
This is the same Geographical and Sector Constraints, but optimised to have a negative
correlation to the S&P index. This is a portfolio constructed to have a specific risk attribute.
Constraints Set:
Optional Inputs 2: Group level Constraints
Sub Portfolio Gross and Net Limits
Category Group minNet maxNet minGross maxGross
Sector Information Technology-10.0% 10.0% 0.0% 40.0%
Sector Industrials -10.0% 10.0% 0.0% 40.0%
Sector Financials -10.0% 10.0% 0.0% 40.0%
Sector Health Care -10.0% 10.0% 0.0% 40.0%
Sector Consumer Discretionary-10.0% 10.0% 0.0% 40.0%
Sector Materials -10.0% 10.0% 0.0% 40.0%
Sector Utilities -10.0% 10.0% 0.0% 40.0%
Sector Consumer Staples -10.0% 10.0% 0.0% 40.0%
Sector Telecommunication Services-10.0% 10.0% 0.0% 40.0%
Sector Energy -10.0% 10.0% 0.0% 40.0%
Area US -10.0% 10.0% 0.0% 150.0%
Area EU -10.0% 10.0% 0.0% 40.0%
Area CN -10.0% 10.0% 0.0% 40.0%
Area JP -10.0% 10.0% 0.0% 10.0%
Area AU -10.0% 10.0% 0.0% 10.0%
Area LA -10.0% 10.0% 0.0% 10.0%
Area IN -10.0% 10.0% 0.0% 10.0%
Area AF -10.0% 10.0% 0.0% 10.0%
Area AS -10.0% 10.0% 0.0% 10.0%
SPXIndex SPXIndex (40) (20) - 100
Portfolio Portfolio -20.00% 20.00% 150.00% 200.00%
We set the desired Correlation
to SPX of the whole portfolio to
be between -20% and -40%,
and pass to the optimiser the
correlation of each stock.
7. Page | 7
RESULTS: NEGATIVE CORRELATION ACHIEVED, SLIGHT COST IN RETURNS.
ORS Set Compliance with Constraints: 82%, Correl to S&P -23%
Original Set Compliance with Constraints: 0%, Correl to S&P -6%
50
75
100
125
150
175
200
225
250
275
300
Date
30-Mar-07
29-Jun-07
28-Sep-07
31-Dec-07
31-Mar-08
30-Jun-08
30-Sep-08
31-Dec-08
31-Mar-09
30-Jun-09
30-Sep-09
31-Dec-09
31-Mar-10
30-Jun-10
30-Sep-10
31-Dec-10
31-Mar-11
30-Jun-11
30-Sep-11
30-Dec-11
30-Mar-12
29-Jun-12
28-Sep-12
31-Dec-12
28-Mar-13
28-Jun-13
30-Sep-13
31-Dec-13
31-Mar-14
30-Jun-14
30-Sep-14
31-Dec-14
31-Mar-15
30-Jun-15
30-Sep-15
Cumulative P&L for Equally weighted and ORS Portfolios,
optimised to have a Negative Correlation to the S&P Index
ORSSized, Sharpe = 93% Correl to S&P = -23%
Equally Weighted Portfolio, Sharpe=95% Correl to
S&P=-6%
SPX
8. Page | 8
EXAMPLE 4
Here we do the same example, but with a required positive correlation to the S&P
Constraints Set:
Optional Inputs 2: Group level Constraints
Sub Portfolio Gross and Net Limits
Category Group minNet maxNet minGross maxGross
Sector Information Technology-20.0% 20.0% 0.0% 40.0%
Sector Industrials -20.0% 20.0% 0.0% 40.0%
Sector Financials -20.0% 20.0% 0.0% 40.0%
Sector Health Care -20.0% 20.0% 0.0% 40.0%
Sector Consumer Discretionary-20.0% 20.0% 0.0% 40.0%
Sector Materials -20.0% 20.0% 0.0% 40.0%
Sector Utilities -20.0% 20.0% 0.0% 40.0%
Sector Consumer Staples-20.0% 20.0% 0.0% 40.0%
Sector Telecommunication Services-20.0% 20.0% 0.0% 40.0%
Sector Energy -20.0% 20.0% 0.0% 40.0%
Area US -20.0% 20.0% 50.0% 150.0%
Area EU -20.0% 20.0% 0.0% 40.0%
Area CN -20.0% 20.0% 0.0% 40.0%
Area JP -20.0% 20.0% 0.0% 10.0%
Area AU -20.0% 20.0% 0.0% 10.0%
Area LA -20.0% 20.0% 0.0% 10.0%
Area IN -20.0% 20.0% 0.0% 10.0%
Area AF -20.0% 20.0% 0.0% 10.0%
Area AS -20.0% 20.0% 0.0% 10.0%
Mkt_Cap Mkt_Cap (20,000) 20,000 - 100,000
RatesRisk RatesRisk (20) 20 (200) 200
CCYRisk CCYRisk (20) 20 (200) 200
VixRisk VixRisk (20) 20 (200) 200
SPXIndex SPXIndex 10 30 (200) 200
PE_Ratio PE_Ratio (20) 20 50 80
Portfolio Portfolio -10.00% 10.00% 150.00% 200.00%
We set the desired Correlation
to SPX of the whole portfolio to
be between +10% and +30%,
and pass to the optimiser the
correlation of each stock.
9. Page | 9
RESULTS SET: POSITIVE CORRELATION WHILST MARKET NEUTRAL AS DESIRED
ORS Set Compliance with Constraints: 92%, Correl to S&P = 37%
Original Set Compliance with Constraints: 0%, Correl = 1%
50
75
100
125
150
175
200
225
250
275
300
Date
30-Mar-07
29-Jun-07
28-Sep-07
31-Dec-07
31-Mar-08
30-Jun-08
30-Sep-08
31-Dec-08
31-Mar-09
30-Jun-09
30-Sep-09
31-Dec-09
31-Mar-10
30-Jun-10
30-Sep-10
31-Dec-10
31-Mar-11
30-Jun-11
30-Sep-11
30-Dec-11
30-Mar-12
29-Jun-12
28-Sep-12
31-Dec-12
28-Mar-13
28-Jun-13
30-Sep-13
31-Dec-13
31-Mar-14
30-Jun-14
30-Sep-14
31-Dec-14
31-Mar-15
30-Jun-15
30-Sep-15
CumulativeP&L for Equally weighted and ORSPortfolios,
optimisedto have a Positive Correlationto the S&P Index
ORS Sized, Sharpe = 101% Correl to SPX = 37%
Equally Weighted Portfolio, Sharpe=95%Correl to S&P=-1%
SPX
10. Page | 10
EXAMPLE 5 JAPAN DOMESTIC SALES GROWTH STRATEGY: THEMATIC INVESTMENTS
Create a portfolio, Long/Short, correlated to easily hedgeable indices (N225/ Topix), but
uncorrelated to USDJPY. Select from stocks with high domestic sales growth.
Here we ignore the sector limits, and focus on resulting portfolio correlations.
Given the constraints, we cannot get the exact target correlations, so we find the best possible
match.
Category Group minNet maxNet minGross maxGross
MktCap MktCap (1,500) 1,500 - 2,872
USDJPY Correl USDJPY Correl 0.0% 25.0% -100.0% 500.0%
N225 Index Correl N225 Index Correl 50.0% 80.0% -100.0% 500.0%
SnP Correl SnP Correl 0.0% 100.0% -100.0% 500.0%
Topix Correl Topix Correl 50.0% 80.0% -100.0% 500.0%
Borrow Cost Borrow Cost -10.0% 10.0% -100.0% 2.5%
Portfolio Portfolio 50.0% 80.0% 100.0% 150.0%
Category Net Gross Num LongNum ShortCompliance
MktCap 435 940 25 12 TRUE
USDJPY Correl 10.3% 23.4% 25 12 TRUE
N225 Index Correl39.3% 90.1% 25 12 FALSE
SnP Correl 3.9% 9.1% 25 12 TRUE
Topix Correl 40.8% 92.7% 25 12 FALSE
Borrow Cost -0.7% 0.7% 25 12 TRUE
Portfolio 78.0% 150.0% 25 12 TRUE
11. Page | 11
RESULTS SET 5:
80.00
100.00
120.00
140.00
160.00
180.00
200.00
220.00
240.00
22-Nov-13 2-Mar-14 10-Jun-14 18-Sep-14 27-Dec-14 6-Apr-15 15-Jul-15 23-Oct-15 31-Jan-16 10-May-16
RebasedReturns, ORS Portfolio, and CorrelatedIndices
Return
NKY Index
TPX Index
USDJPY curncy
13. Page | 13
SUMMARY
You can build Indices, strategies and products where the underlying assets are selected from
independent research (or other alpha generative filter), and the portfolio characteristics are
driven by the a “CIO’s” thematic overviews and the “Client’s” risk tolerances.
You create ‘Smart-Alpha’ Portfolios.
The assets are selected using research, and the Alpha inherent in this process is
preserved, and even enhanced and then customised to fit the overview and risk.
You express a house view, define Risk, Sector, Factor, and per-Asset exposure limits and
constraints.
Any attribute that is measurable against an asset can be constrained within the strategy.
The resulting portfolio can be used to build products that match a house view, have any
desired risk/return characteristics, and be investable given inputs on per-asset constraints.
ORS CREATES PORTFOLIOS THAT BEHAVE AS YOU WANT