PyFolio

pyFolio Overview

This document outlines part of my investment strategy development process and past investment journey, showcasing key milestones and performance highlights. A significant component of this journey involves the use of quantitative tools and in-depth analysis.

Key Features

• Python 2.7 Compatibility: Ensures robustness and backward compatibility.
• Attribution Analysis: Focuses on the attribution of excess returns relative to benchmarks.

Contributing

We welcome contributions to enhance the project. You can participate by:

• Reporting issues or bugs.
• Suggesting improvements and enhancements.
• Sharing your experiences in portfolio management.
• Making a donation to support the project.

Strategy Performance

StrBeta

Performance Metrics

• Compound Annual Growth Rate (CAGR): ~25%
• Maximum Drawdown (MDD): ~-12%
• Sharpe Ratio: Between 1.5 and 1.8

Note: Returns may vary due to missing data on some dates.

| Metric | MSCI World | Portfolio 01 | Portfolio 02 | | --------------- | ---------- | ------------- | ------------- | | Total Return | 3.16% | 6.60% | 5.75% | | Excess Return | N/A | 3.44% | 2.59% | | # of Holdings | 1,632 | <100 | <100 |

Detailed daily returns from March to May 2019 are provided below for further analysis.

Holdings Breakdown (Ciphered)

• Sectors: B41211, B4129, B41225, B41221, B41222, B41216, B4123
• Holdings: A455, D2111, A11612, A319620, B2, B1, A31313, A132614, H4, A334, A01410, A665, B1148, A67, A115, A6516, F2, G15157

Str01 - Compound Return: 2009-2017

| Year | Top Ten Portfolio | TOPIX | Alpha (%) | Winner | | ----------- | ----------------- | -------- | --------- | --------- | | 2009-2010 | n/a | n/a | n/a | n/a | | 2010-2011 | -6.17% | -9.83% | 3.66% | Top Ten | | 2011-2012 | 15.03% | 1.37% | 13.66% | Top Ten | | 2012-2013 | 17.46% | 23.66% | -6.20% | TOPIX | | 2013-2014 | 15.67% | 2.58% | -6.91% | TOPIX | | 2014-2015 | 37.19% | 30.54% | 6.65% | Top Ten | | 2015-2016 | -3.68% | -10.07% | 6.39% | Top Ten | | 2016-2017 | 33.39% | 18.80% | 14.59% | Top Ten | | 2017-2018 | 34.93% | 15.33% | 19.60% | Top Ten |

Total Compound Return from 2009-2017: 212.92% (vs. 103.61% for the TOPIX Index)

Analyst Journey (Since 2017)

My research process identified a significant mispricing in the electricity stock at $7, a conviction strengthened as market panic drove the price even lower to $0.96. However, recognizing the inherent difficulty in acting decisively on research, I observed from the sidelines while those with greater risk tolerance and conviction realized returns exceeding 2500% as the stock rebounded to $25 within two months. This experience underscored the critical distinction between identifying an opportunity and successfully capitalizing on it.

Portfolio Management Experience (Since 2019)

Bond ETF Fund of Funds Performance (Relative Return)

| Metric | Portfolio | Benchmark 01 | Benchmark 02 | | ------------------- | --------- | ------------- | ------------- | | Annualized Return | -2.39% | -3.90% | -5.51% | | Annualized Volatility | 5.55% | 5.68% | 9.54% | | Excess Returns | N/A | +1.51% | +3.12% |

Quarterly NAV Performance (2020)

| Year | Q1 (NAV 3/9) | Q2 | Q3 | Q4 | | ------- | ------------ | ------- | ------- | ------- | | 2020 | 10.00 | 0.00% | -0.20% | 1.00% | | Bmrk01 | 10.00 | -4.97% | 0.80% | 0.78% | | Bmrk02 | 10.00 | -1.47% | 0.72% | -1.45% |

Start Date: March 9, 2020

Focus: A-Rated U.S. Bond ETFs

Benchmarks: Bloomberg Barclays Global Aggregate Total Return Index (Bmrk01), iShares Core US Aggregate (Bmrk02)

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Real Estate Fund of Funds Performance (Absolute Return)

Key Performance Metrics

| Metric | Value | | ------------------------ | ------- | | Annualized Total Return | 7.68% | | Annualized Volatility | 2.96% | | Maximum Drawdown | -1.54% | | Sharpe Ratio | 2.59 |

Monthly Returns (2020)

| Month | Return | | --------- | ------ | | January | 1.24% | | February | 0.53% | | March | 0.47% | | April | -0.04% | | May | 0.17% | | June | 0.06% | | July | 0.32% | | August | -0.19% | | September | -0.22% | | October | 0.06% |

Start Date: June 2020

Institutional Fund Management & Mandate Constraints

• Private Banking & Institutional Mandates: Managed within strict guidelines for risk exposure and asset allocation.
• Bond Fund: Focuses on A-rated U.S. Bonds and balancing risk constraints with performance optimization.
• Real Estate Fund: Prioritizes minimal rebalancing frequency and aims to maximize returns while managing drawdowns.

Performance data demonstrates proficiency in managing institutional portfolios under stringent constraints and optimizing for risk-adjusted returns.