巴黎银行-新兴市场-投资策略-全球风险溢价模型对风险资产的支撑力度加大-20190503-8页_587kb

Summary of BNPP-Global Risk Premium Model Document (03 May 2019)

Core Content

This document outlines the methodology and insights from the BNPP-Global Risk Premium Model (<BNPSGRP Index> on Bloomberg), which is used to assess the probability of a market correction. The model is a global systemic indicator that helps evaluate the current level of risk appetite among investors.

Key Points

• The model is used for short-term market moves, not for structural market calls.
• The decision to scale back positions at the end of January 2019 was based on the model's signals.
• As of 03 May 2019, the model's value has returned to neutral/high risk premium levels, indicating a more supportive environment for Emerging Market (EM) risk assets.
• The last time the model showed similar values was on 26 March 2019.

Main Views

1. Risk Premium and Market Correction

• The BNPSGRP Index is a tool to monitor risk appetite and market correction probabilities.
• The model's value reflects the risk premium of global assets, which is the excess return over the risk-free rate.
• A return to neutral/high risk premium levels suggests a less risky environment for EM assets, but does not guarantee a market rally.

2. Asset Class Performance

• The model has shown contrarian tendencies in SP500, EM credit, and EM FX in most cases.
• However, it is not always accurate, as market trends or idiosyncratic events can override its signals.
• Performance varies across asset classes, and the model does not work equally well for all.

3. Methodology of the Risk Appetite Model

a. Expected Return Formula

• The expected return $ Y $ is approximated as:
  $$
  Y = \alpha + \theta (\sigma^2)
  $$
  Where:
  • $ \alpha $: Systemic or global risk
  • $ \theta $: Appetite for risk
  • $ \sigma^2 $: Variance of the asset

b. Price Dynamics

• The current price of an asset is derived from:
  $$
  \text{Current price of } Y = \text{Long term price of } Y - \alpha - \theta (\sigma^2)
  $$
• A change in risk appetite $ \theta $ leads to a change in asset price, with more volatile assets being more sensitive to such changes.

c. Correlation and Risk Appetite Measurement

• Risk appetite is measured through the correlation between asset risk (σ²) and excess return.
• Spearman rank correlation is used instead of Pearson correlation to avoid issues with linear relationships and extreme values.

d. Daily Monitoring

• The model calculates the rolling 1-month excess return for 23 global assets.
• It compares these returns with risk ex ante to quantify shifts in risk appetite.

Key Information

• The model is not an exhaustive analysis and may be subject to conflicts of interest due to interactions with sales and trading.
• The document is non-independent research and marketing communication, not investment research.
• It is intended for professional clients and eligible counterparties as defined by MiFID II.
• The information is not guaranteed for accuracy or completeness and should not be relied upon as such.
• Performance data is based on back-testing, which may not reflect real-world conditions such as liquidity constraints or transaction costs.

Disclaimer

• The document does not constitute an offer to sell or issue any financial instruments.
• No liability is accepted for any loss arising from reliance on the document.
• Simulated performance is for illustrative purposes only and does not guarantee future results.
• Confidentiality is emphasized; the document is only for selected recipients and cannot be distributed without prior consent.
• U.S. and Canadian disclosures highlight the complexity of financial instruments and the need for professional advice before investing.

Conclusion

The BNPP-Global Risk Premium Model provides insights into global risk appetite and serves as a contrarian indicator for certain asset classes. While it offers a useful framework for assessing short-term market conditions, it is not a perfect predictor and should be used in conjunction with other analyses and professional judgment.