The Framework

Capital market expectations are expectations concerning the risk and return prospects of asset classes.

Asset allocation is the primary determinant of long-run portfolio performance.

It is not possible to forecast results with precision. The goal is to ensure consistency across asset classes (cross-sectional consistency) and over various time horizons (intertemporal consistency).

  • The CME Framework:
    1. Specify what expectations are needed and the time horizon
    2. Research the historical record
    3. Specify the models and methods that will be used and what information is needed
    4. Find the best sources of the required information
    5. Interpret the current investment environment
    6. Provide the expectations and conclusions including underlying reasoning
    7. Monitor actual outcomes and compare with expectations \(\rightarrow\) Ensure consistency

You need at least 30 observations to meaningfully test a hypothesis.

Challenges in Forecasting

Data Limitations

  • Time lag
  • Revisions to data
  • Changing definitions and calculation methods

Time zone differences can make some data appear synchronous by label even though it is not. This can distort correlations. This is exacerbated by high-frequency data.

Data Biases

  • Transcription errors
  • Survivorship bias
  • Appraisal/Smoothed data

Analysts sometimes assume normality where it is not appropriate. Asset return distributions have skew and fat tails. Sometimes the increased complexity of analyzing the non-normality is not worth the improved accuracy.

Limitations of Historical Extrapolation

Historical trends can be useful but they should not be uncritically extrapolated. Historical data may not be representative of the future, or may result in poor estimates.

Data may not be representative due to changes in regime resulting in nonstationarity.

The analyst should use the longest data history for which there is a reasonable assurance of stationarity.

Higher frequency data does not always improve precision of estimates.

Analyst Biases

Ex-Post Risk
Analysts are vulnerable to overestimate ex ante returns and underestimate ex ante risk if recent negative possibilities were not borne out. Inversely recent negative events can have the opposite effect.
Data-Mining Bias
Excessive research generating apparently winning strategies that do not reflect an underlying economic reality.
Time-Period Bias
Obtaining results that are only relevant to the time period of the data used in the analysis
Correlation \(\neq\) Causation
Assuming causation without investigating the underlying linkages

Behavioural Biases

Several behavioural biases have been identified as affecting analysts’ ability to accurately forecast returns.

These include:

Anchoring bias
The tendency to give disproportionate weight to the first information received or first number envisioned, which is then adjusted. Such adjustment is often insufficient, and approximations are consequently biased. Analysts can try to avoid anchoring bias by consciously attempting to avoid premature conclusions.
Status quo bias
The tendency for forecasts to perpetuate recent observations—that is, to avoid making changes and preserve the status quo, and/or to accept a default option. This bias may reflect greater pain from errors of commission (making a change) than from errors of omission (doing nothing). Status quo bias can be mitigated by disciplined effort to avoid “anchoring” on the status quo.
Confirmation bias
The tendency to seek and overweight evidence or information that confirms one’s existing or preferred beliefs and to discount evidence that contradicts those beliefs. This bias can be mitigated by examining all evidence with equal rigor and/or debating with a knowledgeable person capable of arguing against one’s own views.
Overconfidence bias
unwarranted confidence in one’s own intuitive reasoning, judgment, knowledge, and/or ability. This bias may lead an analyst to overestimate the accuracy of her forecasts and/or fail to consider a sufficiently broad range of possible outcomes or scenarios. Analysts may not only fail to fully account for uncertainty about which they are aware (sometimes described as “known unknowns”) but they also are very likely to ignore the possibility of uncertainties about which they are not even aware (sometimes described as “unknown unknowns”).
Prudence bias
The tendency to temper forecasts so that they do not appear extreme or the tendency to be overly cautious in forecasting. In decision-making contexts, one may be too cautious when making decisions that could damage one’s career or reputation. This bias can be mitigated by conscious effort to identify plausible scenarios that would give rise to more extreme outcomes and to give greater weight to such scenarios in the forecast.
Availability bias
The tendency to be overly influenced by events that have left a strong impression and/or for which it is easy to recall an example. Recent events may likewise be overemphasized. The effect of this bias can be mitigated by attempting to base conclusions on objective evidence and analytical procedures.

Other sources of uncertainty

  • Model uncertainty: whether the model is conceptually/structurally correct
  • Parameter uncertainty: the error of the estimate
  • Input uncertainty: whether the inputs are correct

The Role of Analysis

The most important thing to remember is that all investment outcomes are inherently linked to the economy.

There are several unforeseeable shocks which are known to have sudden and significant affects on asset prices.

  • These include:
    • Policy changes
    • New products and technologies
    • Geopolitics
    • Natural disasters
    • Natural resources/critical inputs (change in supply)
    • Financial crises

There are three types of crises:
Type 1: A decline in output but the trend rate of growth is unchanged Type 2: No decline in output but a decline in growth Type 3: Both a decline in output and a decline in growth

Growth Analysis

Growth can be decomposed into its components i.e. labor size, labor participation, available capital, and total factor productivity.

Some components are easier to predict than others. The labor force is relatively predictable but TFP can change rapidly.

Mature economies generally have stable growth while developing economies can have significant variation due to rapid structural changes.

The average level of low risk government bond yields is linked to the trend rate of growth.

The aggregate value of equity can be expressed in terms of the nominal GDP, profit margin of the economy, and the P/E ratio as: \(V_e = GDP \times \frac{E}{GDP} \times \frac{P}{E}\)

As both P/E and E/GDP are bounded, only GDP can affect the long run growth rate of value.

Just because a country has a higher growth rate does not mean it will have higher equity returns. The higher growth rate may already be factored into the market price.

Approaches to Forecasting

The trend growth rate is a long-term average but there are short to medium term fluctuations around the trend. That is the business cycle. It is a key focus of macroeconomic analysis.

Econometric Models

Structural models
specify relationships among variables based on economic theory.
Reduced form models
less theoretical models that aim to provide a more compact representation than structural models.
Data models
Non theoretical models that are entirely data driven

Indicators

Indicators are easier to access than econometric models. Leading indicators are subject to revision and so can exhibit look-ahead bias.

Checklists

Checklists are a heuristic approach that an analyst designs for their own needs. They can vary widely and are more subjective than other approaches.

Business Cycle Analysis

Phases of the Business Cycle

  1. Initial Recovery: uptick in spending after recession
  2. Early Expansion: momentum, increased profits and demand
  3. Late Expansion: output gap is closed, boom mentality
  4. Slowdown: rising interest rates, rising inflation, inverted yield curve
  5. Contraction: 12-18 month, low investment and lending, cut production, easing monetary policy, steep yield curve

The phases vary in length and amplitude making them hard to predict.

Over the short term expectations are subject to significant noise. In the long term the economy is likely to have experienced several business cycle phases and returns should approach the long term trend. Business cycle analysis generates the most reliable and actionable expectations in the 2-3 year range.

Inflation

A central bank’s policy tools are more effective at slowing the economy than accelerating it. As such, they prefer to promote persistent positive inflation.

This inflation gives a buffer for the bank to operate in without causing deflation which makes the bank less effective and undermines the mortgage sector.

Compared to deflation moderate inflation has only modest costs on the economy.

Inflation is procyclical.

Policy Analysis

Most central banks had a mandate to intervene in the business cycle.

The impact of monetary policy has long and variable lags.

Fiscal policy is not usually implemented to affect the business cycle. Fiscal policy takes too long to implement to be useful in short term crises.

Due to progressive taxation the effective tax rate is procyclical.

In the short run monetary policy is more important to expectations. In the long run fiscal policy is more important.

Central banks do not all act the same or have the same mandate. Generally they want to mitigate extreme inflation or growth.

Taylor Rule

\[ i^{*} = r_{neutral} + \pi_e + 0.5 \cdot (\hat{Y}_e - \hat{Y}_{trend}) + 0.5 \cdot (\pi_e - \pi_{target}) .\]

where:

  • \(i = \text{nominal policy rate}\)
  • \(r = \text{real policy rate}\)
  • \(Y = \text{GDP growth rate}\)
  • \(\pi = \text{inflation rate}\)

Zero and Negative Interest Rates

Prior to the 2008 crisis it was believed there was a lower bound to interest rates beyond which participants would prefer to hold physical currency rather than short term negative earning accounts.

The credit crunch caused by withdrawals would put upward pressure on rates and thwart central bank policy even if they wanted to push interest rates down.

Quantitative easing was utilized in an attempt to overcome this situation.

QE did increase asset prices but proceeds funded dividends and repurchases rather than increasing investment.

Negative policy rates were proven to be sustainable due to the impracticality of cash for large, fast, and global transactions. While the convenience yield outweighs the negative interest deposits will remain in the bank.

Negative rates have similar incentives to low positive rates but market participants may have greater uncertainty which makes the monetary policy increasingly ineffective as rates are pushed lower.

When short term rates are negative the neutral policy rate can be adjusted to approximate long run equilibrium short term rates/risk free rate.

Negative policy rates are expected to occur in the contraction and early recovery phases of the business cycle.

Yield Curve Shape

Fiscal policy is political while monetary policy is usually more independent.

Loose fiscal policy increases real rates.

Loose monetary policy increases inflation and nominal rates.

When fiscal and monetary policy is opposed the combined impact is uncertain.

The yield curve is upward sloping because of the maturity premium.

Sufficiently large sales of bonds of a particular maturity can affect the shape of the yield curve in the short term. May be important factor with central bank open market activities.

Some investors must comply with regulations pertaining to their bond portfolio duration (especially pension funds). This causes inelastic demand for some bonds and accordingly lower yields in particular maturity ranges.

The central bank may be politicized to inflate away government debt. If this occurs the curve will steepen.

Inverted Curve and the Business Cycle

The curve tends to be steep at the bottom of the cycle and flatten or invert at the peak. This relationship has been shown to be predictive. The direction of the causation is unclear.

International Interactions

Smaller economies are influenced more by international developments.

Increased global trade makes international interactions more impactful for all economies.

Current Account and Capital Account analysis:

  • \((X-M) = (S-I) + (T-G)\)

The current and capital accounts are kept in balance through changes in income, relative prices, interest rates, and exchange rates.

The capital account must adjust to balance the current account.

Interest rates and exchange rates are linked.

No country can simultaneously:

  • allow unrestricted capital flows,
  • maintain a fixed exchange rate, and
  • pursue an independent monetary policy.

Low credibility about a currency exchange peg can cause exchange rates to diverge. The weaker currency will have higher yields. This has even happened in the eurozone despite the countries sharing the same currency.