Capital Market Expectations Flashcards
7 Step process to CME
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1. HORIZON Set a time horizon, choose assets and investor tax status
2. RESEARCH Research the historical record
3. SPECIFY METHODS Specify the methods and/or models to be used and their information requirements.
4. COLLECT BEST Collect BEST data possible.
5. EXPERIENCE & JUDGEMENT Apply experience and judgement to current environment
6. DOCUMENT Document conclusions
7. MONITOR & FEEDBACK Monitor performance and feedback to improve the expectation-setting process.
9 Problems in producing forecasts
- Limitations in using economic data - lag in data reporting points such as IMF 2 year reporting dates.
- Data Measurement errors - Transcription errors where data was recorded incorrectly. Property returns looking smoothed due to infrequent mark to market NAVs.
- Limitations of Historical Estimates - Historical data should be adjusted as the political, regulatory and technological environment changes.
- Using ex post data (after the fact) to determine ex ate (before the fact) risk and return is problematic. - Markets might react in hindsight but not for the reason you expcted ie markets might overestimate inflation and when it doesn’t come to fruition markets rally.
- Data patterns which are unlikely to happen into the future. Some correlations (from data mining) may appear if you look hard enough however they might not be ‘true’ correlations.
- Failing to account for conditional information - Some assets may perform better in expansions 1.4b than contractions 1.0b but on average will show a beta 1.2
- Misinterpreting of correlations (causality) - Spurious correlations could have in fact come from a third variable.
- Analysts a susceptible to psychological biases - Anchoring, status quo, confirmation, overconfidence, availability.
- Model uncertainty - Do I use DCF or relative value models to evaluate expected stock return?
Exogenous shocks
Endogenous shocks
Exogenous shocks - cannot be predicted ie covid, housing crisis, political events and change in policy, natural disasters, cuts in defence spend could increase growth.
Endogenous shocks - can be predicted and are priced into normal market trends.
Inputs for forecasting economic growth
Labour - Growth in labour (population growth)and labour participatioun
Capital per worker - Increases in Labour productivity
Total Factor Productivity - Technological progress
3 Major approaches to economic forecasting
- Econometric modelling
- Economic indicators
- Checklist approach
Econometric modelling
Structural models?
Reduced form models?
Which regression is used?
+
-
Econometric modelling uses current and lagged variables.
The approach uses statistical methods to explain economic relationships and formulate forecasting models.
Structural models is a type of econometric models based on ECONOMIC THEORY.
Reduced form models are more compact structural models or DATA DRIVEN with heuristic rationale for selection.
Ordinary least squares regression is used.
+ Incorporates many variables with reliable output
+ Once the model is specified it can be re-used
- Complex and time consuming
- Models can be mis-specified as relationships may change over time.
- Does not forecast turning points/recessions well
Economic/leading Indicators (a type of economic forecast)
What is a diffusion index?
Coincident & lagging indicators?
Available from government, international organisations and private organisations.
Leading indicators - move ahead of the business cycle with a stable lead time.
A diffusion index combines multiple indicators to point towards expansion or contraction (TEA S&W) a type of ‘leading indicator approach’
Coincident & lagging indicators move after changes in the business cycle
+ simple and easy to interpret
+ data is readily available
+ focus on forecasting turning points
- Current data not a reliable input for historical analysis
- Indicators can give false signals
5 phases of the business cycle
- Initial recovery - first few months, business confidence rising, Government stimulus. Bond yields bottoms and equities rising.
- Early expansion - duration several years, low inflation and growth with rising short term rates. Low inflation and stock prices rise. Output gap narrows.
- Late expansion - Central bank limits money supply. Interest rates and bond yields increase as inflation increases. Rising/peaking stock prices.
- Slowdown - Duration a few months. Declining confidence. Inflation still rising. Short term interest rates peak. Yield curve inversion and stock prices fall.
- Contraction - Duration 12 - 18 months. Declingin profits and confidence. Increasing unemployment and bankrupcy. Inflation topping. Falling short term rates. Falling yields/rising bond prices. Stock prices may rise in the latter stages anticipating the end of a recession.
Inflation
Disinflation
Deflation
Equilibrium rate of inflation
Inflation - generally rising prices: CPI 100 - 105
Disinflation - a deceleration in the rate of inflation increase: CPI 100 - 105 - 108 (+5 followed by +3% change shows slowing)
Deflation - generally falling prices. Danger as homes fall into negative equity which spurs further sell off, of assets. Low or zero interest rates maximised limiting central bank ability to stimulate further.
Equilibrium rate of inflation aka Neutral Rate is the rate at which a balance of growth and inflation is achieved.
Taylor rule meaning
Short term interest rate equation =
Taylor rule meaning - embodies the idea of raising rates to slow inflation.
Short term interest rate equation =
nominal Target = rNeutral + iExpected + (0.5 x (GDP expected - GDPtrend) + (0.5 x (iExpected - iTarget)
real Target (ignores inflation from the equation)
Questions usually as for ‘real Target’ in which case you drop iExpected.
rNeutral = neutral short term interest rate
iExpected = inflation expectation
Loose fiscal policy =
Fiscal Tightening =
Loose fiscal policy = lower taxes, increased spending
Fiscal Tightening = higher taxes.
Yield curve shape
Fiscal & Monetary Stimulative
Fiscal & Monetary Restrictive
Fiscal Stimulative, Monetary Restrictive
Fiscal Restrictive, Monetary Stimulative
Fiscal & Monetary Stimulative - Steep upward sloping
Fiscal & Monetary Restrictive - Inverted yield curve
Fiscal Stimulative, Monetary Restrictive - Flat
Fiscal Restrictive, Monetary Stimulative - Moderately steep yield curve
current account
capital account
current account is a country’s net exports
capital account is net investment flows
Two sides of the same coin, a surplus in one means a deficit in the other.
Current account surplus equation
(X - M) = (S-I) + (T-G)
exports minus imports = (private savings - Investment) + (Tax - government spending)
Increase in savings and an increased government surplus which is T-G will increase the current account SURPLUS.
DEFICIT will increase if taxes are cut (small T) and domestic investment increases (Big I)
If a country runs a 6% deficit it would need to be plugged by an increase in 6% savings to close the deficit etc.
Tax cuts
Tax cuts create increased current and capital accounts.
Growth in other countries will increase
A country must attract additional capital flows from abroad.
Cut in taxes will increase company earnings though and stock prices should look more attractive.
Sample statistics 2 rules to make it reliable?
Factor Model
Biased or Unbiased? Consistent or Inconsistent?
Shrinkage models
Time series estimate
Discounted cash flow models
risk premium or buildup model.
Sample statistics - Is UNbiased and CONSISTENT. It uses well-known data, including means, variance, and correlation, to forecast future data. This is the clearest approach in forecasting, but it can be imprecise. The sample variance/covariance matrix is an unbiased estimate of VCV structure. Two main problems is that some portfolios will appear to be riskless if the number of assets exceeds the number of historical observations so it cannot be used. The 10 to 1 rule will give more reliable estimates (observatiosn should be 10x the number of assets)
Factor Model can handle a very large nuumber of assets. However is BIASED and INCONSISTENT.
Shrinkage estimates - (p x Xi) + 1-p x Z. It is a weighted average of the Sample VCV (Xi) and Factor based VCV (Z) matrices. It adjusts the expected return your model expects, to a more realistic level. If your model expects GDP to be 10% but 50 years of data suggest it was be 6% you maybe would weight the estimates based on how confident you are ie 0.25 x 10% + 0.75 x 6%). Plus it can be applied to the historical estimate if the analyst believes simple historical results do not fully reflect expected future conditions.
A time series estimate can also be used to make forecasts. A time series estimate forecasts a variable using lagged values of the same variable and combines it with lagged values of other variables, which allows for incorporating dynamics (volatilities) into the forecasts
Discounted cash flow models express the intrinsic value of an asset as the present value of future cash flows.
Build up/risk premium models: The approach starts with a risk-free interest rate and then adds compensation for priced risks, or risks for which an investor would want to be compensated. Risk premium models include equilibrium models (e.g., the Capital Asset Pricing Model), a factor model, and building blocks.
4 primary drivers of term premium
The ‘other’ factors effecting term premium to be aware of.
Inflation uncertainty: Higher inflation levels typically correspond to higher inflation uncertainty, causing nominal yields to rise and the term premium to increase.
Recession hedge: When inflation is caused by strong aggregate demand, nominal bond returns are negatively correlated with growth, corresponding to low term premiums. When inflation is caused by aggregate supply, nominal bond returns are positively correlated with growth, corresponding to higher term premiums.
Supply and demand: The relative supply of short- and long-term default-free bonds determines the slope of the yield curve, which influences the level of term premiums.
Business cycles: The slope of the yield curve and level of term premiums are also related to the business cycle.
Ex ante (forecast) real yield.
Cochrane and Piazzesi curve factor: a measure that captures both the slope and curvature of the yield curve.
Kim and Wright premium: a three-factor model of the term structure.
Slope of the yield curve.
Supply indicator: proportion of debt with a maturity greater than 10 years.
Cyclical proxies: corporate profit-to-GDP ratio, business confidence, unemployment rate.
The building block approach starts with a risk-free rate and then adds compensation for additional risks. The required return will include the one-period default-free rate, a term premium, a credit premium, and a liquidity premium
Short term default free premium
Term premiums
Credit premiums
Liquidity premiums
The short-term default-free rate matches the forecast horizon and is calculated from the most liquid instrument. As a result, it is closest to the government zero-coupon yield and is closely tied to the central bank policy rate.
See term premium brainscape card
The credit premium compensates for the expected level of losses and for the risk of default losses, both of which are components of the credit spread. Historical evidence for U.S. investment grade corporate bonds suggests that high corporate option-adjusted spreads correspond to a higher credit premium,
Liquidity tends to be the highest at the earliest stages of a bond’s life, typically during the first few weeks only. Securities with the highest liquidity are the newest sovereign bond issues, current coupon mortgage-backed securities, and some high quality corporate bonds
EM Debt
Emerging market debt offers the investor high expected returns at the expense of higher risk. Many emerging countries are dependent on foreign borrowing, which can later create crisis situations in their economy, currency, and financial markets.
Many emerging countries also have unstable political and social systems. Their undiversified nature makes them susceptible to volatile capital flows and economic crises.
Signs an Emerging market is more susceptible to risk:
Wealth concentration.
Income concentration and less diverse tax base.
Greater dominance of cyclical industries, including commodities and less pricing power.
Restrictions on capital flows and trade; currency restrictions.
Inadequate fiscal and monetary policies.
Poor workforce education and infrastructure and weak technological advancement.
Large amounts of foreign borrowing in foreign currencies.
Less developed and smaller financial markets.
Exposure to volatile capital flow
Guidelines that look at the health of an emerging market.
- To gauge fiscal policy, most analysts examine the deficit-to-GDP ratio. Ratios greater than 40% indicate substantial credit risk. Most emerging counties borrow short term and must refinance on a periodic basis. A buildup of debt increases the likelihood that the country will not be able to make its payments. The debt-to-GDP ratio of 70% to 80% has been troublesome for emerging countries.
- Investors should expect a real growth rate of at least 4%. Growth rates less than that may indicate that the economy is growing slower.
- A current account deficit exceeding 4% of GDP has been a warning sign of potential difficulty.
- Foreign debt levels greater than 50% of GDP indicate that the country may be overleveraged. Debt levels greater than 200% of the current account receipts also indicate high risk.
- Foreign exchange reserves (LIQUIDITY MEASURE) relative to short-term debt is important because many emerging country loans must be paid back in a foreign currency. Foreign exchange reserves less than 100% of short-term debt is a sign of trouble (greater than 200% is considered strong)
When the government is committed to responsible fiscal policies, competition, and the privatization of state-owned businesses, there are better prospects for growth. Weak enforcement laws, property rights laws, nationalization of property, and corruption are hazard signs.
Example question:
An analyst is evaluating an emerging market for potential investment. She notices that the country’s current account deficit has been growing. Is this a sign of increasing risk? If so, explain why
Example answer
When exports are less than imports, a current account deficit usually results. This can be problematic because the deficit must be financed through external borrowing. If the emerging country becomes overleveraged, it may not be able to pay back its foreign debt. A financial crisis may ensue where foreign investors quickly withdraw their capital. These financial crises are accompanied by currency devaluations and declines in emerging market asset values.
Grinold-Kroner model Er =
Long term Er =
Er = D/P + (%ΔE − %ΔS) + %ΔP/E
Long term Er = D/P + %Δ Nominal GDP Growth
E(Re) = expected equity return
D/P = dividend yield
%ΔE = expected percentage change in NOMINAL total earnings. Long run E = NOMINAL GDP growth
%ΔS = expected percentage change in shares outstanding usually a negative so a negative minus negative creates a positive so it’s added
%ΔP/E = expected percentage change in the P/E ratio
List two adjustments that analysts must make to the risk premiums calculated using equilibrium models.
Once an analyst estimates the risk premiums using equilibrium models, the analyst should (1) remove the impact of smoothing from the data, and (2) adjust for illiquidity using a liquidity premium
Capital mobility: The expected percentage change in the exchange rate
E(%ΔSd/f) =
Does a positive E(%ΔSd/f), indicate appreciation/depreciation of the foreign/domestic currency?
E(%ΔSd/f) = (rd – rf ) + (Termd – Termf ) + (Creditd – Creditf ) + (Equityd – Equityf ) + (Liquidd – Liquidf )
SUM OF = Domestic - Foreign
A positive number suggests DOMESTIC currency DEPRECIATES.
Purchasing power parity (PPP), long or short run indicator?:
Uncovered interest rate parity (UIP):
PPP implies that the prices of goods and services in different countries should reflect changes in exchange rates. As a result, the expected exchange rate movement should follow the expected INFLATION rate differentials. It Holds ONLY in the Long run. News flow drives short run exchange rates.
UIP states that exchange rate changes should equal differences in NOMINAL INTEREST RATES.
What are the two types of Variance-covariance matrices? Which can appear risk free?
When can a sample VCV be used given sample size and number of assets? How many observations vs assets are needed in order to reduce sample errors?
VCV Sample Statistics
VCV Factor Model
Which is biased and inconsistent and which is unbiased and consistent?
Which improves cross-sectional consistency?
Remedy for the shortcoming?
What are the two types of Variance-covariance matrices?
Sample VCV matrix creates a lot of sensitivities. Complex. A factor VCV matrix creates less sensitivities but is biased and inconsistent and can appear risk free.
When can it be used given sample size and number of assets? How many observations vs assets are needed in order to reduce sample errors?
Large sample errors will exist unless the number of observations is at least 10 times the number of assets. (ie 26 weeks of data and 17 assets is not even 2x the number of assets) so not ideal. If assets exceed observations it may appear risk free.
VCV Sample Statistics is unbiased and consistent but needs observations to be 10x the number of assets.
VCV Factor Model is Biased and Inconsistent but requires less observations and IMPROVES cross-sectional consistency
Remedy for the shortcoming?
A manager could avoid these issues by using shrinkage estimation of the weighted averages of the sample and factor-based VCV matrices. Shrinkage estimates are also biased though.
What is the global market portfolio
It contains all investable risky assets
The portfolio minimises diversibiable risk (unsystematic)
ETFs can be used as s proxy.
Young Investor vs Old investor
Young = low financial capital and high human capital
Old = Vice versa
Describe Mean Variance Optimisation
Constraints
Assumes investors are risk averse
It is a single period model which identifies the portfolio allocations which maximises return for every level of risk.
Contstraints = garbage in garbage out.
Ignores Skewness and kurtosis
Ignores interim cash flows
illiquid assets such as PE and infrastructure are hard to include in MVO however you can use alternative indexes.
Utility maximisation
= Er - 0.005 x Risk aversion coefficient x Var
Reverse optimisation
Opposite of starting with expected returns and deriving optimal portfolio weights, instead start with optimal portfolio weights from the global portfolio and derive expected returns.
Black - Litterman model
Extension of reverse optiomisation where implied returns are adjusted to reflect invesotrs unique views ie revenue optimisation derives EM equities to return 6.5% however you think this is too low so you adjust up to 7.25% and rerun MVO.
Funding ratio =
Market value of assets / PV of liabilities
<1 = underfunded
>1 = overfunded
TSA - Data measurement errors.
Transcription errors
Survivorship bias
What is Appraisal (Smoothed) data?
Problems with using smoothed data?
Transcription errors is errors in gathering data
Survivorship bias when data only reflects entities which survived to the end of the period.
Smoothed data arises from irregular pricing/trading of assets.
Problems:
High frequency data vs quarterly priced assets hides volatility.
Standard deviation can appear lower than in reality.
Correlations may also appear lower than they actually are.
Checklist approach
The checklist approach uses subjective information which is integrated by an analyst.
+ Limited complexity
+ Changes can be easily incorporated
- No consistency of analysis across items or at different
points in time.
- Time consuming and subjective.
Limitations of historical estimates
Regime
Nonstationary
Regime - change in governments regime creates nonstationarity
Nonstationary - where differing parts of a data set reflect different underlying statistical properties. Models can be used to spot changes and turning points in a regime.
Ex Post Risk Can Be a Biased Measure of Ex Ante Risk
In interpreting historical prices and returns over a given sample period, the analyst needs to evaluate whether asset prices reflected the possibility of a very negative event that did not materialize during the period. This phenomenon is often referred to as the “peso problem.” Looking backward, we are likely to underestimate ex ante risk and overestimate ex ante anticipated returns. The key point is that high ex post returns that reflect fears of adverse events that did not materialize provide a poor estimate of ex ante expected returns.
“Projections in survey data tends to be more volatile than actual performance data.”
High frequency trading
Asynchronism
Precision of sample variances, covariances, correlations, sample mean.
High frequency trading is more sensitive to asynchronism across variables. (due to timing difference of market pricing in short term ie Nikkei vs S&P looks less ocrrelated overnight and more correlated over a month)
High frequency trading IMPROVES Precision of sample variances, covariances and correlations.
Precision of sample mean is NOT improved due to asynchronism.
What is needed to achieve independent monetary policy?
Restricted or unrestricted capital mobility?
Fixed or free float exchange rate?
To achieve independent monetary policy you need either:
RESTRICTED capital mobility.
Free float exchange rates.
Unrestricted capital mobility means you must adhere to the fixed currencies policies whereby restricting capital mobility allows you to pursue your own destiny with monetary policy.
Shorter investment horizon vs Macaulay duration
Which dominates price risk or reinvestment risk?
Mac D =
Mac D = MD x 1+YTM
Time horizon < Mac D
Reinvestment yield < bond price loss
7.5 years vs 7.97 Macaulay duraiton
If yields rise you achieve a Lower YTM as bond price loss will be greater than the reinvestment yield.
That is to say price risk dominates reinvestment risk for shorter investment horizons than duration of the portfolio.
EM fixed income risks
EM fixed income and equity risks
Political risks, concentration of industries, legal risks,
Equity holders face all the usual risks but also CORPORATE GOVERNANCE risks where ownership claims may be expropriated by insiders. Seizure of property, nationalisation and insiders misusing company assets.
ARCH Model
Assets tend to exhibit volatility clustering with periods of higher and lower volatility. Auto regressive conditional heteroskedasticicy are aimed at addressing the time-varying volatilities.
Hot Money
How to slow hot money flowing IN through
1. buy/sell foreign currency?
2. buy/sell government securities?
Overshooting model
Hot money = When capital flows into a country given increase in short term rates and increased equity premium, this is referred to as hot money. Hot money creates monetary policy issues. First, central banks’ ability to use monetary policy effectively is limited. Second, firms use short-term financing to fund long-term investments, which increases financial market risk.
Central banks can slow hot money flooding in by either
1. Buying foreign currency
2. Selling government securities.
They can slow hot money moving out by:
1. Selling foreign currency (weaken domestic)
3. Buying government securities
Overshooting model would see a currency appreciate at first and then depreciate to a level which reflets the risk-adjusted expected returns in the long term.
What is Asynchronous data and how does it effect correlation bias?
Arises when data is measured INFREQUENTLY.
Correlations therefore are likely biased DOWNWARD.
What is an exogenous shock?
Exogenous shocks come from outside the economic system and cannot be forecasted. This may be due to
1. Policy changes
2. New products and technologies
3. Geopolitics
4. Natural disasters and discovery of new natural resources.
5. Financial crises.
Setting up capital market expectations.
Intertemporal consistency
Cross-sectional consistency
Intertemporal consistency = time horizons of data views
Cross-sectional consistency = internal consistency across asset classes ie does a dividend yield value stock follow a value index or growth.
Credit premiums higher at short or long term maturity?
Credit premiums tend to be higher at short end maturities due to event risk.
Anchoring bias
Status quo bias
Confirmation bias
Overconfidence bias
Prudence bias
Availability bias
Anchoring bias - disproportionate weight to the FIRST information received or envisioned. Remedied by consciously avoiding premature conclusions.
Status quo bias - avoid making changes and stick with status quo. Remedied by disciplined effort to avoid anchoring on the status quo
Confirmation bias - Overweight evidence that confirms one’s existing belief. Remedied by debating with someone opposing ones own view.
Overconfidence bias - Overconfidence in ones own reasoning, judgement, knowledge or ability. Failing to account for known unknowns and unknown unknowns.
Prudence bias - Tendency to temper forecasts so they do not appear extreme of being overly cautious.
Availability bias - Tendency to be overly influenced by events that have left a strong impression or which are easy to recall such as recent events. Mitigated by attempting to base conclusions off objective evidence.
Model uncertainty
Parameter uncertainty
Input uncertainty
Model uncertainty pertains to whether a selected model is structurally and/
or conceptually correct.
Parameter uncertainty arises because a quantitative model’s parameters are invariably estimated with error.
Input uncertainty concerns whether the inputs are correct.
Any or all of these may give rise to erroneous forecasts and/or cause the unwary analyst to overestimate the accuracy and reliability of his forecasts.
γ 0.000011
α 0.85
β 0.07
σ2 period t - 1 0.0005
Shock Variable 0.035
ARCH model
σ t2 = γ + α σ t^2− 1 + β η t^2
0.000517 = 0.000011 + (0.85 x 0.0005) + 0.07 x 0.035^2
Risk to EM Bonds.
Political/Legal risk =
Economic risk =
Political/Legal risk = Willingness to pay
Economic risk = Ability to pay
