fixed income strategies

1. Shortfall risk: the probability of not meeting required liabilities obligations...
(how to graph it ) ?

2. Credit spread forward: both parties agree on the rate in future, long pays fixed rate (as agreed today), short pays the spread rate in future.

Long benefits from increase in credit spread, short benefits from decrease.

payoff = (credit spread at maturity - credit spread now)* notional amount * risk fator

Managing funds against bond market index

Index matching strategies for funds:

1. Simple index tracking

2. Enhanced index tracking, low amount of change:
- yield curve positioning
- call exposure positioning : advantage of inefficiency in callbale bonds yields etc
- sector and quality positioning

3. active investment strategy
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Secondary trading of fixed income:

Reasons:

1. Yield / spread pickup trades: thought that more yield compensates more than needed for lower rating
2. Credit upside trade: expect a credit upgrade in future
3. Credit defense : in response to rating change
4. new issue swaps, sector rotation: new fixed income issues, sector changes, fixed to floating

5. Curve adjustment: in response to yield curve changes
6. Structure trades: in and out of puttable, callable and bullet bond structures dpeending upon interest rate moves.
7. Cash flow reinvestment: How much cashflow is coming from matured issues to absorb supply, and new money for new issues etc.

Spread analysis:
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a) Alternative spread measures: swap spreads , credit default swap spread:
CDS spread: the cost of annual insurance
swap spread: a way to compare between floating and fixed rate market
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Primary market:

Counter intuitively: more debt issuance in investment grade market validates and enhances old debt; compressing credit spread instead of increasing it.

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Liability immunization:
Multiple liability immunization:
sufficient liquid assets to meet all the liabilies that come in the way

cash flow matching: need to look at average reinvestment ratio; assume conservative reinvestment estimates, assume this is fully invested for the duration of horizon.

horizon matching strategy: combination of multiple liability immunization and cash flow matching.

Asset allocation (Reading 26)

Paper by BHB in 1986 (Brinson, Hood and Beebower):

Strong evidence thru regression that portfolio performance is 93% explained by asset allocation (the portfolio policy of % dedicated to stocks, sectors in stocks, bonds and cash); and maybe 7% by individual managers' skills.

Made asset allocation strategy a big deal compared to individual; not challenged seriously till 1997 (William Janke)

ALM (Asset / liability mangement): Explicitly model liabilities and find optimal asset allocation to meet those liabilities over the desired time period.
(Ensure matching)

Static vs dynamic: Dyanmic takes inter - period linkages into account whereas static is more like a single period allocation. However applying dynamic ALM could be quite expensive...

Risk objectives and strategic asset allocation:

Investor's expected utility Um =
E(Rm) - 0.005Ra *(sigma)2
(expected return - risk aversion * variance of the return for mix m)


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Safety first ratio
Utility adjusted return
Sharp ratio
Sortino ratio

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Black Litterman MVO: First have estimations of different asset types expected returns.
Add to those : the investor's expectations...and his confidence in his abilities.

Use the new expected returns in the MVO model to get the right asset weights.

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Resampled efficient frontier: values from multiple efficient frontiers.

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corner portfolio concepts in mv optimization...

Reading 13 onwards

Managing individual investor portfolios..

Five things to consider for IPS:

1. Liquidity needs

2. Time horizon for investing

3. Taxes

4. Legal and regulatory constraints

5. Unique circumstances

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Monte Carlo simulation: personal planning (retirement planning)

probabilistic distribution to be used: all different paths for the individual's earnings.
Normally median of distribution may be much lower than the average; fat tail... So providing client a prob distribution is quite useful.
Monte Carlo pitfalls:
a) Relying on historical data for prediction
b) Performance of specific investment relevant to user must be considered instead of general..
c) Tax consequences must be taken into account.

Inefficient market theme

Few of the important points:

1. Analysts are conservative in their forecasts, don't adjust it even in light of new info

2. P/E goes much worse than fundamentals in bad times; goes way more up in good times because of investor sentiment

3. Without any extra info, it is hard to make money even in inefficient markets

4. Long run reversion to fundamental value probably still holds true in stock market.

5. Frame dependence : from current pay, have 50% chance of pay cut or 2x pay raise, how much pay cut do you agree with.
Equity risk premium suggests 4%, but in reality people say for themselves around 23%...

paradoxes...
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Portfolios, pyramids, emotions and biases:

1. prices going down: fear -> anxiety -> regret
2. Prices going up : hope -> anticipation -> pride

'Five year window' to take money out of equities.... for future needs. Not purely related to mean, variance frontier calculations, rather also deals with emotional stuff

3. Financial engines: probability calculations, e.g. 41% chance of achieving their goals

4. Novel ideas to appeal to 'cautiously hopeful' nature:
british premium bonds: principal safety + lottery chance
principal perservation thru zero coupon bond and rest in stocks
insurance company guaranteeing x% return + half of stock market gains if any

5. Hindsight bias: People are fearful of investing in loser stocks... even though they historically outperform the market. (winner - loser effect)

6. investors underestimate beta: their stock will not be affected as much as overall market...

naive diversification: given choices in 401K account, investors just divide equally among those

7. forecast failure: analysts are good at analyzing, not forecasting... anchoring happens without realizing it. hanging onto ones' views for too long.

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13: beta grazers vs alpha hunters

Allocation alphas: akin to buying supplements in supermarket to get a balanced diet...

Rebalancing: number of institutional investors have rigid rules; not allowing them flexibility when needed. Over performers force the funds to be skewed towards them..

- The distribution of outcomes during intermediate times is much wider than the range of returns in a given horizon (end)...