Portfolio Diversification and Investment Strategies

Inefficient Allocation vs. Curve Position

  • "Dumb" or inefficient allocation isn't reflected in Harvard's table, which focuses on the curve's top part.
  • Comparing asset weights becomes complex with multiple securities, requiring computer programs based on assumptions.
  • The process involves asking "what if" questions and designing well-diversified portfolios.

Simple Investment Strategy: Diversification

  • A textbook example: "Don't put all your eggs in one basket." A million-dollar security turns bad.
  • Randomly adding a second security at 50/50 and another, and another.
  • Randomness allows prediction of average portfolio behavior based on stock characteristics.
  • Individual stocks from NYSE and Nasdaq can have high volatility (e.g., 50% per annum).
  • Diversification reduces volatility, moving towards a "market virus" or broad-based market volatility.

Interpreting Diversification

  • Incorrect Interpretation: Portfolio is diversified with only 20 stocks but all in the same industry.
  • Averages matter; avoid flawed averages. Portfolio design should come from first principles, not random choice.
  • Adding more stocks eventually mirrors the market, but without market cap weighting.
  • This strategy may not suit large entities like Harvard due to small-cap focus, necessitating optimal design.
  • One solution: Mimic what everyone else does.

Building an Optimal Portfolio

  • Consider well-diversified stocks like Microsoft, measuring current volatility across its diversified product line.
  • Large stocks correlate with the market. Portfolio design wasn't the goal here, just diversification discussion.
  • Removing unnecessary risk unlocks potential return. Competition drives efficiency.

Market Risk and Diversifiable Risk

  • Two aspects: Limited common market risk and diversifiable, unique risk.
  • Address whether diversifiable risk offers expected return; competition is high in this area.

Systematic vs. Specific Risks

  • Market risk assumptions encompass economy-wide risks like recessions, which are systematic and unavoidable.
  • Ask as to whether there is an appropriate compensation for market risk.
  • Specific risks, like company lawsuits/strikes, are diversifiable and may not offer reward.
  • Academics question whether idiosyncratic risk offers reward, considering behavior of investors who may not be well-diversified.

Consequences of Poor Diversification

  • Recent research indicates idiosyncratic risk can lead to negative returns, as investors chase irrational trends, creating an irrational market.
  • While diversification should yield no return on diversifiable risk, poor diversification can negatively impact returns.

Market Efficiency

  • In well-functioning markets, firms shouldn't generate "rents" (extra profits for nothing), contrasting with monopolies.
  • Financial markets are easily accessible, suggesting market efficiency.
  • Only systematic exposures should generate reward, contradicting previous statement about negative returns. In which investors would make irrational investment decisions.

Implications of Market Efficiency

  • The main way to achieve higher returns in by holding out on systematic risk. Portfolio positions are benchmarked as a result of this hypothesis.
  • Performance evaluation is based on systematic exposures and appropriate risk assessment for chosen investments.
  • The goal is to determine appropriate benchmarking for risk exposure, to evaluate if returns are as a result of the risk or due to manager performance.
  • Examples include Harvard's benchmarking approach and Morningstar's methods.

Testing Market Efficiency

  • Historical strategy analysis can indicate market efficiency.
  • Strong form efficiency considers if prices incorporate all information (including private). Insider trading can generate money; however, it is illegal. Although sometimes it doesn't last long.
  • Strategies using public data are analyzed; weak form efficiency questions whether past prices predict future ones.

Viewpoints on Market Efficiency

  • Markets are generally viewed as efficient, but opportunities exist. Ask what is so unique about someone's investment strategy.
  • Market inefficiencies include events like the 1987 crash, without fundamental causes for the 20% drop. But there was no reason to have done so.
  • Predictable excess returns without systematic risk indicates opportunity. You must be early and quick to gather material information.
  • Experts exist that may provide market efficiency; the issue is selecting the manager as the winners typically don't share their secrets.

Arbitrage and Market Making

  • Opportunities exist in liquidity provision since the 2008 financial crisis, particularly in forward contracting on currencies and interest rates.
  • Regulation post-2008 created profitable wedges for institutions with capital access.
  • However, accessing these opportunities can be challenging due to technical positions, gatekeeping, and more.
  • Endowments who invest with the right firms, large firms, are privy to a set of investment positions that smaller investors are not. This provides a small return compared to the total capital available.

Models for Risk and Return

  • Models are based on reward for risk, diversification, and market efficiency.
  • The concepts are typically termed Alphas for positive results, and Bench-marking via measuring Betas.

Finance Jargon

  • Finance uses unique language, such as "alpha generation."
  • Alpha is excess return relative to a benchmark (beta).
  • Expected return in the stock market stems from betas tied to various exposures, like oil prices.

Defining Risk Premium

  • Risk premium determines extra over zero-risk cash, driven by exposure-based betas. Then multiplied by what you get for that asset.
  • Measurement is critical. Benchmarks track exposures, assessing performance.
  • Benchmarks encompass all betas.

Alpha and Beta: A Simple Model

  • Alpha/beta comes from a model where the stock market aggregate is the risk premium.
  • Excess market return benchmarks stock performance.
  • A stock getting 9% return but with 1.5 beta isn't outperforming; it's just riskier.

The Capital Asset Pricing Model

  • The beta terminology originally comes the Capital Asset Pricing Model.
  • First compares to a market portfolio. It is used in cost of capital calculations for utilities.

Assets, Leverage, and Frontier of Opportunities

  • Assets (bonds/stocks) are combined with cash, aiming for the best reward-for-risk ratio.
  • The frontier of opportunities is efficient, above which is bad use (inefficient).
  • Combining cash and bonds is less rewarding than cash and a yellow asset.

Sharpe Ratio

  • You try to maximize and find your Sharpe ratio.
  • The Sharpe ratio in the US Stock Market is about 1/3. Sustaining a Sharpe ratio above one is considered a superb success.

Relating Volatility and Risk

  • Volatility, or standard deviation, relates to potential losses. The goal is to reduce volatility and make the portfolio more conservative.
  • The general paradox in the marketplace is in the financial theory that you are to match the marker performance as an investor. However investments must be made to move the market and to make that data available.

International Investing Considerations

  • International portfolio must vary asset weighting depending on domicile, and that involves currency selection. There are numerous factors to account for such as Euro vs CAD
  • Currency is always a factor. You have to consider and address currency and determine if it is worthwhile to cover. From a US perspective, there are numerous ways to account for this.
  • There is data that some sources claim unhedged assets are performing better. Immunization can be implemented to prevent currency losses.

The Optimal Tangency Portfolio

  • Sharp ratio is a great risk metric. Diversification also helps Sharpe ratio cause the denominator increases.
  • Conservative investor may have majority cash, while aggressive may leverage.

How Does This all Shift?

  • Expected return should follow and can be assessed. A new asset should follow the most optimal mixture of factors.
  • If a current opportunity can reward the investors, they should take action on it.
  • Long term holdings and market security are two parts. If someone offers private equity, the returns should still outpace the market.

Real vs. Pre Returns

  • Positions should be measured after tax.
  • The tangibles is what matters, such as federal tax, which is going to be factored in at the end. Make sure to consider municipals.
  • Evaluate if you can improve on just doing VTI from Vanguard. Should be a shift for those high ratings. You are beating a number with an efficient asset. It's better to benchmark against something you are unable to do on your own.
  • Some individuals look to the index to find a great tangent. Those assets would increase during the portfolio.

Volatility Revisited

  • Have a standard deviation to work around. Find sharp ratios that fit depending on what has happened. Should be a target for the tangible position.

Measuring if You Beat the Market

  • Beating the market is not a one on one result.
  • Consider if it results in higher volatility.

Evaluating Manager Selection

  • Sharp ratios are not sufficient when evaluating manager selection. Consider the risk profile.
  • It takes managers to measure what risk is being had in the same market. Don't evaluate manager ratios independently.

More on Alpha and Beta

  • Manager A has an edge due to a .1 score in betas. So demands are only 1% from those assets.
  • Manager B is greater and should also meet those greater benchmarks.
  • It is important that a certain product doesn't have a 3rd the rate. Instead diversify.
  • Need to appropriate a proper benchmark. An A is worth it. But B can’t be shorted.
  • Overall, a portfolio optimizer should try to bring in managers with solid return.

How Predictable is Alpha

  • Question: If alpha is seen in history, does it persist?
  • Alpha is based on strategy. It is an extra return on benchmarks, but also is very data biased.
  • History helps determine where to go from there. You might want to select the money ahead of the game.

Understanding Alpha

  • Francis and the DFA case help illustrate generating a large alpha.
  • There are large aspects involved in equity.

Overview on Stock Value

  • High returns result in low price values. Value and Momentum strategies typically have Alphas. Value stock can be referred to as B/M. Book Value Equity/ Market Value Equity.
  • A book value is depreciated over the life of the asset which helps bring it down. Static versus Market over Assets. In Growth prospects the current book isn’t as high. Value comes in what’s embedded in future assets.

Morningstar

  • Morningstar is big as it tracks positions and strategies. The two aspects are Value vs Growth and Small Cap Vs Mid Cap Vs Large Cap. At the point they typically are difference classes with their differences.
  • Morningstar analyzes and follows holdings to assess performance.

Value Premium

  • Take a portion of your value to the market. The main thing is to evaluate from history. The tilt of the portfolio matters going forward.
  • If an asset it cheap, it will beat the market at its function.
  • The market evolved. They can determine a mutual fund to track these and be cheap. A multi investment might be necessary.