CFA Equity, Alt Inv, Risk Management PDF

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CFA Equity, Alt Inv, Risk Management Equity

Portfolio Substyles: – Contrarian: prefers stocks trading at low P/B (typically 100mm, full replication is ok. If number in index is reasonably low (e.g. 100), full replication is ok. – Desire to minimize transaction costs indicate stratified sampling (not optimization). – Stratified sampling has higher tracking error relative to full replication – Optimization typically requires rebalancing (leading to transaction costs) even when index constituents donʼt change. L/S Pros and Cons vs. Long Only Strategies: – Pros: better express negative views, go into high conviction long positions, removal of mkt risk to diversify, better control risk factor exposures. – Cons: potential large losses for shorts, negative exposures to risk premiums, potentially high leverage for mkt-neutral funds, costs of borrowing, collateral demands, short squeeze possibility. Misc Tips: – If a PM is willing to buy both value and growth stocks (regardless of P/E), and focuses solely on whether the stock is trading below its intrinsic value, itʼs a blend/core style and cannot be clearly categorized as value or growth. – The appropriate BM for mkt-neutral portfolio is the risk-free rate, because a mkt-neutral port has no systematic risk, therefore zero beta. – The stock lender is compensated for any dividends that the lender wouldʼve received had the stock not been loaned. – The biggest risk in pairs trading is that the observed price divergence is not temporary and could be due to structural reasons. Frequent use of stop-loss rules, which are set to exit trades when a loss limit is reached, addresses this risk. – “If the Sharpe ratio of the new investment is greater than the current portfolio Sharpe ratio multiplied by the correlation of the new investmentʼs returns with the portfolioʼs returns, adding the investment to the portfolio will improve the portfolio Sharpe ratio” – Less stringent standard of comparison if thereʼs diversification benefits (low correlation) Returns-based vs. Holdings-based style analysis: – Regressing a fundʼs past returns against the past returns from a number of style indexes is a returns-based style analysis. – Returns-based analysis is easier to implement than holdings-based analysis because data are more readily available. – Holdings-based analysis allows for a deeper level of analysis when compared with returns-based analysis because holdings-based analysis uses the actual portfolio holdings. The analysis is more accurate and generates more information for making style allocation decisions. Ideal Indices for returns-based style analysis should be: ^. Mutually exclusive w.r.t. indices/asset classes _. Exhaustive w.r.t. managerʼs investment universe

k. Represent distinct sources of risk Why there are more price inefficiencies on the short side of the market than on the long side: – Impediments to short selling (e.g. need to borrow stock before selling it), relatively few investors search for overvalued stocks —> pessimism not fully reflected in stock prices – Insiders less likely to divulge negative info (I.e. drop in profits, fraud) than positive info, so stock prices might not fully reflect negative info – Sell-side analysts predominantly issue buy recs and positive opinions (commissions). High Frequency Data & Asynchronism: Think about 2 time-series data (i.e - stock returns) for each of the following: daily movements and monthly movements. The daily movements of 2 stocks will be noisy and volatile (i.e - 1 day it gives +0.4% return, the next -0.6%, etc). When you measure the correlation of the 2 stock returns using daily data, it will likely be very low. Monthly movements: this will be less noisy for the 2 stocks and more correlated to each other. In general, the longer out (macro view, zoomed out) your data, the more “smoothed” it is. That is why high-frequency data is very noisy (asynchronous) —> correlation will be very low. Top-down vs. Bottom-Up: Given bottom-up systematic manager: Emphasizing security-specific factors is a bottom-up method. Targeting low idiosyncratic risk along with low concentrations indicates a systematic approach, not a discretionary approach. Although the Soar Fund does sometimes consider macro data and events, this is not its primary top-down driver of portfolio construction. Bottom-up methods use approaches like GARP to identify attractively-priced stocks Discretionary vs. Systematic: Discretionary: consideration of firm specific factors (e.g. ESG, management quality). Can result in concentrated portfolios (reflecting depth of managersʼ insights on company characteristics). More likely to emphasize non financial variables such as quality of management, competitive landscape, and pricing power of the firm. Shareholder Engagement Pros: – Help develop a more effective corporate governance structure —> lead to better company performance to the benefit of shareholders/stakeholders. – Investors also benefit cuz they will have more info about companies or sectors in which the company operate. – Can address concerns such as ESG. Cons: – Time consuming and can be costly. – Pressure on company management to meet short term share price or earnings targets could be made at the expense of long term corporate decisions. – Selective disclosure of important info to a certain subset of shareholders —> breach of insider trading rules – Conflict of interest (e.g. PM supports the management who invests with the PM) – “Free-rider problem”: A PM uses active strategy and succeeds in increase stock price —> everyone benefits. Approaches to constructing an indexed portfolio: – Full replication: minimal tracking risk but high costs – Stratified sampling: retains basic characteristics of index without costs associated with buying all the stocks. Uses strata (that are mutually exclusive and exhaustive, like countries and sectors) to cover all the stocks. Useful when want to track indexes that have many constituents or when having a relatively low AUM. – Optimization: seeks to match portfolioʼs risk exposures (incl. covariances) to those of the index but can be misspecified if historical risk relationships change over time. Lower

tracking error than stratified, but costly, requires frequent rebalancing, and requires sophisticated techniques. HHI Index & Effective # of stocks HHI is the sum of the constituent weightings squared. Effective # of stocks is 1/HHI, held in equal weights, that would mimic the concentration level of the chosen index. – Cap weighted indexes have a surprisingly low effective # of stocks. – E.g. NASDAQ 100 consists of 100 stocks. If the index were weighted uniformly, each stockʼs weight would be 0.01 (1%). However, weights for the top 5 stocks totaled almost 38%, and median weight was 0.39%. The squared weights sum to 0.0404, and 1/0.0404 = 24.75, the effective number of stocks. – Thus, the 100 stocks in the index had a concentration level that can be thought of as equivalent to 25 stocks held in equal weights. A Passive PM uses derivatives for overlays, more efficient than cash-mkt transactions: – Completion overlay addresses an indexed port that diverged from its proper exposure (e.g. too much cash causing port beta to be significantly < BM) – Rebalancing overlay addresses a portʼs need to sell certain constituent securities and buy others. – Currency overlay assists a PM in hedging returns of securities held in a foreign currency. Passive factor-based strategies vs. mkt-cap-weighted indexing – Relative to broad-mkt-cap-wgt, passive factor-based tend to concentrate risk exposures, leaving investors exposed during periods when a chosen risk factor is out of favor. – Passive factor-based strategies tend to be transparent in terms of factor selection, weighting, and rebalancing. The strategies can be easily replicated by other investors which can produce overcrowding and reduce the realized advantages of a strategy. E.g. quant over-crowding Sources of return and risk to a passively managed equity portfolio: River Valley Fund Factor

Weight

% Return

Benchmar k Portfolio # of Stocks

Weight

% Return

# of Stocks

Growth

0.22

7.9

23

0.25

7.9

23

Value

0.19

5.2

27

0.19

5.2

27

Quality

0.29

6.7

20

0.26

6.7

20

Momentum

0.30

3.9

24

0.30

4.5

30

Total 1.00 5.84 94 1.00 6.06 100 % of the excess return of the River Valley Fund arising from active factor weighting is closest to: In comparing the weights between the fund and the benchmark, the factors with different weights are Growth and Quality. The total contribution to the return caused by active factor weighting is (Underweighting of the Growth factor + Overweighting of the Quality factor) / Total effect (aka excess return) =[(0.22-0.25)*7.9% + (0.29-0.26)*6.7%] / (5.84%-6.06%) = 16.36% Causes for more relative Tracking Error: ● The portfolio contains a smaller # of the index holdings resulting in a lower level of replication. ● Dividends are reinvested the day following receipt rather than the same day, which would cause cash drag ● The portfolio is reconstituted less frequently ● The portfolio is rebalanced less frequently ● Higher management fee

Rank Correlation: ● Pearson IC = correlation between factor exposure and subsequent period returns, high correlation means factor is good signal for predicting future returns. ○ Disadvantage, Pearson IC is sensitive to outliers. ● Spearman Rank IC is correlation coefficient of factor score rank against stock returns rank, better predictor than Pearson IC because less sensitive to outliers. ● Pearson IC and Spearman Rank IC can contradict each other b/c of outliers affecting Pearson score. ** Indexing Techniques **: ● Buffering involves establishing ranges around breakpoints that define whether a stock belongs in one index or another. Some index providers have adopted policies intended to limit stock migration problems and keep trading costs low for investors who replicate indexes. Size rankings may change daily with market price movements, so buffering makes index transitions a more gradual and orderly process. As long as stocks remain within the buffer zone, they stay in the current index, and as a result, the holdings of the fund may exceed the holdings of the index slightly. ● Reconstitution involves deleting names that are no longer in the index and adding names that have been approved as new index members. ● Packeting involves splitting stock positions into multiple parts. E.g., if a mid-cap stockʼs capitalization increases and breaches the breakpoint between the mid-cap and large-cap indexes, a portion of the total holding is transferred to the large-cap index but the rest stays in the mid-cap index. On the next reconstitution date if the stock value remains large cap and all other qualifications are met, the remainder of the shares are moved out of the mid-cap index into the large-cap index all at once at larger block. Pitfalls in Fundamental Investing: ● Behavioral Biases ○ Confirmation bias: “stock love bias”, look for info that confirms existing belief about their fav companies. Selection bias —> poorly diversified portfolio, excessive risk exposure, holdings in poor performing securities. Should actively seek out opinion of others to mitigate. ○ Illusion of control: could lead to excessive trading and/or heavy weighting on a few stocks. Should seek out contrary viewpoints, and set/enforce proper trading/ diversification rules. ○ Availability bias: easily recalled outcomes perceived more likely to happen. May reduce investment opportunity set and —> insufficient diversification as PM relies on familiar stocks. Should have LT focus to eliminate ST over-emphasis caused by this bias ○ Loss aversion: can cause investors to hold unbalanced ports in which poor performing stocks are maintained in hope of potential recovery, and successful stocks sold prematurely. Should have stop-loss rules. ○ Overconfidence: illusion of exaggerated knowledge and abilities, attribute success to ability than luck. PM will underestimate risks and overestimate E(R). Should seek constructive feedback and review actual investment records for awareness. ○ Regret aversion: prevent making decisions, may hold on to losing stocks for too long or lose out on profitable opps. Should have proper port review process, justify existing positions. ● The Value Trap: A stock that appears to be attractively valued (low P/E or P/B or P/CF) because of a significant price fall but that may still be overpriced given its worsening future prospects. Stock prices need catalysts to advance, without it, itʼs harder to adjust to its fair value. ● The Growth Trap: Expectation that the share price will appreciate when the company grows earnings or CF in the future. But the stock may turn out to have been overpriced at the time of the purchase. Share price may not move any higher due to its already high starting

level. Pitfalls in Quant Investing: ● Survivorship bias: backtests include only stocks that survived and not ones that fail ● Look-ahead bias: use of financial statement data for a company at a pt in time before the data was actually released. ● Data mining and Overfitting: excessive search analysis to uncover patterns that arenʼt really there.

Alternative Investments

Commodities: – Spot return (price return): return related to changes in the underlying commodity using the cost-of-carry model. If spot price of gold expected to rise —> short-dated future price will rise as arbitrage trading occurred. – Collateral return (collateral yield): return from investment in gold futures rather than the physical gold. Iʼm able to invest the full value of the underlying contract to earn Rf. Since I expect int rates to rise, this component will rise as well. – Roll return (roll yield): return from rolling long gold futures contracts over time. If I expect convenience yield (benefit from holding physical gold rather than the future) on gold will increase, increased backwardation (spot even higher than future) —> roll return will increase. But also if I expect interest rates will rise —> holding future rather than actual gold more beneficial because I get a greater collateral return (invest money you would have invested in commodity at the risk free rate) —> futures price rise —> roll return decreases. ● Commodities that are storable and affected by level of economic activity (e.g. metals such as aluminum) are positively related to unexpected changes in inflation and are good inflation hedges. ● Commodities that trade infrequently often have stale prices —> reduces volatility of the fund —> increasing the Sharpe Ratio Hedge Funds: HF managers are not required to return incentive fees if their funds lose value in futures years; however, they may be subject to a high-water mark provision that provides incentive fees only when a fundʼs value is higher than its maximum previous value. Both private equity funds and hedge funds sometimes have hurdle rates that award incentive fees only for returns that exceed the hurdle rate of return. Ways to Game the Sharpe Ratio: ^. Lengthen the measurement interval (lowers volatility) _. Compounding the monthly returns but calculating the stdev from the uncompounded monthly returns k. Writing out-of-the-money puts and calls on the portfolio (increases return by collecting premium without paying off for several years). v. Smoothing returns (using certain derivatives, infrequent mark to market of illiquid assets, and bad pricing models, reduce reported volatility) w. Getting rid of extreme returns that increase the stdev. Sortino Ratio (annualized rate of return - annualized min acceptable return) / Downside deviation ^. Calculate total fund return = [(1+r1)(1+r2)…] - 1 = 0.0777 _. Calculate geometric mean per year = (1.0777^(1/12))*12 = 7.51% k. We know hurdle rate = 5% per year, so itʼs 0.4167% per month. For each month of fund returns, deviation from hurdle rate squared is computed if the fund return < hurdle rate, otherwise itʼs 0 v. Downside deviation = sqrt(sum of deviation from hurdle rate squared)/sqrt(12-1) * sqrt(12) = 3.07 w. Sortino ratio = (7.51% - 5%)/3.07% = 0.81 Distressed debt strategies:

– Most significant risk is Liquidity risk (quick exit could be costly) – Market risk is relatively low as long bonds and short stocks of a company removes systematic risk. – Sharpe ratio is often overstated due to stale valuations – Due diligence costs are likely to be costly because investing in distressed securities is complex and requires legal, operational, and financial analysis and requires a unique approach and solution – J factor risk - the effect of judge on results of bankruptcy proceedings. Judge may rule more in favor of debt or equity holders, which would impact returns – If you are a fund with a 3yr investment horizon, and the distressed debt fund youʼre investing has a 3yr lockup period, thatʼs good because it prevents other investors with shorter time horizons from withdrawing their capital early, which could potentially reduce your overall return. HF Index Problems: – Less stale price bias compared to PE, as HF usually have public securities with market prices available – Backfill bias—that is, applying returns that “would have been earned” by following a strategy before it was followed. Occurs because only strategies that would have worked historically are adopted. – Survivorship bias—including the returns of only those funds that survived long enough to meet requirements for inclusion—shifts returns upward by not including the returns of funds that failed quickly. – Use of manager-based index - self-reported index not likely to neutrally reflect the underlying performance of the strategy; managers with better track records more likely to report their returns —> bias index returns upward. Self-reported index may also suffer from inconsistent reporting by component managers over time. – If index weights based on managerʼs AUM, then index is value-weighted (instead of equalweighted), which may result in the index taking on the return characteristics of the bestperforming HFs in a particular time period (top performing funds grow from new inflows and high returns, poor perf funds closed, top perf represent an increasing share of index). Could create momentum effect in index returns —> index difficult to track. – Value-weighted indices more heavily weighted in the recent best-performing funds relative to equal-weighted, so the past returns of the index reflect the performance of a different set of managers from todayʼs or tomorrowʼs manager. Private Equity: – Although management fees are typically based on the % of the value of limited partnersʼ committed funds, management fees often scale down in the later years of a partnership to reflect a lower workload as the fund becomes fully invested. Consequently, the manager is not actively involved in identifying potential investment companies. – Returns to PE have relatively high correlations with publicly traded equity; therefore, not much diversification benefits for a portfolio with a high allocation to equity. – Clawback provisions. These are sometimes included in PE funds, and they require managers to return incentive fees earned from profitable investments that are sold earlier in the life of the fund if later investments are sold at a loss. Managed Futures (CTAs): designed to produce positive returns regardless of market conditions (e.g., absolute return strategies); however, it is incorrect that managed futures programs are available to investors only as separately managed accounts, because limited partnerships are available as private commodity pools run by commodity pool operators (CPOs). Fund of Funds (FoFs): Potential benefits vs. individual HFs are: ^. The skill at selecting fund managers provided by the fund-of-funds manager _. The diversification provided by the fund-of-funds investment in multiple hedge funds, which may be diffic...