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Literature: authors starting with B

78 studies, books and laws, each with its reference, a sentence on the content and the pages that cite it. All letters

Bacon (2019) · Performance Attribution: History and Progress

Bacon, Carl R.. CFA Institute Research Foundation, Literature Review; accessed October 25, 2026. Source

Survey of attribution from Brinson to the present: multi-level models, top-down and bottom-up, currencies following Karnosky and Singer, bonds, linking, arithmetic versus geometric, and derivatives with notional holdings.

Cited in: Multi-asset attribution: weighting schemes, top-down and bottom-up, currencies and overlays · Glossary: Multi-level attribution · Glossary: Geometric attribution

Baele et al. (2010) · The Determinants of Stock and Bond Return Comovements

Baele, Lieven; Bekaert, Geert; Inghelbrecht, Koen. The Review of Financial Studies 23 (6), pp. 2374–2428. doi:10.1093/rfs/hhq014

A dynamic factor model with regime switching: macroeconomic fundamentals barely explain the correlation between stocks and bonds, while liquidity measures and other factors play a larger role; the model fits the covariances worst.

Cited in: Stock-bond correlation: regimes, drivers and what it means for 60/40, risk parity and hedging

Bai and Collin-Dufresne (2019) · The CDS-bond basis

Bai, Jennie; Collin-Dufresne, Pierre. Financial Management 48 (2), pp. 417–439. doi:10.1111/fima.12252

The CDS-bond basis deviates further from zero where liquidity, funding costs, counterparty risk and collateral quality make arbitrage harder.

Cited in: Basis trades: positive and negative basis in bonds, CDS and futures · Glossary: CDS-bond basis

Bai and Perron (1998) · Estimating and Testing Linear Models with Multiple Structural Changes

Bai, Jushan; Perron, Pierre. Econometrica 66 (1). doi:10.2307/2998540

Theory for estimating and testing multiple structural breaks in regressions, including tests for the number of break points.

Cited in: Regime models: hidden Markov, Markov switching and more · Glossary: Structural break

Bai et al. (2015) · The Impact of Leveraged and Inverse ETFs on Underlying Real Estate Returns

Bai, Qing; Bond, Shaun A.; Hatch, Brian. Real Estate Economics 43 (1), pp. 37–66. doi:10.1111/1540-6229.12061

Six leveraged and inverse real estate ETFs influenced the end-of-day prices of 63 real estate stocks, increased their volatility and amplified price momentum.

Cited in: How leveraged ETFs are built: swaps, daily rebalancing and gamma risk

Bailey and López de Prado (2012) · The Sharpe ratio efficient frontier

Bailey, David H.; López de Prado, Marcos. The Journal of Risk 15 (2), pp. 3–44. doi:10.21314/JOR.2012.255

Introduces the probabilistic Sharpe ratio and the minimum track record length: how likely is it that an estimated Sharpe ratio exceeds a threshold when returns are not normally distributed?

Cited in: Deflated Sharpe ratio: how much skill is in a Sharpe ratio? · Overfitting check and diversification return: the calculations in Backtest and Tactical · Glossary: Probabilistic Sharpe ratio · Glossary: Minimum track record length · Glossary: Standard error of the Sharpe ratio

Bailey et al. (2014) · Pseudo-Mathematics and Financial Charlatanism: The Effects of Backtest Overfitting on Out-of-Sample Performance

Bailey, David H.; Borwein, Jonathan M.; López de Prado, Marcos; Zhu, Qiji Jim. Notices of the American Mathematical Society 61 (5), pp. 458–471. doi:10.1090/noti1105

Shows how quickly a high backtest Sharpe ratio emerges when many variants are tested, and derives a minimum backtest length.

Cited in: Deflated Sharpe ratio: how much skill is in a Sharpe ratio? · Probability of backtest overfitting: does the best variant deliver what the backtest promises? · Overfitting check and diversification return: the calculations in Backtest and Tactical

Bailey and López de Prado (2014) · The Deflated Sharpe Ratio: Correcting for Selection Bias, Backtest Overfitting, and Non-Normality

Bailey, David H.; López de Prado, Marcos. The Journal of Portfolio Management 40 (5), pp. 94–107. doi:10.3905/jpm.2014.40.5.094

The deflated Sharpe ratio corrects a Sharpe ratio for the number of strategies tried and for skewness and kurtosis.

Cited in: How to backtest an ETF portfolio: a guide to portfolio backtesting · Sharpe ratio: return per unit of risk · Backtest overfitting: when the past looks too good · Deflated Sharpe ratio: how much skill is in a Sharpe ratio? · Probability of backtest overfitting: does the best variant deliver what the backtest promises? · Overfitting check and diversification return: the calculations in Backtest and Tactical · Glossary: Expected maximum Sharpe ratio · Glossary: Effective number of trials · Glossary: Multiple testing · Glossary: Selection bias · Glossary: Deflated Sharpe ratio

Bailey and López de Prado (2021) · How “Backtest Overfitting” in Finance Leads to False Discoveries

Bailey, David H.; López de Prado, Marcos. Significance 18 (6), pp. 22–25. doi:10.1111/1740-9713.01588

Written for a general audience: why strategies optimized on historical data are often statistical mirages and perform poorly in practice.

Cited in: Probability of backtest overfitting: does the best variant deliver what the backtest promises?

Bailey (1992) · Are Manager Universes Acceptable Performance Benchmarks?

Bailey, Jeffery V.. The Journal of Portfolio Management 18 (3), pp. 9–13. doi:10.3905/jpm.1992.9

Lists the properties of a valid benchmark (unambiguous, investable, measurable, appropriate, reflective of current investment opinions, specified in advance) and shows that peer groups of other managers do not meet them.

Cited in: Portfolio reporting: how to report return, risk, attribution and costs properly

Bailey (1992) · Evaluating Benchmark Quality

Bailey, Jeffery V.. Financial Analysts Journal 48 (3), pp. 33–39. doi:10.2469/faj.v48.n3.33

Tests of benchmark quality: coverage, turnover, predominantly positive active weights, tracking error, correlations of market-adjusted returns and similar style characteristics.

Cited in: Portfolio reporting: how to report return, risk, attribution and costs properly

Bailey et al. (1963) · A Regression Method for Real Estate Price Index Construction

Bailey, Martin J.; Muth, Richard F.; Nourse, Hugh O.. Journal of the American Statistical Association 58 (304), pp. 933–942. doi:10.1080/01621459.1963.10480679

Establishes the repeat-sales index: prices of the same property at different times, combined in a regression, sidestep quality differences and yield standard errors for the index.

Cited in: Collectibles as an investment: what art, wine, watches and classic cars really return · Real estate as an investment: rental property, REITs, open-end funds and private real estate · Glossary: Repeat-sales index

Bajgrowicz and Scaillet (2012) · Technical trading revisited: False discoveries, persistence tests, and transaction costs

Bajgrowicz, Pierre; Scaillet, Olivier. Journal of Financial Economics 106 (3), pp. 473–491. doi:10.1016/j.jfineco.2012.06.001

Technical rules on the Dow Jones in 1897–2011 assessed with the false discovery rate: even low trading costs eliminate the in-sample excess return.

Cited in: Technical analysis, chart patterns and candlesticks from a quant perspective

Baker and Wurgler (2004) · A Catering Theory of Dividends

Baker, Malcolm; Wurgler, Jeffrey. The Journal of Finance 59 (3), pp. 1125–1165. doi:10.1111/j.1540-6261.2004.00658.x

Companies start paying dividends when investors value dividend payers at a premium, so they are catering to demand.

Cited in: Dividend strategies and dividend ETFs under scrutiny: irrelevance, factors, risks

Baker and Wurgler (2006) · Investor Sentiment and the Cross-Section of Stock Returns

Baker, Malcolm; Wurgler, Jeffrey. The Journal of Finance 61 (4), pp. 1645–1680. doi:10.1111/j.1540-6261.2006.00885.x

When sentiment is low, small, young, volatile and hard-to-value stocks subsequently earn higher returns; when it is high, they earn lower returns.

Cited in: Sentiment: methodology for the fear and greed index, put/call ratio and COT

Baker et al. (2011) · Benchmarks as Limits to Arbitrage: Understanding the Low-Volatility Anomaly

Baker, Malcolm; Bradley, Brendan; Wurgler, Jeffrey. Financial Analysts Journal 67 (1), pp. 40–54. doi:10.2469/faj.v67.n1.4

Explains the low-volatility anomaly by benchmark mandates for fund managers and investors' preference for lotteries.

Cited in: The low-volatility anomaly and betting against beta · Glossary: Low-volatility anomaly

Bakshi and Kapadia (2003) · Delta-Hedged Gains and the Negative Market Volatility Risk Premium

Bakshi, Gurdip; Kapadia, Nikunj. Review of Financial Studies 16 (2), pp. 527–566. doi:10.1093/rfs/hhg002

Delta-hedged long positions in index options perform worse than zero on average, which is evidence of a negative volatility risk premium.

Cited in: Market expectations: what the yield curve, inflation-linked bonds and options reveal about the future · Option pricing: where fair option prices come from · Tail hedging: what put protection costs, when it pays off and what short-vol strategies teach

Bakshi et al. (2011) · The Baltic Dry Index as a Predictor of Global Stock Returns, Commodity Returns, and Global Economic Activity

Bakshi, Gurdip; Panayotov, George; Skoulakis, Georgios. SSRN. doi:10.2139/ssrn.1787757

Growth in a dry bulk freight rate index predicts stock and commodity returns and global economic activity, both in and out of sample.

Cited in: Ship tracking data and satellite images: what they reveal about commodities · Glossary: Freight rate index

Bali et al. (2011) · Maxing out: Stocks as lotteries and the cross-section of expected returns

Bali, Turan G.; Cakici, Nusret; Whitelaw, Robert F.. Journal of Financial Economics 99 (2), pp. 427–446. doi:10.1016/j.jfineco.2010.08.014

Stocks with the highest daily return in the previous month (MAX) subsequently earn lower returns: investors overpay for lottery-like chances of large gains.

Cited in: Stock picking: why individual stocks are so hard to get right · Glossary: Lottery stock

Ball and Brown (1968) · An Empirical Evaluation of Accounting Income Numbers

Ball, Ray; Brown, Philip. Journal of Accounting Research 6 (2), pp. 159–178. doi:10.2307/2490232

Classic study of the price reaction to annual earnings: much of the information is already in the price before the announcement.

Cited in: Event studies: how to measure and test price reactions to events

Baltas and Kosowski (2020) · Demystifying Time-Series Momentum Strategies: Volatility Estimators, Trading Rules and Pairwise Correlations

Baltas, Nick; Kosowski, Robert. Wiley; in: Satchell, Stephen; Grant, Andrew (eds.), Market Momentum: Theory and Practice. doi:10.1002/9781119599364.ch3

How volatility estimators and signals drive the turnover of trend strategies and why higher correlations between markets after the financial crisis depressed results; with a cost model for rolling and rebalancing.

Cited in: CTAs and managed futures: industry, position sizing, costs and crisis protection

Baltussen et al. (2021) · Hedging Demand and Market Intraday Momentum

Baltussen, Guido; Da, Zhi; Lammers, Sten; Martens, Martin. Journal of Financial Economics 142 (1), pp. 377–403. doi:10.1016/j.jfineco.2021.04.029

Hedging short gamma means trading with the market: in more than 60 futures on equities, bonds, commodities and currencies (1974 to 2020), the return over the rest of the day predicts the return in the last 30 minutes before the close, linked to the gamma hedging of options market makers and leveraged ETFs.

Cited in: How leveraged ETFs are built: swaps, daily rebalancing and gamma risk

Banca d'Italia (2026) · The European Parliament decided to open negotiations on the Digital Euro Regulation (July 9, 2026)

Banca d'Italia. Banca d'Italia; accessed October 25, 2026. Source

The European Parliament adopted its negotiating mandate on the digital euro by 416 votes to 169 with 22 abstentions; the aim is to conclude the legislative process by the end of 2026.

Cited in: Digital assets: tokenization, stablecoins, crypto securities and the digital euro

BIS (2018) · The equity market turbulence of 5 February: the role of exchange-traded volatility products (box in the BIS Quarterly Review, March 2018, pp. 4-6)

Bank for International Settlements. Bank for International Settlements, March 11, 2018 (chart corrected March 21, 2018); accessed October 26, 2026. Source

On February 5, 2018 the S&P 500 fell by 4.2% and the VIX rose by 20 points; leveraged and inverse VIX products had to buy VIX futures shortly before 16:15, and the inverse product XIV lost 84% and was terminated.

Cited in: Tail hedging: what put protection costs, when it pays off and what short-vol strategies teach · Glossary: Volmageddon

BIS (2025) · Next-generation monetary and financial system takes shape, based on a tokenised unified ledger: BIS (press release on the Annual Economic Report 2025, Chapter III, June 24, 2025)

Bank for International Settlements. Bank for International Settlements; accessed October 25, 2026. Source

Tokenization on a unified ledger with central bank reserves, bank deposits and government bonds; stablecoins fail the tests of singleness, elasticity and integrity.

Cited in: Digital assets: tokenization, stablecoins, crypto securities and the digital euro · Glossary: Tokenization

BIS (2026) · Annual Economic Report 2026, Chapter III: Anchoring trust in money: innovation beyond stablecoins

Bank for International Settlements. Bank for International Settlements; accessed October 25, 2026. Source

The market value of stablecoins was about US$320 billion at the end of May 2026, with 99.4% of fiat-backed stablecoins pegged to the dollar; redemption at par across issuers and blockchains is not assured in all circumstances.

Cited in: Digital assets: tokenization, stablecoins, crypto securities and the digital euro · Glossary: Stablecoin

Bank of England (2023) · Bank staff paper: LDI minimum resilience – recommendation and explainer

Bank of England. Bank of England, Financial Policy Committee, March 29, 2023; accessed October 25, 2026. Source

Recommendation to the UK pensions regulator: LDI funds and mandates should be able to withstand a yield rise of at least about 250 basis points without forced sales.

Cited in: Liability-driven investing and cash flow driven investing: covering liabilities with bonds · Overlay management with futures: beta, duration and currency overlays, contract numbers and liquidity needs

Bank of England, APF (2023) · Asset Purchase Facility Quarterly Report – 2022 Q4

Bank of England. Bank of England; accessed October 25, 2026. Source

The size and unwinding of the temporary gilt purchases made to safeguard financial stability in autumn 2022.

Cited in: Liability-driven investing and cash flow driven investing: covering liabilities with bonds

Banz (1981) · The relationship between return and market value of common stocks

Banz, Rolf W.. Journal of Financial Economics 9 (1), pp. 3–18. doi:10.1016/0304-405x(81)90018-0

Discovers the size effect: small companies earned higher returns than the CAPM would predict.

Cited in: Equal weight vs cap weight: weighting, rebalancing and factor tilts · Factor investing: understanding the Fama-French factors · Glossary: SMB · Glossary: Size premium

Bao et al. (2011) · The Illiquidity of Corporate Bonds

Bao, Jack; Pan, Jun; Wang, Jiang. The Journal of Finance 66 (3), pp. 911–946. doi:10.1111/j.1540-6261.2011.01655.x

The illiquidity of US corporate bonds in 2003–2009 is substantial, greater than bid-ask spreads can explain, and accounts for a large part of the time variation in the yield spreads of highly rated bonds.

Cited in: Market making and bond trading: spread, inventory, axes, RFQ, cross trades and matrix pricing

Barber and Lyon (1997) · Detecting long-run abnormal stock returns: The empirical power and specification of test statistics

Barber, Brad M.; Lyon, John D.. Journal of Financial Economics 43 (3), pp. 341–372. doi:10.1016/S0304-405X(96)00890-2

Over one to five years, tests against a market index are misspecified; matching firms of the same size and book-to-market ratio largely fix this.

Cited in: Event studies: how to measure and test price reactions to events · Glossary: Buy-and-hold abnormal return

Barber and Odean (2000) · Trading Is Hazardous to Your Wealth: The Common Stock Investment Performance of Individual Investors

Barber, Brad M.; Odean, Terrance. The Journal of Finance 55 (2), pp. 773–806. doi:10.1111/0022-1082.00226

Individual investors who trade a lot earn markedly lower returns than passive investors.

Cited in: Core-satellite with a broad core and targeted satellites: costs, tracking error and rules · Market timing: can you pick the right moment? · Stock picking: why individual stocks are so hard to get right · The efficient market hypothesis: why it is so hard to beat the market · Time-weighted and money-weighted return: what measures what? · Glossary: Overconfidence

Barber and Odean (2008) · All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors

Barber, Brad M.; Odean, Terrance. The Review of Financial Studies 21 (2), pp. 785–818. doi:10.1093/rfs/hhm079

Individual investors mainly buy attention-grabbing stocks: stocks in the news, with unusually high trading volume or with extreme daily returns.

Cited in: Core-satellite with a broad core and targeted satellites: costs, tracking error and rules · Thematic ETFs and hype: what studies, costs and overlaps reveal

Barden et al. (2024) · Fewer tankers transit the Red Sea in 2024

Barden, Justine; Dunn, Candace; Merolli, Paul. U.S. Energy Information Administration, Today in Energy, October 11, 2024. Source

After the attacks in the Red Sea, oil flows through the Bab el-Mandeb fell by more than half, while more tankers sailed around the Cape of Good Hope.

Cited in: Ship tracking data and satellite images: what they reveal about commodities

Barkhagen et al. (2023) · Optimising portfolio diversification and dimensionality

Barkhagen, M.; García, S.; Gondzio, J.; Kalcsics, J.; Kroeske, J.; Sabanis, S. et al.. Journal of Global Optimization 85 (1), pp. 185–234. doi:10.1007/s10898-022-01202-7

Portfolio dimensionality: links diversification to the non-normality of portfolio returns through ratios of homogeneous risk measures (independent of leverage); maximizing it is non-convex and is solved with two global optimization methods.

Cited in: Beyond Markowitz: estimation error, noise and true diversification · Glossary: Portfolio dimensionality

Barroso and Santa-Clara (2015) · Momentum has its moments

Barroso, Pedro; Santa-Clara, Pedro. Journal of Financial Economics 116 (1), pp. 111–120. doi:10.1016/j.jfineco.2014.11.010

Momentum had the highest Sharpe ratio of the classic factors but the worst crashes; its risk varies strongly and is predictable, and managing it accordingly nearly eliminates the crashes and almost doubles the Sharpe ratio.

Cited in: Momentum crashes: why momentum collapses rarely but violently, and what volatility scaling and crowding measures show

Barth and Kahn (2021) · Hedge Funds and the Treasury Cash-Futures Disconnect

Barth, Daniel; Kahn, R. Jay. Office of Financial Research, U.S. Department of the Treasury, Working Paper 21-01. doi:10.67236/faxi2748

The rise and unwinding of hedge funds' Treasury basis trade after 2016 and in March 2020, more a consequence than the main cause of the market stress.

Cited in: Basis trades: positive and negative basis in bonds, CDS and futures

Barth et al. (2023) · Recent Developments in Hedge Funds' Treasury Futures and Repo Positions: is the Basis Trade “Back”?

Barth, Daniel; Kahn, R. Jay; Mann, Robert. Board of Governors of the Federal Reserve System, FEDS Notes, August 30, 2023. doi:10.17016/2380-7172.3355

Analysis of futures and repo data: the basis trade is probably back, at least in part.

Cited in: Basis trades: positive and negative basis in bonds, CDS and futures

Bartram et al. (2008) · Does adverse selection affect bid–ask spreads for options?

Bartram, Söhnke M.; Fehle, Frank; Shrider, David G.. Journal of Futures Markets 28 (5), pp. 417–437. doi:10.1002/fut.20316

Bank-issued warrants on the EUWAX had narrower bid-ask spreads than comparable Eurex options; adverse selection accounts for at least half of the spread on Eurex.

Cited in: Glossary: Warrant

Basel Committee on Banking Supervision (2009) · Principles for sound stress testing practices and supervision

Basel Committee on Banking Supervision. Bank for International Settlements, May 2009 (superseded in 2018); accessed October 25, 2026. Source

Principles for banks' stress testing and its review by supervisors, in response to the weaknesses in stress testing that the financial crisis had exposed.

Cited in: Scenario analysis and sensitivity analysis: stress testing equity, interest rate, credit and currency risk

Basel Committee (2011) · Capital treatment for bilateral counterparty credit risk finalised by the Basel Committee (press release)

Basel Committee on Banking Supervision. Bank for International Settlements, Basel, June 1, 2011; accessed October 25, 2026. Source

Finalization of the Basel III rules on counterparty risk, with a capital charge for CVA risk; during the financial crisis, about two thirds of counterparty credit risk losses came from CVA changes.

Cited in: Counterparty and issuer risk: CVA, ETCs, certificates and swaps · Glossary: Credit valuation adjustment

Basel Committee on Banking Supervision (2018) · Stress testing principles

Basel Committee on Banking Supervision. Bank for International Settlements, October 17, 2018; accessed October 25, 2026. Source

Nine principles on the objectives, governance, data, models and review of stress tests; scenarios should be severe but plausible, and reverse stress tests look for scenarios that could cause a bank to fail.

Cited in: Historical stress testing: how to apply past crises to your portfolio today · Scenario analysis and sensitivity analysis: stress testing equity, interest rate, credit and currency risk · Scenario methodology: how Portfolio Lab runs stress tests · Glossary: Stress test · Glossary: Reverse stress test · Glossary: Historical scenario · Glossary: Hypothetical scenario

Basel Committee (2020) · Basel Committee publishes final revisions to the credit valuation adjustment risk framework (press release)

Basel Committee on Banking Supervision. Bank for International Settlements, Basel, July 8, 2020; accessed October 25, 2026. Source

Final revisions to the Basel III CVA framework: risk weights, cleared client transactions, the standardized and basic approaches, aligned with the market risk framework.

Cited in: Counterparty and issuer risk: CVA, ETCs, certificates and swaps

BCBS, CPMI and IOSCO (2022) · BCBS-CPMI-IOSCO finalise analysis of margining practices during the March 2020 market turmoil (press release on the report “Review of margining practices”)

Basel Committee on Banking Supervision; Committee on Payments and Market Infrastructures; International Organization of Securities Commissions. Bank for International Settlements, September 29, 2022; accessed October 26, 2026. Source

In March 2020, central counterparties' variation margin calls peaked at US$140 billion on March 9, and initial margin in central clearing rose by about US$300 billion over the month.

Cited in: Overlay management with futures: beta, duration and currency overlays, contract numbers and liquidity needs · Glossary: Variation margin

Basel Committee (2024) · Basel Committee publishes final disclosure framework for banks' cryptoasset exposures and targeted amendments to its cryptoasset standard (press release, July 17, 2024)

Basel Committee on Banking Supervision. Bank for International Settlements; accessed October 25, 2026. Source

A disclosure framework and targeted amendments to the December 2022 cryptoasset standard, mainly on the criteria for Group 1b stablecoins; both apply from January 1, 2026.

Cited in: Crypto in institutional portfolios: access, custody, regulation and risk budget

Basel Framework, SCO60 (2024) · The Basel Framework, SCO60: Cryptoasset exposures (version in force from January 1, 2026, last amended November 27, 2024)

Basel Committee on Banking Supervision. Bank for International Settlements; accessed October 25, 2026. Source

Banks' crypto exposures in Groups 1a, 1b, 2a and 2b; a risk weight of 1,250% for Group 2b, and total Group 2 exposures generally up to 1%, and at most 2%, of Tier 1 capital.

Cited in: Crypto in institutional portfolios: access, custody, regulation and risk budget

Basel Committee (2026) · Basel Committee meets to advance supervisory and regulatory initiatives and discuss risks and vulnerabilities to the global banking system (press release, October 1, 2026)

Basel Committee on Banking Supervision. Bank for International Settlements; accessed October 25, 2026. Source

The Committee is conducting a targeted review of specific elements of its standard for banks' crypto exposures and intends to provide an update by the end of 2026.

Cited in: Crypto in institutional portfolios: access, custody, regulation and risk budget

Baule et al. (2008) · Credit risk and bank margins in structured financial products: Evidence from the German secondary market for discount certificates

Baule, Rainer; Entrop, Oliver; Wilkens, Marco. Journal of Futures Markets 28 (4), pp. 376–397. doi:10.1002/fut.20309

Discount certificates in the secondary market: with a model that combines market and credit risk, total margins are rather low, and the component for the bank's credit risk makes up a substantial part of them.

Cited in: Glossary: Discount certificate · Glossary: Issuer margin

Baule and Blonski (2015) · The Demand for Warrants and Issuer Pricing Strategies

Baule, Rainer; Blonski, Philip. Journal of Futures Markets 35 (12), pp. 1195–1219. doi:10.1002/fut.21703

Retail investors tend to buy the warrant with the lowest margin among similar ones but do not respond to the general margin level; issuers vary the margin with moneyness.

Cited in: Glossary: Warrant

Baum et al. (1970) · A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains

Baum, Leonard E.; Petrie, Ted; Soules, George; Weiss, Norman. The Annals of Mathematical Statistics 41 (1), pp. 164–171. doi:10.1214/aoms/1177697196

An iterative method for estimating hidden Markov chains, known today as the Baum-Welch algorithm.

Cited in: Regime models: hidden Markov, Markov switching and more · Regime methodology: how the hidden Markov model works · Glossary: Hidden Markov model · Glossary: Baum-Welch algorithm

Baur and Lucey (2010) · Is Gold a Hedge or a Safe Haven? An Analysis of Stocks, Bonds and Gold

Baur, Dirk G.; Lucey, Brian M.. Financial Review 45 (2), pp. 217–229. doi:10.1111/j.1540-6288.2010.00244.x

On average, gold is a hedge against equities and a safe haven in extreme downturns, but only in the short term.

Cited in: All Weather portfolio: ready for every economic climate? · Gold in a portfolio: safe haven, inflation hedge or just shiny? · Glossary: Safe haven · Glossary: Gold

Baur and McDermott (2010) · Is gold a safe haven? International evidence

Baur, Dirk G.; McDermott, Thomas K.. Journal of Banking & Finance 34 (8), pp. 1886–1898. doi:10.1016/j.jbankfin.2009.12.008

Tests gold as a safe haven for the stock markets of many countries, including in individual crises.

Cited in: Gold in a portfolio: safe haven, inflation hedge or just shiny?

Baxter and Jermann (1997) · The International Diversification Puzzle Is Worse Than You Think

Baxter, Marianne; Jermann, Urban J.. American Economic Review 87 (1), pp. 170–180. Source

Returns on human and physical capital are closely linked in four industrial countries; hedging human capital would require a short position in domestic assets.

Cited in: Your whole wealth: total wealth from portfolio, home, human capital and car

Beasley et al. (2003) · An evolutionary heuristic for the index tracking problem

Beasley, J. E.; Meade, N.; Chang, T.-J.. European Journal of Operational Research 148 (3), pp. 621–643. doi:10.1016/s0377-2217(02)00425-3

Heuristic for selecting a limited number of securities that track an index as closely as possible.

Cited in: Index replication: full replication, optimized sampling and swaps

Beber and Pagano (2013) · Short-Selling Bans Around the World: Evidence from the 2007–09 Crisis

Beber, Alessandro; Pagano, Marco. The Journal of Finance 68 (1), pp. 343–381. doi:10.1111/j.1540-6261.2012.01802.x

Short-selling bans in the financial crisis harmed liquidity, slowed price discovery and did not support prices, except possibly for US financial stocks.

Cited in: Short selling, hedge funds and hedging: types and how they work

Becker et al. (2015) · Markowitz versus Michaud: portfolio optimization strategies reconsidered

Becker, Franziska; Gürtler, Marc; Hibbeln, Martin. The European Journal of Finance 21 (4), pp. 269–291. doi:10.1080/1351847X.2013.830138

Large simulation study: on average, classical optimization beats resampling, and the choice of estimators and weight constraints matters more.

Cited in: Michaud resampled optimization: more stable portfolio weights through simulation · Optimization methodology: estimation, objectives, Black-Litterman, resampling and walk-forward

Ben Dor and Xu (2011) · Fallen Angels: Characteristics, Performance, and Implications for Investors

Ben Dor, Arik; Xu, Zhe. The Journal of Fixed Income 20 (4), pp. 33–58. doi:10.3905/jfi.2011.20.4.033

After the downgrade, fallen angels initially perform worse than comparable high-yield bonds and then recover over up to two years, the more strongly the deeper the fall.

Cited in: Distressed debt: strategies, bankruptcy law, recovery rates and returns when investing in crises · Glossary: Fallen angel

Ben-David et al. (2017) · Exchange-Traded Funds

Ben-David, Itzhak; Franzoni, Francesco; Moussawi, Rabih. Annual Review of Financial Economics 9 (1), pp. 169–189. doi:10.1146/annurev-financial-110716-032538

An overview of ETFs: structure, arbitrage, liquidity and their effect on markets.

Cited in: ETF basics: costs, replication and distributions · Thematic ETFs and hype: what studies, costs and overlaps reveal · Index providers and valuation points: why the same index is calculated differently · Order types and execution: from limit orders to MOC, VWAP, TAS and BTIC · Glossary: ETF · Glossary: Creation and redemption

Ben-David et al. (2018) · Do ETFs Increase Volatility?

Ben-David, Itzhak; Franzoni, Francesco; Moussawi, Rabih. The Journal of Finance 73 (6), pp. 2471–2535. doi:10.1111/jofi.12727

ETFs pass liquidity shocks on to the stocks they hold and increase the volatility of those stocks.

Cited in: ETF basics: costs, replication and distributions

Ben-David et al. (2023) · Competition for Attention in the ETF Space

Ben-David, Itzhak; Franzoni, Francesco; Kim, Byungwook; Moussawi, Rabih. The Review of Financial Studies 36 (3), pp. 987–1042. doi:10.1093/rfs/hhac048

Specialized ETFs on attention-grabbing themes lose about 30% on a risk-adjusted basis in their first five years, mainly because their stocks are overvalued at launch.

Cited in: Thematic ETFs and hype: what studies, costs and overlaps reveal · Glossary: Thematic ETF

Benartzi and Thaler (1995) · Myopic Loss Aversion and the Equity Premium Puzzle

Benartzi, S.; Thaler, R. H.. The Quarterly Journal of Economics 110 (1), pp. 73–92. doi:10.2307/2118511

Myopic loss aversion: investors who check their portfolio too often perceive equities as too risky.

Cited in: Dollar-cost averaging: what the average-cost effect really delivers · Lump sum or dollar-cost averaging: invest a large amount at once or in installments? · Equity risk premium: how much more equities return and why it is a puzzle · Glossary: Equity premium puzzle · Glossary: Myopic loss aversion

Benartzi (2001) · Excessive Extrapolation and the Allocation of 401(k) Accounts to Company Stock

Benartzi, Shlomo. The Journal of Finance 56 (5), pp. 1747–1764. doi:10.1111/0022-1082.00388

About a third of the assets of large US company retirement plans is invested in the employer's own stock, the more so the better the stock has performed before.

Cited in: Your whole wealth: total wealth from portfolio, home, human capital and car · Glossary: Employer stock

Beneish and Whaley (1996) · An Anatomy of the “S&P Game”: The Effects of Changing the Rules

Beneish, Messod D.; Whaley, Robert E.. The Journal of Finance 51 (5), pp. 1909–1930. doi:10.1111/j.1540-6261.1996.tb05231.x

Since S&P began announcing changes five days in advance, added stocks have risen more than average between the announcement and the effective date; part of the gain reverses afterward.

Cited in: Smart indexing: added value for index funds around corporate actions and index changes

Bengen (1994) · Determining Withdrawal Rates Using Historical Data

Bengen, William P.. Journal of Financial Planning. Source

Uses US data since 1926 to test which inflation-adjusted initial withdrawal would have survived every historical period; the origin of the 4% rule, with a recommended equity share of 50 to 75%.

Cited in: Safe withdrawal rate: how good is the 4% rule? · FIRE (Financial Independence, Retire Early): Lean, Fat, Coast and Barista FIRE · Financial goals methodology: how Portfolio Lab simulates a life plan · Methodology of the free calculators: FIRE, savings plan, withdrawal and leveraged ETF · Glossary: FIRE number

Benzoni et al. (2007) · Portfolio Choice over the Life-Cycle when the Stock and Labor Markets Are Cointegrated

Benzoni, Luca; Collin-Dufresne, Pierre; Goldstein, Robert S.. The Journal of Finance 62 (5), pp. 2123–2167. doi:10.1111/j.1540-6261.2007.01271.x

If wages and dividends move together over the long run, human capital is equity-like for the young and bond-like for older people, and the optimal equity share follows a hump shape.

Cited in: Your whole wealth: total wealth from portfolio, home, human capital and car · Glossary: Life-cycle model

Berg et al. (2022) · Aggregate Confusion: The Divergence of ESG Ratings

Berg, Florian; Kölbel, Julian F.; Rigobon, Roberto. Review of Finance 26 (6), pp. 1315–1344. doi:10.1093/rof/rfac033

Compares the ESG ratings of six agencies and decomposes their divergence: 56% stems from different measurement, 38% from the scope of categories and 6% from weighting.

Cited in: Alternative data: job ads, Reddit, X, satellites and card payments · ESG ETFs: index rules, ratings, returns and the limits of sustainable funds · ESG methodology: sustainability in the look-through · Glossary: ESG rating

Berg et al. (2008) · Prediction market accuracy in the long run

Berg, Joyce E.; Nelson, Forrest D.; Rietz, Thomas A.. International Journal of Forecasting 24 (2), pp. 285–300. doi:10.1016/j.ijforecast.2008.03.007

Iowa Electronic Markets versus 964 polls in the US presidential elections from 1988 to 2004: the market was closer to the result 74% of the time and, for forecasts more than 100 days ahead, significantly better in every election (abstract checked on the Iowa Electronic Markets website).

Cited in: Prediction markets as bets on events: what they can and cannot do · Glossary: Prediction market

Berk and Green (2004) · Mutual Fund Flows and Performance in Rational Markets

Berk, Jonathan B.; Green, Richard C.. Journal of Political Economy 112 (6), pp. 1269–1295. doi:10.1086/424739

Competition for capital and decreasing returns to scale explain why active funds do not outperform on average and why success does not persist, even though most managers have skill.

Cited in: Active ETFs: how they work and what they deliver

Berkowitz (2000) · A coherent framework for stress testing

Berkowitz, Jeremy. The Journal of Risk 2 (2), pp. 5–15. doi:10.21314/jor.2000.021

Criticizes stress tests run outside the risk model because their scenarios have no probability, and proposes building them into the risk model with probabilities; previously published as a Federal Reserve working paper in 1999.

Cited in: Historical stress testing: how to apply past crises to your portfolio today · Scenario analysis and sensitivity analysis: stress testing equity, interest rate, credit and currency risk · Scenario methodology: how Portfolio Lab runs stress tests

Berkowitz et al. (1988) · The Total Cost of Transactions on the NYSE

Berkowitz, Stephen A.; Logue, Dennis E.; Noser, Eugene A.. The Journal of Finance 43 (1), pp. 97–112. doi:10.1111/j.1540-6261.1988.tb02591.x

Introduces the day's volume-weighted average price (VWAP) as a benchmark for execution costs; across more than 14,000 orders, commission and market impact together cost 23 basis points on average.

Cited in: Order types and execution: from limit orders to MOC, VWAP, TAS and BTIC · Glossary: VWAP

Bernardo and Ledoit (2000) · Gain, Loss, and Asset Pricing

Bernardo, Antonio E.; Ledoit, Olivier. Journal of Political Economy 108 (1), pp. 144–172. doi:10.1086/262114

Measures the attractiveness of an investment by the ratio of expected gain to expected loss (gain-loss ratio) and derives price bounds from it.

Cited in: Risk metrics beyond the Sharpe ratio: Treynor, Calmar, Omega, Ulcer Index and more

Bernhardt and Eckblad (2013) · Stock Market Crash of 1987

Bernhardt, Donald; Eckblad, Marshall. Federal Reserve History, as of November 22, 2013. Source

Overview of Black Monday on October 19, 1987, its causes including portfolio insurance, and the Fed's response.

Cited in: CPPI: portfolio insurance with cushion, floor and multiplier

Bernstein (2000) · The Intelligent Asset Allocator

Bernstein, William J.. McGraw-Hill.

An introduction to asset allocation using historical returns, correlations and rebalancing.

Cited in: Rebalancing: getting your portfolio back on course

Bertrand and Prigent (2002) · Portfolio Insurance Strategies: OBPI versus CPPI

Bertrand, Philippe; Prigent, Jean-Luc. SSRN. doi:10.2139/ssrn.299688

Compares option-based portfolio insurance (OBPI) and CPPI by payoff profile and behavior over time.

Cited in: CPPI: portfolio insurance with cushion, floor and multiplier · Glossary: OBPI

Bessembinder (1992) · Systematic Risk, Hedging Pressure, and Risk Premiums in Futures Markets

Bessembinder, Hendrik. Review of Financial Studies 5 (4), pp. 637–667. doi:10.1093/rfs/5.4.637

Returns on currency and agricultural futures are related to hedgers' net positions, so hedging pressure is part of the risk premium.

Cited in: Active or passive in bonds and commodities: why the rules differ from equities · Sentiment: methodology for the fear and greed index, put/call ratio and COT

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