Basis Point Definition
Basis point (BPS) is a commonly used unit for measuring interest rates as well as other percentages used in the finance sector. One basis point tells how much percentage change a financial instrument has experienced. It is equivalent to 0.01% or 0.0001, and is calculated by taking 1/100th of 1%. There is a link between the change in percentage and basis points, where a change of 1% translates to 100 basis points, and that of 0.01% translates to 1 basis point.The word ‘basis’ in the term refers to the base movement taking place between two percentages. It can also be referred to as spread occurring between two rates of interest. Since the fluctuations are not too huge, and these little fluctuations can have huge results, the basis becomes a fraction of 1%.
A Little More on What is a Basis Point
The basis point is usually considered for ascertaining fluctuations in interest rates, equity-based indices, and the returns offered by a fixed-income instrument. Both bonds and loans usually receive quotes in the form of basis point. For instance, you may say that your bank offers interest rate that is 50 basis points more than LIBOR or London Interbank Offered Rate. When the yield of a bond rises from 5% to 5.5%, it means that it has increased by 50 basis points, and when the rate of interest increases by 1%, it is considered to be risen by 100 basis points. Target interest rate, when raised by the Federal Reserve Board, by 25 basis points, it refers to the increase in interest rates by 0.25%. In case, the Fed increases the interest rate from 2.50% to 2.75%, it means that there has been an increase of 25 basis points.
Basis points make it easier for people including traders, and financial analysts to understand the essence of changes in percentage. For instance, a financial instrument that carries a 10% rate of interest, and has a 10% increase ahead, it could either give a perception that the new rate is 11% (10% + 10% of 10), or 20% (10% + 10%). Here, the above statement gave vague information. However, by using the concept of basis point, it gets pretty obvious to ascertain that if the rate of interest of an instrument is 10%, and it experiences an upward movement of 100 basis points, then it is 11% now. Had the basis points increased by 1000, it would have resulted in 20%.
The price value of a basis point (PVBP) ascertains the absolute value of the bond’s price change with respect to the change in one basis point in yield. This also helps in ascertaining risks associated with interest rates, just like the duration that determines how much a bond price changes if there is a 1% change made in the interest rates.
PVBP tends to be a unique case for dollar duration. Here, the price value of a basis point considers using a 1 basis point change rather than 100 basis points. Whether the rates are going up or down, it holds no relevance as this tiny movement in rates will almost be the same in any of the directions. It can also be known as dollar value change for a 1 bp move or DV01.
Analysts use basis points at the time of ascertaining the costs associated with mutual funds and exchange-traded funds. If a mutual fund bears an annual management expense ratio of 0.10%, it will receive a quote of having 15bps. At the time of comparing one fund with another, basis points enables to give a clear picture of variations in the costs of investment funds. For instance, a financial analyst can say that a mutual fund having 0.45% as annual expenses is 10 basis points more than the one having annual costs of 0.35%.
As interest rates are not applicable on equity, basis points are not significantly used for quoting prices in the stock market.
Reference for “Basis Point (BPS)”
Academics research on “Basis Point (BPS)”
US unconventional monetary policy and transmission to emerging market economies, Bowman, D., Londono, J. M., & Sapriza, H. (2015). US unconventional monetary policy and transmission to emerging market economies. Journal of International Money and Finance, 55, 27-59. We investigate the effects of U.S. unconventional monetary policies on sovereign yields, foreign exchange rates, and stock prices in emerging market economies (EMEs), and we analyze how these effects depend on country-specific characteristics. We find that, although EME asset prices, mainly those of sovereign bonds, responded strongly to U.S. unconventional monetary policy announcements, these responses were not outsized with respect to a model that takes into account each country’s currency regime and vulnerability to U.S. financial conditions.
Semiparametric estimates of monetary policy effects: string theory revisited, Angrist, J. D., Jordà, Ò., & Kuersteiner, G. M. (2018). Semiparametric estimates of monetary policy effects: string theory revisited. Journal of Business & Economic Statistics, 36(3), 371-387. We develop flexible semiparametric time series methods for the estimation of the causal effect of monetary policy on macroeconomic aggregates. Our estimator captures the average causal response to discrete policy interventions in a macrodynamic setting, without the need for assumptions about the process generating macroeconomic outcomes. The proposed estimation strategy, based on propensity score weighting, easily accommodates asymmetric and nonlinear responses. Using this estimator, we show that monetary tightening has clear effects on the yield curve and on economic activity. Monetary accommodation, however, appears to generate less pronounced responses from both. Estimates for recent financial crisis years display a similarly dampened response to monetary accommodation.
Extreme estimation uncertainty in fair value estimates: Implications for audit assurance, Christensen, B. E., Glover, S. M., & Wood, D. A. (2012). Extreme estimation uncertainty in fair value estimates: Implications for audit assurance. Auditing: A Journal of Practice & Theory, 31(1), 127-146. The overall complexity and estimation uncertainty inherent in financial statements have increased in recent decades; however, the related reports and services have changed very little, including the format of the balance sheet and income statement, the content in the auditor’s report, and the level and nature of assurance provided on estimates. We examine estimates reported by public companies and find that fair value and other estimates based on management’s subjective models and inputs contain estimation uncertainty or imprecision that is many times greater than materiality. Importantly, changes in the estimates often impact net income; consequently, the extreme estimation uncertainty also resides in measures such as earnings per share. We do not question the value audits provide to the marketplace, the importance of fair value reporting, or the ability of auditors to deploy up-to-date valuation and auditing techniques. Rather, we suggest that the convergence of relatively recent events is placing an increasingly difficult, and perhaps in some cases unrealistic, burden on auditors. We consider whether the convergence of events in regulation and standard setting may have outstripped auditors’ ability to provide the level and nature of assurance currently required on estimates with extreme estimation uncertainty by auditing standards and regulators. We discuss potential changes to financial reporting and auditing standards that may improve the information provided to users and also address the concerns we raise. Finally, we suggest avenues for future research that may be fruitful in addressing how changes to standards would influence the behavior of preparers, auditors, and users.
An analysis of critical accounting estimate disclosures of pension assumptions, Bauman, M. P., & Shaw, K. W. (2014). An analysis of critical accounting estimate disclosures of pension assumptions. Accounting Horizons, 28(4), 819-845.
Sources of the small firm financing premium: Evidence from euro area banks, Holton, S., & McCann, F. J. (2017). Sources of the small firm financing premium: Evidence from euro area banks. The post-2008 period in the euro area was characterised by sharp dispersion in borrowing costs faced by firms, across both countries and firm types. This dispersion was an important manifestation of the “financial fragmentation” which hampered the smooth transmission of accommodative monetary policy. Using bank level data from 2007 to 2015, we directly measure the borrowing cost dispersion across firm types by calculating the difference in the interest rate charged by the same bank in the same month for loans to small and large firms (the “Small Firm Financing Premium”, SFFP). We assess the role played by both bank and macroeconomic factors in explaining the variation in the SFFP across countries and through time. We provide evidence that bank market power, sovereign bond holdings and balance sheet weaknesses led to disproportionate borrowing cost increases for small firms, and exacerbated the impact of a weak macroeconomy during this period.