Reference Rates - FIMMDA-NSE MIBID MIBOR
A reference rate is an accurate measure of the market price. In the fixed income market, it is an interest rate that the market respects and closely watches. It plays a useful role in a variety of situations.
In particular, a call money reference rate can find the following applications:
- Traders can make many decisions as offsets compared with the prevailing reference rate.
- Derivatives require a clearly defined reference rate as a foundation, off which the pay-off from the derivative is defined.
- A variety of contracts can be structured as offsets from the future levels of a reference rate. The simplest example may be a floating rate bond that uses an interest rate which is a given 'n' offsets above a given reference rate.
Apart from its accuracy, such a reference rate needs to have other qualities. The methodology of collation and computation should be scientific, should eliminate noise, and resist manipulation. It should be from an unbiased source, be representative of the market, transparent, reliable and continuously available. Moreover, it should find applicability across a wide range of products. A reference rate, which embodies all these qualities, would be widely acceptable to the market as the benchmark rate.
About FIMMDA-NSE MIBID MIBOR
The yardstick for the money market
The Committee for the Development of the Debt Market had studied and recommended the modalities for the development for a benchmark rate for the call money market. Accordingly, NSE had developed and launched the NSE Mumbai Inter-bank Bid Rate (MIBID) and NSE Mumbai Inter-bank Offer Rate (MIBOR) for the overnight money market on June 15, 1998. The success of the Overnight NSE MIBID MIBOR encouraged the Exchange to develop a benchmark rate for the term money market. NSE launched the 14-day NSE MIBID MIBOR on November 10, 1998 and the longer term money market benchmark rates for 1 month and 3 months on December 1, 1998. Further, the exchange introduced a 3 Day FIMMDA-NSE MIBID-MIBOR on all Fridays with effect from June 6, 2008 in addition to existing overnight rate.
The MIBID/MIBOR rate is used as a bench mark rate for majority of deals struck for Interest Rate Swaps, Forward Rate Agreements, Floating Rate Debentures and Term Deposits.
Fixed Income Money Market and Derivative Association of India (FIMMDA) has been in the forefront for creation of benchmarks that can be used by the market participants to bring uniformity in the market place. To take the process of development further, FIMMDA and NSEIL have taken the initiative to co-brand the dissemination of reference rates for the Overnight Call and Term Money Market using the current methodology behind NSE – MIBID/MIBOR. The product was rechristened as 'FIMMDA-NSE MIBID/MIBOR'. The 'FIMMDA-NSE MIBID/MIBOR' is now jointly disseminated by FIMMDA as well as NSEIL through their websites and other means and simultaneous dissemination of the information would be as per international practice.
Why NSE MIBID MIBOR
The National Stock Exchange of India (NSEIL) has been trusted by the securities markets for its unbiased independence and professionalism. The function of forecasting has become more meaningful as the information comes from a source, which is not only reliable but has no vested interest of its own in the market movements.
- Market Representation
FIMMDA-NSE MIBID MIBOR is based on rates polled by NSE from a representative panel of 30 banks/ primary dealers.
The reference rate is released to all the market participants simultaneously through various media, making it transparent with the aspiration of the market. Ensuing transparency helps the market participants to judge the market mood and the probable rate one is likely to encounter in the market. This information is useful not only to the banks but also to the issuers and investors.
The high level of co-relation between actual deals and the reference rate gives an indication of its reliability. The bootstrapping technique guards against the possibility of cartelisation and of extreme observations influencing the mean.
- Scientifically Computed
The methodology of "Polling" with "Bootstrapping" is scientific and the values are generated through a system that has been extensively tested. The technique involves generating multiple data sets based on the rates polled with a dynamically determined number of iterations, identification of outliers, trimming the data set of its extreme values and computation of the mean and its standard deviation.
- Elimination of Noise
The trimming procedure is vulnerable to market manipulation of the rates due to the amount of sampling noise. Excessive trimming may lead to loss of information whereas no trimming may lead to excessive influence of the extreme values. To derive a true representative benchmark for the market NSE ensures that after trimming at least 14 data points should remain in observation for the bid and for the ask rates.
The Exchange ensures that everyday the FIMMDA-NSE MIBID MIBOR along with the respective standard deviations are disseminated to the market at 0955 (IST) for overnight rate and at 1200 (IST) for 14 day, 1 month and 3 month rates..
The Committee for the Development of the Debt Market studied various alternative methodologies, which could be used for compiling a true reference rate in the market. This market is characterised by limited number of participants, who at times, take a unidirectional view of the market. Some of the methodologies studied by the committee are as under:
Volume weighted average (VWA) is calculated by averaging the reported trades after weighting them with their respective volume. The VWA needs price volume data of all executed deals and is a reliable measure of the market sentiment. However the calculation of VWA has some constraints in the Indian context, as most participants prefer to keep their transactions confidential. Moreover, this method can give results only at the close of the market and therefore tends to give post-facto information and cannot be used to gauge the market mood at a point of time.
Polling (Delphic oracle) is used for obtaining reference rates by polling a few market participants and summarizing the prices they report. The highly liquid CME Eurodollar contract uses this method for its futures contract. The procedure involves querying bid and offer prices from eight market participants.
The basic question that is asked about this approach is, what motivates the respondents to report accurately? It is hard to design an incentive structure whereby the respondent does participate, and produces an accurate information. Full transparency would clearly help- if all eight quotes along with the name of the respondents are reported through a transparent medium, it would generate pressure to report fair prices. At the same time, this degree of public visibility might deter some players from participating. This is particularly a problem in an illiquid market, where various participants could have genuine or selfish reasons for reporting widely differing rates. Dealers have an incentive to falsify the reported rates to inject noise into the decision making of the market participants who use the reported reference rate or to gain from positions on derivative contracts which calculate payoffs using the reference rate.
Identifying and isolating noise in data: Having selected an appropriate technique for collecting data, one has to devise methods to identify and isolate the noise in data so as to minimise the impact of the extreme values on the final result, i.e. the reference rate. The most commonly used methods for this purpose are discussed hereunder:
Traded mean: Calculating fixed trimmed mean of the reported rates have been used by some organizations which need to use a reference rate, e.g. the CME for its Eurodollars contract, the CBOT for its Municipal Bond Index, etc. They collect rates from individual dealers and compute a reference rate as the trimmed mean is obtained after deleting "n" highest and lowest observations. For example, at CME Eurodollar, the two highest and two lowest quotes are rejected and the rest of the quotes averaged to get a reference rate.
The major concerns in such a trimming procedure are vulnerability to market manipulation of the rates and the amount of sampling noise. Secondly, excessive trimming may lead to loss of information, whereas too little trimming may lead to excessive influence of the extreme values on the reference rate. Thirdly, the sample sizes are typically very small and hence statistics based on the assumptions of normal distribution give wrong inferences.
Bootstrapping: The bootstrap technique is a non-parametric method for computing the test statistics, i.e.
- Computing the reference rate as an average of the polled rates after an appropriate amount of trimming to minimise noise.
- Computing a measure of dispersion i.e. the confidence intervals for the trimmed means.
In order to arrive at an efficient estimate of the reference rate, from the bid and offer rates collected from a known sample of dealers, the outliers or extreme values are identified. This is required so that the reference rate, which is a mean of the polled rates, is not unduly influenced by extreme observations, which are likely to be noisy.
A user is also interested in knowing the efficiency of this mean value. That is to say, he is interested in knowing the probability that the estimated trimmed mean lies in a given range. Thus, the standard deviation of the mean has to be estimated. Since the call market is heterogeneous, constrained by limited participants and dealers, the underlying distribution of the offer and bid rates is not normal and hence the usual measures of efficiency of the mean rate, i.e. the standard deviation, is not valid.
The bootstrap method does not make any assumptions about the distribution from which the trimmed mean is drawn. The bootstrap method facilitates construction of the entire distribution for the mean and hence all the required parameters can be calculated from this constructed distribution.
Since the observations are drawn at random and the number of simulations is very high, the probability of any extreme observations affecting the mean value and its standard deviation is extremely minimal.
The procedure for choosing an adaptive 'n' as opposed to using a fixed 'n' allows for reduction of sampling noise and hence makes the estimated mean more efficient.
As discussed above, the "Polling" with "Bootstrapping" scores over the other alternatives to collect data in a limited data set and to isolate the extreme values. FIMMDA-NSE MIBID/MIBOR therefore, uses polling to collect data from the market participants. While the quotes for the overnight money are polled between 0940- 0945 hours, quotes for the other terms are polled between 1130- 1140 hours to capture the market sentiment in a short interval of time. Thereafter, the data so collected is subjected to bootstrapping to identify the extreme values.
The bootstrapping technique involves generating multiple data sets based on the rates polled, wherein the number of iterations required is determined dynamically and could be as high as 10,000. Based on the means generated from these multiple data samples, the standard deviation is calculated. The bootstrapping technique is also used to identify the outliers in the polled data. This is done by trimming the data set of its extreme values and again using a bootstrapped sample to calculate the standard deviation. Bootstrapping ensures that the data sets are drawn at random and this guards against the possibility of cartelisation and of extreme observations influencing the mean. The mean corresponding to the lowest standard deviation is finally reported by ensuring acceptability of at least 14 observations each for bid and offers. The standard deviations associated with FIMMDA-NSE MIBID/MIBOR are also reported to help the market in assessing the distribution of rates.
Thus, the methodology adopted by FIMMDA-NSE MIBID/MIBOR not only seeks to tackle the limitation of the polling method but also uses adaptive trimming to identify and isolate the extreme value to derive a true representative benchmark for the market. Moreover, the entire process of polling and processing of data is completed in a time-bound schedule and the reference rates are released to the market every day.
Panel of Participants
Public Sector Banks
- Bank of Baroda
- Bank of India
- Canara Bank
- Central Bank of India
- Corporation Bank
- Indian Bank
- Indian Overseas Bank
- Punjab National Bank
- State Bank of India
- State Bank of Hyderabad
- State Bank of Patiala
- Syndicate Bank
- Union Bank of India
- UCO Bank
Private Sector Banks
- Axis Bank Ltd.
- HDFC Bank Ltd.
- ICICI Bank Ltd.
- IndusInd Bank Ltd.
- IDBI Bank Ltd.
- Kotak Bank
- Yes Bank Ltd.
- CitiBank N.A.
- Deutsche Bank AG
- Development Bank of Singapore
- Standard Chartered Bank
- SBI DFHI Ltd.
- ICICI Securities Ltd. (I-Sec).
- PNB Gilts Ltd.
- Securities Trading Corporation India Ltd. (STCI)
FIMMDA-NSE MIBID MIBOR rates are broadcast through the NEAT-WDM trading system immediately on release. The NSE website carries the daily rates as well as the historical data on the FIMMDA-NSE MIBID MIBOR. The FIMMDA also disseminates the FIMMDA-NSE MIBID MIBOR rates through its website and other means.
In addition leading information vendors carry these rates on a daily basis. Reuters on its news information page, Bridge News Service (Knight Ridder) on page no.2811, Bloomberg on its money market page as well as a news story and PTI on its money market page.
FIMMDA-NSE MIBID MIBOR rates are also carried by all leading financial dailies including Economic Times, Financial Express, Business Standard and Business Line.
In addition to the above, FIMMDA-NSE MIBID MIBOR rates are released to contributors and users through E-mail.
Products linked to MIBID/MIBOR
Floating Rate Notes
- GE Capital
- GE Capital
- ICICI bank
Interest Rate Swaps
- Parties: Standard Chartered Bank & Multinational entity
- Parties: HSBC & Corporate entity
- Parties: HDFC Bank & KEC International
- Parties: ABN AMRO N. V. & Multinational entity
- Parties: ABN AMRO N. V. & Reliance Industries
- Parties: ABN AMRO N. V. & Multinational entity
- Parties: Deutsche Bank & ICICI Ltd.
- Parties: Deutsche Bank & Multinational entity
Forward Rate Agreements
Bank : HSBC