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This article looks at some facts on the latest regulation Volcker Rule. I specifically focus on the Quantitative metrics and RENTD (reasonably estimating near term demand)
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VOLCKER RULE SOME FACTS
Chandra S Khandrika
Volcker Rule Post financial crisis we have witnessed a spate of regula<on. Volcker rule has come into effect this year and focusing on restraining proprietary trading. To do so it has asked banks to gather quan<ta<ve metrics as evidence to support their trading strategies. In this ar<cle I will go over how Volcker metrics can be understood in this framework.
• Market Making only – No Prop Trading • Report Quan<ta<ve Metrics to prove market making • Develop process to es<mate RENTD (Reasonably expected Near Term Demand)
I think Volcker metric repor<ng has some pros and cons. In terms of pros, it will create an environment of beOer compliance and more oversight on risk taking. On the other hand, it is aiming more on the symptom of proprietary trading rather than working towards the transparency. I personally believe, Dodd Frank act requirements towards repor<ng trading ac<vity at various Swap depositories is a great step towards transparency. Regulators should analyze this data to understand the banks rather than adding draconian rules. In the long run I believe Volcker rule might go away.
Market Making only Sec<on 619 of the Dodd Frank Act (also known as the Volcker Rule) introduced a general prohibi<on on proprietary trading, but the regula<ons implemen<ng the law proved extraordinarily difficult to construct in a manner that accommodated the language and intent of the statute – notably provisions allowing banks to con<nue underwri<ng, market making, and risk-‐mi<ga<ng hedging ac<vi<es. For a bank to be defined as market making en<ty Volcker rule has provided some guidance around who is a customer, Trading desk, Demonstrable analysis and Arbitrage. Trading Desk: The smallest discrete unit of organiza<on of a banking en<ty that purchases or sells financial instruments for the trading account of the banking en<ty or its affiliates. Trading desk does not capture mul<ple levels in the organiza<on. ‘ “ This guidance can be construed as for instance, a Large bank A makes market in Interest Rate deriva<ve products in various currencies. To be more clear, this bank trades, Interest rate swaps, Swap<ons, caps and floors and other exo<c products in USD, EUR, GBP, EUR and other currencies. In general Banks structure their trading desks by product, currency and some <mes maturity of the deriva<ve. In this scenario, a bank can and should have mul<ple desks. Then this will lead to snowballing of repor<ng requirements. To prevent this banks might end up lumping the desks together. This will lead to a situa<on where the reported Quan<ta<ve metrics make no sense.” ARBITRAGE: A trading desk would not qualify for the market-‐making exemp<on if it is wholly or principally engaged in arbitrage trading or other trading that is not in response to, or driven by, the demands of clients, customers or counterpar<es. DEMONSTRABLE ANALYSIS: Demonstrable analysis must cover the following factors: historical customer demand, current inventory of financial instruments, and market and other factors regarding the amount, types and risks of or associated with financial instruments in which the trading desk makes a market, including through block trades.
Market Making only CLIENT, CUSTOMER OR COUNTERPARTY: For the market making-‐related permiOed ac<vity, client, customer or counterparty refers to market par<cipants that make use of the banking en<ty’s market making-‐related services by obtaining such services, responding to quota<ons, or entering into a con<nuing rela<onship with respect to such services
1. A trading desk may engage in interdealer trading to meet the reasonably expected near term demands of its clients, customers or counterpar<es, including current demand, unwind or sell posi<ons acquired from clients, customers or counterpar<es, or engage in risk-‐mi<ga<ng or inventory management transac<ons. However, a trading desk or other organiza<onal unit of another banking en<ty is not a client, customer or counterparty of the trading desk if that other en<ty has trading assets and liabili<es of $50 billion or more, unless:
2. The trading desk documents how and why a par<cular trading desk or other organiza<onal unit of the en<ty should be treated as a client, customer, or counterparty of the trading desk for purposes of market making-‐related permiOed ac<vity; or
3. The purchase or sale by the trading desk is conducted anonymously on an exchange or similar trading facility that permits trading on behalf of a broad range of market par<cipants.
Volcker Rule enforcement is having implica<ons around how trading desks are organized for transac<ng with their customers. Interes<ngly, traders who are compensated for taking risks for the firm are now allowed to do market making not risk taking and risk op<mizing. This creates a situa<on for trader where he has to prove via demonstrable evidence why and how he is carrying out par<cular transac<on. In such a scenario do you s<ll need a human to trade. Shouldn't’t we start thinking of brining ROBOTS to the job. They will take every instruc<on in leOer and spirit.
Report Quan<ta<ve Metrics to prove market making
QuanAtaAve Metric Business Unit related
VaR and Stressed VaR Risk Management
Risk Factor Sensi<vi<es Risk Management
Risk and Posi<on Limits Usage Risk Management
Comprehensive P&L AOribu<on Finance
Inventory Turnover Opera<ons
Inventory Aging Opera<ons
Customer Facing Trade Ra<o Opera<ons
Each banking en<ty directly supervised by the Federal Reserve that meets relevant thresholds specified in the rule must furnish the following quan<ta<ve measurements for each of its trading desks engaged in covered trading. For domes<c en<<es, report the total trading assets and liabili<es on a world-‐wide consolidated basis. Foreign en<<es should report their total trading assets and liabili<es for their combined U.S opera<ons only Federal Reserve is looking to understand the nature of business by looking at the following metrics from each trading desk. These metrics are distributed across Risk management, Finance and Opera<ons groups with in each book. I think, metrics from opera<ons group that look at Inventory provide details of who the trading desk is engaged with and PL aOribu<on from finance gives insight to how much money is made and Risk measures from Risk Management provides insights to the magnitude of Risk and poten<al losses. Each of these metrics alone cannot provide a picture of whether a desk is market making or Prop trading. But together they can help in pain<ng a coherent story.
Quan<ta<ve metrics • Metric 1: VaR and Stressed VaR. When repor<ng the VaR and Stress VaR, en<<es should reflect a
loss in a trading unit that is expected to be exceeded less than 1% of the <me over a one-‐day period. Banking en<<es should compute and report VaR and Stress VaR consistently with federal regulatory capital requirements. If a trading unit does not have a standalone VaR or Stress VaR calcula<on, but is part of a larger aggrega<on of posi<ons for which a VaR or stress VaR calcula<on is performed, a VaR or Stress VaR calcula<on that includes only the trading desk’s holdings must be performed consistent with the VaR or Stress VaR model and methodology used for the larger aggrega<on of posi<ons.
• “Volcker rule is clearly enjoining VaR at trading Desk level rather than Business Unit level”. To a common market par<cipant it is very clear why VaR and Stressed VaR are needed. As these two indicators gives the magnitude of loss that a desk can incur over a 1 day period.
• Banks with big trading desks will have large VaR and small trading desks will have small VaR. This is pure func<on of how much risk is retained on the porpolio and risk appe<te of the Business.
• Market making desk should have small VaR not large sized VaR as they are going to outlay the risks in the inter dealer market for facilita<ng client trades.
Quan<ta<ve Metrics • Metric 2: Risk Factor SensiAvity (RFS) :Report the risk factor sensi<vi<es that are monitored and managed as part of the
trading desk’s overall risk management policy. The number and type of Risk Factor Sensi<vi<es that are monitored and managed by a trading desk will depend on the explicit risks assumed by the trading desk. In general, however, reported Risk Factor Sensi<vi<es must be sufficiently granular to account for a preponderance of the expected price varia<on in the trading desk’s holdings. Trading desks must take into account any relevant factors in calcula<ng Risk Factor Sensi<vi<es, including, for example, the following with respect to par<cular asset classes
• Commodity derivaAve posiAons: risk factors with respect to the related commodi<es set out in 17 CFR §20.2, the maturity of the posi<ons, vola<lity and/or correla<on sensi<vi<es (expressed in a manner that demonstrates any significant non-‐lineari<es), and the maturity profile of the posi<ons;
• Credit posiAons: risk factors with respect to credit spreads that are sufficiently granular to account for specific credit sectors and market segments, the maturity profile of the posi<ons, and risk factors with respect to interest rates of all relevant maturi<es;
• Credit-‐related derivaAve posiAons: risk factor sensi<vi<es, for example credit spreads, shits (parallel and non-‐ parallel) in credit spreads -‐-‐ vola<lity, and/or correla<on sensi<vi<es (expressed in a manner that demonstrates any significant non-‐lineari<es), and the maturity profile of the posi<ons;
• Equity posiAons: risk factors for equity prices and risk factors that differen<ate between important equity market sectors and segments, such as a small capitaliza<on equi<es and interna<onal equi<es;
• Equity derivaAve posiAons: risk factor sensi<vi<es such as equity posi<ons, vola<lity, and/or correla<on sensi<vi<es (expressed in a manner that demonstrates any significant non-‐lineari<es), and the maturity profile of the posi<ons;
• Foreign exchange derivaAve posiAons: risk factors with respect to major currency pairs and maturi<es, exposure to interest rates at relevant maturi<es, vola<lity, and/or correla<on sensi<vi<es (expressed in a manner that demonstrates any significant non-‐lineari<es), as well as the maturity profile of the posi<ons; and
• Interest rate posiAons, including interest rate derivaAve posiAons: risk factors with respect to major interest rate categories and maturi<es and vola<lity and/or correla<on sensi<vi<es (expressed in a manner that demonstrates any significant non-‐lineari<es), and shits (parallel and non-‐parallel) in the interest rate curve, as well as the maturity profile of the posi<ons.
Banks should start aggrega<ng the risk factor sensi<vi<es like Delta, Gamma, Vega and other measures that they capture to understand the trading porpolios.
Quan<ta<ve Metrics • Metric -‐3 -‐ Risk and Posi<on Limits and Usage -‐ Risk and Posi<on Limits are the constraints that define the amount of risk
that a trading desk is permiOed to take at a point in <me, as defined by the banking en<ty for a specific trading desk. Usage represents the por<on of the trading desk’s limits that are accounted for by the current ac<vity of the desk.
• “Banks monitor VaR and other Risk posi<on limits ( Delta, Vega, Gamme etc).
– Interest Rate Swap Desk -‐ [ Interest Rate Delta, Interest rate Basis ( 1M vs 3M, 3M vs 6M, 3M vs 12M, 3M vs OIS] – Interest Rate Op<ons Desk – [ Interest Rate Delta, Vega (vola<lity sensi<vity) and Gamma ]
Quan<ta<ve Metrics Metric 4: Profit and Loss (P&L) AXribuAon: Volcker Rule enjoins to report Profit and loss due to trading by aOribu<ng to various factors like P&L due to new posi<ons, exis<ng posi<ons, residual profit and loss. Also wants to explain profit loss due to Risk factor sensi<vi<es. Also, for each desk provide PL vola<lity for 30, 60 and 90 day lag. Consider as an example P&L of 260 for an Interest Rate op<ons book to be aOributed as
New posiAons New Deals and Amendments
100
Exis<ng posi<ons Interest Rate Sensi<vity factor (Delta)
50
Exis<ng posi<ons
Vola<lity Sensi<vity factor (vega)
80
P&L due to Carry and funding
20
Change in Valua<on Adjustments
0
Residual unexplained Residual unexplained
10
Total 260
PL aOribu<on definitely helps in understanding what explains the profit and loss. In general trading desk faces lot of issues with valuing some posi<ons on the book that are highly illiquid and cannot be taken of the books in the interdealer market easily. Trading desk marks these posi<ons to model and taking valua<on adjustments smooth the daily PL. This will lead to a situa<on where reported metrics are not accurate descriptors of the trading strategy.
Quan<ta<ve Metrics • Metric 5: Customer-‐Facing Ac<vity Measurements: Inventory Turnover: Inventory Turnover is a ra<o that measures the
turnover of a trading desk’s inventory. The numerator of the ra<o is the absolute value of all transac<ons over the repor<ng period. The denominator of the ra<o is the value of the trading desk’s inventory at the beginning of the repor<ng period. The beginning of the repor<ng period is considered a rolling period, where the beginning date would change for each reported trading date (e.g., for a 30-‐day period, on July 1, the beginning of the repor<ng period is June 1; on July 2, the beginning of the repor<ng period is June 2; etc).
• Report the Inventory Turnover ra<o over a 30 trading day, 60 trading day and 90 trading day calcula<on period • For deriva<ves, other than op<ons and interest rate deriva<ves, value means gross no<onal value, for op<ons, value
means delta adjusted no<onal value, and for interest rate deriva<ves, value means 10-‐year bond equivalent value. “ Volcker Rule enjoins banks to aggregate gross market values, no<onal values and 10Y bond equivalent values for Cash, FX and Interest rate products to understand how a bank is turning over the inventory”. This is a very interes<ng metric which every business opera<on monitors to understand the opera<onal efficiency. For instance a Cycle selling firm can look at the ra<on of sold cycles to the exis<ng inventory of cycles to understand how to plan for future periods of opera<on. Now how it can be applied to financial instruments”. To the best of my knowledge and experience, Financial industry is no different when you look at the trading inventory
Inventory ra<o = Ending period Inventory / Beginning period Inventory. Product Beginning
Inventory Ending inventory Inventory Turnover Comment
Cash 1000 2000 2000/1000 =2 Inventory is growing over the repor<ng period
FX products 1000,000 500,000 500,000/1000,000 =0.5
Inventory is being reduced
Interest Rate Swaps
50,000 (DV01 ) 100,000 ( DV01) 100,000/50,000 = 2 Inventory Is being increased
Quan<ta<ve Metrics • Metric 6: Customer-‐Facing Ac<vity Measurements: Inventory Aging: Inventory Aging generally describes a schedule of
the trading desk’s aggregate assets and liabili<es and the amount of <me that those assets and liabili<es have been held. Inventory aging should measure the age profile of the trading desk’s assets and liabili<es. Banking en<<es should apply a First In, First Out (FIFO) method in measuring the age profile.
• Inventory Aging includes two schedules, an asset-‐aging schedule and a liability-‐aging schedule. • For deriva<ves, other than op<ons and interest rate deriva<ves, value means gross no<onal value. For op<ons, value
means delta adjusted no<onal value. For interest rate deriva<ves, value means 10-‐year bond equivalent value. “ Volcker Rule enjoins banks to aggregate gross market values, no<onal values and 10Y bond equivalent values for Cash, FX and Interest rate products to understand how a bank is turning over the inventory”. This is a very interes<ng metric which every business opera<on monitors to understand the opera<onal efficiency. For instance a Cycle selling firm can look at the ra<on of sold cycles to the exis<ng inventory of cycles to understand how to plan for future periods of opera<on. Now how it can be applied to financial instruments”. To the best of my knowledge and experience, Financial industry is no different when you look at the trading inventory
Inventory Aging (assets) = Sum of value of assets held from the repor<ng date to 30 days look back period. Inventory Aging (Liabili<es) = Sum of value of liabili<es held from the repor<ng date to 30 days look back period.
Product Inventory ( 0-‐31
days) Inventory ( 31-‐60 days)
Inventory ( 61-‐90 days)
Comment
Cash 1000 1500 2000 Inventory is growing over the repor<ng period
FX products 1000,000 1000,000 1000,000 Inventory has neither increased or reduced
Interest Rate Swaps
50,000 60,000 70,000 Inventory Is being increased
Quan<ta<ve Metrics • Metric 7: Customer-‐Facing AcAvity Measurements: For purposes of calcula<ng the Customer-‐Facing Trade Ra<o, a
counterparty is considered to be a customer of the trading desk if the counterparty is a market par<cipant that makes use of the banking en<ty’s market making-‐related services by obtaining such services, responding to quota<ons, or entering into a con<nuing rela<onship with respect to such services. However, a trading desk or other organiza<onal unit of another banking en<ty would not be a client, customer, or counterparty of the trading desk if the other en<ty has trading assets and liabili<es of $50 billion or more unless the trading desk documents how and why a par<cular trading desk or other organiza<onal unit of the en<ty should be treated as a client, customer, or counterparty of the trading desk. Transac<ons conducted anonymously on an exchange or similar trading facility that permits trading on behalf of a broad range of market par<cipants would be considered transac<ons with customers of the trading desk.
• The Customer-‐Facing Trade Ra<o is a ra<o comparing (i) the transac<ons involving a counterparty that is a customer of the trading desk to (ii) the transac<ons involving a counterparty that is not a customer of the trading desk. En<<es should report the following ra<os given a 30 calendar day, 60 calendar day and 90 calendar day horizon.
• A trade count based ra<o must be computed that records the number of transac<ons involving a counterparty that is a customer of the trading desk and the number of transac<ons involving a counterparty that is not a customer of the trading desk.
• A value based ra<o must be computed that records the value of transac<ons involving a counterparty that is a customer of the trading desk and the value of transac<ons involving a counterparty that is not a customer of the trading desk.
“ Volcker Rule enjoins banks to aggregate gross market values, no<onal values and 10Y bond equivalent values for Cash, FX and Interest rate products to understand how a bank is turning over the inventory”.
Quan<ta<ve Metrics Metric -‐7 – Customer facing trade ra<o – Trade Count ra<o. In this bank has to iden<fy the trades by the counterparty type and es<mate the ra<o individually ( rule says to aggregate all the products)
Product TransacAons with customers
TransacAons with Non customers
Customer RaAo Comment
Cash 1000 2000 1000/2000 =0.5 Desk is execu<ng more trades in the interdealer market than with client
FX products 1000,000 100,000 1000,000/100,000 =10 Desk facilitates 10 <mes more trades than on interdealer market
Interest Rate Swaps
50,000 (dv01) 100,000 (dv01) 50,000/100,000 = 0.5 Desk is execu<ng more trades in the interdealer market than with client
Product TransacAons with customers
TransacAons with Non customers
Customer RaAo Comment
Cash 1000 2000 1000/2000 =0.5 Desk is execu<ng more trades in the interdealer market than with client
FX products 1000,000 100,000 1000,000/100,000 =10 Desk facilitates 10 <mes more trades than on interdealer market
Interest Rate Swaps
50,000 100,000 50,000/100,000 = 0.5 Desk is execu<ng more trades in the interdealer market than with client
Metric -‐7 – Customer facing trade ra<o – Value ra<o. In this bank has to iden<fy the trades by the counterparty type and es<mate the ra<o individually by aggrega<ng the value pof the transac<ons ( rule says to aggregate all the products)
Quan<ta<ve Metrics Summary QuanAtaAve Metric Comments VaR and Stressed VaR This metric provides the magnitude of the size of the loss desk might
incur in adverse situa<ons. High VaR/Stressed VaR means not a market making desk.
Risk Factor Sensi<vi<es This metric provides the summary of the risk posi<ons on the trading book. Higher risk factor sensi<vity the desk is not market making desk
Risk and Posi<on Limits Usage Risk limits and associated usage is very high is another indicator of desk being a risk taking unit
Comprehensive P&L AOribu<on PL aOribu<on if shows desk is making more money on the exis<ng posi<ons it might be an indicator of skill of the desk and ac<ve porpolio hedging.
Inventory Turnover inventory ra<os at the product level are less than 1.Then it indicates inventory is being turned over quickly
Inventory Aging Inventory aging profile shows how inventory is being accumulated and exited.
Customer Facing Trade Ra<o This ra<o for each product above 1 suggest the desk is client facing.
RENTD – Reasonably es<mate near term demand • RENTD – Reasonably es<mate near term demand by providing demonstrable evidence and establishing a process to
represent a desk as a market making is most challenging task for a bank.
• In general banks, start accumula<ng posi<ons ahead of market events to facilitate or stand by to take client orders. Now real ques<on is how much of this is considered market making? Are there any limits or methods that could be used for guidance.
• Client demand ebbs and flows in the financial markets in response to variety of events. Some of them will be in an<cipa<on to geopoli<cal events, FOMC events, corporate ac<ons and so on. Some <mes there will be a normal trading ac<vity.
• Banks accumulates set of interest rate swaps ahead of large corporate bond issuance to facilitate corresponding hedging by the clients. Some <me this hedging will get realized and some<mes not.
• So it would be not possible to establish perfect guidelines to client demand. But over a 2y to 3y trading horizon, inventory metrics provide some guidelines of how a desk should posi<on itself to meet the client demand
Inventory Turnover Trade accumulaAon by trading desks typically happens over a period of 1 to 2 months. Therefore over a period of 3 months inventory turnover raAo for each product should be stabilized and brought under 1. This way ending inventory will be less than beginning inventory.
Inventory Aging Inventory aging should have a down trending profile
Customer Facing Trade Ra<o This ra<o should be trending toward 1 or above most of the <me.
Since it is difficult to establish exact levels for near term demand. Trading desks should start thinking of using these inventory metrics to restrain their trading ac<vity
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