# Presentation: 160881

## Is enhanced accounting disclosure associated with less private information trading of bank stocks?

- Rocco Huang
- The World Bank
- Financial Sector Operations and Policy
*Disclaimer:* represent personal views only

## Outline

- Information asymmetry problems of banks
- Opacity creates opportunities for private information production and trading in bank stocks. Transparency helps eliminate them.
- Solutions from the pillars of Basel II: (1) official oversight and (2) information disclosure
- Disclosure-> Transparency? Not a trivial question
- How do we detect private information trading (PIT)?
- How do we quantify disclosure practices?
- Do enhanced disclosures help reduce PIT?
- What are the policy implications?

## Private information trading and information asymmetry

- All firms suffer from information asymmetry, but banks may suffer more
- Focus of this study: Information asymmetry between informed investors and other market participants.
- Informed investors are not necessarily illegal!
*    **Illegally informed:* insiders, connected parties, tippees
-     *Legally informed:*  informed outsiders, e.g. institutional investors, who are better equipped to conduct research and private information production
*But,* opportunities for private information production and trading will be limited,  if a bank is transparent

## Two approaches to address the problem

- Information asymmetry of banks can be resolved by disclosures, as in most industries; but some may need government intervention
- Basel II: official oversights and information disclosure
**Government intervention**
- Supervisors with strong authority can extract better information from banks and then communicate to the public when necessary
- However:
- Supervisors in many countries may be incompetent or even corrupt. Could exacerbate private information trading  by passing info to connected parties
- Strong government interventions can add new source of opacity  to the valuation of bank stocks
- Regulatory changes (merger control) heavily affect bank stock returns in 15 industrialized countries (Carletti, *Ongena and Hartmann*)
- Bank stock prices in the U.S. are more and more driven by industry-wide factors (*Houston and Stiroh*);

## Disclosure -> Transparency?

- Third Pillar of Basel II
- More disclosures should reduce information asymmetry between those with privileged information and outside investors (Healy and Palepu [2001])
*Nevertheless,* for banks, disclosure may not necessarily lead to transparency
- Disclosure _could be less important_ for banks (vs. nonfinancial firms)
- Banks are too opaque, and disclosures do not materially change it (Morgan[2002]).
- Difficult for investors to place information into context that make it meaningful (Greenspan [2003])

## Disclosure -> Transparency? (cont.)

- Are banks special? Are they more opaque? Results are mixed
- Banks may be more opaque because there are no active secondary markets for loans, but it is also true for factories, patents, pharma R&D
- Morgan (2002): rating agencies more likely to disagree on banks than on non-financial firms. Iannotta (2002): this is not the case for European banks
- Flannery et al. (2004): trading properties of bank stocks are not different
- Enhanced accounting disclosure _could be more important_ in assessing valuation of banks:
- Banks own few physical and visible assets. Financial reports provide sole source of information
- Banks can easily inflate earnings by taking more risks.
- Aggregate level numbers are inadequate for value assessment, unless risk profile is comprehensively  disclosed

## An empirical study

- It is important to understand whether enhanced information disclosures, and whether disclosure mechanisms that work in other industries, also works in banking industry
- Study sample: more than 300 banks in 47 countries.
- Restricted to the largest ten banks in each country, more comparable, tend to have more liquid stocks.
- International sample to exploit variations in disclosure practices
- In the US, disclosure practices still differ across banks, but the differences are at more advanced level (because Call Report standardizes many disclosures already), and thus harder to quantify based on a checklist of basic items
- The study exploit: Variation of official supervisory power across countries, and disclosure practices across banks

## How do we measure private information trading?

- Private Information trading indicator: Originally from Llorente et al. (2002), based on price-volume pattern of traded stocks. Attempt to capture actual occurrence of private information trading
- A cheaper measure that can be used in most countries. Less demanding data requirement: Return and volume data only
- Used in many empirical studies: Grishchenkko, Litov and Mei (2003), Durnev and Nain (2004), Bharath et al. (2005), Gagnon and Karolyi (2006)

## An Intuitive Example

- Bottom-line: when we observe such a return-volume pattern, _some sellers on day 1 must know something more and earlier than others_
*James could be “informed” for many reasons.* He doesn’t need to be insiders or tippees (i.e., illegal trading), he could be a more intelligent researcher, he could have more resources to follow the stock
***But,***  _if the Bank discloses a lot of information_, there will be less opportunity for anyone to gather/produce private information or keep private information for too long, i.e., there will be less James

- Investor James somehow  knows that Bank of Universe has high exposure to short-term interest rate; _Other people don’t know_

- Short rate rises, James knows this will negatively impact the Bank’s earnings

_**Day 1:**_ He sells large block of stocks -> **Volume up**, **price down**

_**Day 2:**_ The next day, more people sense it. They also sell, **price drift down further**

**We will observe:**  *(1)* high volume on day 1;  and *(2)* autocorrelation of stock returns between day 1 and day 2

## Estimation of PIT

- C1 reflect unconditional autocorrelation, and thus microstructure effects such as bid-ask bounce and nonsynchronous trading
- C2 indicates whether stocks are dominated by hedging trade or _private information trading_
- Positive coefficient on C2 indicates dominance of private information trading. In 11% of cases, significantly positive at 95% conf. level.
- Most of the bank stocks in our sample are large cap liquid stocks, and thus C2 is less likely to be driven by market liquidity

- The following regression is run _for each bank_

## What could explain the variation of private information trading level across banks? 

- Cross-sectional regressions. PIT is explained by:
- Enhanced accounting disclosures by individual banks (Pillar III)
- Bank Disclosure Index
- Bank supervisory power (Pillar II)
- From Barth et al. database, measures bank supervisors’ power to intervene. Proxied by the quantity of intrusive “weapons” given to supervisors, based on a checklist. Not necessarily quality.
- Other CG  mechanisms
- Intl. credit rating, ADR, Accounting quality (big-five, consolidated, clean opinions), pyramidal ownership structure, government ownership
- Country-specific regulatory and legal factors
- Stringency of insider trading law (does not restrict informed outsiders), stringency of self-dealing laws
- Balance sheet characteristics
- Size, loan-to-asset ratio, loan growth rates, asset (income) diversification

## How to measure information disclosure practices?

- _Disclosure Index_ proposed by Erlend Nier
- Based on inclusions/omissions of a checklist of seventeen accounting items specific to banks
- _Example:_ whether a bank classify loans/deposits by maturity (i.e. interest rate risk), by counterparty, etc
- Each related to one or more dimensions of banks’ risk profile (interest rate risk, credit risk, liquidity risk and market risk) or the capital/reserves the banks hold to back the risk
- The Index only reflect disclosure practices in annual reports, but Lang and Lundholm (1993) and Botosan (1997) show that disclosure level in annual report is highly correlate with other forms of disclosures
- Reverse causality?  Less likely.
- The Disclosure Index measures how the banks choose to organize their reporting, and thus commitment to disclosure. It is a decision by the firm about what it will disclose before it knows the content of the information (ex-ante).
- This is different from selective disclosure (ex-post) of specific piece of information
- Variations on  disclosure index are half cross-country and half within-country

## The effect of enhanced disclosures (pillar III)

- Enhanced disclosure is associated with significantly less private information trading

**Notes:**
Three regimes: low, medium, high. Low: significantly positive. Medium: close to zero.  High:  Negative

## The effect of supervisory power (Pillar II)

- Stronger supervisory authority is associated with higher private information trading. Moving from 25th to 75th is associated with PIT 1 point higher, while the mean of PIT is 0.71
- Hard to argue for causality. Very possible that high PIT of banks prompt government to step up supervisory power

## Closing remarks

- Policy Implications:
- Enhanced disclosures by individual banks can help reduce private information trading
- Information disclosure works better than government intervention in improving information environment
- If there are positive externality of an indiviudal bank’s disclosure, then regulated disclosures may add values
- Limitations:
- PIT is only of the several candidate measure of information asymmetry
- Omitted variable problems
- Large fraction of cross-sectional variations still not accounted for
- Future research directions:
- Bridge the missing link: Disclosure-> Transparency-> Market Discipline (through cost of capital?)
- Focus on several large countries where data are richer to conduct more in-depth analysis
- Identify “shocks”, e.g. disclosure reforms, to study time-series changes (Germany, India, etc)
- Thank you for your attentions!