Jad H Bazih
email: jadbazih@hotmail.com

Dr Dieter Vanwalleghem
email: dieter.vanwalleghem@rennes-sb.com

Deriving Value or Risk? Determinants and impact of emerging market banks' derivative usage

Introduction

Banks play an important role in growth and development but also in the propagation of financial turmoil [START_REF] Instefjord | Risk and hedging: Do credit derivatives increase bank risk?[END_REF][START_REF] Huang | Assessing the systemic risk of a heterogeneous portfolio of banks during the recent financial crisis[END_REF][START_REF] Aoki | Bubbles, banks and financial stability[END_REF][START_REF] Brunnermeier | Banks ' Noninterest Income and Systemic Risk[END_REF]. Financial derivatives are a key tool used by banks to hedge their risk exposures, provide hedging opportunities elsewhere in the economy and generate alternative sources of income; however, financial derivatives also have been responsible for propelling bank risk and failure, such as the increase in both experienced during the 2009 financial crisis [START_REF] Chiaramonte | The determinants of bank CDS spreads: Evidence from the financial crisis[END_REF]. Despite the ramifications of the crisis for global financial markets, global derivative activity largely continued to increase both during and post crisis.

According to data from the Bank of International Settlements (BIS), which surveys the sales derivatives across the globe and in emerging markets. Despite the strong growth of the emerging country derivatives markets, our knowledge of emerging market bank operations in these markets is limited. Although emerging market banks play an important role as dealers, as users and providers of hedging and as speculators, we know little about the determinants behind emerging market bank derivative usage and the implications for banks' value, risk, and stability. Given the increasing integration of emerging market financial institutions in global financial markets, it is important, however, that we increase our understanding of this topic. In this paper, we seek to address this gap in the literature by empirically assessing the determinants and risk, stability and value implications of emerging market bank derivative usage for a unique hand-collected database of emerging market banks. An important factor enabling the growth of derivative usage in emerging markets is financial liberalization. Since the early 1990s, a wave of regulatory reforms has swept through the primarily bank-based financial systems of emerging countries, removing barriers for increased usage of financial derivatives either for hedging bank risk exposures or for speculative/revenue generating purposes. Although removing regulatory restrictions is important for market development, classical finance theory does not necessarily imply that this will lead to an increased usage of derivatives, especially for hedging purposes. According to M&M [START_REF] Modigliani | The Cost of Capital, Corporation Finance and the Theory of Investment[END_REF] under the assumption of perfect capital markets, the value of a firm, including that of a financial institution, is the present value of the cash flows produced by the firms' existing assets and new investments. Cash flow risk is appropriately accounted for through a cost of capital estimate that captures the cash flow stream's inherent systematic risk exposure.

To the extent that investors want different risk exposures, they themselves will readjust their positions and do not need or want companies to spend resources in doing this for them.

Real world capital markets, however, due to frictions, such as agency, bankruptcy, contract, information, and transaction costs as well as commissions and taxes, are far from resembling the M&M ideal type [START_REF] Damodaran | Country Risk and Company Exposure : Theory and Practice[END_REF][START_REF] Crouhy | The Essentials of Risk Management[END_REF][START_REF] Choudhry | Bridging Comparative Politics and Comparative Constitutional Law: Constitutional Design for Divided Societies[END_REF].

Building on this, [START_REF] Stulz | Optimal Hedging Policies[END_REF] developed a model based on exchange rate dynamics, hedging costs and managerial compensation and in which profit-maximizing firms engage in hedging, particularly in forward contracts. [START_REF] Smith | The Determinants of Firms' Hedging Policies[END_REF] show how firms, subject to a convex tax schedule, can reduce fluctuations in pretax income and consequently the overall tax liability by appropriately using hedging derivatives. Corporate risk management can also shield firms from underinvestment problems caused by financial frictions [START_REF] Geczy | Why Firms Use Currency Derivatives[END_REF][START_REF] Bartram | Corporate Risk Management as a Lever for Shareholder Value Creation[END_REF][START_REF] Crouhy | The Essentials of Risk Management[END_REF][START_REF] Aretz | Why hedge ? Rationales for corporate hedging and value implications[END_REF], and hedging can reduce the costs of financial distress, which harms shareholders in the event of bankruptcy and makes bondholders require higher yields [START_REF] Aretz | Why hedge ? Rationales for corporate hedging and value implications[END_REF].

In addition to hedging purposes, bank derivative usage is driven to a great extent by speculative motives and the search for alternative sources of income. Proprietary trading in derivatives is used to generate profits mainly through commissions and fees and without an obvious hedging objective [START_REF] Li | The use of financial derivatives and risks of U.S. bank holding companies[END_REF]. Because of the high potential for fee income generation, banks also offer risk management services, the provision of which has become a growing trend, especially over the last decade, to counter the decline in the spreads of traditional bank lending services [START_REF] Egly | Trading income and bank charter value during the financial crisis : Does derivatives dealer designation matter?[END_REF].

Compared to developed markets, emerging markets, on the one hand, are characterized by higher exchange rates, interest rates, capital flows and growth volatility levels and more severe financial frictions [START_REF] Harvey | Predictable Risk and Return in Emerging Markets[END_REF][START_REF] Henisz | The Hidden Risks in Emerging Markets[END_REF][START_REF] Soedarmono | Bank competition , crisis and risk taking : Evidence from emerging markets in Asia[END_REF]. In addition to the greater opportunities for speculation and alternative income generation, financial liberalization can be expected to create strongly developed derivative markets in emerging countries with high trading volumes. However, foreign exchange and interest rate derivatives in emerging markets account for merely 10% of global derivative market turnover [START_REF] Upper | Emerging derivatives markets[END_REF], and this is primarily due, on the one hand, to a lack of liquidity and know-how and, on the other hand, the absence of a sound financial infrastructure permitting convenient trade through the provision of sufficient legal, counterparty and liquidity risk safeguards.

Derivative market development in emerging countries is facing two main obstacles. First, to hedge a risk exposure, counterparties need to be present to take the opposite side of the contract. Emerging markets often suffer from a dearth of speculators willing to take on interest and exchange rate risk in highly volatile markets, which often suffer from substantial political instability [START_REF] Upper | Emerging derivatives markets[END_REF]. Second, emerging derivatives markets are not only smaller but also trade fewer complex contracts than their counterparts in developed countries. This is likely due to the absence of the necessary know-how and expertise in emerging market financial institutions but also implies that available derivatives contracts may not be effective in hedging all corporate and financial risk exposures.

The potential for growth in emerging derivative markets is substantial, however, and could be realized if effective measures are put in place to better deal with counterparty, operational, and legal risks. Counterparty risk mitigation can be achieved through improved netting and collateralization of counterparty risk exposures and can lead to a reduction in regulatory capital requirements by almost 70% [START_REF] Avellaneda | The Global Derivatives Market An Introduction[END_REF]. Central clearing parties or clearing houses can further help to reduce counterparty risk, but most are currently in developed countries, with few operating in emerging markets [START_REF] Sukumar | The Future of Clearing[END_REF]. Operational risk (e.g., fraud, systems failure and technological malfunctions) is generally known to be higher in emerging market contexts [START_REF] Ray | Distribution of cost and profit efficiency : Evidence from Indian banking[END_REF][START_REF] Smimou | International portfolio choice and political instability risk : A multi-objective approach[END_REF]. This risk could be mitigated, however, in emerging derivatives markets by automating trading with exchanges and clearing houses, but such automated trading systems are currently largely absent in emerging markets. Finally, legal risk is a major issue in emerging markets, in which the rule of law, governance and institutional environment is weaker than in developed markets [START_REF] Chen | Legal protection of investors , corporate governance , and the cost of equity capital[END_REF]. Legal risk in emerging derivatives markets could be reduced by increasing contract and netting agreement standardization, a practice that is widely used in developed markets in which derivatives trading occurs more through organized electronic exchanges and less over the counter.

We conduct an empirical analysis by using random and fixed panel regression models to investigate the relationship between financial derivatives, on the one hand, and bank risk, stability, and value, on the other hand, in an emerging market context. In addition, we investigate the determinants of derivative usage by emerging country banks. Numerous studies have examined the relationships between financial derivatives and bank risk, stability, and value for developed market banks [START_REF] Li | The use of financial derivatives and risks of U.S. bank holding companies[END_REF][START_REF] Mayordomo | Derivatives holdings and systemic risk in the U.S. banking sector[END_REF][START_REF] Bliss | Bank risk, financial stress, and bank derivative use[END_REF][START_REF] Chang | Derivatives usage for banking industry : evidence from the European markets[END_REF], but few studies have been dedicated to analyzing these relationships in emerging market banks (Keffala, De Peretti andChan, 2011, 2013;[START_REF] Keffala | How using derivatives affects bank stability in emerging countries? Evidence from the recent financial crisis[END_REF][START_REF] Titova | The impact of hedging and trading derivatives on value, performance and risk of European banks[END_REF]. To further our understanding of emerging market bank derivative usage, we analyze a unique dataset by hand collecting derivative data from the financial statements of listed banks and classifying derivatives according to their main purpose, namely, hedging or speculation. In the context of emerging markets, to estimate the effect of derivative usage on bank stability, risk, and bank value, we match this information with data on bank-and country-specific variables. We control for country-specific variations, including the World Governance Indicators (WGI), bank competition, the World Uncertainty Index (WUI), and financial openness indicators.

In terms of key findings, in line with other research [START_REF] Chang | Derivatives usage for banking industry : evidence from the European markets[END_REF], we first find that the net interest margin, bank concentration and the strength of the institutional environment are major determinants of derivative usage in emerging markets. Second, we find evidence of a significant negative relationship between derivative usage and bank value as measured by Tobin's Q. Third, our panel analysis indicates that higher derivative usage contributes positively and significantly to bank systematic risk but does not contribute significantly to total volatility or idiosyncratic risk. These results are in line with Chang, Ho and Hsiao's (2017) findings regarding systematic risk but are different from their findings for bank value and total risk2 . Finally, we find that derivative usage by emerging market banks reduces their instability as measured by the Z-score.

The paper contributes to the literature on different levels. First, our unique, hand-collected dataset allows us to add to the derivative usage literature by exploring the determinants of bank derivate usage and the effects of this usage on bank risk and value for a wide sample of emerging market banks, a topic that until now has remained unexamined in the literature. Prior research was conducted mainly on U.S. banks or European markets and to our knowledge, our dataset has a much wider emerging market bank coverage than previous studies. Second, this is the first paper that investigates the effects of derivative usage on both value, risk and stability measures for a large sample of emerging market banks in the post-financial crisis era. Finally, for emerging market bank derivative usage, we highlight the importance of the institutional environment, a dimension left largely unexplored in previous research.

The remainder of this paper is organized as follows. Section 2 highlights the literature review, and Section 3 describes the data and methodology. Section 4 analyzes the regression models and discusses the results. Finally, Section 5 concludes the paper.

Literature Review

The literature to date on the determinants and implications for bank derivatives usage is limited, especially for emerging market contexts. First, a few existing studies examine the insolvency risk as measured by the Z-score but that this effect disappears for the post-crisis era.

One of the only studies that focuses exclusively on emerging market banks is [START_REF] Keffala | How using derivatives affects bank stability in emerging countries? Evidence from the recent financial crisis[END_REF], in which the author compares the effect of derivatives on bank stability in the pre-and post-financial crisis eras. Derivatives are classified by contract type3 , and bank stability is captured by the Z-score. The sample includes 66 banks from 24 emerging market countries over the time frames 2003-2006 and 2007-2011. The results show that futures and options weaken bank stability, while forwards and swaps have a minimal effect.

The remaining literature on derivative usage in emerging market contexts predominantly covers non-financial firms. For instance, [START_REF] Trang | Multinationals and the impact of corruption on financial derivatives use and firm value : Evidence from East Asia[END_REF] examine the effect of corruption on derivative usage. For a sample of 881 non-financial firms in East Asia, they conclude that low levels of corruption increase the usage of derivatives. Corruption is one factor that can lead to a difference in the effect and usage of derivatives in emerging versus developed countries, but the literature is divided on the direction of its impact. Some papers argue that corruption increases uncertainty and transaction costs, disrupts a firm's operations [START_REF] Quazi | Corruption and Foreign Direct Investment in East Asia and South Asia : An Econometric Study[END_REF] and therefore disincentivizes banks from investing in a large-scale derivatives infrastructure. On the other hand, corruption can act as a "helping hand" in weak regulatory environments and facilitate economic counterparty selection and screening [START_REF] Bardhan | Corruption and Development : A Review of Issues[END_REF].

Furthermore, for a sample of large Columbian non-financial firms, Gómez-González, Rincón and Rodríguez (2014) find that the use of hedging derivatives is positively related to value as measured by Tobin's Q.

Finally, although not exclusively focusing on emerging countries, a couple of studies have focused on the moderating impact of corporate governance on the relationship between derivative usage and value. To the extent that emerging market economies are predominantly characterized by weaker levels of corporate governance, these studies therefore may shed some light on what to expect for our emerging market bank sample. For a sample of US firms, [START_REF] Fauver | Derivative usage and firm value : The influence of agency costs and monitoring problems[END_REF] find that firms with weaker governance exhibit a negative relation between Tobin's Q and derivative usage. Firms that use derivatives and have higher agency costs and supervisory problems are claimed to channel these costs by virtue of excessive speculation with and mismanagement of derivative securities. Finally, for a sample of nonfinancial firms in 39 countries, [START_REF] Allayannis | The use of foreign currency derivatives , corporate governance , and firm value around the world[END_REF] find that strong corporate governance or strong country-level institutional environments strengthen the positive value impact of foreign currency derivatives.

Overall, our literature review indicates that there is scant research on the determinants and implications of derivative usage by emerging market banks. Part of the reason is undoubtedly the limited accessibility of data, and we address this limitation by hand collecting derivative data from the financial statements of a broad sample of emerging market financial institutions.

Nevertheless, gaining a better understanding of derivative usage in emerging markets is important for at least several reasons. First, the use of financial derivatives may amplify the negative effects of financial liberalization reforms put in place in several emerging markets in recent years. According to [START_REF] Soedarmono | Bank competition , crisis and risk taking : Evidence from emerging markets in Asia[END_REF], financial liberalization increases competition in the banking sector, resulting in lower capital ratios, increased volatility and a higher insolvency risk in banks. The use of financial derivatives can amplify the negative effects of competition and contribute to higher bank risk and instability [START_REF] Mcclintock | International financial instability and the financial derivatives market[END_REF][START_REF] Elyasiani | Derivative Exposure and the Interest Rate and Exchange Rate Risks of U.S. Banks[END_REF]Hirtle, 1997[START_REF] Hirtle | Credit derivatives and bank credit supply[END_REF][START_REF] Instefjord | Risk and hedging: Do credit derivatives increase bank risk?[END_REF][START_REF] Minton | How Much Do Banks Use Credit Derivatives to Hedge Loans?[END_REF][START_REF] Dewally | Financial derivatives, opacity, and crash risk: Evidence from large US banks[END_REF][START_REF] Chang | Derivatives usage for banking industry : evidence from the European markets[END_REF]. Second, the risk shifting mechanisms enabled by financial derivatives contribute to bank instability in the presence of high corporate vulnerability [START_REF] Stiglitz | Credit Rationing in Markets with Imperfect Information[END_REF]. This "vulnerability" is especially prominent in the emerging countries' private sector, which suffers from poor accounting standards, weak corporate governance, high levels of corruption and weak protection for shareholders. Finally, the emerging market banks, which are comparatively smaller than their counterparts in developed countries, may lack experience and capital to efficiently manage risk through innovative instruments such as derivatives. In particular, [START_REF] Tufano | FINANCIAL INNOVATION AND FIRST-IMOVER ADVANTAGES[END_REF] points to the first-mover advantage in investment banking and highlights the higher costs associated with developing new product and service offerings. Additionally, as appealing as financial derivatives may seem for banks, the dealing and trading of derivatives requires substantial investment in financial, reputational and intellectual capital [START_REF] Sinkey | Evidence on the financial characteristics of banks that do and do not use derivatives[END_REF]. Building these key resources, however, takes time, and emerging market banks relatively new to derivative usage might not be capable of dealing effectively and efficiently with derivative securities for hedging or speculative purposes.

Data and Method

Data source

Our sample covers publicly listed 4 emerging market commercial banks for the period 2010 to 2017. To identify emerging markets, we first use the Morgan Stanley MSCI emerging market index, which classifies 54 countries as emerging. The disclosure of information by banks on financial derivative usage is voluntary; however, when disclosing, most banks explain their derivative usage and report the notional and/or fair values in the notes on financial statements of their annual reports. However, as stated by [START_REF] Acharya | Counterparty risk externality: Centralized versus over-thecounter markets[END_REF], the lack of common standards on derivative reporting limits the ability to use derivative data in research. In response to this and to ensure derivatives reporting is as consistent as possible across countries and banks, we sample banks exclusively from countries adopting IFRS accounting standards. because our sample finishes in 2017, this change has no impact on our sample. After excluding countries that do not adopt IFRS accounting standards6 and others with underdeveloped banking sectors with no listed banks, our final sample includes banks from 24 emerging market countries7 .

For these 24 countries, we initially identified 435 listed financial firms, but after the exclusion of non-commercial banks, Islamic banks8 , subsidiaries and banks that do not report on financial derivative usage in their financial statements, we are left with 115 entities. We further need to discard 10 banks with unclear information on financial derivatives9 and achieve a final sample of 105 listed domestic banks over the time period 2010-2017. Where available, data from unconsolidated statements is used to avoid double counting. Financial statement data on derivative usage are then matched with bank-and country-level data from Bloomberg, the World Bank and DataStream.

The number of banks in our sample is limited primarily due to lack of data availability, as IFRS standards do not oblige banks to report on financial derivative usage. Nevertheless, overall, our sample size is consistent with samples used in relevant emerging market literature. Table 1 below gives an overview of the countries represented in our sample and the number of banks per country. Hungary ( 1)

Croatia (2)
Russia ( 4) Bahrain ( 2) Qatar ( 5) Jordan ( 7) Turkey ( 10) Kuwait ( 5)

Lebanon ( 3) UAE ( 7) KSA ( 8)

Oman ( 5) SA ( 6)

Nigeria (3)
Togo ( 1)

Georgia (1)
Kazakhstan ( 2)

Pakistan (6)
Sri Lanka ( 4) Malaysia ( 7)

Philippines ( 4)

Argentina (2)
Brazil ( 5)

Chile (3)

Model specification

The regression models explain the main research questions: (a) the determinants of derivative usage in emerging markets, (b) the effects of financial derivatives on bank risk, value and stability, and (c) the effect of derivative usage on systematic risk.

Variable Specifications

Derivatives (DER)

Financial derivatives can be measured by their notional amounts, which reflect the value of the underlying assets, or by their fair value. According to the Office of the Comptroller of the Currency's (OCC) Quarterly Reports on Bank Trading and Derivatives Activities, notional amounts of derivatives provide insight into the productivity and operational issues of banks.

Thus, we follow the literature and use the notional amount to assess bank performance and profitability [START_REF] Bliss | Bank risk, financial stress, and bank derivative use[END_REF][START_REF] Chang | Derivatives usage for banking industry : evidence from the European markets[END_REF][START_REF] Titova | The impact of hedging and trading derivatives on value, performance and risk of European banks[END_REF]. The data on financial derivatives are collected manually from the financial statements of the banks in our sample, and apart from collecting total derivative usage data, we further distinguish between the subcategories of trading and hedging derivatives.

Derivatives were originally reported in local currencies, so we need to convert the values into millions of USD for consistency across countries and to match our control variables 10 .

Bank Risk and stability

To measure bank risk, consistent with [START_REF] Brewer | Alligators in the Swamp : The Impact of Derivatives on the Financial Performance of Depository Institutions[END_REF], [START_REF] Bartram | The effects of derivatives on firm risk and value[END_REF] and [START_REF] Chang | Derivatives usage for banking industry : evidence from the European markets[END_REF], we use the standard deviation of weekly stock returns (σ return). We follow the literature in assuming that net risk exposure can be estimated by using bank stock price volatility. The data on the weekly stock price for banks were collected from Bloomberg.

Furthermore, in addition to its impact on overall volatility, we also evaluate the effect of derivative usage on bank stability or insolvency risk. As a proxy of bank insolvency, we use the Z-score [START_REF] Laeven | Bank governance, regulation and risk taking[END_REF][START_REF] Duran | Off-balance-sheet activity under adverse selection : The European experience[END_REF][START_REF] Ashraf | Effects of National Culture on Bank Risk-taking Behavior[END_REF][START_REF] Ashraf | Capital regulation , deposit insurance and bank risk : International evidence from normal and crisis periods[END_REF]. Based on accounting data, this indicator is calculated as follows:

= , , , ,
, where ROAi,t and , denote the return on assets and its standard deviation, respectively, for Bank i at time t and E and TA denote the total equity and total assets, respectively, for bank i at time t. Moreover, we use the natural logarithm of the Zscore to reduce skewness [START_REF] Ahamed | Does regulatory forbearance matter for bank stability ? Evidence from creditors ' perspective[END_REF][START_REF] Albaity | Competition and bank stability in the MENA region : The moderating e ff ect of Islamic versus conventional banks[END_REF]. The Zscore is an inverse measure of insolvency risk, and a higher Zscore value indicates higher bank stability and lower insolvency risk.

Bank Value (TOB_Q)

As a proxy for bank value, we follow Jin and Jorion ( 2006), [START_REF] Laeven | Is there a diversification discount in financial conglomerates?[END_REF], and

Gómez-González and Rincón and Rodríguez (2014) and use Tobin's Q, which is calculated as the sum of the market value of common equity, the book value of preferred shares and the book value of total debt all divided by the book value of total assets.

Independent Variables

To estimate our regressions, we identify several major accounting variables from the literature.

We use total return on equity (ROE) as a proxy of bank profitability. Profitable banks are more resilient to financial shocks and far from distress; they thus are more comfortable in dealing with trading derivatives without considering them threatening [START_REF] Mahieu | Hedging with Interest Rate and Credit Derivatives by Banks[END_REF]. We also observe the impact of the net interest rate margin (NIM), which is calculated as a ratio of net interest income and total assets. Banks with a lower net interest margin may engage more in financial derivatives to increase their income and achieve higher stability; on the other hand, banks with a higher net interest margin may engage in financial derivatives to "lock-in" their profits and secure their "spreads" [START_REF] Sinkey | Evidence on the financial characteristics of banks that do and do not use derivatives[END_REF]. Furthermore, we observe the effect of the flow of deposits (DEP_ASSETS), calculated as the ratio of deposits to total assets. This flow acts as a natural hedge against liquidity risks [START_REF] Chang | Derivatives usage for banking industry : evidence from the European markets[END_REF] and encourages banks to engage more in speculative behavior such as derivative trading [START_REF] Minton | How Much Do Banks Use Credit Derivatives to Hedge Loans?[END_REF]. Another variable that may affect financial derivatives usage is bank capital (EQRAT), calculated as a ratio of equity capital to total assets [START_REF] Minton | How Much Do Banks Use Credit Derivatives to Hedge Loans?[END_REF]. Banks with more capital are better able to deal with the drawbacks of derivative usage and are able to invest more in such assets. Another variable is bank size (LNTASS), calculated as the natural logarithm of total assets [START_REF] Sinkey | Evidence on the financial characteristics of banks that do and do not use derivatives[END_REF]. Bank size may correlate with the banks' ability and know-how to deal with financial derivatives. Due to a "too big to fail" moral hazard problem, larger banks may also be inclined to engage more in risky behavior through derivatives trading [START_REF] Ashraf | Political institutions and bank risk-taking behavior[END_REF]. We also consider commercial loans (CCLOANS) scaled by total assets. As pointed out by [START_REF] Hirtle | Credit derivatives and bank credit supply[END_REF], banks that are more exposed to credit risk through loans are more inclined to engage in financial derivatives to hedge such risks. Dividends (DIV) have an effect on derivative usage, and this variable is calculated as the ratio of dividend payout to total assets. In times of distress, banks can reduce dividend payments as an alternative to engaging in risky assets, such as financial derivatives. To control for cross-country differences in financial openness, we use the variable (KAOPEN)11 developed by [START_REF] Chinn | A New Measure of Financial Openness[END_REF]. This variable, which is based on the IMF's Annual Report on Exchange

Arrangements and Exchange Restrictions (AREAER), captures the extent of financial liberalization through cross-border financial transactions. To capture the effect of competition, we use the three-bank concentration ratio (CNTRN) from the Financial Development and Structure Database maintained by [START_REF] Cihak | Benchmarking Financial Systems around the World[END_REF]. This variable is calculated as the ratio of the assets of the three largest banks in a country as a share of the assets of all commercial banks. We use this variable as a proxy for competition in the banking sector, in which banks in a highly competitive environment may engage more in financial derivatives to gain an edge over competitors and increase their profit. We also control for the strength of the institutional environment (WGI_AVR) by using an average of the World Government Indicators from the World Bank database. As the six indicators are highly correlated, we consider the average as a proxy of institutional strength. Furthermore, we use the World Uncertainty Index (WUI)12 as a proxy of political and economic uncertainty. "Uncertainty" affects the pricing of financial derivatives [START_REF] Pan | The effect of economic and political uncertainty on sovereign CDS spreads[END_REF] in addition to the trading volume and bank liquidity [START_REF] Berger | Economic Policy Uncertainty and Bank Liquidity Hoarding[END_REF]. Finally, we control for the annual rate of inflation, as the literature argues that through excessive competition, high inflation can affect bank behavior [START_REF] Kasman | Cost and profit efficiencies in transition banking : the case of new EU members[END_REF] and can affect bank margins and overhead costs (Demirgüç-Kunt and Detragiache, 2005). Finally, EXCH_VOL is the exchange rate volatility of the local currency in a certain country per year and is calculated from the average monthly exchange rates as reported by the World Bank. Higher volatility can affect derivative usage and can especially impact the volume and price of foreign exchange derivatives used to hedge exchange rate risk.13

Econometric Models

Determinants of derivative usage

To establish the main determinants of bank derivative usage, we use a panel data regression model. This will allow us to test whether several factors known to drive derivative usage in developed markets drive emerging market derivative usage. We estimate our regression by using a random effects model, as pointed out by the results of the Hausmann test. We use bank clustered random errors and control for both bank-specific and country-level variables, as shown in Equation 1: (1)

DERit = α0 +
DER represents the dependent variable for derivative usage: the total, trading or hedging derivatives measured in notional amounts.

Effects of derivative usage on bank risk and bank value

To capture the effect of financial derivatives on bank total risk and bank value, as implied by the Hausman test, we estimate the following panel regressions by using a fixed effect panel regression model. This model usage also controls for the problem of endogeneity that can occur because of unobserved variations. We also control for time by using year dummies, and we correct for heteroscedasticity by using bank clustered standard errors. (3)

Riski,t = Ɣ0 + Ɣ1

In this study, Riski,t represents the risk measures, which are the bank stock price volatility of weekly returns and the Zscore.

Effect of derivative usage on systematic and idiosyncratic risk

In addition to testing the relationship between derivative usage and total bank volatility, we test whether and how derivatives for trading and hedging purposes might affect bank systematic risk and bank idiosyncratic risk, respectively. Following [START_REF] Elyasiani | Derivative Exposure and the Interest Rate and Exchange Rate Risks of U.S. Banks[END_REF], [START_REF] Shyu | The determinants of derivative use by U.S. and foreign banks[END_REF]

Summary Statistics

Table 2 presents the descriptive statistics of the variables used in the study. All variables are winsorized at the 1 and 99% levels to reduce the effect of outliers. Hedging derivatives represent 10% of the total derivatives in the data collected, and this percentage is consistent with the findings of [START_REF] Upper | Emerging derivatives markets[END_REF], in which total derivatives are dominated by trading derivatives.

Correlation Matrix

Regression results and discussion

Determinants of Derivative Usage

In Table 4, we present the results of the random effects panel regression model and obtain several important findings. First, in models 1 and 2, the coefficient of net interest margin (NIM) is significant and negative, a result in line with previous findings in the literature [START_REF] Chang | Derivatives usage for banking industry : evidence from the European markets[END_REF]. This finding suggests that banks with a lower NIM will engage more in derivatives, especially trading derivatives, to increase their profits and protect their net interest income15 [START_REF] Sinkey | Evidence on the financial characteristics of banks that do and do not use derivatives[END_REF]. Second, the ratio of total loans to assets is significant and positive in models 1 and 3. This finding is consistent with the assumption that banks with proportionally larger lending activities may use more hedging derivatives to manage their lending activityrelated exposures. Banks may, for instance, actively hedge to limit potential distress costs and reduce balance sheet rigidity. These results are consistent with the findings of [START_REF] Brewer | Interest-rate derivatives and bank lending[END_REF]. Third, the coefficient for total assets is significant in model 3, indicating that larger banks use more derivatives for hedging purposes. This finding supports the argument in the literature that there are non-negligible set-up and operating costs associated with active derivative usage [START_REF] Sinkey | Evidence on the financial characteristics of banks that do and do not use derivatives[END_REF][START_REF] Chang | Derivatives usage for banking industry : evidence from the European markets[END_REF] and that larger banks are more willing to accept these costs. Larger banks also likely possess more "in-house" expertise and resources to hedge various portfolio risk exposures on a continuous basis. Fourth, the coefficient for bank concentration is significant and negative in models 1 and 2, which indicates that banks in more competitive environments, i.e., with lower bank concentration, engage more in trading financial derivatives to gain a competitive advantage and increase their profitability over competitors. Fifth, institutional strength is significant and positive in models 1 and 2; this finding indicates a tendency of banks in stronger institutional environments to engage more in financial derivatives mainly through trading. This is consistent with the findings of [START_REF] Bartram | The effects of derivatives on firm risk and value[END_REF] that banks in more developed countries use more financial derivatives and in line with the arguments made above that the quality of the market infrastructure will drive to a substantial extent the banks' participation in derivate markets .

Along similar lines, we also find that higher levels of country-level uncertainty significantly reduce bank derivative usage. Higher political and economic uncertainty is not conducive to a market environment supporting the infrastructure for derivatives trading. Note that despite what might have been expected, exchange rate volatility does not increase the banks' usage of derivatives for hedging or trading. This is in line with the findings of Au Yong, [START_REF] Au Yong | Derivative activities and Asia-Pacific banks' interest rate and exchange rate exposures[END_REF], who in a sample of 110 Asia-Pacific banks ,find no significant association between exchange rate exposure and derivative usage.

In addition to being statistically significant, our results also have an important and economically meaningful impact on bank derivative usage. In our sample, the average ratio of derivatives to total assets is approximately 0.54 (table 2), indicating that on average, banks use derivatives in an amount equal to approximately half the value of their total assets. If we now increase a bank's net interest margin (NIM) by one standard deviation, then our results indicate that the ratio of total derivatives to total assets drops by approximately 7 percentage points to 0.47 16 , a substantial reduction. Along the same lines, we find that the institutional environment is potentially of even greater importance. A one standard deviation increase in the World Uncertainty Index (WUI) results in a 4 percentage point drop in the ratio of total derivatives to total assets, while a one standard deviation increase in the World Governance Index results in a 15 percentage point increase. This causes a large difference in the derivative usage of banks in stronger versus weaker institutional environments. 4 reports the results of Equation .(1) estimated by using a random effects panel regression model. The models are estimated by using bank clustered standard errors. We report the coefficients, with the standard errors shown between the parentheses. The dependent variable in model 1 is total derivative usage, in model 2, the dependent variable is denoted by trading derivatives, and in model 3, the dependent variable is denoted by hedging derivatives. Multicollinearity is tested by using the variance inflation test and yields very low values. To test for autocorrelation, we perform Wooldridge's test, which does not detect any autocorrelation. As a robustness check, we replace ROA with ROE (return on equity), which yields the same results. We also report the number of observations and the R-square for each model. See the "Appendix" for a detailed definition of the variables. ***, **, * denote statistical significance at the 1%, 5% and 10% levels, respectively.

Derivative usage, Bank Risk and Bank Value

Table 5 presents the effect of financial derivative usage on bank risk and bank value. We estimate equations 2 and 3 by using a fixed effects model, as implied by the Hausman test. In models 1, 2 and 3, the dependent variable is Tobin's Q, a standard proxy for bank value.

Interestingly, contrary to the findings of [START_REF] Chang | Derivatives usage for banking industry : evidence from the European markets[END_REF] for developed markets, we find a significant negative relation between derivative usage and bank value in emerging markets. This finding suggests that derivative usage in emerging markets decreases bank value, and the results support the strand of literature that points to the contribution of derivatives to a loss in bank value and the relation of derivative usage to financial turmoil [START_REF] Jorion | Firm Value and Hedging: Evidence from U.S. Oil and Gas Producers[END_REF][START_REF] Acharya | Causes of the Financial Crisis[END_REF][START_REF] Greenberger | The Role of Derivatives in the Financial Crisis[END_REF][START_REF] Khediri | Do investors really value derivatives use ? Empirical evidence from France[END_REF]. In addition to severe financial friction and information asymmetry, the high-risk environment in emerging markets (higher operational, documentation, contract risks, etc.) and the absence of a well-developed financial infrastructure may all contribute to the inability of emerging market banks to use derivatives efficiently to increase value. In contrast, increased derivative usage by emerging market banks seems to reduce the banks' value.

In models 4, 5 and 6 of table 5, we investigate the impact of derivative usage on total risk measured by the standard deviation of weekly stock returns expressed in the local currency [START_REF] Brewer | Alligators in the Swamp : The Impact of Derivatives on the Financial Performance of Depository Institutions[END_REF]. Since the financial crisis in 2008, derivative activity has become controversial. The literature on the effect on bank risk is divided: one strand finds a significant positive effect of derivative usage on bank risk [START_REF] Hassan | Deposit insurance , market discipline and off-balance sheet banking risk of large U .S. commercial banks[END_REF][START_REF] Chang | Derivatives usage for banking industry : evidence from the European markets[END_REF], while another does not [START_REF] Venkatachalam | Value-relevance of banks' derivatives disclosures[END_REF]Hirtle, 1997;[START_REF] Peek | Derivatives Activity at Troubled Banks[END_REF]. In this study, we find no evidence of a relationship between derivative usage and total bank risk. Our results are in line with the findings of Cyree, [START_REF] Cyree | The Economic Consequences of Banks' Derivatives Use in Good Times and Bad Times[END_REF], who find no compelling evidence that banks' derivative usage contributes to higher risk. This could be attributed to the relatively lower volume of derivatives traded in emerging markets but also to their simpler structure compared to that of the complex derivatives used in developed markets [START_REF] Upper | Emerging derivatives markets[END_REF]. However, even though derivative usage does not appear to contribute to total risk or volatility, this does not imply that there could not be independent and perhaps counteracting effects on total risk's two subcomponents, namely, systematic risk and idiosyncratic risk. In the next section, we decompose total risk into systematic and idiosyncratic risk and investigate this possibility. Table 5 reports the results of the fixed effects regression in which the year dummies and the robust standard errors are estimated by using bank clustering. We report the coefficients, and the robust standard errors are in parentheses. The dependent variables in Models 1, 2 and 3 (4, 5 and 6) are Tobin's Q (stock return volatility). All variables are calculated based on millions of USD and by using the BIS yearly rate of exchange. The derivatives are scaled by total assets, and to deal with outliers, all variables are winsorized to the 1 and 99 th percentiles. TOT_DER, TRD_DER and HDG_DER denote total, trading and hedging derivatives, respectively. See the "Appendix" for a detailed variable description.

***, **,* denote statistical significance at the 1%, 5%, and 10% levels, respectively

Derivative Usage and Systematic and Idiosyncratic Risk

Table 5 pointed out that derivative usage did not impact total bank volatility, but it is still possible that there is an impact on its two subcomponents, namely, systematic market risk and idiosyncratic risk. The results in table 6 indicate that this is indeed the case. Bank usage of trading derivatives increases systematic risk but not idiosyncratic risk. It therefore appears that banks take speculative positions that amplify systematic risk factors, and this result is consistent with the findings of [START_REF] Chang | Derivatives usage for banking industry : evidence from the European markets[END_REF]. Hedging derivatives, on the other hand, neither affect systematic nor idiosyncratic risk in a systematic way. Note, however, that although trading derivatives do not affect idiosyncratic risk in a significant way, the coefficient is negative and thus appears to cancel out the positive impact of trading derivatives on systematic risk, leaving total risk or volatility unchanged. Finally, although stock volatility is a key indicator of bank risk and uncertainty, it is not the only indicator. Next, we explore the impact of derivative usage on bank stability or the risk of bank failure. Bank stability in the literature is traditionally captured by the Z-score, and previous studies, such as [START_REF] Ghosh | How do derivative securities affect bank risk and profitability?: Evidence from the US commercial banking industry[END_REF], that examine the effect of derivative usage on the Z-score, find that aggregate derivatives reduce a bank's insolvency risk. In addition, [START_REF] Elyasiani | Derivative Exposure and the Interest Rate and Exchange Rate Risks of U.S. Banks[END_REF], for a sample of 59 banks in the period spanning 1975-1992, find that different derivative contracts may reduce bank instability. [START_REF] Keffala | How using derivatives affects bank stability in emerging countries? Evidence from the recent financial crisis[END_REF], one of the few papers examining derivative usage in emerging markets, found that unlike forwards and swaps, which do not affect bank stability, options and futures decrease bank stability. On the other hand, Hirtle (1997) find that bank instability is amplified by derivatives. Our findings in table 7 are in line with [START_REF] Ghosh | How do derivative securities affect bank risk and profitability?: Evidence from the US commercial banking industry[END_REF], who also pointed to a positive significant relationship between derivative usage and bank stability as proxied by the Z-score17 . This relationship is more significant for hedging derivatives, which seem to be used more efficiently in emerging markets to promote bank stability. 7 reports the results of the fixed effects regression of derivative usage on the Zscore, with year dummies and robust standard errors estimated by using bank clustering. We report the coefficients, and the robust standard errors are in parentheses. The dependent variable in Models 1, 2 and 3 is the natural logarithm of the Zscore. See the "Appendix" for a detailed variable description. ***, **,* denotes statistical significance at the 1%, 5%, and 10% levels, respectively

Conclusion

In this paper, we examine the determinants of emerging market banks' derivative usage and the effect of derivatives on total bank risk, bank value, systematic risk, and bank stability. We find that for total and trading derivatives, an important bank-level stimulant of derivative usage is the net interest margin and that for hedging derivatives, an important bank-level stimulant is the amount of total assets and loans. Country-level determinants include higher competition, a stronger institutional environment and "uncertainty", as presented by the World Uncertainty Index. We also find that derivative usage undermines bank value for our sample of emerging market banks. Given the presence of factors, such as higher financial friction in emerging markets, higher information asymmetry and weaker institutional environments, that contribute to operational risk, unlike financial derivatives in developed countries, financial derivatives in emerging countries are not value adding but are rather value undermining. Moreover, our findings regarding the positive effect of derivative usage on systematic risk are in line with those of [START_REF] Chang | Derivatives usage for banking industry : evidence from the European markets[END_REF], but unlike them, we do not find a significant effect on bank total risk. Nevertheless, it seems that banks in our sample use derivatives, especially hedging derivatives, in an efficient way that promotes stability and decreases insolvency risk. Overall, for policy makers and investors, the paper has important implications regarding the assessment of banks' value, risk, and stability. Following the recent financial crisis, a debate has been ongoing regarding the impact of derivatives on bank value and stability. In the extant literature, this paper helps fill the gap regarding our understanding of the effects of derivative usage on banks in emerging markets. The research in emerging market contexts is often hindered by the lower reliability of data sources and the outright unavailability of data on certain dimensions.

One of the current paper's limitations, which is a shortcoming also common in the emerging market literature, is the relatively small sample size on which we work. Because our sample covers banks from a wide variety of emerging market countries, however, our results nevertheless yield important insights for market practitioners and policy makers. Future research could investigate in more detail the impact of bank-level and country-level institutional variables on derivative usage and derivative impact. In particular, it would be interesting to link the impact of derivative usage to different dimensions of bank-level governance to discern, for instance, whether the positive impact of derivative usage on bank

Fig 1 .

 1 Fig 1. OTC interest rate derivatives average daily turnover EM vs. DEV on a "net-gross" basis. Daily averages, in billions of US dollars (BIS Triennial Survey 2019)

  Fig 2. OTC foreign exchange derivatives average daily turnover EM vs. DEV: "net-gross" basis. In Billions of US dollars (BIS Triennial Survey 2019)

Figure 3

 3 Figure 3 below gives an overview of the countries adopting IFRS standards: the countries

Figure 3 .

 3 Figure 3. IFRS adopting countries (Dark Gray) vs. non IFRS adopting countries (Light Gray)

Table 1 .

 1 Number of banks (between parenthesis) by country and region

	Europe	Middle East	Africa	Asia	Latin America
	Poland (7)

  , Au Yong,[START_REF] Au Yong | Derivative activities and Asia-Pacific banks' interest rate and exchange rate exposures[END_REF] and[START_REF] Chang | Derivatives usage for banking industry : evidence from the European markets[END_REF], Systematic risk is then captured by the coefficient on the appropriate market index, , and idiosyncratic risk is the standard deviation of the residual, . We use the same regression specification as before to determine the relationship between derivatives and systematic and idiosyncratic risk. The Hausman test again indicates the use of a fixed effects model, and we again use standard errors clustered at the bank level.

	we estimate systematic and idiosyncratic risk for a given bank and year by applying a simple
	market model to stock returns:
	= +	+
	= Ƞ0 + Ƞ1 DERit + Ƞ2 ROEit + Ƞ3 NIMit + Ƞ4 DEP_ASSETSit + Ƞ5 EQRATit + Ƞ6 LNTASSit + Ƞ7
	CCLOANit + Ƞ8 DIVit + Ƞ9 KAOPEN it + Ƞ 10 CNTRN it + Ƞ11 WGI_AVRit + Ƞ12 WUIit + Ƞ13 INFit + vit +
	Eit. (4)
	= Ƞ0 + Ƞ1 DERit + Ƞ2 ROEit + Ƞ3 NIMit + Ƞ4 DEP_ASSETSit + Ƞ5 EQRATit + Ƞ6 LNTASSit + Ƞ7
	CCLOANit + Ƞ8 DIVit + Ƞ9 KAOPEN it + Ƞ 10 CNTRN it + Ƞ 11 WGI_AVRit + Ƞ 12 WUIit + Ƞ 13 INFit + vit +
	Eit. (5)

Table 2 . Descriptive Statistics For Bank-Level And Country-Level Variables

 2

	Variable	Obs. Mean	Std.Dev. Min.	Max.
	STK_RTN	817 0.038	0.018	0.007	0.103
	TOB_Q	809 1.027	0.118	0.158	1.2174
	ZSCORE	714 3.599	0.738	-0.245	4.889
	BETA	768 0.212	0.406	-1.421	1.681
	IDIO	672 0.152	0.162	0	0.952
	TOT_DER	794 0.540	1.127	3.85E-05 9.001
	TRD_DER	794 0.488	1.096	0	9.001
	HDG_DER	774 0.051	0.134	0	0.833
	ROE	823 13.128	6.368	-12.684	30.248
	NIM	830 0.164	0.757	0.013	5.227
	DEP_ASSETS 822 64.887	16.738	0.076	86.292
	EQRAT	835 0.116	0.0368	0.052	0.2804
	DIV	829 0.005	0.005	0	0.0298
	CCLOANS	809 60.305	13.139	25.196	82.328
	LNTASS	837 9.786	1.443	6.085	12.989
	CNTRN	848 57.991	17.301	28.508	99.979
	KAOPEN	848 0.581	1.321	-1.210	2.359
	WGI_AVR	848 0.060	0.603	-1.248	1.211
	WUI	848 0.075	0.068	0	0.418
	INF	848 4.981	7.946	-25.958	41.119
	EXCH_VOL	848 0.014	0.016	0	0.087

Table

2

presents the following: the number of observations (Obs.) per variable; the mean and the standard deviation (Std.Dev.) of the variables; and the variables' minimum and maximum values.

  Table3reports the correlation matrix for the dependent and independent variables in our regression models. The correlation coefficients are low, which indicates the absence of a multicollinearity problem.14

Table 4 . Random Effects Model Panel Regression: Determinants of Derivative Usage In Emerging Markets

 4

		Model 1	Model 2	Model 3
		TOT_DER	TRD_DER	HDG_DER
	Cons	-0.154(0.564)	0.001(0.551)	-0.216(0.086) **
	ROE	-0.001(0.006)	-0.005(0.055)	-0.004(0.005)
	NIM	-0.093(0.043) **	-0.084(0.041) **	-0.0061(0.055)
	DEP_ASSETS	-0.002(0.003)	-0.002(0.003)	-0.0024(0.044)
	EQRAT	-0.096(0.986)	-0.119(0.913)	0.036(0.114)
	DIV	3.675(6.825)	4.103(6.456)	-0.213(0.519)
	CCLOANS	0.007(0.004) *	0.005(0.003)	0.001(0.001) **
	LNTASS	0.058(0.043)	0.045(0.041)	0.019(0.007) ***
	CNTRN	-0.004(0.001) ***	-0.004(0.001) ***	0.024(0.016)
	KAOPEN	-0.061(0.043)	-0.052(0.042)	-0.007(0.005)
	WGI_AVR	0.257(0.139) *	0.242(0.138) *	0.005(0.014)
	WUI	-0.677(0.367) *	-0.666(0.364) *	-0.029(0.036)
	INF	0.001(0.003)	0.002(0.003)	-0.009(0.034)
	EXCH_VOL	1.726(1.669)	1.593(1.579)	0.056(0.207)
	Year	Yes	Yes	Yes
	Obs.	766	766	752
	R-Square	25.32	24.57	6.07
	Table

Table 5 . Fixed Effects Model Panel Regression: Derivative Usage Effect on Bank Value and Bank Risk in Emerging Markets

 5

	Model	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6
	Dependent	TOB_Q			STK_VOL
	variable
	Cons	0.908(0.267) ***	0.909(0.267) ***	0.887(0.263) *** 0.065(0.071)	0.065(0.070)	0.064(0.071)
	TOT_DER	-0.006(0.003) **			-0.001(0.001)
	TRD_DER		-0.005(0.003) **			-0.001(0.001)
	HDG_DER			-0.071(0.025) ***			-0.009(0.011)
	ROE	0.001(0.001) ***	0.001(0.005) ***	0.001(0.005) *** -0.012(0.017)	-0.011(0.017)	-0.076(0.0165)
	NIM	-0.321(0.345)	-0.327(0.345)	-0.275(0.365)	0.013(0.003) *** 0.013(0.003) *** 0.013(0.003) ***
	DEP_ASSETS 0.001(0.001) **	0.001(0.001) **	0.001(0.004) **	-0.023(0.015)	-0.023(0.015)	-0.026(0.015)
	EQRAT	0.233(0.188)	0.234(0.188)	0.225(0.189)	0.056(0.038)	0.056(0.038)	0.056(0.038)
	DIV	3.301(1.167) ***	3.295(1.168) ***	3.170(1.168) *** 0.300(0.219)	0.299(0.219)	0.295(0.219)
	CCLOANS	-0.001(0.001) **	-0.001(0.005) **	-0.001(0.005) ** 0.008(0.0139)	0.008(0.014)	0.001(0.001)
	LNTASS	0.017(0.026)	0.017(0.026)	0.018(0.026)	-0.002(0.007)	-0.002(0.007)	-0.002(0.007)
	CNTRN	-0.004(0.002) *	-0.004(0.002) *	-0.004(0.002)	0.023(0.067)	0.023(0.067)	0.024(0.068)
	KAOPEN	-0.008(0.004) *	-0.007(0.004) *	-0.006(0.005)	-0.045(0.002)	-0.044(0.002)	-0.001(0.002)
	WGI_AVR	0.047(0.022) **	0.047(0.022) **	0.051(0.021) **	-0.007(0.006)	-0.007(0.006)	-0.007(0.006)
	WUI	0.012(0.052)	0.012(0.052)	-0.005(0.053)	0.001(0.013)	0.001(0.013)	0.003(0.013)
	INF	0.001(0.004)	0.001(0.001)	0.001(0.004)	0.014(0.001)	0.014(0.009)	0.014(0.009)
	Year	Yes	Yes	Yes	Yes	Yes	Yes
	Obs.	722	722	708	726	726	712
	R Square	40.41	40.35	41.11	9.45	9.45	9.62

TABLE 6 . Fixed Effects Regression Model of Derivative Usage Effect On Systematic And Idiosyncratic Risk

 6

		Model 1	Model 2	Model 3	Model 4	Model 5	Model 6
	Dependent	BETA			Idiosyncratic risk
	Variable
	CONS	-1.866(0.837) **	-1.872(0.836) **	-1.917(0.855) ** 0.461(0.668)	0.462(0.668)	0.435(0.667)
	TOT_DER	0.035(0.014) **			-0.004(0.009)
	TRD_DER		0.037(0.014) **			-0.004(0.009)
	HDG_DER			-0.069(0.326)			-0.002(0.107)
	ROE	0.003(0.003)	0.003(0.003)	0.003(0.003)	-0.001(0.002)	-0.001(0.002)	-0.001(0.002)
	NIM	0.023(0.085)	0.023(0.085)	0.027(0.086)	1.078(1.383)	1.081(1.383)	1.021(1.474)
	DEP_ASSETS 0.004(0.002) **	0.004(0.002) **	0.005(0.002) *** -0.001(0.001)	-0.001(0.001)	-0.002(0.001)
	EQRAT	0.418(0.946)	0.421(0.946)	0.435(0.976)	0.396(0.565)	0.396(0.566)	0.377(0.572)
	DIV	-1.877(5.323)	-1.88(5.319)	-1.858(5.352)	2.118(1.907)	2.119(1.907)	2.156(1.843)
	CCLOANS	-0.002(0.003)	-0.002(0.003)	-0.002(0.003)	0.001(0.002) **	0.001(0.002) ** 0.001(0.002)
	LNTASS	0.180(0.081) **	0.181(0.081) **	0.182(0.083) **	-0.041(0.068)	-0.041(0.067)	-0.038(0.067)
	CNTRN	0.002(0.001)	0.002(0.001)	0.002(0.001)	0.001(0.001)	0.001(0.001)	0.001(0.001)
	KAOPEN	0.029(0.029)	0.029(0.029)	0.025(0.029)	0.011(0.015)	0.011(0.017)	0.014(0.018)
	WGI_AVR	-0.297(0.118) **	-0.297(0.118) **	-0.302(0.119) ** -0.012(0.072)	-0.012(0.072)	-0.004(0.072)**
	WUI	0.323(0.268)	0.323(0.268)	0.301(0.274)	0.066(0.125)	0.066(0.124)	0.073(0.126)
	INF	-0.005(0.003) *	-0.005(0.003) *	-0.004(0.003) *	0.001(0.001)	0.001(0.001)	0.001(0.001)
	Year	Yes	Yes	Yes	Yes	Yes	Yes
	Obs.	689	689	675	689	689	675
	R Square	9.53	9.55	9.57	6.38	6.38	6.5

Table 6

 6 reports the results of the fixed effects panel regression of the effects of derivative usage on systematic risk and idiosyncratic risk. We report the coefficients, and the robust standard errors are in parentheses. Systematic Risk (BETA) is captured by the coefficient on the appropriate market index, β, in a standard one-factor market model. Idiosyncratic risk is calculated as the standard deviation of the residuals in that model. We estimate robust standard errors by using bank clustering. We report the presence of year dummies (Year) and the R-Square and number of observations (Obs.) for each model.

	***, **,* denote statistical significance at the 1%, 5%, and 10% levels, respectively
	4.4 Derivative usage and Bank Stability (Zscore):

Table 7 . Fixed Effects Panel Regression Model: The Effect of Derivative Usage On Bank's Insolvency Risk in Emerging Markets

 7

	Zscore	Model 1	Model 2	Model 3
	Cons	1.549(0.568) ***	1.543(0.567) ***	1.519(0.572) ***
	TOT_DER	0.024(0.011) **
	TRD_DER		0.025(0.011) **
	HDG_DER			0.003(0.073) ***
	ROE	0.012(0.003) ***	0.012(0.003) ***	0.012(0.003) *
	NIM	0.254(0.149) *	0.254(0.149) *	0.254(0.151)
	DEP_ASSETS -0.001(0.001)	-0.001(0.001)	-0.001(0.001)
	EQRAT	7.601(0.554) ***	7.602(0.554) ***	7.581(0.553) ***
	DIV	-4.737(3.114)	-4.745(3.115)	-4.619(3.138)
	CCLOANS	0.003(0.001)	0.004(0.001)	0.001(0.001)
	LNTASS	0.103(0.054) *	0.103(0.054) *	0.106(0.055) *
	CNTRN	-0.001(0.001)	-0.001(0.001)	-0.001(0.001)
	KAOPEN	0.046(0.021) **	0.046(0.021) **	0.049(0.021) **
	WGI_AVR	-0.035(0.048)	-0.034(0.048)	-0.029(0.047)
	WUI	0.091(0.085)	0.091(0.085)	0.053(0.089)
	INF	0.001(0.001)	0.002(0.001)	0.004(0.001)
	Year	Yes	Yes	Yes
	Obs.	654	654	644
	R Square	74.14	74.14	74.17
	Table

[START_REF] Chang | Derivatives usage for banking industry : evidence from the European markets[END_REF] find that total derivatives, foreign exchange derivatives and interest rate derivatives are significantly positively related to bank risk, systematic risk and value. Their sample is based on developed European markets.

[START_REF] Keffala | How using derivatives affects bank stability in emerging countries? Evidence from the recent financial crisis[END_REF] identifies derivatives by contract type, namely, forwards, futures, swaps and options, regardless of whether their purpose is for hedging or trading.

To have stock market information available to calculate different bank level risk measures, we require banks to be listed.

Some of the countries that do not follow the IFRS standards include North African countries, China, India, Indonesia, and some other countries. For other countries no information on derivatives can be found and those, such as Kenya, Bangladesh, Benin, Burkina Faso no listed banks can be found.

The dataset contains banks from 24 Middle Eastern, East Asian, African, East European and Latin American countries. Domestic commercial banks are identified by the availability of data on derivative usage as indicated by notional amounts reported in annual reports and financial statements. Table1presents the countries and number of banks in each country.

We exclude Islamic banks since "Islamic" derivatives are still not standardized and follow ununified legal provisions and accounting standards. Moreover, finance theories governing conventional derivatives are different for Islamic finance that is governed by Shariah that forbids speculation or profit from interest or guaranteed return.

Banks in our sample clearly report derivative usage in the notes on financial statements. We discarded banks that do not clearly report financial derivatives or report only the fair values without the notional amounts.

We use the exchange rates reported by the BIS to convert the notional derivative usage from the local currency value reported in the annual reports, to millions of USD and match it with the bank-specific control variables collected from the Bloomberg database.

The KAOPEN variable developed by[START_REF] Chinn | A New Measure of Financial Openness[END_REF] is available at http://web.pdx.edu/~ito/.

The WUI is a panel index of uncertainty for a large set of developed and developing economies and is based on the frequency counts of "uncertainty" in the quarterly Economist Intelligence Unit (EIU) country reports for 189 countries. The dataset is built by[START_REF] Ahir | The World Uncertainty Index[END_REF] and provided by the IMF. See https://worlduncertaintyindex.com/data/

Details on the variables' description are reported in the Appendix

The variance inflation factors are reported in the appendix and further confirm the absence of multicollinearity in the models used.

NIM is a measure of intermediation profitability, and banks will attempt to increase their fee income through derivative trading to compensate for a decrease in NIM[START_REF] Sinkey | Evidence on the financial characteristics of banks that do and do not use derivatives[END_REF]

The average derivative usage ratio to assets is 0.54. An increase in one standard deviation of NIM (0.76) will decrease the average derivative usage ratio by 0.07 to 0.47.

The Zscore is an inverse measure of bank stability/insolvency; an increase in the Zscore implies more stability and less insolvency risk.

value is more pronounced in banks with stronger board oversight. Similarly, how financial market regulation in emerging markets affects bank derivative usage is a largely open question that merits further investigation.

Appendix

This table identifies the dependent and independent variables

Variable Definition

Dependent variables TOT_DER Notional amount of Total Derivatives divided by total assets TRD_DER Notional amount of Trading Derivatives divided by total assets HDG_DER Notional amount of Hedging Derivatives divided by total assets σ return Standard deviation of stock return as a proxy of bank total risk Zscore A proxy used for the bank's stability (insolvency risk); calculated by using the banks' returns on assets, and its volatility, and its leverage ratio; the natural logarithm of the Zscore is used to solve for skewness, as is common in the literature [START_REF] Albaity | Competition and bank stability in the MENA region : The moderating e ff ect of Islamic versus conventional banks[END_REF]; an inverse measure that implies that a higher value indicates higher stability/lower insolvency risk TOB_Q Tobin's Q, as calculated by [START_REF] Laeven | Is there a diversification discount in financial conglomerates?[END_REF]


Dr Julien Frandon

PhD Elsa Bey

MD Aymeric Hamard

MD Hélène Mohammad

MD Samia Gonzalez

MD Joël Greffier

PhD Thierry Chevallier

PhD Hélène De Forges

PhD Jean-Paul Beregi

PhD Stéphane Droupy

Early Results of Unilateral Prostatic Artery Embolization as a Focal Therapy in Patients with Prostate Cancer under Active Surveillance: Cancer Prostate Embolisation, a Pilot Study

Keywords: conceptualization, data curation, formal analysis, interpretation of data, funding acquisition, project administration, supervision, Prostatic artery embolization, low-risk prostate cancer, active surveillance, mpMRI, target lesion, focal therapy, fusion biopsy BMI: Body Mass Index, MRI: Magnetic Resonance Imaging, PSA: prostate specific antigen, PIRADS: Prostate Imaging Reporting and Data System *

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Prostate cancer is the second most common cancer in men worldwide, with 29.3 new cases per 100,000 men in 2018 [START_REF] Bray | GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries[END_REF]. Its incidence has increased due to greater life expectancy and a better detection of this asymptomatic localized low-risk disease with the widespread use of prostate-specific antigen (PSA) screening. Management of these very low-or low-risk patients with a life expectancy >10 years is based on active surveillance (AS) [START_REF] Briganti | Active Surveillance for Low-risk Prostate Cancer: The European Association of Urology Position in 2018[END_REF]. Eligibility for AS varies according to recommendations and includes a PSA level <10ng/mL, stage T1 or T2 and a Gleason score of 6 or 7 (3+4) (International Society of Urological Pathology (ISUP) score 1 or 2) on up to 2 positives biopsy cores <3mm [START_REF] Briganti | Active Surveillance for Low-risk Prostate Cancer: The European Association of Urology Position in 2018[END_REF][START_REF] Bokhorst | A Decade of Active Surveillance in the PRIAS Study: An Update and Evaluation of the Criteria Used to Recommend a Switch to Active Treatment[END_REF]. AS aims to reduce overtreatment and postpone curative radical treatment (radiotherapy and prostatectomy) which induce side-effects on sexual quality of life (QoL) and urinary continence, with no major improvement in overall survival [START_REF] Mottet | EAU-ESTRO-SIOG Guidelines on Prostate Cancer. Part 1: Screening, Diagnosis, and Local Treatment with Curative Intent[END_REF][START_REF] Matta | Pelvic Complications After Prostate Cancer Radiation Therapy and Their Management: An International Collaborative Narrative Review[END_REF][START_REF] Ficarra | Retropubic, laparoscopic, and robot-assisted radical prostatectomy: a systematic review and cumulative analysis of comparative studies[END_REF]. A recent study randomized 1643 patients between radiotherapy, surgery and AS 7 . The cancer-related mortality rate at 10 years was not significantly different between groups. However, disease progression, including the occurrence of metastasis, was significantly higher in patients under AS.

The rate of patients who switch over to radical treatment due to disease progression, grade reclassification or patient decision greatly varies from 37% to 73% at 10 years [START_REF] Bokhorst | A Decade of Active Surveillance in the PRIAS Study: An Update and Evaluation of the Criteria Used to Recommend a Switch to Active Treatment[END_REF][START_REF] Hamdy | 10-Year Outcomes after Monitoring, Surgery, or Radiotherapy for Localized Prostate Cancer[END_REF][START_REF] Klotz | Long-term follow-up of a large active surveillance cohort of patients with prostate cancer[END_REF]. Focal therapies have thus emerged as an alternative to radical curative treatment [START_REF] Van Der Poel | Focal Therapy in Primary Localised Prostate Cancer: The European Association of Urology Position in 2018[END_REF][START_REF] Valerio | New and Established Technology in Focal Ablation of the Prostate: A Systematic Review[END_REF], including thermal therapies such as cryotherapy [START_REF] Jung | Primary cryotherapy for localised or locally advanced prostate cancer[END_REF] and high-frequency focused ultrasound (HIFU) [START_REF] Bass | Oncologic and Functional Outcomes of Partial Gland Ablation with High Intensity Focused Ultrasound for Localized Prostate Cancer[END_REF], or a new vasculartargeted photodynamic therapy called Tookad® which induces local thrombosis within the blood vessels leading to ischemia [START_REF] Azzouzi | Padeliporfin vascular-targeted photodynamic therapy versus active surveillance in men with low-risk prostate cancer (CLIN1001 PCM301): an open-label, phase 3, randomised controlled trial[END_REF][START_REF] Azzouzi | TOOKAD® Soluble focal therapy: pooled analysis of three phase II studies assessing the minimally invasive ablation of localized prostate cancer[END_REF]. A phase III randomized trial compared Tookad® with standard AS in low-risk patients and showed a longer time to progression and a lower disease progression rate with Tookad®. More patients presented negative biopsy results at 24 months after treatment [START_REF] Azzouzi | Padeliporfin vascular-targeted photodynamic therapy versus active surveillance in men with low-risk prostate cancer (CLIN1001 PCM301): an open-label, phase 3, randomised controlled trial[END_REF].

Locoregional ischemia-based therapies have thus demonstrated their efficiency in prostate cancer treatment.

Prostatic artery embolization (PAE) is used in the treatment of lower urinary tract symptoms related to benign prostatic hyperplasia treatment and has been shown to be safe and efficient [START_REF] Gao | Benign prostatic hyperplasia: prostatic arterial embolization versus transurethral resection of the prostate--a prospective, randomized, and controlled clinical trial[END_REF][START_REF] Pisco | Medium-and Long-Term Outcome of Prostate Artery Embolization for Patients with Benign Prostatic Hyperplasia: Results in 630 Patients[END_REF][START_REF] Shim | Efficacy and Safety of Prostatic Arterial Embolization: Systematic Review with Meta-Analysis and Meta-Regression[END_REF].

Randomized trials comparing PAE with standard treatment have reported few adverse effects, with preservation of erectile and urinary functions [START_REF] Gao | Benign prostatic hyperplasia: prostatic arterial embolization versus transurethral resection of the prostate--a prospective, randomized, and controlled clinical trial[END_REF]. PAE was recently used in prostate cancer patients in two studies, with no significant results. Patients included had advanced-stage prostate cancer (T2c/T3) under treatment or were in a palliative situation [START_REF] Pisco | Safety and Efficacy of Prostatic Artery Chemoembolization for Prostate Cancer-Initial Experience[END_REF][START_REF] Mordasini | Prostatic Artery Embolization in the Treatment of Localized Prostate Cancer: A Bicentric Prospective Proof-of-Concept Study of 12 Patients[END_REF]. This pilot study evaluated the feasibility, safety and efficacy of unilateral PAE in patients under AS with low-risk prostate cancer presenting a focal lesion visible on MRI with PIRADS ≥3/5 confirmed by mpMRI target biopsy.

Materials and Methods

Study design and objectives

The primary objective of this prospective monocentric pilot study was to evaluate the feasibility of unilateral PAE in patients with localized low-risk prostate cancer under AS. Secondary objectives were to evaluate safety, response of the target lesion on biopsy and multiparametric Magnetic Resonance Imaging (mpMRI), PSA level, functional outcomes and short-term oncologic efficacy i.e. switching over to radical treatment. All patients signed an informed consent and the study was approved by an ethical review board. The study was performed according to Good Clinical Practice requirements and the Helsinki Declaration and registered on ClinicalTrials.gov (NCT03407963). After inclusion of 5 patients, an independent surveillance committee was formed to evaluate safety and before allowing the study to continue.

Study population

Patients with unilateral low-risk prostate cancer (d'Amico classification) at clinical stage <T2b were included. The main inclusion criteria were: age 18 to 80 years old, life expectancy >10 years; focal lesion on MRI, PIRADS (Prostate Imaging Reporting and Data System) v2 ≥3/5; positive mpMRI target lesion; PSA level <10ng/mL (or ≥10ng/mL in the event of a large prostate volume); presence of unilateral positive MRI-targeted biopsies; Gleason score ≤6 (ISUP 1) with <3 positive biopsies and <50% of positive biopsy length. The main criteria for non-inclusion included the patient's ineligibility or refusal to undergo active surveillance, contraindication for MRI (incompatible pacemaker, claustrophobia, hip prosthesis or metallic implanted device) or for administration of the study products, a tumor on both lobes or a hemostasis disorder.

From June 2018 to June 2019, 10 patients of median age 72 years (range: 62-77) were included in the study. Baseline patient and tumor characteristics of prostate biopsies are reported in Table 1.

Technical procedures

Biopsy

Biopsies were performed at baseline and 6 months after PAE by one experienced operator: 1 to 3 mpMRI-targeted biopsies in the target lesion region under real-time transrectal ultrasonographic (TRUS) guidance and visual real-time matching between MRI target lesions and prostate image (Toshiba, Applio 500 TM smart fusion) and 9 to 12 TRUS standard systematic biopsies [START_REF] Haffner | Role of magnetic resonance imaging before initial biopsy: comparison of magnetic resonance imaging-targeted and systematic biopsy for significant prostate cancer detection[END_REF].

Prostatic artery embolization

PAE was performed by one interventional radiologist (JF, with 10 years of experience and more than 30 cases of PAE performed) under local anesthesia. Both Digital Subtraction Angiography (DSA) and cone-beam computed tomography (CBCT) were performed using a pump injection to evaluate the iliac vessels and identify the prostatic arteries. Prior to PAE, each artery was controlled by CBCT to assess which part of the prostate was vascularized and avoid off-target prostate ischemia. Unilateral embolization was performed using Trisacryl® microspheres (Embosphere, 300-500µm, Merit Medical System, South Jordan, USA) until the prostatic artery was completely occluded. The volume of microspheres injected was reported and compared with the embolized prostate volume. PAE was performed on an ALLURA Xper FD20 (Philips Healthcare) and the radiation dose, i.e. total Kerma-Area Product was collected for all patients.

A follow-up angiography was performed to check for any prostatic lobe blood supply after PAE.

Patients were discharged on the following day.

Imaging

An mpMRI was performed at baseline, at 2 weeks and 6 months after PAE, using a 3.0-T scanner (Magnetom Skyra, Siemens, Erlangen, Germany) with a pelvic phased-array coil. 3DT2-weighted (T2WI), diffusion-weighted (DWI), and dynamic contrast-enhanced (DCE) imaging sequences were acquired according to European guidelines [START_REF] Dickinson | Magnetic resonance imaging for the detection, localisation, and characterisation of prostate cancer: recommendations from a European consensus meeting[END_REF].

Endpoints and assessments

The primary endpoint was technical feasibility, defined as blood flow arrest assessed by angiography, ischemia of the prostatic lobe on the imaging at 2 weeks and the absence of specific risks, especially off-target ischemia (penis, bladder, rectum) assessed at Day 1, Day 5 (follow-up phone call) and Day 15 (clinical evaluation at the time of the MRI) and at 1, 3 and 6 months. Secondary endpoints were: safety (Clavien-Dindo classification), negative targeted and systematic biopsies at 6 months; mpMRI response of the target lesion at 6 months (PIRADS v2 score); functional outcomes evaluated using validated questionnaires/tests at baseline, 1, 3 and 6 months after PAE: urinary-specific QoL (International Prostate Symptom Score, IPSS), incontinence (24-hour Pad test in the event of urinary leakage), erectile dysfunction (Index of Erectile Function, IIEF-6) and QoL (EQ-5D); early oncologic efficacy at one year i.e. the rate of patients switching over to radical treatment (with the decision being made at a multidisciplinary meeting after mpMRI, biopsies and biology results).

Study population

From June 2018 to June 2019, 10 patients of median age 72 years (range: 62-77) were included in the study. Baseline patient and tumor characteristics of prostate biopsies are reported in Table 1.

Statistical considerations

Considering the study design and lack of literature data, no formal calculation was made to determine the number of required subjects, but 10 patients were included. Quantitative variables are presented using medians and ranges. Qualitative variables are presented with numbers and percentages. Values were compared using Mann-Whitney U tests.

Results

Feasibility and safety

Embolization was successfully achieved in all patients. The median embolization procedure time was 50 min. and the median radiation dose received was 101 666mGy.cm 2 (39 666-211 118) (Table 2). The artery selected for embolization was confirmed by CBCT (Figure 1). Prostate ischemia was confirmed by mpMRI at 2 weeks. No off-prostate ischemia was reported and no target lesions were seen on the angiography.

No major complications were reported. Minor complications (Clavien-Dindo I or II) occurred in 3 patients (30%). Patient 3 reported a Grade II urinary infection on Day 3, successfully treated with ofloxacine (200 mg) twice a day for 10 days; patient 5 had Grade I prostatic pain just after embolization which resolved within 5 days on prednisolone (20 mg) combined with omeprazole (20 mg) once a day and paracetamol (1000 mg) four times a day; patient 6 had a Grade I superficial hematoma at the puncture site 2 days after embolization, with spontaneous resolution and no clinical consequences. All patients were discharged the day after embolization according to protocol requirements.

Biopsy and imaging results

At baseline, 8 patients (80%) reported 1 positive targeted biopsy, 2 patients (20%) 2 positive targeted biopsies, and 2 patients (20%) also reported 1 positive systematic biopsy (Table 3). Six months after PAE, 3 patients (30%) had targeted biopsies in the area where the tumor was previously located as no target lesion was visible on mpMRI (Table 3 and Figure 2). In these 3 patients (30%) with complete response on mpMRI (no visible PIRADS v2 lesion, Table ), 2 reported negative biopsies performed in the former target location. Overall, 4 patients (40%) reported both negative targeted and systematic biopsies. One patient's PC (10%) had progressed on a systematic biopsy at 6 months (Gleason score 7, 3+4), outside the target lesion.

The size of the target lesion on mpMRI, 10mm (7-16) at baseline, was stable. Ischemia of the prostatic lobe was partial and heterogeneous, involving 20% (10-40) of tissue (Figure 2 and Table 4). Ischemia was visible at 2 weeks after PAE, not at 6 months.

PSA levels were similar before and after embolization. As expected, the prostatic volume decreased from 67.5cm 3 at baseline to 54.0cm 3 (37-95) at 6 months (p=0.344) (Table 4).

Functional outcomes

Overall, functional outcomes were improved after PAE: no urinary incontinence was reported, and patients showed better urinary status (IPSS: 5 (1-16) at baseline and 1 (1-19) at 6 months) (Table 5).

No erectile dysfunction was reported after embolization either.

Early oncologic efficacy

At one year, 9 patients (90%) were still under AS and the patient whose PC had progressed on a systemic biopsy, outside the target, was reclassified and switched over to curative external beam radiotherapy.

Discussion

Results show that therapeutic unilateral PAE in patients under AS for low-risk prostate cancer with a focal lesion visible on MRI with PIRADS ≥3/5 confirmed by a targeted mpMRI biopsy is feasible and seems safe and promising. PAE is already used for the treatment of benign prostatic hyperplasia with good results in terms of safety and efficacy [START_REF] Pisco | Medium-and Long-Term Outcome of Prostate Artery Embolization for Patients with Benign Prostatic Hyperplasia: Results in 630 Patients[END_REF]. PAE was assessed in patients with low-risk prostate cancer under AS to postpone switching over to radical treatment and limit the side-effects on erectile and urinary functions.

It was decided to perform unilateral PAE for various reasons. First, patients were addressed for unilateral prostate cancer and not for low urinary tract symptoms. Secondly, unilateral PAE represented a shorter procedure time with potentially fewer side effects. Thirdly, it would allow us to study the locoregional effect of PAE in greater depth. The feasibility of unilateral PAE for these patients was demonstrated as partial prostatic ischemia was achieved for all of them. This noninvasive treatment was performed in a short time (median duration 50min), with discharge the following day. If complete safety is confirmed, an ambulatory setting may be possible. The PAE procedure has advantages compared to other focal therapies developed as alternatives to radical treatment. Indeed, most other therapies published are costly, require specific logistics (dark room etc.) and adverse events such as erectile dysfunction and other complications related to off-target tissue ablation have been reported. Also, some prostate locations such as anterior sites or those close to the apex or urethra are either inaccessible or too risky for other focal therapies [START_REF] Ganzer | Which technology to select for primary focal treatment of prostate cancer?-European Section of Urotechnology (ESUT) position statement[END_REF]. In this study, PAE was possible in many prostate locations as the procedure consists of embolizing the whole prostate lobe with no off-target ischemia.

In this study, safety was as good as for other studies on PAE for HBP which reported very few complications [START_REF] Ray | Efficacy and safety of prostate artery embolization for benign prostatic hyperplasia: an observational study and propensity-matched comparison with transurethral resection of the prostate (the UK-ROPE study)[END_REF]. Functional outcomes were good, with no incontinence or sexual dysfunction, in agreement with other results on PAE for HBP reported [START_REF] Gao | Benign prostatic hyperplasia: prostatic arterial embolization versus transurethral resection of the prostate--a prospective, randomized, and controlled clinical trial[END_REF][START_REF] Pisco | Medium-and Long-Term Outcome of Prostate Artery Embolization for Patients with Benign Prostatic Hyperplasia: Results in 630 Patients[END_REF]. PAE may also have the potential benefit of relieving emotional stress in patients who are anxious about their untreated cancer. The two previous studies on PAE in prostate cancer showed significant complications with equivocal oncologic results. Mordarsini et al. reported Grade 3b partial bladder wall necrosis in two patients and infected lymphocele (grade 3a) [START_REF] Mordasini | Prostatic Artery Embolization in the Treatment of Localized Prostate Cancer: A Bicentric Prospective Proof-of-Concept Study of 12 Patients[END_REF], as for Pisco et al. who reported off-target necrosis (bladder wall) [START_REF] Pisco | Safety and Efficacy of Prostatic Artery Chemoembolization for Prostate Cancer-Initial Experience[END_REF]. They also reported Grade 2 incontinence and sexual dysfunctions [START_REF] Pisco | Safety and Efficacy of Prostatic Artery Chemoembolization for Prostate Cancer-Initial Experience[END_REF][START_REF] Mordasini | Prostatic Artery Embolization in the Treatment of Localized Prostate Cancer: A Bicentric Prospective Proof-of-Concept Study of 12 Patients[END_REF]. They used smaller microspheres (100-300µm) which could induce higher morbidity [START_REF] Gonçalves | Comparative Study Using 100-300 Versus 300-500 μm Microspheres for Symptomatic Patients Due to Enlarged-BPH Prostates[END_REF]. Also, Pisco et al. performed bilateral chemoembolization with docetaxel in advanced cancer patients, which may explain this higher toxicity [START_REF] Pisco | Safety and Efficacy of Prostatic Artery Chemoembolization for Prostate Cancer-Initial Experience[END_REF]. In this study, unilateral PAE was performed in patients with low-risk cancer and limited symptoms at baseline (median IPSS of 5). Overall, these results are encouraging as the purpose of AS is precisely to avoid or postpone side-effects induced by radical treatments [START_REF] Kluytmans | Exploring the risk-reward balance in focal therapy for prostate cancer-a contribution to the debate[END_REF]. It is thus essential that new focal therapies, proposed as an alternative to AS, do not induce important sideeffects.

Focal treatment during AS is debated [START_REF] Tay | Patient selection for prostate focal therapy in the era of active surveillance: an International Delphi Consensus Project[END_REF] and therefore patient selection was an important issue in this study. Only patients under AS presenting consequent lesions visible on mpMRI (median index lesion 10mm, upper Gleason 3+3 score) confirmed by targeted biopsy were included. Very low-risk patients weren't included [START_REF] Tay | Patient selection for prostate focal therapy in the era of active surveillance: an International Delphi Consensus Project[END_REF]. Indeed, these patients with lesions found on the MRI have a poorer disease evolution and oncologic outcome which justifies proposing focal therapy during AS [START_REF] Bloom | Predicting Gleason Group Progression for Men on Prostate Cancer Active Surveillance: Role of a Negative Confirmatory Magnetic Resonance Imaging-Ultrasound Fusion Biopsy[END_REF].

Targeted biopsies have been shown to lead to better identification of patients under AS who can benefit from hemi-ablative focal therapies [START_REF] Tran | Combination of multiparametric MRI and transperineal template-guided mapping biopsy of the prostate to identify candidates for hemi-ablative focal therapy[END_REF]. Indeed, targeted biopsies enabled us to carefully select patients, thus avoiding misclassifications during systematic follow-up biopsies [START_REF] Tosoian | Active Surveillance of Grade Group 1 Prostate Cancer: Long-term Outcomes from a Large Prospective Cohort[END_REF][START_REF] Hu | Targeted prostate biopsy in select men for active surveillance: do the Epstein criteria still apply?[END_REF].

Although recent literature has highlighted the crucial role of mpMRI in AS follow-up [START_REF] Schoots | Magnetic resonance imaging in active surveillance of prostate cancer: a systematic review[END_REF], this study seems to report limitations in the use of mpMRI for these patients. Indeed, 4 patients had negative systematic, targeted biopsies and 2 of them had a visible target on the imaging. It seems that the response on mpMRI may be delayed compared with the biopsy results. Moreover, one patient with a complete response on mpMRI reported a positive biopsy in the former target location. This emphasizes the limitations of concordance between the PIRADS V2 classification and oncologic results [START_REF] Kasivisvanathan | MRI-Targeted or Standard Biopsy for Prostate-Cancer Diagnosis[END_REF]. These results also suggest that both targeted and systematic biopsies are important; indeed, in the one patient whose disease had progressed, this was detected with systematic biopsies and not with the targeted biopsy [START_REF] Rouvière | Use of prostate systematic and targeted biopsy on the basis of multiparametric MRI in biopsy-naive patients (MRI-FIRST): a prospective, multicentre, paired diagnostic study[END_REF]. However, it is possible that the lesion was missed by the systematic biopsies, and that this patient may initially have been understaged.

Azzouzi et al. reported similar results with Tookad®. They showed a 28% progression rate and switch to radical treatment and 49% negative biopsies at 2 years [START_REF] Azzouzi | Padeliporfin vascular-targeted photodynamic therapy versus active surveillance in men with low-risk prostate cancer (CLIN1001 PCM301): an open-label, phase 3, randomised controlled trial[END_REF]. It seems that ischemic strategies do not achieve complete success rates, probably due to complex prostate vascularization, modified by the tumor [START_REF] Cimadamore | Re: Prostatic Artery Embolization in the Treatment of Localized Prostate Cancer: A Bicentric Prospective Proof-of-Concept Study of 12 Patients[END_REF]. This may explain a heterogeneous distribution of the embolization microspheres and the partial, heterogeneous ischemia reported in the study. It is also possible that the number of microspheres injected plays a role in this random distribution of particles in the prostate volume. This raises the question of performing bilateral embolization in refractory patients who may have developed contralateral arterial anastomoses. As PAE is a safe procedure, it may be possible to repeat PAE in the event of failure. Pisco et al. have shown the efficacy of such a strategy: among 3 patients who had biochemical failure of their first chemoembolization at 6 months and underwent a second procedure, 2 achieved biochemical success afterwards [START_REF] Pisco | Safety and Efficacy of Prostatic Artery Chemoembolization for Prostate Cancer-Initial Experience[END_REF].

Usual focal treatments are based on high focal energy deposits mainly using thermal ablation (HIFU or, cryotherapy) [START_REF] Ganzer | Which technology to select for primary focal treatment of prostate cancer?-European Section of Urotechnology (ESUT) position statement[END_REF]. One reason why they cannot be used for all lesions may be the necessity to obtain clear margins, especially when close to regions at risk. This study opens new perspectives with this new targeted vascular therapy. PAE is a different concept based on vascular territories, which may be used for patients with difficult-to-access lesions or regions at risk. It may also lead to the possibility of using chemotherapy-loaded particles that could be administered directly within the prostate, reducing the side-effects of systemic chemotherapy. Moreover, potential radiotherapy treatment may still be possible after PAE in the event of disease progression; indeed, the 6-month MRI showed complete regression of the ischemic effect of PAE.

This study shows certain limitations, including those inherent to the pilot study design as this was a mandatory stage before conducting further studies. The main limitations are the small number of patients included, and the short follow-up (1 year) required due to the safety design. A 5-year followup would be more clinically meaningful for oncological results, especially regarding the switch to radical treatment. Another limitation is the absence of precise targeting of the lesion leading to the embolization of the entire prostatic lobe. Indeed, the lesions were not visible on the angiogram and this did not allow us to better target the embolization. Although there was a lack of a control group to assess the magnitude of treatment effect, these results are promising and warrant further investigations to determine the right number of microspheres to use and explore the long-term efficacy of PAE in these patients.

In conclusion, this pilot study showed that prostatic artery embolization is feasible and appears safe in patients with low-risk prostate cancer and a visible lesion on MRI PIRADS ≥3/5 confirmed by mpMRI targeted biopsy under active surveillance. This procedure offers patients eligible for AS a "reinforced active surveillance" as an alternative to focal therapy before eventually switching over to radical treatment. Early results with 40% of negative targeted biopsies and 90 % of patients still under AS at one year are encouraging and justify the pursuit of further studies. Randomized multicentric studies with, as an endpoint, the proportion of patients switching over to radical treatment, would help to confirm the interest of this promising procedure.

Morphologic Changes in Periprostatic Arteries Have an Influence on Prostatic Artery

Embolization? Eur. Urol. 2019; 75: e110-e113.

Figure and Table legends

Figure 1 :

 1 Figure 1: Feasibility of prostatic artery embolization: mpMRI of Patient 6 with the target lesion

Figure 2 :

 2 Figure 2: Efficacy of the procedure: At baseline, patient 2's mpMRI showed a PIRADS 4 target

*

  Dynamic contrast enhancement is reported with a + Ø assessable: target lesion not clearly identifiable because of ischemic remodeling MRI: Magnetic Resonance Imaging; CR: complete tumor response (no target lesion visible on MRI)

Table 1 :

 1 Patients' characteristics at baseline

Table 2 :

 2 Technical and angiographic data

Table 3 :

 3 Biopsy results at baseline and 6 months after prostatic artery embolization

Table 4 :

 4 MRI target at baseline, and at 2 weeks and 6 months after prostatic artery embolization

Table 5 :

 5 Functional outcomes at baseline and at 1, 3 and 6 months after prostatic artery embolization

Table 1 :

 1 Patients' characteristics at baseline

Table 2 :

 2 Technical and imaging data

	Patient	Embolized prostatic artery number, side, origin	Volume of Microspheres injected (mL)	Procedure duration (min)	Total Kerma Area Product (mGy.cm 2 )
	1	1, right, superior vesical artery	3	35	184 329
	2	1, right, rectal artery	3	85	138 930
	3	1, left, superior vesical artery	5	31	58 316
	4	1, left, superior vesical artery	4.5	51	82 396
	5	2, right, obturator artery x 2	4 (2 + 2)	55	120 937
	6	1, right, superior vesical artery	3	50	39 666
	7	1, right, gluteal artery	4	69	69 743
	8	1, right, obturator artery	4	47	139 687
	9	1, left, superior vesical artery	3.5	46	71 089
	10	2,

right, pudendal and obturator arteries 7 (3+4) 125 211 118 Bold:

  No positive biopsy reported in the targeted or systemic biopsies at 6 months Embolization was performed with a mixture of 12 mL of contrast media, 8 mL of saline, and 2 mL of microparticles (Embosphere, 300-500µm, Merit Medical System, South Jordan, USA).

Table 3 :

 3 Biopsy results at baseline and at 6 months after prostatic artery embolization

	Baseline

* Patients 2, 6 and 8: no target lesion was visible on MRI at 6 months, target biopsies were performed in the area where the tumor was previously located.

** Patient 3 progressed outside of target lesion

Bold: No positive biopsy reported in the targeted or systemic biopsies at 6 months

Table 4 :

 4 MRI target at baseline, and at 2 weeks and 6 months after prostatic artery embolization

		Baseline			At 2 weeks			At 6 months
	PIRADS score*	Target lesion size, mm	Necrosis of the prostatic lobe, %	Prostate volume, cm 3	PIRADS score*	Target lesion size, mm	Necrosis of the prostatic lobe, %	Prostate volume, cm 3	PIRADS score*	Target lesion size, mm	Necrosis of the prostatic lobe, %	Prostate volume, cm 3

Table 5 :

 5 Functional outcomes at baseline and at 1, 3 and 6 months after prostatic artery embolization

		Baseline (N=10)	(N=9*) 1 month	p**	3 months (N=9*)	p**	6 months (N=10)	p**
	IPSS (/35), median (range) Urinary symptoms QoL	5 (1-16)	2 (1-16)	0.179	2 (1-9)	0.197	1 (1-19)	0.321
	(/6), median (range)	2 (0-4)	1 (0-4)	0.189	1 (0-3)	0.486	1 (0-3)	0.365
	IIEF-6 (/30), median (range)	24 (1-30)	24 (0-30)	1.000	27 (1-30)	0.528	27 (0-30)	0.970
	EQ-5D score (/100), median (range)	90 (40-100)	90 (50-95)	0.855	90 (40-95)	0.486	90 (40-100)	0.786

IPSS: International Prostate Symptom Score; QoL: Quality of life; IIEF-6: International Index of Erectile Function; EQ-5D: European Quality of Life (EuroQoL) questionnaire *: Data missing for one patient at 1 month (patient 5) and for one patient at 3 months (patient 7) **: compared to baseline

Acknowledgements

The authors thank the patients who participated to the study for their trust. They also thank Drs Corinne Palamara and Cyrille Blion of the Urology Department for their participation in the study.

They thank the Clinical Research Department of the Nimes CHU and the BESPIM unit for their methologic, regulatory and administrative support all along the study, Pierre Rataboul for his help in protocol writing, and Elisabeth Dusserre and Ali Franzini for their work as clinical research assistants.

Funding statement

The study was funded by an internal CHU Nîmes call for projects, NIMAO, funding number NIMAO/2017-01/01-JF.

Conflict of interest statement , final approval of the manuscript; Joël Greffier: data curation, investigation, writing review and editing, final approval of the manuscript; Thierry Chevallier: conceptualization, methodology, final approval of the manuscript; draft, writing review and editing, final approval of the manuscript; Jean-, funding acquisition, project administration, supervision, writing review and editing, final approval of the manuscript; Stéphane Droupy: conceptualization, interpretation of data, funding acquisition, project administration, supervision, writing review and editing, final approval of the manuscript.

Data availability statement

All data supporting the findings of this study are available from the corresponding author, upon reasonable request.