Is OCIO superior in asset allocation performance?

ThisstudyaimstoempiricallyanalyzetheassetallocationcapabilitiesofOutsourcedChiefInvestmentOfficers(OCIOs)inKorea.Theempiricalanalysisuseddatafrom35fundsthatwereevaluatedbytheMinistryofStrategyandFinancefrom2012to2020.Theresultsoftheanalysisaresummarizedasfollows.First,thisstudy foundthatfundsthatadoptedOCIOimprovedtheirassetallocationperformance.Second,thesensitivitybetweenrisk-takingandperformancedecreasedforfundsthatadoptedOCIO.Third,itisfoundthatOCIO adoptionimprovesafund ’ s asset management execution (tactical capabilities). This study has methodological limitations in which the methodology used in this study is not based on theoretical prior research, but on practical applications. However, considering the need to clearly analyze the capabilities of OCIO and the timeliness of the topic, this study is valuable and can provide meaningful information to funders who are considering adopting OCIO in the future.


Introduction
Outsourced Chief Investment Officer (hereafter OCIO) is an asset management system that comprehensively entrusts an asset owner's asset management to an external asset manager.Compared to conventional asset management systems, it greatly expands strategic asset management decision power to the custodian.In Korea, the OCIO market started with a pension fund investment pool in 2001 and it has grown to 100tn won size.However, more than 80% of the total assets under OCIO management is focused on four large public funds including the Housing and Urban Fund, Employment Insurance Fund, Workers' Compensation Insurance Fund and Pension Fund Investment Pool.Recently, however, OCIO market's scope is expanding to private companies and university funds from large public funds and public institutions.In addition to conventional OCIOs that entrust all assets management, asset class-specific OCIO that grants strategic decision power to specific asset classes is introduced by deposit insurance funds, construction cooperatives and the Korea Health Insurance Corporation.Also, relatively conservative university funds such as the Seoul National University Development Fund, Ewha Womans University and Sungkyunkwan University have also adopted OCIOs recently.It indicates large asset owners' interest in OCIO is growing in both the public and private sectors.Thanks to the rising interest in OCIO, securities firms and asset managers are responding to the expanding OCIO market by supplementing personnel and reorganizing of firms.Considering aging Korean society and stronger demands for retirement asset management, the expansion of the OCIO market is not a short-term trend, but a long-term trend that can change the fundamental structure of the Korean asset management market.Another fundamental reason for expanding the OCIO market is that the size of professional asset management people is limited compared to the growth of the pension fund market.Therefore, OCIO is a realistic alternative to solve the shortage of professional manpower as the responsible manager of pension funds.
In countries like USA where the asset management industry is advanced, the asset management market has been expanding since the global financial crisis of 2008.The expansion has led to stronger demand for OCIO, particularly, from large pension funds and the managers came from asset managers, investment advisors and investment banks.As of 2021, public funds, public institutions and university cover funds about 200tn won in the Korean OCIO market.And the OCIO market is expected to grow further in size as retirement pensions grow up quickly.
However, despite the rapid growth of the OCIO market and its future growth expectations, we do not find enough research on the superiority of OCIO management compared to conventional asset management systems.Previous research on OCIOs has focused on the market structure of OCIOs (Park and Ryu, 2020, 2021, 2022;Kim and Ryu, 2020;Shin et al., 2020), with few studies analyzing the benefits of OCIO adoption.In particular, the key question on OCIO which is whether OCIO is superior in strategic asset allocation is not investigated according to our knowledge.
Considering the most important change with more adoption of the OCIO system is its more responsibility in asset management planning particularly, the planning of OCIO asset management needs to be further investigated.In this work, we provide significant empirical evidence that OCIO's asset allocation capabilities have a partial superiority compared to conventional asset management.Also, we further find that the adoption of OCIOs gives a consistent and significant positive effect on the fund's asset allocation in terms of the Sharpe ratio and the fund's % score [1].Overall, our empirical results support the importance of portfolio management strategies, given the superiority of OCIOs in improving the ex ante planning of fund management.This study also finds meaningful policy and practical implications based on the significant asset allocation power of OCIOs.
This study is organized as follows.Section 2 summarizes the domestic and foreign studies on OCIO and asset allocation.Related to the literature, it also explains the implications of this study.Section 3 describes the data and basic statistical properties employed in empirical analysis.Section 4 interprets the results of the empirical analysis and its implications.Section 5 discusses the implications of this study and future research directions.

Literature review 2.1 Research on the OCIO
There has been a huge body of studies on pension funds' performances in Korea.Recently, studies on OCIO performances in domestic public funds are focused on market structure and possible related problems.Nam (2019) compares domestic and foreign OCIO markets in terms of their current status and characteristics.He finds inefficiencies and structural problems in the domestic OCIO market through the business structure, customer service and fee system of representative foreign OCIO managers.Nam (2020) also adds critical problems in the domestic OCIO market of strategic decision-making is left to non-professional trustees and OCIOs do not provide appropriate advisory service to the trustees.These roles of OCIOs are likely to be more JDQS 31,2 intensified in future.Nam (2022) concludes that in order to fully achieve the goal of the OCIO system, which is to actively utilize external expertise and to strengthen healthy competition among trusteeship organizations, the full discretion system needs to be more intensified.Yoon and Lee (2019) theoretically examine problems arising from the management fee structure.They find Korean OCIO structure has fee structure problems in selecting and operating OCIOs.Park and Ryu (2020) investigate the Korean OCIO market by employing the agency problem model.It focuses on the contract period of the OCIO and the expertise of the fund.They conclude that in the case of domestic OCIOs, longer the contract period gives lower the expertise of the fund which generates a greater likelihood of agency problems.Kim and Ryu (2020) also study OCIO business models in terms of OCIO service providers compared to foreign cases.They suggest the possibility of introducing business models such as OCIO financial investment companies, OCIO specialized companies and OCIO consulting companies in the domestic pension market.Shin et al. (2020) surveyed institutional investors and find potential OCIO service providers related to crucial factors necessary for the development of OCIO business.They further identify the gap in improving returns as an important goal in Korea and risk management.The lack of internal resources would be one of the reasons for the asset management goal in the domestic market compared to foreign markets.Kim et al. (2020) investigate the impact of the governance structure of Korean pension funds on asset management performances in different features of the fund management committee and asset management committee.

Research on asset allocation
We can summarize the full length of the asset management process with the four steps of "Plan → Execute → Monitor → Feedback."It is known that the strategic asset allocation in the planning phase is the most crucial step in which more than 90% of the asset performance is decided.Therefore, there have been keen interest and research in asset allocation by employing theoretical and empirical models.Asset allocation methods, however, are constantly evolving based on Markowitz's mean-variance model.Conventional asset allocation is based on forecasting expected future risk and return of different asset portfolios.In actual asset management industries, Markowitz's mean-variance model and its complements, the Black-Litterman Model (Black and Litterman, 1992;He and Litterman, 1999;Satchell and Scowcroft, 2000) and the Resampling Model (Michaud, 1998) are widely used.Since it is not possible to forecast future returns and risks in an accurate way, however, recent patterns of asset allocation decisions pay more attention to achieving stable and steady performance rather than maximizing returns through return prediction.Related to characteristics of asset classes, methodologies that focus on risk rather than returns are also highly utilized in real practice of asset management (for example, Risk-Budgeting and Risk-Parity and so on).In addition, Asset Liabilities Management based asset allocation methods (ALM Base Asset allocation), Liability Driven Investment (LDI) and Surplus Risk-Based Asset allocation that take into account liabilities are actively incorporated in pension funds and retirement management systems (Kim et al. 2016;Lee et al., 2018).
In addition to research on asset allocation methodologies, there also have been a lot of research on estimating asset class-specific parameters like expected return and expected risk with higher accuracy.In expected returns, James and Stein (1961) give early method based on the assumption that all asset returns converge to their mean which is extended to the capital asset pricing model (CAPM) (Sharpe, 1964;Lintner, 1965;Mossin, 1965).After CAPM, various empirical methods such as the arbitrage pricing model (Stephen, 1976), equilibrium expected return (Fisher, 1975) and implied return (Black andLitterman, 1990, 1992) have been introduced.In risk indicators, on the other side, the conventional standard deviation, VaR (Value at Risk, Mausser and Rosen, 1998;Campbell et al., 2001;Artzner et al., 1999), CVaR (Conditional VaR, Rockafellar andUryasev, 2000), LPM (Lower Partial Moment, Fishburn, Asset allocation performance 1977) and Shortfall Risk (Leibowitz and Henriksson, 1989;Leibowitz and Langatieg, 1989;Leibowitz and Kogelman, 1991;Oh and Lee, 2015) are introduced in asset management industries.

Contributions on OCIO research
Even with a large body of literature on empirical analysis of asset allocation, few studies work on asset allocation capabilities of OCIO management which is a crucial question in asset management markets.The lack of study is related to difficulty in sorting out various endogenous quantitative factors and qualitative factors in the asset decision-making process.
And it has been considered, therefore, as the limitations on asset allocation capability research.This study clearly recognizes the limitations of asset allocation research.However, given the importance and timeliness of analyzing the capabilities of OCIOs in the changing asset management market, this study attempts to investigate the asset allocation capabilities of OCIOs by employing randomized portfolios.This work at least partially contributes to the understanding of the effectiveness of OCIO management performances in the middle of OCIO market expansion.

Data and empirical model 3.1 OCIO market in Korea
Table 1 summarizes the size of the funds and the OCIO adoption fund from 2010 to 2020 in the Korean fund market.Funds are categorized into accounting, financial, business and social insurance funds according to Korean Government Classification Standard.The total amount of funds grew by more than 10% annually from about 347tn won in 2010 to about 884tn won in 2020 in a 2.5-fold increase in 10 years.This is due to the growth of the Social Insurance Funds centered on the National Pension Fund.The National Pension Fund accounts for 90% of the total fund size in Korea.The Financial Services Fund has increased by about 60% over the past decade, while the size of the Business Performance Fund, which implements targeted projects as the government strengthens its social functions, has increased by about four times from KRW 13tn in 2010 to KRW 51tn in 2020.
The OCIO system was first introduced to the Korean fund market through the investment pool for public funds under the supervision of the Ministry of Strategy and Finance.According to the fund management evaluation of 62 funds in the year 1999, crucial problems were found in the asset management part of funds which led to introducing the "pension fund investment pool" system at the 2nd Fund Policy Review Council in August 2001.However, the pension fund investment pool was limited compared to the massive demand for professional investment managers as it was operated as a single pool with different investment objectives and management patterns of the funds participating in the system.As a result, there was a strong need for larger pension funds to establish their own management system.Separating OCIOs were introduced for each fund finally.There are currently six funds that have introduced separate OCIO systems: The Employment Insurance Fund (or EIF), the Radioactive Waste Management Fund (or RWMF), the Industrial Accident Compensation Insurance and Prevention Fund (or IACIPF), the Wage Claim Guarantee Fund (or WCGF), the Employment Promotion and Vocational Rehabilitation Fund for the Disabled (or EPVRF) and the National Housing and Urban Fund (or NHUF).The total size of these funds amounts to KRW 70.6tn as of 2020 which covers about 8% of the total funds size in Korea.
The first fund to introduce an OCIO system by the fund was the Employment Fund under the Ministry of Employment and Labor.It adopted a few securities firms and asset managers in 2013 as OCIOs for the EIF and IACIPF.In addition, the NHUF reorganized its wrap Asset allocation performance management structure through two to five securities firms and adopted the OCIO management system in 2014 by selecting one securities firm and one asset manager.Since then, the RWMF in 2018 and the Seoul National University Power Generation Fund and the first public interest corporation in 2019 have adopted OCIO entrusted management.The Performance Compensation Fund in 2020, the WCGF and EPVRF in 2021, SME Retirement Pension System in 2022, Gangwon Land, Deposit Insurance Fund, KOREA Inclusive Finance Agency and Social Welfare Foundation additionally decided to go through OCIO management.As the funded retirement pension system is in the early stage of implementation, the OCIO market scale is expected to expand on a larger scale and the role of OCIO is expected to expand further too.

Data
This study focuses on OCIO funds that underwent the Korean government's fund management evaluation between 2012 and 2020.In accordance with Article 82 of the National Finance Act, the fund management evaluation started in 2000 to improve the transparency and efficiency of fund management.It has contributed to the establishment of fund policies and institutional improvement.As shown in Table 2, 35 out of 60 OCIO funds every year underwent government's fund evaluation.
This study is interested in the impact of pension funds' OCIO adoption on asset allocation performance, the data starting year is chosen as 2012 when major funds adopted OCIO systems.The ability to allocate assets to medium-term and long-term assets needs to be considered in pension fund management, we limit data employed to pension funds where the share of medium-term and long-term assets exceeds at least 20% of their total assets.We do not include pension funds where the share of fixed-income assets exceeds 50% for a fair evaluation of asset allocation performance.In addition, we exclude small funds where the total size is less than KRW 100bn as there are constraints on asset allocation in small-sized funds.We also excluded funds with no investment in risky assets such as domestic stocks, foreign stocks and alternative assets.Since fund evaluations are regularly implemented every year, our empirical work employs crosssectional data by fund and year in a time series which led us to estimate in a panel framework.The number of funds analyzed was 30 and the number of samples period is 22 which makes the total sample observation 137.Out of the 30 funds in empirical work, 6 funds have adopted OCIO but we exclude long-term funds and debt funds that adopted OCIO only for the purpose of incorporating alternative assets class in 2021.As a result, we have four funds that have introduced OCIO: the employment insurance fund, the Industrial Accident Compensation Insurance and Prevention Fund, the Radioactive Waste Management Fund and the National Housing and Urban Fund.
The pension fund data and information for the study were collected from the MOEF's Open Government Finance data archive.The asset allocation and risk tolerance for each fund is collected from the asset management guidelines (IPS) reported by each fund.Data on funds valuation results are collected from the "Itemized Results of Measured and Unmeasured Valuation by Fund" report published annually by the MOF.
The evaluation items are shown in Table 3.Among the evaluation items, the operational item is operational performance while non-measured evaluation items are asset management system, asset management policy and asset management execution.Evaluation results for each item are collected by year and fund.

Empirical model
This study aims to analyze the impact of OCIO adoption on the asset allocation performance of pension funds.For this purpose, we measure asset allocation performance rather than This data is public and available to anyone.]Table 2.

Characteristics of OCIO funds
Asset allocation performance fund-specific operating performance.Asset allocation performance refers to the strategic asset allocation effectiveness under the performance factor methodology which is defined by the Ministry of Strategy and Finance's "Guidelines for Asset Management."The guideline specifies the weighted average of the asset allocation ratio and the benchmark.Asset allocation ratios are collected from asset management guidelines (IPS) but benchmarks for evaluation vary by fund.Since this study analyzes a large number of pension funds, we construct representative benchmarks for each asset class for appropriate evaluation of fund performance.Listing benchmarks employed in this work, KOSPI for domestic stocks, KIS Composite Bond Index for domestic bonds, MSCI All Country World Index (ACWI) for foreign stocks and Barclays Global Aggregate Index (BGAI) for foreign bonds are employed.We assume that the exchange rate policy for foreign assets is unhedged for foreign stocks and hedged for foreign bonds.The index for alternative investments is the publicly traded alternative investment fund index proposed by Yeo and Song (2021).
While performance in strategic asset allocation effectiveness is meaningful in terms of calculating returns through asset allocation, it has a limit in that the higher the proportion of risky assets, the higher the return on average.In more detail, each fund needs to be compared to a peer group with similar risk for appropriate measures of relative superiority in OCIO performances.However, given the constraints in data of having only 35 funds in our work, we employ a random portfolio as a benchmark of comparison.Randomized portfolios have the advantage of allowing for comparable performance measures within the same operating environment while imposing various constraints on performance comparisons (Cohen and Pogue, 1968;Burns, 2004).Asset allocation performance is measured by determining the relative position of the pension fund's asset allocation in 10,000 randomly selected randomized portfolios.For example, if Fund A has an annual asset allocation plan for 2021, we measure the return on Fund A's asset allocation (strategic asset allocation effect) by weighting the benchmark return by asset class at the end of 2021 and the annualized asset allocation weight.At the same time, 10,000 random portfolios are constructed and their annualized returns are estimated by weighting each portfolio by the annualized benchmark return in 2021.We define the asset allocation performance of the pension fund by calculating the % ranking of the 10,000 random portfolios.In addition to the simple return, the asset allocation performance also measures the standard deviation and Sharpe ratio.In this case, the standard deviation is the standard deviation of the 12-month period monthly return of the year.The risk-free rate of return is measured by the government bond (1 year maturity) in calculating the Sharpe ratio.
Table 4 illustrates allowable risk limits by the fund.Although each pension fund has different risk constraints, the level of risk tolerance is similar to all funds of social insurance, financial and business depending on the fund's classification.In social insurance funds, the risk tolerance is relatively high generally controlling the probability of the 5-year cumulative return falling below the consumer price index (CPI) to 15% [or Shortfall Risk (5 years, CPI) ≤ 15%].In the Ministry of Finance Fund, investment in risky assets is extremely limited.The probability that the principal's 1 year cumulative return will fall below is controlled at 1% [or Shortfall Risk (1-year, Principal) ≤ 1%].In the case of business performance funds, the risk level is generally located in the middle between social insurance and financial performance funds.The size of risk varies depending on the size of the reserve fund and the degree of diversification of investment assets.
The problem in employing the same randomized portfolio in evaluating pension funds with different risk profiles is that asset allocation capabilities are evaluated based on risk profiles regardless of asset allocation capabilities.In addition to the unconstrained random portfolio that does not incorporate constraints, constrained random portfolios where the risk of the pension fund is considered are constructed for relative comparison in asset performance.For this purpose, we construct the size of risk according to the proportion of risky assets with a reference portfolio consisting of stocks (domestic stocks, KOSPI) and bonds (domestic bonds, KIS Composite Bond Index).Using the data from the last 10 years from 2012 to 2021, we estimate the proportion of risky assets by risk level.The risk inclusion in a portfolio that controls the probability of a one-year cumulative return falling below the principal amount to 5% [or Shortfall Risk (1 Year, Principal) ≤ 5%] is similar to a portfolio with a risky asset investment ratio of up to 10%.Therefore, for a pension fund that aims to the allowable risk limit as "Shortfall Risk (1 year, principal) ≤5%".The proportion of risky assets (domestic stocks þ foreign stocks þ alternative investments) is extracted by setting the constraint is located in 10% when extracting the constrained random portfolio.In the same way, the allowable risk limit for "Shortfall Risk (1 year, principal) ≤10%" is set to 20%

Asset allocation performance
of risk assets, and the allowable risk limit for "Shortfall Risk (5 years, CPI) ≤15%" is set to 60% of risk assets.
To summarize our discussion on data building, the asset allocation capabilities which are the dependent variables in estimation are as follows.They are return, volatility, Sharpe ratio in absolute terms, return ranking, volatility ranking and Sharpe ratio ranking in randomized portfolios in relative terms, return ranking, volatility ranking and Sharpe ratio ranking in randomized portfolios along with the fund's risk tolerance.We further investigate the qualitative fund management evaluation to measure the asset allocation capabilities of OCIOs.The explanatory variables are as follows.They are OCIO dummy variable, total fund size, medium-and long-term asset allocation and risk tolerance.The OCIO dummy variable is the main explanatory variable in this study which measures the OCIO's performance in asset allocation.The fund size is a proxy variable representing asset management infrastructure in the fund.Since all medium-term and long-term funds are managed for the purpose of improving profitability, the common factor for both maturity funds is the fund's profitability and then the risk tolerance becomes a proxy variable of the fund's risk appetite.There are many remaining factors that affect the performance of the fund.But we have practical constraints in gaining data for all remaining factors.Therefore we control all these factors by including the return in the previous period(t-1) by assuming that all effects of the remaining factors are reflected in the previous period's return (Park and Cho, 2010).Variables employed in this study are summarized in Table 5.
We construct the following regression equation from ( 1) to ( 6) with the asset allocation capability index as the dependent variable, OCIO status as the main explanatory variable and Rating of the "System" portion of the Fund's evaluation (decision-making structure and organization) test_2_flag Rating the "policy" portion of the fund evaluation (related to asset allocation, risk, etc.) test_3_flag Rating the "Enforcement" portion of the fund assessment (related to TAA, risk management and performance evaluation) Source(s): Author's work (This table reports the definitions of variables we use in this study.)other fund characteristics as control variables.Considering changes in the financial market and changes in the size of the fund by year, the estimation equations include the year effect dummy variable which becomes year-fixed effect panel model.
The dependent variable is changed to standard deviation and Sharpe ratio with independent variables of the return and previous control variables.In the following estimation equations, we add another independent variable of interaction variable between OCIO and the largest share of risky assets (sf_wt) because the largest share of risky assets give a significant impact in all cases.The equations in (2) and ( 3) are also estimated with the same interaction term as an explanatory variable in equation ( 5) and (6).
For investigating both of qualitative and quantitative effects of OCIO adoption, we implement further empirical estimation by employing the Ministry of Economy and Finance's fund management evaluation.The fund evaluation results have six grades (outstanding/ excellent/good/moderate/weak/very weak).We assign the evaluation grade of 5/4/3/2/1/0 in estimation.The fund evaluation categories are composed of three regions of system, policy and execution.The dependent variable becomes the final grade of the fund for each year in equation ( 5).Dummy variables of system, policy and execution are included, respectively, whether each item is positively related to funds that introduced OCIO.

Descriptive statistics
Table 6 shows the descriptive statistics of the variables employed in this study.The size of funds employed in this study averages 40.179tn won, while the medium-and long-term funds averaged 39.905tn won which covers 80.33% of the total size.When the shortfall risk limit is incorporated, the share of risky assets is 24.42% on average.The dependent variable average of return is 3.66% and the standard deviation is 2.53%.The Sharpe ratio average is 0.69 which is positive.The % Rank score of each fund's return average is 34.66 for the unconstrained case and 26.98 for the constrained case.  2 and 4, we performed the analysis (statistics, correlation and regression analysis)] Table 6.Descriptive statistics JDQS 31,2 performs better.The volatility reveals higher level with constraints.It indicates lower risk and the Sharpe ratio with constraints which indicate better risk-adjusted performance.Funds scored an average of two in the final rating/system/policy/enforcement category.It is can be considered as a moderate level out of the six categories.
The correlations between the variables used in this study are presented in Table 7. Significant correlations were found between the explanatory variable, the OCIO dummy variable and the control and dependent variables.Among the control variables, the total size of the fund, size of medium-and long-term assets and share of medium-and long-term assets were positively correlated for OCIO-adopting funds.But the relationships are not significant when applying the allowable risk limit.In terms of return, volatility and risk-adjusted performance, the indicator values show that OCIO has no significant relationship with return and risk-adjusted performance.However, a positive relationship with volatility is found.It suggests that OCIO adoption increases risk without a positive effect on the return and riskadjusted performance based on indicator values.In relative evaluation with randomized portfolios, however, it appears that there are improved returns and risk-adjusted performance.Also, decreased volatility is found regardless of the risky asset allocation constraint.We find significant positive coefficient estimates in the correlation between the results of the qualitative fund evaluation and OCIO variables.These correlations are similar over fund size, medium-and long-term funds and risk tolerance.It partially indicates that performance improvement and risk reduction are influenced by different variables other than OCIO adoption.Since the correlation analysis represent the two variables which leads us to implement further empirical work where various control variables are controlled.

Empirical results
4.1 OCIO's asset allocation performance 1) Asset management performance (return, risk, risk-adjusted performance) Table 8 reports the impact of OCIO's asset allocation capability on asset management performance from the estimation of equation ( 1) and equation ( 4) where the dependent variables are performance variables as strategic asset allocation effect, volatility and riskadjusted performance (Sharpe ratio).The results (1-1, 1-3, 1-5) in equation ( 1 2 and 4, we performed the analysis (statistics, correlation and regression analysis)]   2 and 4, we performed the analysis (statistics, correlation and regression analysis)] Table 8.OCIO asset allocation capabilities' impact on performance JDQS 31,2 the interaction term between OCIO and risky asset weight (sf_wt).Estimation results show that OCIO has no significant impact on return, risk and risk-adjusted performances.Among the explanatory variables, the only statistically significant result is found in the share of risky assets (sf_wt).It indicates as the share of risky assets increases, returns increase along with more risk in the portfolio.This result is consistent with the conventional finance theory of risk and return tradeoff.In the risk-adjusted performances, however, are not significant at the 10% level indicating more risk-taking does not necessarily yield additional returns.
However, we are able to argue that there could be a possibility that OCIOs with specialized management capabilities use risk efficiently.We implement further empirical work by incorporating an interaction term between OCIO and risky asset weight (sf_wt).The estimation results are (1-2), (1)(2)(3)(4) and (1)(2)(3)(4)(5)(6) in Table 8.By adding the interaction term, we find significant results in the OCIO variable.The OCIO variable is significant at a 10% level with a positive coefficient for in both of returns and risk-adjusted performances.But we do not find its significant results in the risk (vol).We find that funds with OCIO management expect an additional 1.4637% annualized return compared to funds without OCIO.This result can be translated as an excess return of 0.6969% over the risk-free return for the same risk-bearing fund.To reiterate the above result, OCIO improves returns and risk-adjusted performance by achieving significant excess returns while controlling risk.It suggests OCIO incorporates more risk effectively than the funds without OCIO by leveraging its specialized management capabilities.

2) OCIO's Asset allocation Capabilities using Randomized Portfolios
In the previous section, we saw that OCIO adoption helps to improve fund management performances.In this section, we analyze the effect of OCIO adoption by employing randomized portfolios.In implementing estimation, we measure the % rank of the asset allocation performance of OCIO funds compared to the randomized portfolio which becomes the dependent variable in this section.The results of the estimation are presented in Table 9.
Table 9 reports empirical results without the interaction term between OCIO and risky asset weight (sf_wt).The OCIO variable is not significant in improving asset allocationrelated performance.However, when the interaction term is added to the estimation, the OCIO variable and the interaction term become both significant at the 10% level.In Table 9's estimation results, the OCIO variable is positively related to return and risk-adjusted performance while significance is not found in the risk.These results support the robustness of the empirical result in Table 9 that OCIO effectively leverages risk to improve performance.
The major difference with the results from Table 8 is that the interaction terms become statistically significant.Risk does not show statistical significance with the OCIO variable.But returns and risk-adjusted performance find a significant negative relationship in contrast with the OCIO variable.For funds without OCIO, the only variable that significantly affect performance variable is the tolerance for risk.This is consistent with conventional finance theory that risk-taking leads to higher returns.Also for funds with OCIO management have a weaker impact on tolerance compared to funds without OCIO management.It basically indicates that OCIO management improves fund performance.Based on equation (2-2), the coefficient estimate on tolerance limit in OCIO adopting funds is 0.2325(5 0.7960-0.5635)which is smaller than a coefficient estimate of 0.7960 for without OCIO managed funds.The OCIO variable has a positively significant coefficient estimate.This suggests that there are factors that improve the performance of OCIO-enabled funds other than risk-taking.Considering the fundamental role of OCIOs in the domestic fund market, OCIO is more involved in tactical asset allocation (TAA) and fund selection.Therefore our empirical results can be interpreted as OCIOs improve performance through TAA and fund selection without taking on additional risk.
To ensure the robustness of empirical results in   2 and 4, we performed the analysis (statistics, correlation and regression analysis)]   2 and 4, we performed the analysis (statistics, correlation and regression analysis)] Table 10.
OCIO's Asset allocation capabilities using randomized portfolios: Constrained Asset allocation performance of each fund is estimated differently.When estimation results are compared to a random portfolio with the same constraints, we suspect that empirical results would be biased depending on the distribution of the random portfolio.For example, if a randomized portfolio is generated with a focus on low-risk portfolios, it is estimated as if it is performing well because it has a high proportion of risky assets regardless of its asset allocation capabilities.The random portfolios are generated by setting the maximum risky asset limit according to the tolerance level.While in Table 9, a set of random portfolios (10,000) for the entire fund is to be analyzed, Table 10 analyzes the results of generating random portfolios by tolerance level by subdividing the analysis target into tolerance level groups.
The results of the analysis with risk constraints are similar to Table 9.Without the interaction term, the OCIO variable is not significant at the 10% level.However, with the interaction term, there comes a positively significant relationship between returns and riskadjusted performances.The interaction term is significant and negative with a reduced relative performance improvement compared to the results in Table 9 with the same statistical significance and sign.It provides robustness of empirical results of Table 9.

OCIO's fund evaluation performances
In the previous two sections, we provide dependent variables are quantitative operational performance variables.We find that the introduction of OCIO has a significant impact on improving asset allocation performance.In this section, we further implement empirical analysis of whether the OCIO asset management system improves the qualitative factors of OCIO.We, therefore, employ the results of the annual fund management evaluation conducted by the Ministry of Strategy and Finance as the dependent variable.
Table 11 reports empirical results from employing fund management evaluation results as the dependent variable.All models show a positively significant effect of fund size [ln(tot_amt)] on the dependent variable in the previous year.This shows that relatively large pension funds with good ratings in the previous year have better evaluation results in the current year.In addition, the OCIO variable has different behavior depending on the dependent variable of evaluation.For the models without interaction terms (4-1, 4-3, 4-5 and 4-7), we do not find a significant effect on other evaluation results except asset management execution (flag3).When the interaction term is added to the estimation equation, the relationship between the asset management system (flag1) and asset management policy (flag2) becomes significantly negative.This means that OCIO adoption funds are rated lower on asset management systems and policy evaluation items.But they are highly evaluated on asset management execution.To more understand these empirical results, it is necessary to further study the exact roles of OCIOs in Korean fund markets.
Table 12 shows the scope of the roles of investment advisors and OCIOs.Investment advisors only advise on the overall asset management but the final decision-making and execution is performed by the trustees.It further indicates that OCIOs are categorized into partial and full roles depending on the scope of asset management responsibility.Generally, partial role is given by the beneficiaries up to strategic asset allocation.Therefore, in the Korean OCIO market, the role of the OCIO in the execution stage is limited while the full range of role performed by the OCIO can be extended from comprehensive asset and liability management to asset allocation and asset management execution.Currently, most of the OCIO systems introduced in Korea are in the form of partial delegation and the full OCIO delegation in the pension fund investment pool is only introduced in 2022.Under the current fund management system where the OCIO role is limited to the execution stage, only asset management execution (flag 3) is the role of the OCIO in the government's fund management evaluation.The asset management system (flag 1) and policy (flag 2) are located at only in the advisory areas of the OCIO.Therefore, the asset management execution (flag 3), which can fully utilize the capabilities of the OCIO, is judged to improve the evaluation of funds   2 and 4, we performed the analysis (statistics, correlation and regression analysis)] Table 11.OCIO's impact on fund Evaluation Asset allocation performance introduced by the OCIO.Funds that do have enough professional personnel still dominate the whole asset management industry.Evaluators have high expectations, however, for the OCIO adoption fund which would be related to weak evaluation results.
The above findings and interpretations are consistent with Nam (2020) domestic fund market problems.He points out that in the Korean OCIO system, strategic decision-making authority remains with the non-professional custodian and, therefore, the role of the OCIO is only to assist asset allocation decisions.The inherent competitiveness of OCIOs lies in the comprehensive delegation of asset management tasks over the entire management spectrum.While this may lead to the argument that a full delegation system should be introduced for each OCIO fund, there are attempts to review and introduce a full delegation system through the pension fund investment pool system among domestic funds.It is necessary to implement various reviews to expand OCIO expertise to areas where it contributes to the improvement of funds performance.

Conclusion
In the middle of rapid OCIO market growth, there has been increasing interest in the superior performance of OCIO from academics and financial market participants.However, academics does not provide enough and significant answers on this issue yet.This study examines the impact of OCIO adoption on asset allocation performance by employing diverse empirical works.
The main empirical findings are as follows.First, in the period from 2012 to 2020, the adoption of OCIO has a consistently significant positive effect on the asset allocation performance of the fund (strategic asset allocation effect, Sharpe ratio) in % score of OCIO funds using randomized portfolio.Second, the interaction variable between the OCIO dummy variable and the maximum percentage of risky assets has a significant negative effect on the performance variable.It suggests that OCIO funds are relatively less risky and OCIO improves performance on average.Given that the main role of OCIOs is tactical asset allocation (TAA) and fund selection, it is allowed to interpret that they improve performance through TAA and fund selection without taking on additional risk.Third, the empirical results of OCIO adoption in qualitative evaluation are mixed.But the results find that OCIOs perform well in asset management execution which is the main role of OCIOs in the Korean OCIOs market.Overall, empirical results suggest that asset management through OCIOs has a partial superiority in terms of asset allocation capabilities.This also confirms the importance of portfolio management strategy given the superiority of OCIOs in improving ex ante planning of fund management.
These findings are expected to serve as a stepping stone for future studies on the effectiveness of OCIO asset management in addition to academic implications.This study's results may provide practical help for OCIO management strategies in the asset management industry.However, there is a limit in that the analysis simplifies pension funds into those that have adopted OCIO and those that have not.Pension funds range from national pensions worth 900tn won to small funds worth only a few billion won.Compared with the size of the funds, the capabilities of the asset management organizations and the size of personnel in charge of managing are not enough at all.Another constraint of this study is that various information on fund characteristics is not publicly available which led us to analyze fund characteristics with limited control using the information in the IPS.In particular, controlling the proxies for the asset management capacity of the fund with the variables of fund size and tolerance for risk has an oversimplifying problem.In future studies, more detailed and extensive research can be conducted if the fund's sensitive information is disclosed to the public.Then more effective suggestions can be provided for asset management market policy.
): Author's work [The author's classification is based on the Ministry of Economy and Finance data archive and IPS (Investment Policy Statement) of each Fund.
): Author's work [Using the data in Tables ): Author's work [Using the data in Tables ): Author's work [Using the data in Tables ): Author's work [Using the data in Tables

Table 1 .
Fund status and OCIO adoption fund Source(s): Ministry of Economy and Finance/Unit: Amount in trillions of won, percentage in percent Ministry of Economy and Finance, Fund Management Evaluation Guidelines

Table 4 .
Author's work [The author's classification is based on the Ministry of Economy and Finance data archive and IPS (Investment Policy Statement) of each Fund.This data is public and available to anyone.]Risk tolerance

Table 5 .
It indicates the constrained case ) do not include Author's work [Using the data in Tables

Table 7 .
Pearson's correlation coefficient Table 9, risk constraints added randomized portfolio estimation results are reported in Table 10.In Table 4, the risk tolerance