Amit Mane Email & Phone Number

Valley Forge, Pa, Us

Provided thought leadership in the quantitative research / technical aspects of the team's deliverables along with developing talent. Worked with senior leaders to set priorities for the risk team that aligned with its objectives.Defined and established holistic risk frameworks for funds, strategies and the overall business in collaboration with quantitative researchers, PMs, technology teams and business leaders.Developed and managed relationship with the desk while striking the right balance between collaboration (promote optimal risk-taking by making PMs aware of emerging risks and opportunities) and providing an independent & constructive challenge when necessary.Managed responses and communication regarding risk-related inquiries from senior leaders in the risk & investment management groups and other key internal partners (client facing group, finance etc.)Helped source and develop talent on the team by working with individuals on their developmental & stretch assignments and helping leaders create opportunities and structure for growth of individuals

Valley Forge, Pa, Us

As a member of the Risk Management Group partner with Investment Management Group to define and develop an effective and efficient risk management infrastructure across equity funds.Multi-Portfolio Optimization: Used R/Python/Axioma API to concurrently re-balance multiple portfolios, considering their joint effects while adhering to account-specific and group-specific constraints.Equity Risk Model Evaluation: Used Python and risk model flat files (Axioma/Barra) to evaluate equity risk models (Medium horizon / Trading) . Different components of risk (Factor risk, Specific Risk, Linked Specific Risk) were evaluated independently in the context of a variety of trading strategies / portfolios.Single Stock Liquidity / Event Risk: Researched and defined a liquidity measures that incorporates market impact (ITG cost model API). Explored relationship between this measure of liquidity and volatility to predict event risk.Multi-Period Optimization in Transition management: Used Python/Axioma API to build a transition management framework for index funds that allows PM/Trader to efficiently tailor the transition trading strategy by considering 3 competing factors - t-costs, active risk and investor's biases toward the two.Multi-Asset Portfolios: Applying multi-asset risk models, helped set a framework to hedge asset level exposures using highly liquid derivatives.

Chicago, Il, Us

Risk Analysis and Portfolio Construction • Defined market, credit and liquidity risk approach appropriate for a variety of different asset classes and strategies investing in cash and derivatives instruments.• Decomposed risk using a variety of different measures (Volatility, VaR, Beta, Risk Factors – observed and unobserved / PCA) to understand drivers of risk.• Helped build asset allocation frameworks, which integrated risk management with investment strategy.Portfolio Protection Solutions• Equity Risk / Illiquidity Risk (convexity) – Quantified direct and indirect exposure to global equities and the source of this risk. Through simulations defined the shape of the left tail and tested different solutions to mitigate local risk and eliminate large tail risks. Designed a framework to evaluate Cost of protection vs. Utility/Magnitude vs. Basis Risk/Reliability.• Event Risk – Analyzed the implications of an “Event” and designed “what-ifs” scenarios / simulations to understand the impact on the portfolio and the source of risk. Tested strategies to mitigate this event risk.• Concentration Risk / Crowding Risk – Used the concepts of asset centrality and relative value to identify source of tail risk and proposed solutions to mitigate this riskEvaluation of hedge fund strategies (Equity, Credit, Systematic/RV, Macro/Vol-Arb) • Interviewed Portfolio Managers and Analysts to understand their strategy and investment philosophy. Conducted in-depth performance attribution and benchmarking analyses to evaluate skill of the manager• Assessed the investment universe, market trends and valuations to build a regime-based framework to aid Strategy Leads and CIO in risk capital allocationAuthored investment/research reports to summarize findings from above analysis and presented these reports at the Investment Committee and Portfolio Construction meetings Tools used: MATLAB, R, SQL, Bloomberg, Factset, Barra Factor Models, Riskmetrics, MS Excel, VBA

Chicago, Il, Us

• Modeled and studied non-linear payoffs of funds investing in derivatives to set risk and return expectations. Furthermore, used x-sigma-rho framework to align risk and performance attribution• Carried out clustering analysis to group strategies on commonality and then used regime analysis to form a top down outlook for each cluster of strategies.Tools used: MATLAB, R, SQL, Bloomberg, Factset, Barra Factor Models, Riskmetrics, MS Excel, VBA

Chicago, Il, Us

• Applied style-based performance model to evaluate Long/Short Equity, Short Biased and Quantitative Equity Hedge Funds to see if active investments are adding value relative to passive alternatives.• Quantified drivers of risk / sources of returns – Global Equity Risk, Leverage, Liquidity, Style Factor TiltsTools used: MATLAB, R, SQL, Bloomberg, Factset, Barra Factor Models, Riskmetrics, MS Excel, VBA

Chicago, Il, Us

• Enhanced the data model – Developed analytics and reporting capabilities by building a data warehouse on top of the SQL server, which was helpful to slice-dice and aggregate data by different dimensions • Extended the performance model – Mesirow had a classic Brinson sector-based Model that explained active returns in terms of Tactical Asset Allocation and Selection decisions. Expressed this as a factor model and extended it to include Barra Style Factors, which appropriately attributed performance to market vs industries vs style factors

Led a team of 3 to build asset allocation solutions for institutional investors• Built a Black-Litterman Model, which overcomes certain big limitations of traditional mean-variance optimization in incorporating investor’s views and making results intuitive and practical.• Developed a Multi-moment Model for a portfolio of Alternatives. This model overcomes an important limitation (normality) of BL Model by incorporating higher order moments into portfolio optimization.Tools used: MATLAB, SQL, C#, .net

Walldorf, Bw, De

1. Product Development, Product Support2. SAP NetWeaver Business Intelligence3. Enhancing and developing new features of BEx Analyzer of SAP BI. Microsoft Excel,C#, VB.net, VB Script, ABAP.

Bangalore, Karnataka, In

Developed business reporting software (C#, VB.net) for clients in financial, retail and industrial sectors

Master Of Business Administration (Mba), Economics, Finance, Analytic Finance, General Management

Masters, Finance

Bachelor Of Engineering - Be, Computer Engineering