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"ABSTRAKThis study analyzes optimal asset mix for Australian portfolios with the main investment objective for capital preservation. An alternative measure of risk of annual maximum drawdown has been used to reflect investor preference for capital preservation as opposed to conventional risk measure of standard deviation and variance. The contribution of the study is two folds. First, this study has put different perspective to look at portfolio risk in the view of capital preservation. Second, the optimal weight for asset class mix that minimizes annual maximum drawdown has been analyzed for the case of Australian market. The results suggest that for capital preservation, investors should expect lower returns and need to put a greater allocation on less risky assets such as cash or bond. To this end, cash and bond have provided stable long term annual returns along with contained level of annual maximum drawdowns. In contrast, when investors demand higher expected return, they should increase asset allocation into stocks (equities) market at the expense of higher maximum drawdowns."

"Penentuan alokasi saham menggunakan Mean-Variance Optimization membutuhkan estimasi dari return setiap saham yang akan dioptimasi. Proses estimasi return saham tersebut menjadi tantangan karena terlalu banyak faktor yang dapat memengaruhi return sehingga dapat memengaruhi kualitas keputusan dari hasil proses optimasi. Proses estimasi return ini biasanya bergantung kepada prediction error atau seberapa jauh predicted return dengan actual return. Padahal, minat investor dalam proses alokasi bobot saham adalah decision error atau seberapa jauh best predicted decision dengan best actual decision. Selain itu, proses estimasi return dengan konsiderasi decision error, atau biasa disebut Smart Predict-then-Optimize, sejauh ini belum mengeksplorasi beberapa auxiliary features selain momentum. Oleh karena itu, kontribusi dari penelitian ini adalah untuk feature engineering dalam proses Smart Predict-then-Optimize. Hasil penelitian menunjukkan dengan auxiliary feature dan parameter model tertentu, rata-rata return bulanan bisa mencapai 5.7% dengan confidence untuk break-even bisa mencapai 99% yakni peningkatan sebesar 8.5% dibandingkan dari algoritma Smart Predict-then-Optimize tanpa auxiliary features meskipun IHSG dan indeks mayor seperti IDX30, LQ45, dan KOMPAS100 tidak menunjukkan performa terbaiknya.

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Stock allocation with Mean-Variance Optimization requires estimating stock returns, which is challenging due to numerous influencing factors that affect optimization quality. This process typically focuses on prediction error, while investors prioritize decision error. Moreover, the return estimation process that considers decision error, commonly referred to as Smart Predict-then-Optimize, has so far not explored several auxiliary features beyond momentum. Therefore, the contribution of this research is to test whether auxiliary features can improve the results from the Smart Predict-then-Optimize process. The research results show that, by using auxiliary features with specific model parameters, the average monthly return can reach up to 5.7%, with the confidence of break-even point can reach up to 99%, a 8.5% increase compared to the Smart Predict-then-Optimize algorithm without auxiliary features, even though the IHSG and major indices such as IDX30, LQ45, and KOMPAS100 did not show their best performance. "

"Penelitian ini bertujuan melakukan analisis pengaruh likuiditas terhadap alokasi portofolio asing di negara BRICS dan MIST periode 2002-2012. Likuiditas diukur menggunakan Price Impact, Trading Volume, Turnover Ratio, dan Corwin Schultz Spread. Penelitian menggunakan data panel serta metode regresi Fixed dan Random Effect Model. Selain itu, penelitian juga bertujuan untuk menganalisis hubungan variabel bilateral dan makroekonomi terhadap alokasi portofolio asing di negara BRICS dan MIST periode 2002-2012. Penelitian menemukan bahwa likuiditas memiliki pengaruh positif terhadap alokasi portofolio asing di negara BRICS dan MIST periode 2002-2012.

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The aim of this research is to analyze the impact of liquidity on Foreign Portofolio Allocation in BRICS and MIST Countries during 2002-2012. Liquidity are measured using Price Impact, Trading Volume, Turnover Ratio, and Corwin Schultz Spread. This research uses panel data with Fixed and Random Effect Model as a regression method. Furthermore, this research also analyze the effect of bilateral and macroeconomic condition on Foreign Portfolio Allocation. This research found that market liquidity positively affects Foreign Portfolio Invesments in BRICS and MIST Countries during 2002-2012."

"In this paper, we analyze the empirical relationship between stock return and trading volumebased on stock market cycles. Using daily data for Jakarta Composite Index (JCI) closing price andtrading volume from 2010 to 2014, we identify the bull and bear phases, then we analyze the return–volume relationship in both contemporaneous and dynamic context. We find that (1) there is a positivecontemporaneous return–volume relationship in both bull and bear markets, which is only significantin bull markets; (2) no evidence of asymmetry in contemporaneous relationship is found; and (3)there exists a positive unidirectional causality from stock return to trading volume. Our research hastwo implications. First, in the bull market, overconfidence may grow with long-lasting past successand there is also momentum or positive feedback trading. Second, stock return is able to forecasttrading volume. In addition, our findings are robust for different sample period and data frequency."