1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
//!
//!  File : portfolio_5_card.rs
//!
//!  Copyright : Copyright (c) MOSEK ApS, Denmark. All rights reserved.
//!
//!  Description :  Implements a basic portfolio optimization model
//!                 with cardinality constraints on number of assets traded.
//!

extern crate mosek;
use mosek::{Task,Objsense,Soltype,Variabletype,Boundkey,Solsta};
extern crate itertools;
use itertools::{izip,iproduct};

const INF : f64 = 0.0;

/// Solve the Markowitz portfolio problem with cardinality constraints.
///
/// ```
/// Maximize mu'x
/// Such That
///   budget:      𝐞'x = w0+sum(x0)
///   risk:        γ^2 > ||G'x||^2
///   cardinality: 𝐞'y < p
///                [ y_j == 0 AND x0_j == x_j ] OR y_j == 1
///                y ∈ R^n
///                y ∈ R+^n
/// ```
///
/// Where
///
/// - `y_j` ∈ `{0,1}` is an indicator of whether we change the
///   investment in asset j, that is if `y_j=0`, then we do not change
///   investment in assert `j`.
///
/// # Arguments
///
/// - `n` number of assets
/// - `mu` vector of expected returns
/// - `GT` Covariance matrix factor
/// - `x0` vector if initial investment
/// - `gamma` risk bound (bound on the standard deviation)
/// - `w` initial uninvested wealth
/// - `p` maximum number of assets to invest in
#[allow(non_snake_case)]
fn portfolio(n     : i32,
             mu    : &[f64],
             GT    : &[f64],
             x0    : &[f64],
             gamma : f64,
             p     : i32,
             w     : f64) -> Result<(Vec<f64>,f64),String> {

    /* Create the optimization task. */
    let mut task = match Task::new() {
        Some(e) => e,
        None => return Err("Failed to create task".to_string()),
    };

    let k = (GT.len() / n as usize) as i32;
    // task.put_stream_callback(Streamtype::LOG, |msg| print!("{}",msg))?;

    /* Compute total wealth */
    let w0 = w + x0.iter().sum::<f64>();

    task.append_vars(3*n)?;

    let all_vars : Vec<i32> = (0..3*n).collect();
    let x = &all_vars[0..n as usize];
    let y = &all_vars[n as usize..2*n as usize];
    let z = &all_vars[2*n as usize..3*n as usize];

    task.put_var_bound_slice_const(0,n,mosek::Boundkey::LO,0.0,INF)?;
    task.put_var_bound_slice_const(n,2*n,mosek::Boundkey::RA,0.0,1.0)?;
    task.put_var_bound_slice_const(2*n,3*n, mosek::Boundkey::FR, -INF,INF)?;

    for (i,xj,yj,zj) in izip!(0..n,x,y,z) {
        task.put_var_name(*xj,format!("x[{}]",i+1).as_str())?;
        task.put_var_name(*yj,format!("y[{}]",i+1).as_str())?;
        task.put_var_name(*zj,format!("z[{}]",i+1).as_str())?;
        task.put_var_type(*yj, Variabletype::TYPE_INT)?;
    }

    // objective
    task.put_obj_sense(Objsense::MAXIMIZE)?;
    for (j,mui) in x.iter().zip(mu.iter()) {
        task.put_c_j(*j, *mui)?;
    }

    let n_ones = vec![1.0; n as usize];
    // budget constraint
    {
        let coni = task.get_num_con()?;
        task.append_cons(1)?;
        task.put_con_name(coni,"budget")?;
        task.put_a_row(coni,
                       x,
                       n_ones.as_slice())?;
        task.put_con_bound(coni,mosek::Boundkey::FX,w0,w0)?;
    }

    // |x-x0| <= z
    {
        let coni = task.get_num_con()?;
        task.append_cons(2 * n)?;
        for i in 0..n {
            task.put_con_name(coni+i,   format!("zabs1[{}]",1 + i).as_str())?;
            task.put_con_name(coni+n+i, format!("zabs2[{}]",1 + i).as_str())?;
        }
        let ones      = vec![1.0; n as usize];
        let minusones = vec![-1.0; n as usize];
        let con_abs1 : Vec<i32> = (coni..coni+n).collect();
        let con_abs2 : Vec<i32> = (coni+n..coni+2*n).collect();
        task.put_aij_list(con_abs1.as_slice(), x, minusones.as_slice())?;
        task.put_aij_list(con_abs1.as_slice(), z, ones.as_slice())?;
        task.put_con_bound_slice(coni,coni+n, vec![Boundkey::LO; n as usize].as_slice(), x0.iter().map(|&v| -v).collect::<Vec<f64>>().as_slice(), vec![INF; n as usize].as_slice())?;
        task.put_aij_list(con_abs2.as_slice(), x, ones.as_slice())?;
        task.put_aij_list(con_abs2.as_slice(), z, ones.as_slice())?;
        task.put_con_bound_slice(coni+n,coni+n*2, vec![Boundkey::LO; n as usize].as_slice(), x0, vec![INF; n as usize].as_slice())?;
    }

    // cardinality constraint
    {
        let coni = task.get_num_con()?;
        task.append_cons(1)?;
        task.put_con_name(coni,"cardinality")?;
        task.put_a_row(coni, y, n_ones.as_slice())?;
        task.put_con_bound(coni,mosek::Boundkey::UP,p as f64,p as f64)?;
    }

    // (gamma,G'x) in Q
    {
        let afei = task.get_num_afe()?;
        let acci = task.get_num_acc()?;

        task.append_afes(k as i64+1)?;
        let dom = task.append_quadratic_cone_domain(k as i64+1)?;
        task.append_acc_seq(dom,
                            afei,
                            vec![0.0; k as usize + 1].as_slice())?;
        task.put_acc_name(acci,"risk")?;
        task.put_afe_g(afei,gamma)?;

        for ((i,j),v) in iproduct!(0..n,0..n).zip(GT).filter(|(_,v)| **v != 0.0) {
            task.put_afe_f_entry(afei + i as i64 + 1, j as i32, *v)?;
        }
    }

    // Switch
    {
        let coni = task.get_num_con()?;
        task.append_cons(n)?;
        for i in 0..n {
            task.put_con_name(coni + i, format!("switch[{}]",i+1).as_str())?;
        }

        let conlist : Vec<i32> = (coni..coni+n).collect();
        task.put_aij_list(conlist.as_slice(), z, vec![1.0; n as usize].as_slice())?;
        task.put_aij_list(conlist.as_slice(), y, vec![-w0; n as usize].as_slice())?;

        task.put_con_bound_slice_const(coni,coni+n, Boundkey::UP, 0.0,0.0)?;
    }

    let _ = task.optimize()?;
    task.write_data(format!("portfolio_5_card-{}.ptf",p).as_str())?;

    // Check if the integer solution is an optimal point
    if task.get_sol_sta(Soltype::ITG)? != Solsta::INTEGER_OPTIMAL {
        // See https://docs.mosek.com/latest/rustapi/accessing-solution.html about handling solution statuses.
        eprintln!("Solution not optimal!");
        std::process::exit(1);
    }

    let mut xx = vec![0.0;n as usize];
    task.get_xx_slice(Soltype::ITG, 0,n,xx.as_mut_slice())?;
    Ok((xx[0..n as usize].to_vec(),task.get_primal_obj(Soltype::ITG)?))
}

#[allow(non_snake_case)]
fn main() -> Result<(),String> {
    let n : i32 = 8;
    let w = 1.0;
    let mu = &[0.07197, 0.15518, 0.17535, 0.08981, 0.42896, 0.39292, 0.32171, 0.18379];
        let x0 = &[0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0];
        let GT = &[ 0.30758, 0.12146, 0.11341, 0.11327, 0.17625, 0.11973, 0.10435, 0.10638,
                    0.     , 0.25042, 0.09946, 0.09164, 0.06692, 0.08706, 0.09173, 0.08506,
                    0.     , 0.     , 0.19914, 0.05867, 0.06453, 0.07367, 0.06468, 0.01914,
                    0.     , 0.     , 0.     , 0.20876, 0.04933, 0.03651, 0.09381, 0.07742,
                    0.     , 0.     , 0.     , 0.     , 0.36096, 0.12574, 0.10157, 0.0571 ,
                    0.     , 0.     , 0.     , 0.     , 0.     , 0.21552, 0.05663, 0.06187,
                    0.     , 0.     , 0.     , 0.     , 0.     , 0.     , 0.22514, 0.03327,
                    0.     , 0.     , 0.     , 0.     , 0.     , 0.     , 0.     , 0.2202 ];
    let gamma  = 0.25;

    for K in 1..n+1 {
        let (x,expret) = portfolio(n,
                                   mu,
                                   GT,
                                   x0,
                                   gamma,
                                   K,
                                   w)?;
        println!("Bound {}: x = {:?}", K,x);
        println!("  Return: {:.5e}\n", expret);
    }
    Ok(())
}


#[cfg(test)]
mod tests {
    #[test]
    fn test() {
        super::main().unwrap();
    }
}